[ { "id": "A001", "title": "Computing the Full Earth System at 1km Resolution", "area": "High-resolution physical simulation", "category": "Primary or methodological candidate", "summary": "Examines the physical and computational requirements of kilometre-scale Earth-system simulation, including the tension between process complexity, resolution, and simulation throughput.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "A large physical-model computation is a resolution and cost reference; it does not establish performance of a learned regional emulator.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2511.02021", "identity": "Not independently resolved against publication metadata" }, { "id": "A002", "title": "SPEAR-NeXT: Causal Latent Forecasting Across Multiple Horizons for Spectral–Temporal Earth Representation Learning", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Uses causal prediction across several time horizons to learn reusable satellite representations. Its relevance lies in temporal representation learning rather than proof of atmospheric conservation.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2609.16871", "identity": "Not independently resolved against publication metadata" }, { "id": "A003", "title": "Calibrated Station-Scale Temperature Downscaling from a Temperature-Agnostic Geospatial Foundation Model", "area": "Climate emulation and regional downscaling", "category": "Primary or methodological candidate", "summary": "Tests whether temperature-agnostic satellite embeddings add information for station-temperature downscaling and examines uncertainty calibration, directly raising the problem of pretraining contamination.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A004", "title": "Physically Typed and Geometry-Aware Representations for Earth Foundation Models", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Proposes physically typed and geometry-aware representations and a staged falsification programme. It supports testing vector and tensor transformation properties rather than assuming ordinary embeddings preserve them.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2609.13868", "identity": "Not independently resolved against publication metadata" }, { "id": "A005", "title": "CV-GAN: A Generative Model to Simulate Global Climate Variability", "area": "Methods and adjacent applications", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A006", "title": "Score-based generative emulation of impact-relevant Earth system model outputs", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Uses score-based generation on a spherical mesh to emulate jointly distributed impact-relevant climate variables, evaluating distributions, cross-variable dependence and tails under different forcing conditions.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2510.04358", "identity": "Not independently resolved against publication metadata" }, { "id": "A007", "title": "Fast emulation of climate models for precipitation and flood impact modelling using autoregressive video diffusion", "area": "Climate emulation and regional downscaling", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A008", "title": "Simulating the Visual World with Artificial Intelligence: A Roadmap", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Surveys visually generated world models and their controllability. It provides terminology for visual simulation, but its realism criteria do not establish meteorological accuracy or budget closure.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2511.08585", "identity": "Not independently resolved against publication metadata" }, { "id": "A009", "title": "Understanding Similarities and Differences Between Data-Driven AI Model-Based and Physics Model-Based Ensemble Forecasts", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Compares machine-learning and numerical ensemble systems to understand differences in ensemble behaviour. It motivates diagnosing uncertainty structure rather than relying on a single headline score.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.25923/4pc4-3t39", "identity": "Not independently resolved against publication metadata" }, { "id": "A010", "title": "MeteoVerse: Unified Weather-Controllable Video World Model", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Conditions video generation on weather descriptions and camera motion. It is relevant to presentation and scenario visualisation, with limited evidential value for prognostic atmospheric physics.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2609.36810", "identity": "Not independently resolved against publication metadata" }, { "id": "A011", "title": "PAN: A World Model for General, Interactable, and Long-Horizon World Simulation", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Develops interactive latent dynamics and video generation for general world simulation. It helps distinguish learned visual trajectories from measured, physically constrained atmospheric states.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2511.09057", "identity": "Not independently resolved against publication metadata" }, { "id": "A012", "title": "A Comparison of AI Weather Prediction and Numerical Weather Prediction Models for 1–7-Day Precipitation Forecasts", "area": "Weather prediction and uncertainty", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A013", "title": "Learning representations from different pre-training strategies in the WeatherGenerator", "area": "Weather prediction and uncertainty", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A014", "title": "Latent Representations of Land-Sea Boundaries and Extreme Temperature in Aurora's Encoder (Student Abstract)", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Probes Aurora representations for coastlines and temperature extremes. As a student abstract, it motivates interpretability diagnostics without providing a full independent validation of local extremes.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A015", "title": "Does Aurora Encode Atmospheric Structure? Latent Regime Analysis and Attribution", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Uses latent-space analysis, attribution and perturbation experiments to investigate Aurora's meteorological representations, separating seasonal organisation from storm-specific information.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2606.26361", "identity": "Not independently resolved against publication metadata" }, { "id": "A016", "title": "Fine-Tuning a Weather Foundation Model With Lightweight Decoders for Unseen Physical Processes", "area": "Weather prediction and uncertainty", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A017", "title": "Foundation-Scale Satellite Embeddings Reframe Hydrological Generalization as a Representation Problem", "area": "Observations and Earth representations", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the observations and earth representations strand; apply only to its stated variables, scales and task.", "limitation": "A retrieval, embedding or reanalysis is not independent ground truth; quantify shared inputs and errors.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A018", "title": "Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves", "area": "Physical constraints and scientific learning", "category": "Primary or methodological candidate", "summary": "Fine-tunes a weather foundation model for unresolved atmospheric gravity-wave fluxes. It illustrates learned closure modelling and the need to assess small-flux behaviour as well as averages.", "application": "Evaluate in the physical constraints and scientific learning strand; apply only to its stated variables, scales and task.", "limitation": "A small residual or exact aggregation constraint alone does not establish an accurate or closed atmospheric simulation.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2509.03816", "identity": "Not independently resolved against publication metadata" }, { "id": "A019", "title": "WeatherNext 3: Increasing resolution and performance of global weather models with raw observations", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Describes a weather model trained and initialised with observations to improve temporal and spatial resolution. It is a recent preprint comparator whose precise version and input availability matter.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2609.03582", "identity": "Not independently resolved against publication metadata" }, { "id": "A020", "title": "AlphaEarth Foundations: An embedding field model for accurate and efficient global mapping from sparse label data", "area": "Observations and Earth representations", "category": "Primary or methodological candidate", "summary": "Introduces reusable multisource Earth-observation embeddings. It supports testing land-surface contextual information while requiring an audit of which climate products entered pretraining.", "application": "Evaluate in the observations and earth representations strand; apply only to its stated variables, scales and task.", "limitation": "A retrieval, embedding or reanalysis is not independent ground truth; quantify shared inputs and errors.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2507.22291", "identity": "Not independently resolved against publication metadata" }, { "id": "A021", "title": "Physically Interpretable AlphaEarth Foundation Model Embeddings Enable LLM-Based Land Surface Intelligence", "area": "Observations and Earth representations", "category": "Primary or methodological candidate", "summary": "Analyses associations between satellite embedding dimensions and environmental variables. Such associations support representation diagnostics but do not alone identify causal physical mechanisms.", "application": "Evaluate in the observations and earth representations strand; apply only to its stated variables, scales and task.", "limitation": "A retrieval, embedding or reanalysis is not independent ground truth; quantify shared inputs and errors.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2602.10354", "identity": "Not independently resolved against publication metadata" }, { "id": "A022", "title": "Changes in extreme precipitation patterns over the Greater Antilles and teleconnection with large-scale sea surface temperature", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Relates Greater Antilles precipitation-extreme indices to large-scale sea-surface-temperature variability using gridded precipitation and ocean products, providing a regional teleconnection test case.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.5194/esd-16-497-2025", "identity": "Crossref title and metadata match" }, { "id": "A023", "title": "Resolution-Dependent Perspectives on Caribbean Hydro-Climate Change", "area": "Caribbean climate physics", "category": "Primary or methodological candidate", "summary": "Shows how representation of Caribbean orography and thermal circulations changes with spatial resolution. It challenges island-wide interpretations based solely on coarse regional averages.", "application": "Evaluate in the caribbean climate physics strand; apply only to its stated variables, scales and task.", "limitation": "A regional association is not a causal mechanism or evidence of dLEGOS skill; preserve the study region and period.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.3390/hydrology7040093", "identity": "Not independently resolved against publication metadata" }, { "id": "A024", "title": "Rain on small tropical islands", "area": "Methods and adjacent applications", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A025", "title": "An Intercomparison of Observational, Reanalysis, Satellite, and Coupled Model Data on Mean Rainfall in the Caribbean", "area": "Caribbean climate physics", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the caribbean climate physics strand; apply only to its stated variables, scales and task.", "limitation": "A regional association is not a causal mechanism or evidence of dLEGOS skill; preserve the study region and period.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A026", "title": "A Suite of Tools for Continuous Land Change Monitoring in Google Earth Engine", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Provides tools for continuous land-change monitoring in Earth Engine. It supports reproducible preparation of evolving land-cover context rather than an atmospheric forecasting model.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.3389/fclim.2020.576740", "identity": "Crossref title and metadata match" }, { "id": "A027", "title": "Climate Engine: Cloud Computing and Visualization of Climate and Remote Sensing Data for Advanced Natural Resource Monitoring and Process Understanding", "area": "Observations and Earth representations", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the observations and earth representations strand; apply only to its stated variables, scales and task.", "limitation": "A retrieval, embedding or reanalysis is not independent ground truth; quantify shared inputs and errors.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A028", "title": "Google Earth Engine: Planetary-scale geospatial analysis for everyone", "area": "Observations and Earth representations", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the observations and earth representations strand; apply only to its stated variables, scales and task.", "limitation": "A retrieval, embedding or reanalysis is not independent ground truth; quantify shared inputs and errors.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A029", "title": "A global daily gap-filled chlorophyll-a dataset in open oceans during 2001–2021 from multisource information using convolutional neural networks", "area": "Observations and Earth representations", "category": "Primary or methodological candidate", "summary": "Reconstructs missing ocean-colour information using convolutional learning and multisource data. It offers an adjacent example of gap filling whose variable and observational operator differ from atmospheric reconstruction.", "application": "Evaluate in the observations and earth representations strand; apply only to its stated variables, scales and task.", "limitation": "A retrieval, embedding or reanalysis is not independent ground truth; quantify shared inputs and errors.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.5194/essd-15-5281-2023", "identity": "Crossref title and metadata match" }, { "id": "A030", "title": "Statistical and machine learning ensemble modelling to forecast sea\n surface temperature", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Compares statistical and machine-learning approaches for sea-surface-temperature prediction using remotely sensed and atmospheric inputs, including accuracy and computational considerations.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/1909.08573", "identity": "Not independently resolved against publication metadata" }, { "id": "A031", "title": "The colours of the ocean: using multispectral satellite imagery to estimate sea surface temperature and salinity on global coastal areas, the Gulf of Mexico and the UK", "area": "Observations and Earth representations", "category": "Primary or methodological candidate", "summary": "Estimates coastal temperature and salinity from multispectral imagery. It supports observation-operator and coastal-domain discussions, with transfer to Caribbean conditions requiring separate testing.", "application": "Evaluate in the observations and earth representations strand; apply only to its stated variables, scales and task.", "limitation": "A retrieval, embedding or reanalysis is not independent ground truth; quantify shared inputs and errors.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.3389/fenvs.2024.1426547", "identity": "Crossref title and metadata match" }, { "id": "A032", "title": "Statistical Downscaling of SEVIRI Land Surface Temperature to WRF Near-Surface Air Temperature Using a Deep Learning Model", "area": "Climate emulation and regional downscaling", "category": "Primary or methodological candidate", "summary": "Uses satellite land-surface-temperature information to emulate WRF near-surface air temperature. It illustrates why skin temperature and air temperature must remain distinct target variables.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.3390/rs15184447", "identity": "Not independently resolved against publication metadata" }, { "id": "A033", "title": "Downscaling Aster Land Surface Temperature over Urban Areas with Machine Learning-Based Area-To-Point Regression Kriging", "area": "Climate emulation and regional downscaling", "category": "Primary or methodological candidate", "summary": "Combines random forests with area-to-point regression kriging for land-surface-temperature downscaling, providing a geostatistical alternative to neural super-resolution.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.3390/rs12071082", "identity": "Not independently resolved against publication metadata" }, { "id": "A034", "title": "A comprehensive remote sensing-based Agriculture Drought Condition Indicator (CADCI) using machine learning", "area": "Observations and Earth representations", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the observations and earth representations strand; apply only to its stated variables, scales and task.", "limitation": "A retrieval, embedding or reanalysis is not independent ground truth; quantify shared inputs and errors.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A035", "title": "Downscaling SMAP Soil Moisture to 1 km with Machine Learning and MODIS Data for Agricultural Drought Assessment in Békés County, Hungary", "area": "Climate emulation and regional downscaling", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A036", "title": "Bridging satellite missions: deep transfer learning for enhanced tropical cyclone intensity estimation", "area": "Weather prediction and uncertainty", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A037", "title": "Physics-augmented Deep Learning to Improve Tropical Cyclone Intensity and Size Estimation from Satellite Imagery", "area": "Weather prediction and uncertainty", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A038", "title": "A Machine Learning-Based Approach for Surface Soil Moisture Estimations with Google Earth Engine", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Uses Earth Engine and machine learning to estimate surface soil moisture. It supplies an adjacent retrieval example and motivates uncertainty-aware land-surface covariates.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.3390/rs13112099", "identity": "Crossref title and metadata match" }, { "id": "A039", "title": "Estimating Tropical Cyclone Intensity by Satellite Imagery Utilizing Convolutional Neural Networks", "area": "Weather prediction and uncertainty", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A040", "title": "Tropical Cyclone Intensity Estimation Using a Deep Convolutional Neural Network", "area": "Weather prediction and uncertainty", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A041", "title": "Using Deep Learning to Estimate Tropical Cyclone Intensity from Satellite Passive Microwave Imagery", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Estimates cyclone intensity from passive microwave imagery using deep learning. The task offers satellite-feature evidence but does not demonstrate rainfall-field or atmosphere-state reconstruction.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.1175/MWR-D-18-0391.1", "identity": "Crossref title and metadata match" }, { "id": "A042", "title": "Oya: Deep Learning for Accurate Global Precipitation Estimation", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Develops a deep-learning approach to global precipitation estimation. It is relevant to satellite observation quality and latency, which must be separated from subsequent nowcasting skill.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2511.10562", "identity": "Not independently resolved against publication metadata" }, { "id": "A043", "title": "A Deep Learning Architecture for Passive Microwave Precipitation Retrievals using CloudSat and GPM Data", "area": "Observations and Earth representations", "category": "Primary or methodological candidate", "summary": "Uses CloudSat and GPM observations for passive-microwave precipitation retrieval. It supports discussion of vertically sensitive measurements and the indirect nature of retrieved surface rainfall.", "application": "Evaluate in the observations and earth representations strand; apply only to its stated variables, scales and task.", "limitation": "A retrieval, embedding or reanalysis is not independent ground truth; quantify shared inputs and errors.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2212.02236", "identity": "Not independently resolved against publication metadata" }, { "id": "A044", "title": "Global Precipitation Nowcasting of Integrated Multi-satellitE Retrievals\n for GPM: A U-Net Convolutional LSTM Architecture", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Applies a U-Net and convolutional recurrent architecture to IMERG precipitation nowcasting, providing a satellite-domain comparison for radar-based nowcasting methods.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2307.10843", "identity": "Not independently resolved against publication metadata" }, { "id": "A045", "title": "Conditional Generative Adversarial Networks (cGANs) for Near Real-Time Precipitation Estimation from Multispectral GOES-16 Satellite Imageries—PERSIANN-cGAN", "area": "Observations and Earth representations", "category": "Primary or methodological candidate", "summary": "Uses conditional adversarial learning for precipitation estimation from GOES imagery. It supports comparing retrieval structure and calibration rather than treating generated rainfall as direct observation.", "application": "Evaluate in the observations and earth representations strand; apply only to its stated variables, scales and task.", "limitation": "A retrieval, embedding or reanalysis is not independent ground truth; quantify shared inputs and errors.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.3390/rs11192193", "identity": "Crossref title and metadata match" }, { "id": "A046", "title": "A Deep Neural Network Modeling Framework to Reduce Bias in Satellite Precipitation Products", "area": "Observations and Earth representations", "category": "Primary or methodological candidate", "summary": "Develops neural bias reduction for satellite precipitation products. It motivates reporting both retrieval bias and forecast error rather than attributing every improvement to atmospheric dynamics.", "application": "Evaluate in the observations and earth representations strand; apply only to its stated variables, scales and task.", "limitation": "A retrieval, embedding or reanalysis is not independent ground truth; quantify shared inputs and errors.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.1175/JHM-D-15-0075.1", "identity": "Not independently resolved against publication metadata" }, { "id": "A047", "title": "PERSIANN-CNN: Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Convolutional Neural Networks", "area": "Methods and adjacent applications", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A048", "title": "Assessing Rainfall Variability in Jamaica Using CHIRPS: Techniques and Measures for Persistence, Long and Short-Term Trends", "area": "Caribbean climate physics", "category": "Primary or methodological candidate", "summary": "Analyses persistence and trends in Jamaican CHIRPS rainfall. It supplies local diagnostics and highlights how the chosen product and aggregation shape regional conclusions.", "application": "Evaluate in the caribbean climate physics strand; apply only to its stated variables, scales and task.", "limitation": "A regional association is not a causal mechanism or evidence of dLEGOS skill; preserve the study region and period.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.3390/geographies3020020", "identity": "Not independently resolved against publication metadata" }, { "id": "A049", "title": "Climate change impacts on critical international transportation assets of Caribbean Small Island Developing States (SIDS): the case of Jamaica and Saint Lucia", "area": "Caribbean climate physics", "category": "Primary or methodological candidate", "summary": "Assesses climate exposure of transport infrastructure in Jamaica and Saint Lucia. It motivates decision-relevant climate information but is supporting impact literature rather than a solver-validation source.", "application": "Evaluate in the caribbean climate physics strand; apply only to its stated variables, scales and task.", "limitation": "A regional association is not a causal mechanism or evidence of dLEGOS skill; preserve the study region and period.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A050", "title": "Deep Learning and Foundation Models for Weather Prediction: A Survey", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Surveys deep learning and foundation models for weather prediction. It provides a taxonomy and citation chain, while primary studies remain necessary for method-specific claims.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2501.06907", "identity": "Not independently resolved against publication metadata" }, { "id": "A051", "title": "Determining sea-level rise in the Caribbean: A shift from temperature to mass control", "area": "Caribbean climate physics", "category": "Primary or methodological candidate", "summary": "Examines Caribbean sea-level change and the balance of thermal and mass contributions. It supports keeping sea-level height distinct from sea-surface temperature in coupled-model inputs.", "application": "Evaluate in the caribbean climate physics strand; apply only to its stated variables, scales and task.", "limitation": "A regional association is not a causal mechanism or evidence of dLEGOS skill; preserve the study region and period.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.1038/s41598-024-60201-8", "identity": "Crossref title and metadata match" }, { "id": "A052", "title": "Hybrid physics-AI outperforms numerical weather prediction for extreme precipitation nowcasting", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Independently evaluates NowcastNet against HRRR, advection and persistence for extreme rainfall nowcasting. It motivates regional event testing without establishing transferability to Jamaica.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.1038/s41612-024-00834-8", "identity": "Not independently resolved against publication metadata" }, { "id": "A053", "title": "Skilful nowcasting of extreme precipitation with NowcastNet", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Combines physical precipitation evolution with conditional generative learning using radar data. It supports separating transport structure from stochastic fine-scale generation.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.1038/s41586-023-06184-4", "identity": "Crossref title and metadata match" }, { "id": "A054", "title": "Ocean-atmosphere variability and drought in the insular Caribbean", "area": "Caribbean climate physics", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the caribbean climate physics strand; apply only to its stated variables, scales and task.", "limitation": "A regional association is not a causal mechanism or evidence of dLEGOS skill; preserve the study region and period.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A055", "title": "SamudrACE: Fast and Accurate Coupled Climate Modeling with 3D Ocean and Atmosphere Emulators", "area": "Climate emulation and regional downscaling", "category": "Primary or methodological candidate", "summary": "Develops coupled learned ocean and atmospheric emulators. It supplies a coupling comparator and illustrates why stability must be assessed after components interact.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2509.12490", "identity": "Not independently resolved against publication metadata" }, { "id": "A056", "title": "Samudra: An AI Global Ocean Emulator for Climate", "area": "Climate emulation and regional downscaling", "category": "Primary or methodological candidate", "summary": "Builds a global ocean emulator. Its direct contribution is ocean-state evolution and boundary-condition context, rather than proof of an island atmospheric model.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2412.03795", "identity": "Not independently resolved against publication metadata" }, { "id": "A057", "title": "Insights from a New High-Resolution Drought Atlas for the Caribbean Spanning 1950–2016", "area": "Caribbean climate physics", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the caribbean climate physics strand; apply only to its stated variables, scales and task.", "limitation": "A regional association is not a causal mechanism or evidence of dLEGOS skill; preserve the study region and period.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A058", "title": "Climate-Invariant Machine Learning", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Uses physically motivated transformations to improve climate-regime generalisation. It supports testing invariance and extrapolation, rather than assuming historical accuracy persists under warming.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2112.08440", "identity": "Not independently resolved against publication metadata" }, { "id": "A059", "title": "Spatiotemporal Pyramid Flow Matching for Climate Emulation", "area": "Climate emulation and regional downscaling", "category": "Primary or methodological candidate", "summary": "Uses multiscale flow matching for climate emulation. It is a candidate probabilistic generator whose distributional fidelity and physical budgets require separate assessment.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2512.02268", "identity": "Not independently resolved against publication metadata" }, { "id": "A060", "title": "Breaking the link: warming disrupts early-season rainfall predictability in the Caribbean", "area": "Caribbean climate physics", "category": "Primary or methodological candidate", "summary": "Shows that historical absolute-SST relationships with early Caribbean rainfall can weaken as atmospheric stability and circulation change, directly motivating nonstationary predictor tests.", "application": "Evaluate in the caribbean climate physics strand; apply only to its stated variables, scales and task.", "limitation": "A regional association is not a causal mechanism or evidence of dLEGOS skill; preserve the study region and period.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.1038/s41612-026-01325-8", "identity": "Not independently resolved against publication metadata" }, { "id": "A061", "title": "Climate in a Bottle: Towards a Generative Foundation Model for the Kilometer-Scale Global Atmosphere", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Explores generative modelling of kilometre-scale atmospheric states. It supports distributional-emulation comparisons while raising the distinction between plausible samples and dynamically justified trajectories.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2505.06474", "identity": "Not independently resolved against publication metadata" }, { "id": "A062", "title": "Long‐term trends in precipitation and temperature across the Caribbean", "area": "Caribbean climate physics", "category": "Primary or methodological candidate", "summary": "Analyses long-term Caribbean precipitation and temperature trends. It provides regional context for evaluating whether learned models preserve seasonality and climate-change signals.", "application": "Evaluate in the caribbean climate physics strand; apply only to its stated variables, scales and task.", "limitation": "A regional association is not a causal mechanism or evidence of dLEGOS skill; preserve the study region and period.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A063", "title": "ClimateSet: A Large-Scale Climate Model Dataset for Machine Learning", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Assembles a multi-model climate dataset for machine learning. It supports separating within-model emulation from transfer across driving climate models.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2311.03721", "identity": "Not independently resolved against publication metadata" }, { "id": "A064", "title": "ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation", "area": "Physical constraints and scientific learning", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the physical constraints and scientific learning strand; apply only to its stated variables, scales and task.", "limitation": "A small residual or exact aggregation constraint alone does not establish an accurate or closed atmospheric simulation.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A065", "title": "Recent changes in climate extremes in the Caribbean region", "area": "Caribbean climate physics", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the caribbean climate physics strand; apply only to its stated variables, scales and task.", "limitation": "A regional association is not a causal mechanism or evidence of dLEGOS skill; preserve the study region and period.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A066", "title": "Application of the AI2 Climate Emulator to E3SMv2's Global Atmosphere Model, With a Focus on Precipitation Fidelity", "area": "Climate emulation and regional downscaling", "category": "Primary or methodological candidate", "summary": "Tests an atmospheric emulator on E3SMv2 with emphasis on precipitation fidelity. It links long integrations to distributional assessment rather than short forecast accuracy alone.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.1029/2024JH000136", "identity": "Crossref title and metadata match" }, { "id": "A067", "title": "ACE2: Accurately learning subseasonal to decadal atmospheric variability and forced responses", "area": "Climate emulation and regional downscaling", "category": "Primary or methodological candidate", "summary": "Extends an atmospheric emulator to varying boundary conditions and forcing. It provides a direct precedent for assessing daily-to-decadal behaviour and forced climate response separately.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2411.11268", "identity": "Not independently resolved against publication metadata" }, { "id": "A068", "title": "ACE: A fast, skillful learned global atmospheric model for climate prediction", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Develops a stable autoregressive atmospheric emulator with explicit examination of physical budgets. It motivates long-rollout tests and distinguishes learned near-conservation from enforced constraints.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2310.02074", "identity": "Not independently resolved against publication metadata" }, { "id": "A069", "title": "Improving our understanding of future tropical cyclone intensities in the Caribbean using a high-resolution regional climate model", "area": "Caribbean climate physics", "category": "Primary or methodological candidate", "summary": "Uses high-resolution regional modelling to study Caribbean cyclone intensity. It supplies regional dynamical context and highlights the dependence of hazard conclusions on model resolution.", "application": "Evaluate in the caribbean climate physics strand; apply only to its stated variables, scales and task.", "limitation": "A regional association is not a causal mechanism or evidence of dLEGOS skill; preserve the study region and period.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.1038/s41598-023-49685-y", "identity": "Crossref title and metadata match" }, { "id": "A070", "title": "LUCIE: A Lightweight Uncoupled ClImate Emulator with long-term stability\n and physical consistency for O(1000)-member ensembles", "area": "Climate emulation and regional downscaling", "category": "Primary or methodological candidate", "summary": "Develops a lightweight climate emulator for large ensembles. It makes inference efficiency and long-run physical behaviour relevant comparison dimensions for constrained Caribbean emulation.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2405.16297", "identity": "Not independently resolved against publication metadata" }, { "id": "A071", "title": "Changes to Sea Surface Temperatures and Vertical Wind Shear and Their Influence on Tropical Cyclone Activity in the Caribbean and the Main Developing Region", "area": "Caribbean climate physics", "category": "Primary or methodological candidate", "summary": "Studies Caribbean and Atlantic sea-surface-temperature and vertical-wind-shear changes in relation to cyclone activity, supporting physically differentiated predictor groups.", "application": "Evaluate in the caribbean climate physics strand; apply only to its stated variables, scales and task.", "limitation": "A regional association is not a causal mechanism or evidence of dLEGOS skill; preserve the study region and period.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.3390/atmos14060999", "identity": "Crossref title and metadata match" }, { "id": "A072", "title": "ClimaX: A foundation model for weather and climate", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Develops transferable weather and climate representations through foundation-model pretraining. It supports adaptation experiments but does not by itself establish local conservation or station accuracy.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2301.10343", "identity": "Not independently resolved against publication metadata" }, { "id": "A073", "title": "Scaling transformer neural networks for skillful and reliable medium-range weather forecasting", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Studies how transformer scaling affects weather forecasting. It provides a capacity and compute comparator, helping distinguish architectural scale from physically informed gains.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2312.03876", "identity": "Not independently resolved against publication metadata" }, { "id": "A074", "title": "Energy use per hour is key determinant of future transport energy consumption", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Analyses energy use in human transport. It is peripheral to the atmospheric PhD question and should not enter the core methodological argument merely because it is in the collection.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A075", "title": "FuXi-ENS: A machine learning model for medium-range ensemble weather\n forecasting", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Develops a learned ensemble weather system. It supports evaluating spread, calibration and extremes rather than comparing only deterministic ensemble means.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2405.05925", "identity": "Not independently resolved against publication metadata" }, { "id": "A076", "title": "FuXi Weather: A data-to-forecast machine learning system for global weather", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Connects observations to learned global weather forecasts. It supports the distinction between analysis-initialised models and systems that directly ingest observations.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.1038/s41467-025-62024-1", "identity": "Crossref title and metadata match" }, { "id": "A077", "title": "FuXi: a cascade machine learning forecasting system for 15-day global weather forecast", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Uses a cascade of learned models for different forecast horizons. It motivates checking whether horizon-specific training improves stability or simply redistributes error.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.1038/s41612-023-00512-1", "identity": "Crossref title and metadata match" }, { "id": "A078", "title": "Recent intense hurricane response to global climate change", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Examines intense-hurricane changes in relation to anthropogenic forcing. It provides climate-risk context while requiring careful separation of attribution from prediction.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.1007/s00382-013-1713-0", "identity": "Crossref title and metadata match" }, { "id": "A079", "title": "Increasing Magnitude of Hurricane Rapid Intensification in the Central and Eastern Tropical Atlantic", "area": "Caribbean climate physics", "category": "Primary or methodological candidate", "summary": "Studies changes in the magnitude of rapid hurricane intensification. It motivates tail-sensitive evaluation and event-wise withholding rather than mean-error-only validation.", "application": "Evaluate in the caribbean climate physics strand; apply only to its stated variables, scales and task.", "limitation": "A regional association is not a causal mechanism or evidence of dLEGOS skill; preserve the study region and period.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.1029/2018GL077597", "identity": "Not independently resolved against publication metadata" }, { "id": "A080", "title": "An update to ECMWF's machine-learned weather forecast model AIFS", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Updates AIFS using physical consistency constraints, training changes and additional variables. It provides evidence that constraints must be evaluated within the complete forecast system.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2509.18994", "identity": "Not independently resolved against publication metadata" }, { "id": "A081", "title": "AIFS -- ECMWF's data-driven forecasting system", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Describes ECMWF's learned global forecasting system with graph encoders and a transformer processor, supplying a strong data-driven benchmark and a provenance comparison.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2406.01465", "identity": "Not independently resolved against publication metadata" }, { "id": "A082", "title": "Climatic trends and regional climate models intercomparison over the CORDEX‐CAM (Central America, Caribbean, and Mexico) domain", "area": "Caribbean climate physics", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the caribbean climate physics strand; apply only to its stated variables, scales and task.", "limitation": "A regional association is not a causal mechanism or evidence of dLEGOS skill; preserve the study region and period.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A083", "title": "Dynamical Downscaling Projections of Twenty-First-Century Atlantic Hurricane Activity: CMIP3 and CMIP5 Model-Based Scenarios", "area": "Climate emulation and regional downscaling", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A084", "title": "An Operational Deep Learning System for Satellite-Based High-Resolution Global Nowcasting", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Describes an operational satellite-based nowcasting system. It brings observation latency and regional data coverage into the evaluation of practical rainfall prediction.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2510.13050", "identity": "Not independently resolved against publication metadata" }, { "id": "A085", "title": "Future Caribbean temperature and rainfall extremes from statistical downscaling", "area": "Caribbean climate physics", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the caribbean climate physics strand; apply only to its stated variables, scales and task.", "limitation": "A regional association is not a causal mechanism or evidence of dLEGOS skill; preserve the study region and period.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A086", "title": "Caribbean low‐level jets and accompanying moisture fluxes in a global warming climate projected with CMIP3 multi‐model ensemble and fine‐mesh atmospheric general circulation models", "area": "Caribbean climate physics", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the caribbean climate physics strand; apply only to its stated variables, scales and task.", "limitation": "A regional association is not a causal mechanism or evidence of dLEGOS skill; preserve the study region and period.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A087", "title": "Deep Learning for Day Forecasts from Sparse Observations", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Forecasts weather directly from sparse observations. It offers a route beyond reanalysis-only training, with observation availability central to operational comparisons.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2306.06079", "identity": "Not independently resolved against publication metadata" }, { "id": "A088", "title": "Why dry? Investigating the future evolution of the Caribbean Low Level Jet to explain projected Caribbean drying", "area": "Caribbean climate physics", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the caribbean climate physics strand; apply only to its stated variables, scales and task.", "limitation": "A regional association is not a causal mechanism or evidence of dLEGOS skill; preserve the study region and period.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A089", "title": "Deep learning for twelve hour precipitation forecasts", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Extends neural precipitation forecasting to longer lead times. It supports analysing skill as a function of horizon and the environmental information available beyond simple advection.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.1038/s41467-022-32483-x", "identity": "Crossref title and metadata match" }, { "id": "A090", "title": "MetNet: A Neural Weather Model for Precipitation Forecasting", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Introduces a neural precipitation forecast model integrating spatial context and temporal observations. It provides an architecture baseline rather than a guarantee of local transfer.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2003.12140", "identity": "Not independently resolved against publication metadata" }, { "id": "A091", "title": "Future climate of the Caribbean from a regional climate model", "area": "Caribbean climate physics", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the caribbean climate physics strand; apply only to its stated variables, scales and task.", "limitation": "A regional association is not a causal mechanism or evidence of dLEGOS skill; preserve the study region and period.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A092", "title": "A foundation model for the Earth system", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Presents Aurora as a transferable Earth-system foundation model. It motivates adaptation across variables while requiring new tests for coastal geometry, extremes and training-data dependence.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.1038/s41586-025-09005-y", "identity": "Not independently resolved against publication metadata" }, { "id": "A093", "title": "Future Caribbean Climates in a World of Rising Temperatures: The 1.5 vs 2.0 Dilemma", "area": "Caribbean climate physics", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the caribbean climate physics strand; apply only to its stated variables, scales and task.", "limitation": "A regional association is not a causal mechanism or evidence of dLEGOS skill; preserve the study region and period.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A094", "title": "FourCastNet 3: A geometric approach to probabilistic machine-learning weather forecasting at scale", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Develops geometry-aware probabilistic global weather forecasting. It supports comparing spherical representations and ensemble generation with the cost of iterative sampling.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2507.12144", "identity": "Not independently resolved against publication metadata" }, { "id": "A095", "title": "Climate Response to Anomalously Large and Small Atlantic Warm Pools during the Summer", "area": "Methods and adjacent applications", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A096", "title": "FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Uses adaptive Fourier neural operators for global weather prediction. It supplies a spectral architecture baseline and motivates explicit treatment of geometry and rollout error.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2202.11214", "identity": "Not independently resolved against publication metadata" }, { "id": "A097", "title": "Deep learning in the abyss: a stratified Physics Informed Neural Network\n for data assimilation", "area": "Physical constraints and scientific learning", "category": "Primary or methodological candidate", "summary": "Reconstructs layered ocean flow from sparse pseudo-observations using a stratified PINN. It is a close inverse-modelling precedent, with idealised dynamics and observation assumptions limiting atmospheric transfer.", "application": "Evaluate in the physical constraints and scientific learning strand; apply only to its stated variables, scales and task.", "limitation": "A small residual or exact aggregation constraint alone does not establish an accurate or closed atmospheric simulation.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2503.19160", "identity": "Not independently resolved against publication metadata" }, { "id": "A098", "title": "Towards Optimally Weighted Physics-Informed Neural Networks in Ocean\n Modelling", "area": "Physical constraints and scientific learning", "category": "Primary or methodological candidate", "summary": "Examines loss weighting for ocean PINNs. It supports testing optimisation sensitivity and competing physical and data residuals rather than choosing weights by intuition.", "application": "Evaluate in the physical constraints and scientific learning strand; apply only to its stated variables, scales and task.", "limitation": "A small residual or exact aggregation constraint alone does not establish an accurate or closed atmospheric simulation.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2106.08747", "identity": "Not independently resolved against publication metadata" }, { "id": "A099", "title": "Investigating the link between early season Caribbean rainfall and the El Niño + 1 year", "area": "Caribbean climate physics", "category": "Primary or methodological candidate", "summary": "Studies links between early Caribbean rainfall and the year following El Niño. It supports season-specific predictors and cautions against one invariant teleconnection model for the whole year.", "application": "Evaluate in the caribbean climate physics strand; apply only to its stated variables, scales and task.", "limitation": "A regional association is not a causal mechanism or evidence of dLEGOS skill; preserve the study region and period.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.1002/joc.711", "identity": "Crossref title and metadata match" }, { "id": "A100", "title": "The Neural Particle Method -- An Updated Lagrangian Physics Informed\n Neural Network for Computational Fluid Dynamics", "area": "Physical constraints and scientific learning", "category": "Primary or methodological candidate", "summary": "Introduces an updated Lagrangian PINN particle method for fluid simulation. It supplies a discretisation alternative whose applicability depends on free surfaces, coordinates and numerical consistency.", "application": "Evaluate in the physical constraints and scientific learning strand; apply only to its stated variables, scales and task.", "limitation": "A small residual or exact aggregation constraint alone does not establish an accurate or closed atmospheric simulation.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.1016/j.cma.2020.113127", "identity": "Not independently resolved against publication metadata" }, { "id": "A101", "title": "Interannual Variability of Caribbean Rainfall, ENSO, and the Atlantic Ocean*", "area": "Caribbean climate physics", "category": "Primary or methodological candidate", "summary": "Explains interannual Caribbean rainfall in terms of coupled ocean-atmosphere patterns. It motivates regional boundary forcing rather than treating each Jamaican cell as independent.", "application": "Evaluate in the caribbean climate physics strand; apply only to its stated variables, scales and task.", "limitation": "A regional association is not a causal mechanism or evidence of dLEGOS skill; preserve the study region and period.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A102", "title": "Simplifying Hamiltonian and Lagrangian Neural Networks via Explicit\n Constraints", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Enforces explicit constraints in Hamiltonian and Lagrangian neural formulations. It provides an inductive-bias comparison whose conservative mechanics assumptions need modification for moist dissipative flow.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2010.13581", "identity": "Not independently resolved against publication metadata" }, { "id": "A103", "title": "Lagrangian Neural Networks", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Learns Lagrangian representations of dynamical systems. It supports structured dynamics, but an open atmospheric volume cannot generally be represented as a closed conservative mechanical system.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2003.04630", "identity": "Not independently resolved against publication metadata" }, { "id": "A104", "title": "Influence of the tropical Atlantic versus the tropical Pacific on Caribbean rainfall", "area": "Caribbean climate physics", "category": "Primary or methodological candidate", "summary": "Distinguishes tropical Atlantic and Pacific influences on Caribbean rainfall across seasons. It provides a central regional mechanism and a test of context-variable selection.", "application": "Evaluate in the caribbean climate physics strand; apply only to its stated variables, scales and task.", "limitation": "A regional association is not a causal mechanism or evidence of dLEGOS skill; preserve the study region and period.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.1029/2001JC001097", "identity": "Not independently resolved against publication metadata" }, { "id": "A105", "title": "Caribbean precipitation: review, model and prospect", "area": "Caribbean climate physics", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the caribbean climate physics strand; apply only to its stated variables, scales and task.", "limitation": "A regional association is not a causal mechanism or evidence of dLEGOS skill; preserve the study region and period.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A106", "title": "A Framework for Hybrid Physics-AI Coupled Ocean Models", "area": "Observations and Earth representations", "category": "Primary or methodological candidate", "summary": "Develops a hybrid ocean-model coupling framework combining learned and physical components. It motivates conservation and feedback diagnostics at interfaces between modules.", "application": "Evaluate in the observations and earth representations strand; apply only to its stated variables, scales and task.", "limitation": "A retrieval, embedding or reanalysis is not independent ground truth; quantify shared inputs and errors.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2510.22676", "identity": "Not independently resolved against publication metadata" }, { "id": "A107", "title": "Revisiting mechanisms of the Mesoamerican Midsummer drought", "area": "Caribbean climate physics", "category": "Primary or methodological candidate", "summary": "Reassesses mechanisms of the Mesoamerican midsummer drought. It provides regional process context without implying that all Caribbean islands share one seasonal cycle.", "application": "Evaluate in the caribbean climate physics strand; apply only to its stated variables, scales and task.", "limitation": "A regional association is not a causal mechanism or evidence of dLEGOS skill; preserve the study region and period.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.1007/s00382-022-06338-6", "identity": "Crossref title and metadata match" }, { "id": "A108", "title": "Air-sea interactions and dynamical processes associated with the midsummer drought", "area": "Caribbean climate physics", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the caribbean climate physics strand; apply only to its stated variables, scales and task.", "limitation": "A regional association is not a causal mechanism or evidence of dLEGOS skill; preserve the study region and period.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A109", "title": "Beyond the Training Data: Confidence-Guided Mixing of Parameterizations in a Hybrid AI-Climate Model", "area": "Physical constraints and scientific learning", "category": "Primary or methodological candidate", "summary": "Mixes parameterisations using confidence information under conditions beyond the training data. It motivates abstention or fallback strategies for unfamiliar atmospheric states.", "application": "Evaluate in the physical constraints and scientific learning strand; apply only to its stated variables, scales and task.", "limitation": "A small residual or exact aggregation constraint alone does not establish an accurate or closed atmospheric simulation.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2510.08107", "identity": "Not independently resolved against publication metadata" }, { "id": "A110", "title": "The midsummer drought over Mexico and Central America", "area": "Caribbean climate physics", "category": "Primary or methodological candidate", "summary": "Examines the midsummer drought over Mexico and Central America, supplying a regional circulation and rainfall-seasonality reference for wider Caribbean comparisons.", "application": "Evaluate in the caribbean climate physics strand; apply only to its stated variables, scales and task.", "limitation": "A regional association is not a causal mechanism or evidence of dLEGOS skill; preserve the study region and period.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A111", "title": "Winter and Summer Structure of the Caribbean Low-Level Jet", "area": "Caribbean climate physics", "category": "Primary or methodological candidate", "summary": "Diagnoses winter and summer structure of the Caribbean low-level jet and its hydroclimatic relationships, directly supporting wind-profile and moisture-transport evaluation.", "application": "Evaluate in the caribbean climate physics strand; apply only to its stated variables, scales and task.", "limitation": "A regional association is not a causal mechanism or evidence of dLEGOS skill; preserve the study region and period.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.1175/2007JCLI1855.1", "identity": "Not independently resolved against publication metadata" }, { "id": "A112", "title": "Features of the Caribbean low level jet", "area": "Caribbean climate physics", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the caribbean climate physics strand; apply only to its stated variables, scales and task.", "limitation": "A regional association is not a causal mechanism or evidence of dLEGOS skill; preserve the study region and period.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A113", "title": "Stable climate simulations using a realistic general circulation model with neural network parameterizations for atmospheric moist physics and radiation processes", "area": "Physical constraints and scientific learning", "category": "Primary or methodological candidate", "summary": "Integrates learned moist-physics and radiation parameterisations into a general circulation model. It supports judging learned closures through stable coupled integrations rather than offline accuracy alone.", "application": "Evaluate in the physical constraints and scientific learning strand; apply only to its stated variables, scales and task.", "limitation": "A small residual or exact aggregation constraint alone does not establish an accurate or closed atmospheric simulation.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.5194/gmd-15-3923-2022", "identity": "Crossref title and metadata match" }, { "id": "A114", "title": "Physics-informed deep-learning parameterization of ocean vertical mixing improves climate simulations", "area": "Physical constraints and scientific learning", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the physical constraints and scientific learning strand; apply only to its stated variables, scales and task.", "limitation": "A small residual or exact aggregation constraint alone does not establish an accurate or closed atmospheric simulation.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A115", "title": "Deep learning and process understanding for data-driven Earth system science", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Connects deep learning to process understanding in Earth-system science. It motivates explanatory diagnostics and clear physical questions rather than architecture-led research.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A116", "title": "CORDEX-ML-Bench: A Benchmark for Data-Driven Regional Climate Downscaling—Experiment Design and Overview", "area": "Climate emulation and regional downscaling", "category": "Primary or methodological candidate", "summary": "Sets out a benchmark design for regional downscaling. As a recent manuscript, it supports comparison design while its protocol and evaluation scope require version-specific reading.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2606.29172", "identity": "Not independently resolved against publication metadata" }, { "id": "A117", "title": "Graph neural networks for hourly precipitation projections at the convection permitting scale with a novel hybrid imperfect framework", "area": "Methods and adjacent applications", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A118", "title": "On the suitability of a convolutional neural network based RCM-emulator for fine spatio-temporal precipitation", "area": "Methods and adjacent applications", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A119", "title": "Deep Learning Regional Climate Model Emulators: A Comparison of Two Downscaling Training Frameworks", "area": "Climate emulation and regional downscaling", "category": "Primary or methodological candidate", "summary": "Compares downscaling training frameworks for regional-model emulation. It shows why the source of predictors and targets determines the meaning of apparent emulator skill.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.1029/2022MS003593", "identity": "Not independently resolved against publication metadata" }, { "id": "A120", "title": "Statistical Downscaling and Bias Correction for Climate Research", "area": "Climate emulation and regional downscaling", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A121", "title": "Transferability and Explainability of Deep Learning Emulators for Regional Climate Model Projections: Perspectives for Future Applications", "area": "Climate emulation and regional downscaling", "category": "Primary or methodological candidate", "summary": "Studies transferability and explanation of regional climate emulators, directly supporting tests across driving models, forcing conditions and physically distinct regimes.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.1175/AIES-D-23-0099.1", "identity": "Crossref title and metadata match" }, { "id": "A122", "title": "Multivariate bias correction and downscaling of climate models with trend-preserving deep learning", "area": "Climate emulation and regional downscaling", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A123", "title": "Training Physics-Based Machine-Learning Parameterizations With Gradient-Free Ensemble Kalman Methods", "area": "Physical constraints and scientific learning", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the physical constraints and scientific learning strand; apply only to its stated variables, scales and task.", "limitation": "A small residual or exact aggregation constraint alone does not establish an accurate or closed atmospheric simulation.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A124", "title": "Diffusion Model-based Probabilistic Downscaling for 180-year East Asian Climate Reconstruction", "area": "Climate emulation and regional downscaling", "category": "Primary or methodological candidate", "summary": "Uses diffusion-based downscaling for historical climate reconstruction. It motivates probabilistic reconstruction while separating enhanced resolution from independent recovery of past atmospheric states.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A125", "title": "Conditional diffusion models for downscaling and bias correction of Earth system model precipitation", "area": "Climate emulation and regional downscaling", "category": "Primary or methodological candidate", "summary": "Combines diffusion-based precipitation downscaling with bias correction. It supports treating structural generation, distributional adjustment and preservation of climate signals as separate obligations.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2404.14416", "identity": "Not independently resolved against publication metadata" }, { "id": "A126", "title": "Dynamical-generative downscaling of climate model ensembles", "area": "Climate emulation and regional downscaling", "category": "Primary or methodological candidate", "summary": "Combines intermediate-resolution dynamical downscaling with generative refinement. It is a close hybrid comparator that limits claims that combining physics and generative AI is itself novel.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.1073/pnas.2420288122", "identity": "Not independently resolved against publication metadata" }, { "id": "A127", "title": "Perspectives of physics-based machine learning strategies for geoscientific applications governed by partial differential equations", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Reviews physics-based machine learning for PDE-governed geoscience. It provides the broader methodological setting for selecting meaningful constraints and assessing approximation errors.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.5194/gmd-16-7375-2023", "identity": "Not independently resolved against publication metadata" }, { "id": "A128", "title": "Machine learning emulation of precipitation from km-scale UK regional climate simulations using a diffusion model", "area": "Climate emulation and regional downscaling", "category": "Primary or methodological candidate", "summary": "Uses diffusion to emulate precipitation from kilometre-scale regional simulations. It supplies a strong generative comparator and demonstrates the distinction between parent-model fidelity and observational realism.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2407.14158", "identity": "Not independently resolved against publication metadata" }, { "id": "A129", "title": "Learning earth system models from observations: machine learning or data assimilation?", "area": "Methods and adjacent applications", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A130", "title": "On the Extrapolation of Generative Adversarial Networks for downscaling\n precipitation extremes in warmer climates", "area": "Climate emulation and regional downscaling", "category": "Primary or methodological candidate", "summary": "Tests adversarial downscaling outside its historical temperature range, directly motivating warming and extreme-regime holdouts rather than random-split interpolation tests.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "Readable text retrieved; not independently replicated", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A131", "title": "A Reliable Generative Adversarial Network Approach for Climate Downscaling and Weather Generation", "area": "Climate emulation and regional downscaling", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A132", "title": "Fast and accurate learned multiresolution dynamical downscaling for\n precipitation", "area": "Climate emulation and regional downscaling", "category": "Primary or methodological candidate", "summary": "Compares neural multiresolution precipitation emulators and loss choices. It supports comparing statistical fidelity, generation quality and runtime under a shared target definition.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2101.06813", "identity": "Not independently resolved against publication metadata" }, { "id": "A133", "title": "A Generative Deep Learning Approach to Stochastic Downscaling of\n Precipitation Forecasts", "area": "Climate emulation and regional downscaling", "category": "Primary or methodological candidate", "summary": "Generates spatially coherent stochastic precipitation downscaling from forecast-model output. It provides a probabilistic baseline and a warning against treating one sample as the forecast distribution.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.1029/2022MS003120", "identity": "Crossref title and metadata match" }, { "id": "A134", "title": "Living in the Physics and Machine Learning Interplay for Earth\n Observation", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Discusses the interaction of physics and machine learning in Earth observation. It supports matching physical knowledge to the retrieval or prediction task rather than using a generic physics label.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2010.09031", "identity": "Not independently resolved against publication metadata" }, { "id": "A135", "title": "Correcting Coarse-Grid Weather and Climate Models by Machine Learning From Global Storm-Resolving Simulations", "area": "Weather prediction and uncertainty", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A136", "title": "Stochastic Super-Resolution for Downscaling Time-Evolving Atmospheric Fields with a Generative Adversarial Network", "area": "Climate emulation and regional downscaling", "category": "Primary or methodological candidate", "summary": "Uses adversarial super-resolution for time-varying atmospheric fields. It supports testing temporal coherence as well as spatial sharpness in reconstructed rainfall sequences.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2005.10374", "identity": "Not independently resolved against publication metadata" }, { "id": "A137", "title": "Advancing Parsimonious Deep Learning Weather Prediction using the HEALPix Mesh", "area": "Weather prediction and uncertainty", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A138", "title": "Improving Data‐Driven Global Weather Prediction Using Deep Convolutional Neural Networks on a Cubed Sphere", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Uses convolutional weather prediction on a cubed sphere. It provides a geometry-aware comparator and illustrates why map topology can influence learned dynamics.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2003.11927", "identity": "Not independently resolved against publication metadata" }, { "id": "A139", "title": "Accurate medium-range global weather forecasting with 3D neural networks", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Uses three-dimensional neural representations for medium-range global weather forecasting. It is a global prediction benchmark whose skill does not directly establish island-scale precipitation fidelity.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.1038/s41586-023-06185-3", "identity": "Not independently resolved against publication metadata" }, { "id": "A140", "title": "Hard-Constrained Deep Learning for Climate Downscaling", "area": "Physical constraints and scientific learning", "category": "Primary or methodological candidate", "summary": "Enforces coarse-to-fine aggregation constraints in learned downscaling. It provides a direct precedent for exact conservation and requires testing sensitivity to errors in the imposed coarse totals.", "application": "Evaluate in the physical constraints and scientific learning strand; apply only to its stated variables, scales and task.", "limitation": "A small residual or exact aggregation constraint alone does not establish an accurate or closed atmospheric simulation.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2208.05424", "identity": "Not independently resolved against publication metadata" }, { "id": "A141", "title": "Mitigating Time Discretization Challenges with WeatherODE: A Sandwich\n Physics-Driven Neural ODE for Weather Forecasting", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Combines learned evolution with a physics-driven neural ODE formulation, addressing time-discretisation effects that can be hidden by fixed-step evaluation.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2410.06560", "identity": "Not independently resolved against publication metadata" }, { "id": "A142", "title": "PIANO: Physics Informed Autoregressive Network", "area": "Physical constraints and scientific learning", "category": "Primary or methodological candidate", "summary": "Develops a physics-informed autoregressive architecture. Its role is a structured temporal comparator, with conservation and extrapolation requiring task-specific verification.", "application": "Evaluate in the physical constraints and scientific learning strand; apply only to its stated variables, scales and task.", "limitation": "A small residual or exact aggregation constraint alone does not establish an accurate or closed atmospheric simulation.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2508.16235", "identity": "Not independently resolved against publication metadata" }, { "id": "A143", "title": "Deep-learning based down-scaling of summer monsoon rainfall data over\n Indian region", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Applies deep downscaling to Indian summer-monsoon rainfall. It contributes an external complex-rainfall comparison while requiring caution about transferring monsoon-specific results to Caribbean islands.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.1007/s00704-020-03489-6", "identity": "Crossref title and metadata match" }, { "id": "A144", "title": "Clifford Neural Layers for PDE Modeling", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Uses Clifford algebra layers for PDE modelling. It motivates testing transformations of multicomponent physical quantities, without establishing that geometric structure guarantees forecast accuracy.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2209.04934", "identity": "Not independently resolved against publication metadata" }, { "id": "A145", "title": "Fourier Neural Operator with Learned Deformations for PDEs on General Geometries", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Uses learned geometric deformations in a Fourier neural operator. It supports irregular-domain representation and terrain-sensitive modelling rather than assuming a rectangular spectral grid is sufficient.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2207.05209", "identity": "Not independently resolved against publication metadata" }, { "id": "A146", "title": "High-resolution downscaling of CMIP6 Earth system and global climate models using deep learning for Iberia", "area": "Climate emulation and regional downscaling", "category": "Primary or methodological candidate", "summary": "Downscales CMIP6 temperature and precipitation over Iberia. It supplies an external projection comparison and a testbed for whether climate-change signals survive refinement.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.5194/gmd-17-229-2024", "identity": "Not independently resolved against publication metadata" }, { "id": "A147", "title": "Fourier Neural Operator for Parametric Partial Differential Equations", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Learns mappings between function spaces through Fourier kernels. It provides an operator-learning baseline, whose tested PDEs and boundary conditions must not be confused with full moist atmospheric dynamics.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2010.08895", "identity": "Not independently resolved against publication metadata" }, { "id": "A148", "title": "DeepPhysiNet: Bridging Deep Learning and Atmospheric Physics for\n Accurate and Continuous Weather Modeling", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Combines deep learning and atmospheric physics for continuous weather modelling. It is a close comparator for coordinate-based atmospheric reconstruction and weakens broad novelty claims based on continuity alone.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2401.04125", "identity": "Not independently resolved against publication metadata" }, { "id": "A149", "title": "Complementing Dynamical Downscaling With Super‐Resolution Convolutional Neural Networks", "area": "Climate emulation and regional downscaling", "category": "Primary or methodological candidate", "summary": "Uses super-resolution convolutional networks to complement dynamical downscaling. It supports hybrid benchmarking and establishes that learned refinement of dynamical output predates dLEGOS.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.1029/2024GL111828", "identity": "Crossref title and metadata match" }, { "id": "A150", "title": "M‐ENIAC: A Physics‐Informed Machine Learning Recreation of the First Successful Numerical Weather Forecasts", "area": "Physical constraints and scientific learning", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the physical constraints and scientific learning strand; apply only to its stated variables, scales and task.", "limitation": "A small residual or exact aggregation constraint alone does not establish an accurate or closed atmospheric simulation.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A151", "title": "Deep Learning for Daily Precipitation and Temperature Downscaling", "area": "Climate emulation and regional downscaling", "category": "Primary or methodological candidate", "summary": "Downscales daily precipitation and temperature using deep learning. It supports multivariable regional targets and motivates separate evaluation of occurrence, magnitude and temperature bias.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.1029/2020WR029308", "identity": "Not independently resolved against publication metadata" }, { "id": "A152", "title": "Physics-Informed Learning of Aerosol Microphysics", "area": "Physical constraints and scientific learning", "category": "Primary or methodological candidate", "summary": "Applies physics-informed learning to aerosol microphysics. It provides a closure-learning analogy whose chemical and microphysical processes require explicitly defined state variables and conservation terms.", "application": "Evaluate in the physical constraints and scientific learning strand; apply only to its stated variables, scales and task.", "limitation": "A small residual or exact aggregation constraint alone does not establish an accurate or closed atmospheric simulation.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2207.11786", "identity": "Not independently resolved against publication metadata" }, { "id": "A153", "title": "Modeling Global Surface Dust Deposition Using Physics-Informed Neural Networks", "area": "Physical constraints and scientific learning", "category": "Primary or methodological candidate", "summary": "Applies PINNs to dust deposition, providing a geophysical transport-and-sink example. Its relevance is formulation of sources and losses rather than direct validation of rainfall prediction.", "application": "Evaluate in the physical constraints and scientific learning strand; apply only to its stated variables, scales and task.", "limitation": "A small residual or exact aggregation constraint alone does not establish an accurate or closed atmospheric simulation.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.1038/s43247-024-01942-2", "identity": "Not independently resolved against publication metadata" }, { "id": "A154", "title": "Downscaling CORDEX Through Deep Learning to Daily 1 km Multivariate Ensemble in Complex Terrain", "area": "Climate emulation and regional downscaling", "category": "Primary or methodological candidate", "summary": "Downscales CORDEX output in complex terrain using multivariate ensembles. It supports assessing spatial scale, cross-variable dependence and ensembles together.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "Readable text retrieved; not independently replicated", "identifier": "https://doi.org/10.1029/2023EF003531", "identity": "Not independently resolved against publication metadata" }, { "id": "A155", "title": "On the suitability of deep convolutional neural networks for continental-wide downscaling of climate change projections", "area": "Climate emulation and regional downscaling", "category": "Primary or methodological candidate", "summary": "Examines CNN downscaling of climate projections beyond perfect-predictor settings. It motivates verifying predictor-domain shifts and extrapolation before future-climate claims.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.1007/s00382-021-05847-0", "identity": "Crossref title and metadata match" }, { "id": "A156", "title": "Downscaling multi-model climate projection ensembles with deep learning (DeepESD): contribution to CORDEX EUR-44", "area": "Climate emulation and regional downscaling", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A157", "title": "Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations", "area": "Physical constraints and scientific learning", "category": "Primary or methodological candidate", "summary": "Introduces PINNs for data-driven PDE solutions and inverse problems. It establishes the underlying residual-based formulation, with later geophysical work needed to assess practical atmospheric scalability.", "application": "Evaluate in the physical constraints and scientific learning strand; apply only to its stated variables, scales and task.", "limitation": "A small residual or exact aggregation constraint alone does not establish an accurate or closed atmospheric simulation.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/1711.10561", "identity": "Not independently resolved against publication metadata" }, { "id": "A158", "title": "Physics-informed neural networks for modeling atmospheric radiative transfer", "area": "Physical constraints and scientific learning", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the physical constraints and scientific learning strand; apply only to its stated variables, scales and task.", "limitation": "A small residual or exact aggregation constraint alone does not establish an accurate or closed atmospheric simulation.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A159", "title": "PINT: Physics-Informed Neural Time Series Models with Applications to Long-term Inference on WeatherBench 2m-Temperature Data", "area": "Physical constraints and scientific learning", "category": "Primary or methodological candidate", "summary": "Applies physics-informed temporal modelling to WeatherBench temperature. It supports a temporal baseline but does not establish that temperature-only performance transfers to coupled moist dynamics.", "application": "Evaluate in the physical constraints and scientific learning strand; apply only to its stated variables, scales and task.", "limitation": "A small residual or exact aggregation constraint alone does not establish an accurate or closed atmospheric simulation.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2502.04018", "identity": "Not independently resolved against publication metadata" }, { "id": "A160", "title": "Configuration and intercomparison of deep learning neural models for statistical downscaling", "area": "Climate emulation and regional downscaling", "category": "Primary or methodological candidate", "summary": "Compares neural downscaling configurations with traditional methods under a common validation framework. It supports benchmarking complexity against strong statistical alternatives.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.5194/gmd-13-2109-2020", "identity": "Crossref title and metadata match" }, { "id": "A161", "title": "Designing Sub-Regional Anticipatory Action for Hurricanes in the Eastern Caribbean", "area": "Caribbean climate physics", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the caribbean climate physics strand; apply only to its stated variables, scales and task.", "limitation": "A regional association is not a causal mechanism or evidence of dLEGOS skill; preserve the study region and period.", "access": "Full text unavailable through this retrieval", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A162", "title": "On the limitations of deep learning for statistical downscaling of climate change projections: The transferability and the extrapolation issues", "area": "Climate emulation and regional downscaling", "category": "Primary or methodological candidate", "summary": "Tests transferability and extrapolation limits of neural climate downscaling through pseudo-reality experiments. It directly motivates separating parent-model fidelity from generalisation to unseen climates.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.1002/asl.1195", "identity": "Crossref title and metadata match" }, { "id": "A163", "title": "High-Resolution Climate Projections Using Diffusion-Based Downscaling of a Lightweight Climate Emulator", "area": "Climate emulation and regional downscaling", "category": "Primary or methodological candidate", "summary": "Combines a lightweight climate emulator with diffusion-based refinement. It supplies a close end-to-end comparator and requires separate tests of emulator drift and downscaling fidelity.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2602.13416", "identity": "Not independently resolved against publication metadata" }, { "id": "A164", "title": "DeepSD: Generating High Resolution Climate Change Projections through\n Single Image Super-Resolution", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Uses stacked super-resolution networks for climate downscaling. It provides an early neural benchmark and shows that increased output resolution alone is not a new methodological contribution.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/1703.03126", "identity": "Not independently resolved against publication metadata" }, { "id": "A165", "title": "Regional climate model emulator based on deep learning: concept and first evaluation of a novel hybrid downscaling approach", "area": "Climate emulation and regional downscaling", "category": "Primary or methodological candidate", "summary": "Introduces a learned regional-model emulator for daily temperature. It establishes the regional-emulation lineage and distinguishes model emulation from observational prediction.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.1007/s00382-022-06343-9", "identity": "Crossref title and metadata match" }, { "id": "A166", "title": "Advancing Seasonal Prediction of Tropical Cyclone Activity with a Hybrid AI-Physics Climate Model", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Tests a hybrid climate model for seasonal cyclone activity. It motivates examining event statistics and climate context, rather than assuming short-range forecast skill establishes seasonal predictability.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://anara.com", "identity": "Not independently resolved against publication metadata" }, { "id": "A167", "title": "Probabilistic weather forecasting with machine learning", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Uses generative machine learning for probabilistic global forecasting. It supports ensemble verification and the distinction between improved deterministic scores and reliable probabilities.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.1038/s41586-024-08252-9", "identity": "Crossref title and metadata match" }, { "id": "A168", "title": "GraphCast: Learning skillful medium-range global weather forecasting", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Uses a multimesh graph neural network for global medium-range weather forecasting. It supplies a strong graph-based benchmark while retaining dependence on analysed training states.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2212.12794", "identity": "Not independently resolved against publication metadata" }, { "id": "A169", "title": "Neural General Circulation Models for Weather and Climate", "area": "Climate emulation and regional downscaling", "category": "Primary or methodological candidate", "summary": "Combines a differentiable dynamical core with learned physical parameterisations. It directly supports hybrid atmospheric modelling, while limiting novelty claims based only on combining physics with AI.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2311.07222", "identity": "Not independently resolved against publication metadata" }, { "id": "A170", "title": "Modelling Climate Change Impacts on Tropical Dry Forest Fauna", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Links Jamaican dry-forest fauna to rainfall and temperature variability. It motivates local impact relevance but does not validate the atmospheric model or establish ecological transfer under changed conditions.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.3390/su14084760", "identity": "Crossref title and metadata match" }, { "id": "A171", "title": "PCE-PINNs: Physics-Informed Neural Networks for Uncertainty Propagation\n in Ocean Modeling", "area": "Physical constraints and scientific learning", "category": "Primary or methodological candidate", "summary": "Combines polynomial-chaos uncertainty propagation with PINNs for ocean modelling. It motivates uncertainty in physical parameters rather than treating optimisation variability as the entire uncertainty budget.", "application": "Evaluate in the physical constraints and scientific learning strand; apply only to its stated variables, scales and task.", "limitation": "A small residual or exact aggregation constraint alone does not establish an accurate or closed atmospheric simulation.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2105.02939", "identity": "Not independently resolved against publication metadata" }, { "id": "A172", "title": "Generating Projections for the Caribbean at 1.5, 2.0 and 2.5 °C from a High-Resolution Ensemble", "area": "Caribbean climate physics", "category": "Primary or methodological candidate", "summary": "Uses a regional-model ensemble to assess Caribbean conditions at specified warming levels. It supplies a regional projection benchmark and distinguishes forcing-conditioned climate response from weather forecasts.", "application": "Evaluate in the caribbean climate physics strand; apply only to its stated variables, scales and task.", "limitation": "A regional association is not a causal mechanism or evidence of dLEGOS skill; preserve the study region and period.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://doi.org/10.3390/atmos12030328", "identity": "Not independently resolved against publication metadata" }, { "id": "A173", "title": "ClimODE: Climate and Weather Forecasting with Physics-informed Neural\n ODEs", "area": "Physical constraints and scientific learning", "category": "Primary or methodological candidate", "summary": "Uses a physics-informed neural ODE with transport, compression and source terms for weather evolution. It is a close structural comparator, requiring careful matching of prognostic variables and closure assumptions.", "application": "Evaluate in the physical constraints and scientific learning strand; apply only to its stated variables, scales and task.", "limitation": "A small residual or exact aggregation constraint alone does not establish an accurate or closed atmospheric simulation.", "access": "All numbered pages retrieved; analytical annotation available", "identifier": "https://arxiv.org/abs/2404.10024", "identity": "Not independently resolved against publication metadata" }, { "id": "D001", "title": "CARIB_Diff_Reference_Tracker-v4.xlsx", "area": "Methods and adjacent applications", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Register or archive; not a research-paper text", "identifier": "https://docs.google.com/spreadsheets/d/1xMZOXyo2RD0jBVeM0fTaXIxGM-JWamaN/edit?usp=drivesdk&ouid=114437531400852940319&rtpof=true&sd=true", "identity": "Not independently resolved against publication metadata" }, { "id": "D002", "title": "Literature Review Tracker", "area": "Methods and adjacent applications", "category": "Unappraised metadata", "summary": "Metadata or collection record only. No finding is attributed from this entry; obtain and appraise the full text before evidential use.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Register or archive; not a research-paper text", "identifier": "https://docs.google.com/spreadsheets/d/1fIClpmHyJfQLhS8lp-1q-KZc1MeH4JbdjleLo09b7ow/edit?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D003", "title": "2019_Lebedev_Precipitation_Nowcasting_with_Satellite_Imagery.pdf", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Develops satellite-image precipitation nowcasting, providing an image-sequence baseline whose predictive task differs from reconstructing an atmospheric state.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1yOl64RX0VEviiC402lmsY-RAmR2eJVyl/view?usp=drivesdk", "identity": "Crossref title and metadata match" }, { "id": "D004", "title": "2025_Cat_o_Precipitation_nowcasting_of_satellite_data_using_physically.pdf", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Studies physically motivated satellite nowcasting. It supports testing which physical assumptions improve lead-time-specific rainfall estimates rather than assuming all physics penalties help.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1iVbUw05WGFSVKuaPkoANb1FjRpS78drv/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D005", "title": "2015_Funk_The_climate_hazards_infrared_precipitation_with_stations_a_n.pdf", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Introduces CHIRPS, a long precipitation record combining infrared satellite information and stations. Its construction makes station overlap and spatial support important in validation.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1dauBm9F2-hZJpI9rrvxMaOoE0PAwjQ3A/view?usp=drivesdk", "identity": "Crossref title and metadata match" }, { "id": "D006", "title": "2024_Szwarcman_Prithvi_EO_2_0_A_Versatile_Multi_Temporal_Foundation_Model_f.pdf", "area": "Observations and Earth representations", "category": "Primary or methodological candidate", "summary": "Describes a multi-temporal Earth-observation foundation model. Its representations are possible predictors, not independent evidence of atmospheric consistency.", "application": "Evaluate in the observations and earth representations strand; apply only to its stated variables, scales and task.", "limitation": "A retrieval, embedding or reanalysis is not independent ground truth; quantify shared inputs and errors.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1nHcjd9bwnj-ukd0UdLFE4S31J8-CnnQ3/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D007", "title": "Future_climate_of_the_Caribbean_from_a_regional_cl.pdf", "area": "Caribbean climate physics", "category": "Primary or methodological candidate", "summary": "Assesses future Caribbean climate with a regional climate model, connecting regional forcing and resolution choices to the physical interpretation of projected change.", "application": "Evaluate in the caribbean climate physics strand; apply only to its stated variables, scales and task.", "limitation": "A regional association is not a causal mechanism or evidence of dLEGOS skill; preserve the study region and period.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1TmWpkcJoHrvGI61gf_iM_MJAX97rcIkb/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D008", "title": "Assessing the effect of domain size over the Caribbean region using the PRECIS.pdf", "area": "Caribbean climate physics", "category": "Primary or methodological candidate", "summary": "Tests the effect of regional-model domain size over the Caribbean, demonstrating that domain and boundary choices belong in the uncertainty assessment.", "application": "Evaluate in the caribbean climate physics strand; apply only to its stated variables, scales and task.", "limitation": "A regional association is not a causal mechanism or evidence of dLEGOS skill; preserve the study region and period.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1eDHFMMpC0FHzJY-7WZ41CtHHbtPJbjwc/view?usp=drivesdk", "identity": "Crossref title and metadata match" }, { "id": "D009", "title": "Regional_climate_model_emulator_based_on_deep_lear.pdf", "area": "Climate emulation and regional downscaling", "category": "Primary or methodological candidate", "summary": "Develops and evaluates a learned regional climate-model emulator, providing a close comparator for the emulation component of the PhD.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1WQy-9GJvU46crQ6Yta0LI9myUHh_5RUi/view?usp=drivesdk", "identity": "Rejected title mismatch" }, { "id": "D010", "title": "Deep_Learning_Regional_Climate_Model_Emulators_A_C.pdf", "area": "Climate emulation and regional downscaling", "category": "Primary or methodological candidate", "summary": "Compares two training frameworks for regional climate emulation, motivating explicit control of training targets and transfer conditions.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1mtToMadW98WM0ZxKb-RnROTx1hjUNEko/view?usp=drivesdk", "identity": "Rejected title mismatch" }, { "id": "D011", "title": "Generating physically-consistent high-resolution climate data with hard-constrained neural networks.pdf", "area": "Physical constraints and scientific learning", "category": "Primary or methodological candidate", "summary": "Constructs high-resolution climate outputs under hard constraints. It directly informs the distinction between exact coarse-fine consistency and independent fine-scale accuracy.", "application": "Evaluate in the physical constraints and scientific learning strand; apply only to its stated variables, scales and task.", "limitation": "A small residual or exact aggregation constraint alone does not establish an accurate or closed atmospheric simulation.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1-M3YBBSyNiBOZn1ZMvT74DtogJgpQOeJ/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D012", "title": "Global Forecasting of Tropical Cyclone Intensity Using Neural Weather Models.pdf", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Uses neural weather models for global tropical-cyclone intensity forecasting, motivating event-specific verification beyond broad global forecast averages.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/18uPqW-kFI6wzFOEafBvJTXRLc49hIZQ9/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D013", "title": "Global Tropical Cyclone Intensity Forecasting with Multi-modal Multi-scale Causal Autoregressive Model.pdf", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Combines multiple modalities and scales for tropical-cyclone intensity forecasting; its causal information set is relevant to preventing retrospective leakage.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1FHlBj1znapAW9CUjBjKdGsUzDMFhYAXI/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D014", "title": "hope-or-hype---ai-driven-risk-modeling-of-tropical-cyclones.pdf", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Critically examines AI tropical-cyclone risk modelling, informing the separation of hazard prediction, uncertainty and decision-relevant risk claims.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1Q7irIexLrHlpTsd_unIfO1_kaeIe6P0Q/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D015", "title": "Modelling and simulating spatial extremes by combining EVT with GAN.pdf", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Combines extreme-value theory with generative modelling of spatial extremes. It motivates tail and dependence diagnostics, while synthetic samples cannot remove structural uncertainty.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1X7ay_wddlX-c59cTkQGKwdrRIMLzAJHQ/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D016", "title": "Future Caribbean Climates in a World of Rising Temperatures.pdf", "area": "Caribbean climate physics", "category": "Primary or methodological candidate", "summary": "Examines future Caribbean climates under rising temperatures, supplying regional physical context for forced-response and warming-level comparisons.", "application": "Evaluate in the caribbean climate physics strand; apply only to its stated variables, scales and task.", "limitation": "A regional association is not a causal mechanism or evidence of dLEGOS skill; preserve the study region and period.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1CWrcznv0oo7r-GiSitQHLz1VCYhm76f7/view?usp=drivesdk", "identity": "Crossref title and metadata match" }, { "id": "D017", "title": "Preformance of RegCM43 over the Caribbean region using different configurations of the Tiedtke convective parameterization scheme.pdf", "area": "Caribbean climate physics", "category": "Primary or methodological candidate", "summary": "Compares Tiedtke convective-parameterisation configurations in RegCM4.3 over the Caribbean. It shows why closure choices can materially affect regional-model references.", "application": "Evaluate in the caribbean climate physics strand; apply only to its stated variables, scales and task.", "limitation": "A regional association is not a causal mechanism or evidence of dLEGOS skill; preserve the study region and period.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1A75ie_e0DgLcCRLxhTGuHG3XyXMVbYsW/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D018", "title": "Physics-Informed Neural Networks for Climate Modeling: Bridging Machine Learning and Physical Laws.pdf", "area": "Physical constraints and scientific learning", "category": "Primary or methodological candidate", "summary": "Discusses physics-informed climate learning. It is contextual synthesis rather than evidence that the proposed dLEGOS implementation is physically complete.", "application": "Evaluate in the physical constraints and scientific learning strand; apply only to its stated variables, scales and task.", "limitation": "A small residual or exact aggregation constraint alone does not establish an accurate or closed atmospheric simulation.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/11cT4I60x1Qv3L3Pod0bFbPp7QkCo1ByY/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D019", "title": "Deep Learning Emulators for Accessible Climate Projections - PhD thesis", "area": "Climate emulation and regional downscaling", "category": "Primary or methodological candidate", "summary": "Doctoral work on accessible deep-learning climate emulators supplies extended methodological and thesis-structure context; its conclusions remain specific to its experiments.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1b1mQH7ehY5fuF7wXo8Ubjz0otH2mmzB0/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D020", "title": "A Study of the Uncertainty in Future Caribbean Climate Using the PRECIS Regional Climate Model.pdf", "area": "Caribbean climate physics", "category": "Primary or methodological candidate", "summary": "Examines uncertainty in future Caribbean climate using PRECIS, motivating separation of configuration and scenario uncertainty from emulator error.", "application": "Evaluate in the caribbean climate physics strand; apply only to its stated variables, scales and task.", "limitation": "A regional association is not a causal mechanism or evidence of dLEGOS skill; preserve the study region and period.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1du9AydLHnzi6_aqVbsfvi7B-hz6shaHF/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D021", "title": "Physics-Informed Neural Networks of the Saint Venant Equations for DS Large Scale River Model.pdf", "area": "Physical constraints and scientific learning", "category": "Primary or methodological candidate", "summary": "Applies PINNs to the Saint-Venant river equations. It provides a scientific-learning example under a different physical system and does not establish atmospheric performance.", "application": "Evaluate in the physical constraints and scientific learning strand; apply only to its stated variables, scales and task.", "limitation": "A small residual or exact aggregation constraint alone does not establish an accurate or closed atmospheric simulation.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1oV7vJUFZgdjF_wUsNHrqJVrF2K1qOsBo/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D022", "title": "iclr2021_conference_copy.pdf", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Stored ICLR paper copy with an opaque filename. Bibliographic identity needs resolution from the original document before formal citation; readable text remains available for screening.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1ku2ukXtiDFRV-lleK-Tp8xQMkY6bEgS1/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D023", "title": "2404.10024v1_copy.pdf", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Stored arXiv copy with an opaque filename. Resolve the exact title, authors and version before bibliographic use; do not infer its contribution from the filename alone.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1_03vvLLT5NUYrSKEZk-pPwcjMvo2s-Nh/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D024", "title": "kashinath-et-al-2021-physics-informed-machine-learning-case-studies-for-weather-and-climate-modelling.pdf", "area": "Physical constraints and scientific learning", "category": "Primary or methodological candidate", "summary": "Reviews physics-informed machine learning through weather and climate case studies, helping distinguish different ways of incorporating physical knowledge.", "application": "Evaluate in the physical constraints and scientific learning strand; apply only to its stated variables, scales and task.", "limitation": "A small residual or exact aggregation constraint alone does not establish an accurate or closed atmospheric simulation.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1Ps1c3gQ-YP9P8iNMKUF79UcbVuBlhDeU/view?usp=drivesdk", "identity": "Crossref title and metadata match" }, { "id": "D025", "title": "2105.02939v1_copy.pdf", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Stored preprint copy with an opaque filename. Its identity needs normalization against the actual title page before use in a submission bibliography.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1C9z-p60tm71mNROzQblDCAz3GwruVtKz/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D026", "title": "PINNsforClimateModeling__copy.pdf", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Stored PINN climate-modelling discussion, useful for conceptual context and citation chaining, with paper-specific empirical claims requiring original-source verification.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1KSHN9nt3WwaABWGO9EXQlc3CVMrg2pvy/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D027", "title": "PINNsforClimateModeling__copy.pdf", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Duplicate-named PINN climate-modelling discussion; preserve the file identity and compare bytes or version metadata before merging records.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1QlZDdxGmAE9NE5s7gMdBJZGepmNmn-BU/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D028", "title": "2409.01626v1_copy.pdf", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Stored preprint identified by arXiv number in its filename; bibliographic normalization is pending rather than assuming a particular title or contribution.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1vtA2-FyFeP9rYMKwWD0yhe88odCQmVRs/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D029", "title": "2021_Moseley_Finite_Basis_Physics_Informed_Neural_Networks_FBPINNs_a_scal.pdf", "area": "Domain decomposition and interfaces", "category": "Primary or methodological candidate", "summary": "Introduces finite-basis PINNs with local overlapping networks, a direct architectural ancestor for the decomposition proposed in dLEGOS.", "application": "Evaluate in the domain decomposition and interfaces strand; apply only to its stated variables, scales and task.", "limitation": "Established decomposition methods restrict novelty claims; benchmark atmospheric coupling and computational scaling separately.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1Lqde4iKnq0SvCEu6i9Scp9I9_5lW1gcl/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D030", "title": "2022_Dolean_Finite_basis_physics_informed_neural_networks_as_a_Schwarz_d.pdf", "area": "Domain decomposition and interfaces", "category": "Primary or methodological candidate", "summary": "Interprets finite-basis PINNs through Schwarz domain decomposition, linking neural locality to established numerical analysis.", "application": "Evaluate in the domain decomposition and interfaces strand; apply only to its stated variables, scales and task.", "limitation": "Established decomposition methods restrict novelty claims; benchmark atmospheric coupling and computational scaling separately.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1gW_viOi7OfdNfuaaYdc8oQCNElSwdlu8/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D031", "title": "2023_Dolean_Multilevel_domain_decomposition_based_architectures_for_phys.pdf", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Extends physical neural architectures with multilevel domain decomposition, motivating tests of coarse communication and scaling across local regions.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1y_CT0085DRkOimsEhL2FpkTNu0zfApr9/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D032", "title": "2021_Shukla_Parallel_Physics_Informed_Neural_Networks_via_Domain_Decompo.pdf", "area": "Physical constraints and scientific learning", "category": "Primary or methodological candidate", "summary": "Studies parallel conservative and extended PINNs through domain decomposition, establishing comparators for interface conditions and parallel execution.", "application": "Evaluate in the physical constraints and scientific learning strand; apply only to its stated variables, scales and task.", "limitation": "A small residual or exact aggregation constraint alone does not establish an accurate or closed atmospheric simulation.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1c2Hrk7vB6JHnDF1Hst5ceL2YI0_ihEFy/view?usp=drivesdk", "identity": "Crossref title and metadata match" }, { "id": "D033", "title": "2021_Hu_When_Do_Extended_Physics_Informed_Neural_Networks_XPINNs_Imp.pdf", "area": "Domain decomposition and interfaces", "category": "Primary or methodological candidate", "summary": "Analyses when extended PINNs improve generalization, cautioning that decomposition is not automatically beneficial.", "application": "Evaluate in the domain decomposition and interfaces strand; apply only to its stated variables, scales and task.", "limitation": "Established decomposition methods restrict novelty claims; benchmark atmospheric coupling and computational scaling separately.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1c1ib5dRJ3KHPTPZimLejWHV4xT6fPkK3/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D034", "title": "2021_Krishnapriyan_Characterizing_possible_failure_modes_in_physics_informed_ne.pdf", "area": "Physical constraints and scientific learning", "category": "Primary or methodological candidate", "summary": "Characterizes PINN failure modes and the role of optimization, separating representational capacity from successful training.", "application": "Evaluate in the physical constraints and scientific learning strand; apply only to its stated variables, scales and task.", "limitation": "A small residual or exact aggregation constraint alone does not establish an accurate or closed atmospheric simulation.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/19xtPFzD0M1PDBUvviUMjqF_KBpJ2Cb_H/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D035", "title": "2022_Wang_Respecting_causality_is_all_you_need_for_training_physics_in.pdf", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Develops causality-aware PINN training, motivating explicit temporal ordering and curricula for time-dependent physical systems.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1hTTM67iXuL3qdJyO0jvcpLdhaLP3ptqa/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D036", "title": "2020_Wang_Understanding_and_mitigating_gradient_pathologies_in_physics.pdf", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Diagnoses gradient pathologies in composite physics-informed objectives and proposes mitigation; loss weighting must be evaluated separately from physical validity.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1eeW9bn68gcXSLRRPhLHOwzkBEbdJ-k7n/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D037", "title": "2021_Li_Physics_Informed_Neural_Operator_for_Learning_Partial_Differ.pdf", "area": "Physical constraints and scientific learning", "category": "Primary or methodological candidate", "summary": "Develops physics-informed neural operators for families of PDE solutions, distinguishing operator learning from fitting one field realization.", "application": "Evaluate in the physical constraints and scientific learning strand; apply only to its stated variables, scales and task.", "limitation": "A small residual or exact aggregation constraint alone does not establish an accurate or closed atmospheric simulation.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/18s1QR5IW0s6rOVS5I7wd6o69rGnJpl2f/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D038", "title": "2023_Bonev_Spherical_Fourier_Neural_Operators_Learning_Stable_Dynamics.pdf", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Develops spherical Fourier neural operators for stable dynamics on the sphere, providing a geometry-aware comparator for global learned evolution.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1OtEKT5_2EFXBNEDhloqXPQQrYN6k2kOO/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D039", "title": "2022_Harder_Hard_Constrained_Deep_Learning_for_Climate_Downscaling.pdf", "area": "Physical constraints and scientific learning", "category": "Primary or methodological candidate", "summary": "Studies hard constraints in climate downscaling, directly informing the benchmark between exact aggregation and soft penalties.", "application": "Evaluate in the physical constraints and scientific learning strand; apply only to its stated variables, scales and task.", "limitation": "A small residual or exact aggregation constraint alone does not establish an accurate or closed atmospheric simulation.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1dCpUETiVMJukYGcQtaa8Y7Wq-e6YRXQx/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D040", "title": "2018_Rasp_Deep_learning_to_represent_sub_grid_processes_in_climate_mod.pdf", "area": "Physical constraints and scientific learning", "category": "Primary or methodological candidate", "summary": "Learns subgrid climate processes with deep networks, illustrating the importance of defining closures and evaluating their behavior after coupling.", "application": "Evaluate in the physical constraints and scientific learning strand; apply only to its stated variables, scales and task.", "limitation": "A small residual or exact aggregation constraint alone does not establish an accurate or closed atmospheric simulation.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1v3UPV8JywcoJTWoeVVddF2nXYhNaCr5Z/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D041", "title": "2021_Kochkov_Machine_learning_accelerated_computational_fluid_dynamics.pdf", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Combines machine learning with computational fluid dynamics, providing a hybrid numerical comparator rather than evidence specific to Caribbean moist atmospheres.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1xqfmt8kFbz16Cr65XNFrwEXXhPAyr63E/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D042", "title": "2020_Willard_Integrating_Scientific_Knowledge_with_Machine_Learning_for_E.pdf", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Surveys integration of scientific knowledge with machine learning, supporting distinctions among architectural, objective-based and hybrid formulations.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1oUxWO-XKZeJya5vwybHjLyD06htc5dgG/view?usp=drivesdk", "identity": "Rejected title mismatch" }, { "id": "D043", "title": "2025_Chin_PIANO_Physics_informed_Dual_Neural_Operator_for_Precipitatio.pdf", "area": "Physical constraints and scientific learning", "category": "Primary or methodological candidate", "summary": "Develops a physics-informed dual neural operator for precipitation, motivating task-matched comparison of operator design and physical constraints.", "application": "Evaluate in the physical constraints and scientific learning strand; apply only to its stated variables, scales and task.", "limitation": "A small residual or exact aggregation constraint alone does not establish an accurate or closed atmospheric simulation.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/13M1ilm0EFpTB1bv5a-0VRzqYXx_jOqM3/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D044", "title": "2024_Yin_Precipitation_Nowcasting_Using_Physics_Informed_Discriminato.pdf", "area": "Physical constraints and scientific learning", "category": "Primary or methodological candidate", "summary": "Uses physically informed discriminators for precipitation nowcasting. Its adversarial notion of physical structure needs distinction from exact budget conservation.", "application": "Evaluate in the physical constraints and scientific learning strand; apply only to its stated variables, scales and task.", "limitation": "A small residual or exact aggregation constraint alone does not establish an accurate or closed atmospheric simulation.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1g_mZcSlWV9GyizxrlYNxJ1FPbg85v7ow/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D045", "title": "Attention is All You Need.pdf", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Introduces the Transformer attention architecture. It is foundational method context, not direct evidence of atmospheric skill or causal inference.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1C7Z_DaTOmzF2xKmocF5CSN30qg_bl-9q/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D046", "title": "Are Transformers Effective for Time Series Forecasting.pdf", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Examines Transformer effectiveness in time-series forecasting, motivating strong simple baselines and controlled architectural comparisons.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1eK2vy9NzAxCvQOPZhhffVTyP1Vdy6g1v/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D047", "title": "2025_Alet_Skillful_joint_probabilistic_weather_forecasting_from_marginals.pdf", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Studies joint probabilistic weather forecasting from marginals, making dependence structure and coherent joint fields explicit evaluation targets.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1MLvufws5ttRpOvX_30ZJ9RXtA0gSPHMe/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D048", "title": "2026_Rasp_WeatherNext_3_Increasing_resolution_and_performance_of_globa.pdf", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Recent WeatherNext 3 preprint addresses global resolution and observational inputs. Availability, version and Caribbean performance must be checked separately from headline claims.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1GyBnpXcI3qvMJMawebC3w1-1yqpYj0Dq/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D049", "title": "2026_Alet_Operational_tropical_cyclone_forecasting_with_AI.pdf", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Studies operational AI tropical-cyclone forecasting, motivating attention to issue-time information, latency and event-specific skill.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1TyqaNZ9nFHCDlgxA2_2sByIHB3VYSOlU/view?usp=drivesdk", "identity": "Crossref title and metadata match" }, { "id": "D050", "title": "2024_Yuval_Neural_general_circulation_models_optimized_to_predict_satel.pdf", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Optimizes neural general-circulation models toward satellite observations, a relevant alternative to learning solely from analysis targets.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/10tZCoGMa9ryJnLiLZgqIbHIFnjzJBFxU/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D051", "title": "2025_Agrawal_An_Operational_Deep_Learning_System_for_Satellite_Based_High.pdf", "area": "Observations and Earth representations", "category": "Primary or methodological candidate", "summary": "Develops an operational satellite-based high-resolution nowcasting system, emphasizing latency, product availability and lead-time-dependent verification.", "application": "Evaluate in the observations and earth representations strand; apply only to its stated variables, scales and task.", "limitation": "A retrieval, embedding or reanalysis is not independent ground truth; quantify shared inputs and errors.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1eqWUciF2uiwXonJgc4laRk35GZhSopQl/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D052", "title": "2023_Andrychowicz_Deep_Learning_for_Day_Forecasts_from_Sparse_Observations.pdf", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Forecasts from sparse observations, providing a comparator for direct observation-to-prediction learning under incomplete data.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/19jHkIkqlMJVdr2C-haI8reHO0fPizzgs/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D053", "title": "2021_Espeholt_Skillful_Twelve_Hour_Precipitation_Forecasts_using_Large_Con.pdf", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Develops large-context precipitation forecasting, useful for comparing nowcasting horizons and spatial context with inverse reconstruction.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1shwINiLvBfm5bX3b0kWZmRHNQuNRrQ3h/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D054", "title": "2024_Bodnar_A_Foundation_Model_for_the_Earth_System.pdf", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Develops an Earth-system foundation model, motivating transfer-learning comparators while leaving task-specific physical validity to be tested.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1TjM0xfj3gXtuO6Au0Nv40GYhQDSkI3aQ/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D055", "title": "2024_Schmude_Prithvi_WxC_Foundation_Model_for_Weather_and_Climate.pdf", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Describes a weather and climate foundation model, supplying a representation and adaptation comparator rather than proof of local fine-scale accuracy.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1CDtr66pp7No8clb-nD9t9V0COtwQpjdu/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D056", "title": "2024_Lang_AIFS_ECMWF_s_data_driven_forecasting_system.pdf", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Describes ECMWF's data-driven forecasting system, supplying an institutional learned-weather comparator with a defined initialization and forecast task.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1_EexmfpKguzu8V3ZiWKdLbdVI10gtAOV/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D057", "title": "2024_Lang_AIFS_CRPS_Ensemble_forecasting_using_a_model_trained_with_a.pdf", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Trains an ensemble forecasting system using a probabilistic score, informing ensemble verification and the difference between deterministic and distributional targets.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1iGwqNYtHjfBmThP8mGmBI4kDB27JH9Jo/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D058", "title": "2024_Vaughan_Aardvark_weather_end_to_end_data_driven_weather_forecasting.pdf", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Studies end-to-end data-driven weather forecasting, directly relevant to the distinction between observational input and analysis-initialized prediction.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1uI_Uk-lzerGoTeXkbx60wGhcpI3HnZql/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D059", "title": "2025_Bonev_FourCastNet_3_A_geometric_approach_to_probabilistic_machine.pdf", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Uses geometry-aware probabilistic machine learning for weather prediction, motivating joint ensemble, geometry and stability diagnostics.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/19aXLJLSrInv_qQR5OOEzFgGqePsouOhK/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D060", "title": "2025_Brenowitz_Climate_in_a_Bottle_Towards_a_Generative_Foundation_Model_fo.pdf", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Explores a generative foundation model for climate, informing distributional emulation and the need to test forced response and long-run statistics.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1Ya5dEzLI-2w6f4JrlpG_YBqYyhK5UA11/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D061", "title": "2024_Pathak_Kilometer_Scale_Convection_Allowing_Model_Emulation_using_Ge.pdf", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Studies generative emulation of kilometre-scale convection-allowing models. It supplies a close comparator for learned fine-scale distributions, not observational truth by itself.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1-kUfLhyQcWB9NgVtWjYW5hRuMvd8BGd5/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D062", "title": "2023_Chen_FuXi_A_cascade_machine_learning_forecasting_system_for_15_da.pdf", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Develops the FuXi cascade for 15-day global forecasts, providing a weather comparator whose lead-time skill must remain separate from climate fidelity.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1vdUlkOettDOIJhlaR5iGy82zRdfkILiy/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D063", "title": "2023_Chen_FengWu_Pushing_the_Skillful_Global_Medium_range_Weather_Fore.pdf", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Develops FengWu medium-range global forecasting, contributing an alternative learned-weather architecture and training target.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1BfpS9VrE4onxHP-BCSmzNhc64vIYfVV8/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D064", "title": "2023_Nguyen_Scaling_transformer_neural_networks_for_skillful_and_reliabl.pdf", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Examines scaling Transformer weather models for skill and reliability, informing matched-capacity and probabilistic evaluation.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/12b2ARP2vIrKCOdNxRXXlk0CI8MBjR-e2/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D065", "title": "2023_Watt_Meyer_ACE_A_fast_skillful_learned_global_atmospheric_model_for_cli.pdf", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Develops ACE, a learned atmospheric emulator for climate, shifting evaluation from short forecasts to climate statistics and long integrations.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1FkVpAkmS6I9VDRZK94rRjouqXeiMwDE4/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D066", "title": "2025_Shi_Deep_Learning_and_Foundation_Models_for_Weather_Prediction_A.pdf", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Reviews deep learning and foundation models for weather, supplying citation pathways and taxonomy rather than a substitute for primary experimental evidence.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1cjHrvlXTfeW7GH0mTSG0K8LVl1bzmms8/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D067", "title": "2026_Mozaffari_The_Rise_of_AI_in_Weather_and_Climate_Information_and_its_Im.pdf", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Examines the rise and implications of AI weather and climate information, providing contextual discussion for interpreting model capabilities and use.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1vkZXua_IkCrbhJDAGSZy1RVV08IKP50f/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D068", "title": "2026_Ozdemir_Earth_System_Foundation_Model_ESFM_A_unified_framework_for_h.pdf", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Proposes a unified Earth-system foundation-model framework, relevant to scope and multimodal representation but requiring component-specific empirical appraisal.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1GuKKAaETzllEW1Z-_Y6yfnycsNpVrdlA/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D069", "title": "2017_Vandal_DeepSD_Generating_High_Resolution_Climate_Change_Projections.pdf", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Develops DeepSD super-resolution for climate projections, an established learned-downscaling comparator with transfer and training-climate assumptions.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1K9hEdyq-zgrKYJfqdMWyYbiIfL3QCdQn/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D070", "title": "2020_Ba_o_Medina_Configuration_and_intercomparison_of_deep_learning_neural_mo.pdf", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Compares neural-model configurations for statistical downscaling, motivating controlled baselines, predictor choices and transferability assessment.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1epo8A4LtV2L-63Va8ssq4aAzYRtjpdHv/view?usp=drivesdk", "identity": "Crossref title and metadata match" }, { "id": "D071", "title": "2020_Stengel_Adversarial_super_resolution_of_climatological_wind_and_sola.pdf", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Uses adversarial super-resolution for climatological wind and solar fields, illustrating distributional spatial refinement outside the exact target rainfall task.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1xNnyoyKfGFrHfbPf-LUpIG9bY5uvtUmu/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D072", "title": "2020_Leinonen_Stochastic_Super_Resolution_for_Downscaling_Time_Evolving_At.pdf", "area": "Climate emulation and regional downscaling", "category": "Primary or methodological candidate", "summary": "Uses stochastic adversarial super-resolution for time-evolving atmospheric fields, motivating coherence and uncertainty tests beyond a conditional mean.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1x88DJz1m6yvf6IoweJ_aDpKpG5nhTQ2y/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D073", "title": "2022_Price_Increasing_the_accuracy_and_resolution_of_precipitation_fore.pdf", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Studies increasing precipitation-forecast accuracy and resolution with learning, informing the distinction between finer outputs and verified added skill.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1qLUmCJ9JkUNkhU1A-Vg20JQQD9cLS1M0/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D074", "title": "2022_Addison_Machine_learning_emulation_of_a_local_scale_UK_climate_model.pdf", "area": "Climate emulation and regional downscaling", "category": "Primary or methodological candidate", "summary": "Emulates a local-scale UK climate model, providing a regional emulation precedent whose geographic transfer to Caribbean terrain must be tested.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1GID4YMrohGRIF8VrptMICLa3YqOGjO_o/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D075", "title": "2024_Watt_Generative_Diffusion_based_Downscaling_for_Climate.pdf", "area": "Climate emulation and regional downscaling", "category": "Primary or methodological candidate", "summary": "Uses diffusion for generative climate downscaling, motivating conditional-distribution and warming-transfer evaluation.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1AAMC3w4JFBcuyfBrAooA1tnHcYlwUfnW/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D076", "title": "2024_Kalita_Data_driven_rainfall_prediction_at_a_regional_scale_a_case_s.pdf", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Studies data-driven regional rainfall prediction in a case-study setting, offering comparative method context while limiting claims to the studied region and support.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1JtP7gGJD9-O6fNA9GLUMAxlrxDbDkfEP/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D077", "title": "2023_Yu_ClimSim_Online_A_Large_Multi_scale_Dataset_and_Framework_for.pdf", "area": "Physical constraints and scientific learning", "category": "Primary or methodological candidate", "summary": "Describes an online multi-scale climate-emulation dataset and framework, making coupled evaluation and feedback behavior important beyond offline fitting.", "application": "Evaluate in the physical constraints and scientific learning strand; apply only to its stated variables, scales and task.", "limitation": "A small residual or exact aggregation constraint alone does not establish an accurate or closed atmospheric simulation.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1ZITKM-C_lUOw0qsweZ5Ra8RFdVybtu-Z/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D078", "title": "Hybrid physics-AI outperforms numerical weather prediction for extreme precipitation nowcasting.pdf", "area": "Weather prediction and uncertainty", "category": "Primary or methodological candidate", "summary": "Combines physical and AI components for extreme-precipitation nowcasting. Its task-specific numerical-model comparison should not be generalized to all forecasting or climate tasks.", "application": "Evaluate in the weather prediction and uncertainty strand; apply only to its stated variables, scales and task.", "limitation": "Preserve initialisation time, valid time and information availability; do not transfer global scores directly to Caribbean extremes.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1jAw198JUU1fw5_zTs4koT6NMnNrisNsi/view?usp=drivesdk", "identity": "Crossref title and metadata match" }, { "id": "D079", "title": "Deep Reinforcement Learning - An Overview.pdf", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Surveys deep reinforcement learning. It is peripheral unless adaptive control solves a demonstrated optimization problem better than simpler schedules.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1Gp22NpYvuf33UIiI-uiAB4XwS3Y9svnf/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D080", "title": "Emulators of climate model output.pdf", "area": "Climate emulation and regional downscaling", "category": "Primary or methodological candidate", "summary": "Discusses emulators of climate-model output, supporting the distinction between a statistical surrogate and a physically complete replacement model.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/12H3GGOzvNmF1q5c7YpUt0rbSEuy-bbI4/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D081", "title": "BUILDING OCEAN CLIMATE EMULATORS.pdf", "area": "Climate emulation and regional downscaling", "category": "Primary or methodological candidate", "summary": "Examines ocean climate emulation, offering methodological parallels while requiring care about atmospheric versus oceanic dynamics and boundary conditions.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1jN6hxBjZzgTj3kxp6uqAgn5NXsBkjPvf/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D082", "title": "Emulation and Intepretation of High Dimensional Climate Model Outputs.pdf", "area": "Climate emulation and regional downscaling", "category": "Primary or methodological candidate", "summary": "Examines emulation and interpretation of high-dimensional climate outputs, motivating explicit targets, dimension reduction and uncertainty accounting.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/19g6A_44xa98WTZ-Vc-XVyjsjs7pAocGf/view?usp=drivesdk", "identity": "Crossref title and metadata match" }, { "id": "D083", "title": "Statistical mechanics in climate emulation- Challenges and perspectives.pdf", "area": "Climate emulation and regional downscaling", "category": "Primary or methodological candidate", "summary": "Discusses statistical-mechanical challenges in climate emulation, helping frame long-run distributions and physical interpretation beyond short-horizon error.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1WFFM_uAzaEP3ibIiBSF6DQLzhlypyf1B/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D084", "title": "ClimSim -A large multi-scale dataset for hybrid physics-ML climate emulation.pdf", "area": "Physical constraints and scientific learning", "category": "Primary or methodological candidate", "summary": "Introduces a multi-scale hybrid physics–ML climate dataset, supporting closure-learning comparisons and reproducible benchmark design.", "application": "Evaluate in the physical constraints and scientific learning strand; apply only to its stated variables, scales and task.", "limitation": "A small residual or exact aggregation constraint alone does not establish an accurate or closed atmospheric simulation.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1HX21wsW-EU-bYRi__ADtuYwZYPHw-ekg/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D085", "title": "Dynamic climate emulators for solar geoengineering.pdf", "area": "Climate emulation and regional downscaling", "category": "Primary or methodological candidate", "summary": "Develops dynamic climate emulation for solar-geoengineering questions, illustrating forcing-conditional surrogates and the limits of transfer outside training scenarios.", "application": "Evaluate in the climate emulation and regional downscaling strand; apply only to its stated variables, scales and task.", "limitation": "Fidelity to a reference simulation is distinct from independent observational validity; weather skill is insufficient for climate claims.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1HytKvbISQGzIUy2t64It8uJtyYzXVy48/view?usp=drivesdk", "identity": "Crossref title and metadata match" }, { "id": "D086", "title": "Flash droughts present a new challenge.pdf", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Discusses flash drought as an emerging challenge, motivating rapid-onset hazard context but not itself validating an atmospheric reconstruction method.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1elWuC7-jvECRcuGPKFVTgt7dstbMp-v-/view?usp=drivesdk", "identity": "Rejected title mismatch" }, { "id": "D087", "title": "Global distribution, trends, and drivers of flash.pdf", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Examines the distribution, trends and drivers of flash droughts, providing a physical hazard context distinct from rainfall prediction alone.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1yLo8dud408Un_4hK7eaGf2ryuvHiPSo3/view?usp=drivesdk", "identity": "Crossref title and metadata match" }, { "id": "D088", "title": "Geophysical Research Letters - 2015 - Mo - Heat wave flash droughts in decline.pdf", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Studies heat-wave flash-drought trends, demonstrating that rapid drying involves temperature and evaporative demand as well as precipitation.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1f4ne3-oHI961rsmYxQ9rMzf8ldFe-eM5/view?usp=drivesdk", "identity": "Crossref title and metadata match" }, { "id": "D089", "title": "Prediction of Flash Droughts over the United States.pdf", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Studies prediction of flash drought in the United States, offering comparative verification ideas whose regional transfer needs justification.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1u648o1Wmq8dHJ3ga5TQjlBoCrP7uokiY/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D090", "title": "Atmospheric Flash Drought in the Caribbean.pdf", "area": "Caribbean climate physics", "category": "Primary or methodological candidate", "summary": "Studies atmospheric flash drought in the Caribbean, linking moisture and circulation to a regionally relevant hazard target for later validation.", "application": "Evaluate in the caribbean climate physics strand; apply only to its stated variables, scales and task.", "limitation": "A regional association is not a causal mechanism or evidence of dLEGOS skill; preserve the study region and period.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1kkZjJpUhKvhelYM0GTkxfuCBN3xVZACT/view?usp=drivesdk", "identity": "Crossref title and metadata match" }, { "id": "D091", "title": "dLEGOS_Critical_Literature_Review_October_2026.pdf", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "An earlier internal dLEGOS literature review. Use as a record of previous framing and citation leads, never as independent evidence supporting the same thesis claims.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1EM8rHCTI93PDi6xMx_f788FxIHUay2vM/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D092", "title": "Literature_Review_LaTeX.zip", "area": "Methods and adjacent applications", "category": "Unappraised metadata", "summary": "Archive of literature-review LaTeX materials; a working artifact rather than a primary research paper.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Register or archive; not a research-paper text", "identifier": "https://drive.google.com/file/d/1Rcz6mMgp-z7aesGG0EB35PxGsNa11PdN/view?usp=drivesdk", "identity": "Not independently resolved against publication metadata" }, { "id": "D093", "title": "reference_ledger.csv", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Earlier reference ledger. Preserve as provenance and reconcile identities; historical verification labels are not inherited as fresh checks.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1d0s-QPof3s24pWK1Byf3JIAxXyEupWBe/view?usp=drivesdk", "identity": "Rejected title mismatch" }, { "id": "D094", "title": "anara_shortlist_25.csv", "area": "Methods and adjacent applications", "category": "Primary or methodological candidate", "summary": "Earlier Anara shortlist. It records selection history and does not replace the complete inventory or source appraisal.", "application": "Evaluate in the methods and adjacent applications strand; apply only to its stated variables, scales and task.", "limitation": "Visual plausibility, application success elsewhere or generic AI capability does not validate atmospheric inference.", "access": "Stored text retrieved; analytical screening", "identifier": "https://drive.google.com/file/d/1pkIf4toSrFL33hWaUx94YvU2dnbB7lMU/view?usp=drivesdk", "identity": "Rejected title mismatch" }, { "id": "G01", "title": "UWI library guidance on organising a literature review", "area": "Institutional writing guidance", "category": "Guidance", "summary": "Supports critical, thematic synthesis that compares sources and derives the methodology.", "application": "Apply within the stated physical and inference assumptions.", "limitation": "No direct evidence of dLEGOS empirical skill.", "access": "Primary source text or institutional guidance retrieved", "identifier": "https://libguides.uwi.edu/c.php?g=11323&p=59143", "identity": "Not independently resolved against publication metadata" }, { "id": "G02", "title": "UWI Revised thesis guide", "area": "Institutional presentation guidance", "category": "Guidance", "summary": "Informs thesis presentation; confirm current departmental requirements before submission.", "application": "Apply within the stated physical and inference assumptions.", "limitation": "No direct evidence of dLEGOS empirical skill.", "access": "Primary source text or institutional guidance retrieved", "identifier": "https://www.mona.uwi.edu/postgrad/sites/default/files/postgrad/uploads/Revised-thesis-guide.pdf", "identity": "Not independently resolved against publication metadata" }, { "id": "G03", "title": "Hersbach et al. (2020) The ERA5 global reanalysis", "area": "Atmospheric observations and assimilation", "category": "Primary methodological or regional evidence", "summary": "Defines the reanalysis reference and its assimilation context; motivates avoiding circular validation against shared input data.", "application": "Apply within the stated physical and inference assumptions.", "limitation": "No direct evidence of dLEGOS empirical skill.", "access": "Primary source text or institutional guidance retrieved", "identifier": "https://doi.org/10.1002/qj.3803", "identity": "Not independently resolved against publication metadata" }, { "id": "G04", "title": "Centella-Artola et al. (2020) Evaluation of sixteen gridded precipitation datasets over the Caribbean region using gauge observations", "area": "Caribbean observational uncertainty", "category": "Primary methodological or regional evidence", "summary": "Compares precipitation products against gauges in the Caribbean and motivates product-specific uncertainty rather than treating gridded rainfall as truth.", "application": "Apply within the stated physical and inference assumptions.", "limitation": "No direct evidence of dLEGOS empirical skill.", "access": "Primary source text or institutional guidance retrieved", "identifier": "https://doi.org/10.3390/atmos11121334", "identity": "Not independently resolved against publication metadata" }, { "id": "G05", "title": "Tasim and Sun (2026) Physics Informed Reconstruction of Four-Dimensional Atmospheric Wind Fields Using Multi-UAS Swarm Observations in a Synthetic Turbulent Environment", "area": "Atmospheric reconstruction novelty lead", "category": "Primary methodological or regional evidence", "summary": "Reconstructs synthetic wind with weak physical regularisation rather than full governing dynamics. Methods and conclusions appraised; real-world validity remains open.", "application": "Apply within the stated physical and inference assumptions.", "limitation": "No direct evidence of dLEGOS empirical skill.", "access": "Full text retrieved; reconstruction methods and conclusions appraised", "identifier": "https://arxiv.org/abs/2601.22111", "identity": "Not independently resolved against publication metadata" }, { "id": "G06", "title": "Trémolet (2006) Accounting for an imperfect model in 4D-Var", "area": "Weak-constraint data assimilation", "category": "Primary methodological or regional evidence", "summary": "Compares model-error forcing, bias and full space-time control formulations; constrains novelty claims about physics-regularized reconstruction.", "application": "Apply within the stated physical and inference assumptions.", "limitation": "No direct evidence of dLEGOS empirical skill.", "access": "Primary source text or institutional guidance retrieved", "identifier": "https://doi.org/10.1256/qj.05.224", "identity": "Not independently resolved against publication metadata" }, { "id": "G07", "title": "Evensen (2003) The Ensemble Kalman Filter theoretical formulation and practical implementation", "area": "Ensemble state estimation", "category": "Primary methodological or regional evidence", "summary": "Explains ensemble-based covariance propagation and updates; informs an uncertainty-aware assimilation comparator.", "application": "Apply within the stated physical and inference assumptions.", "limitation": "No direct evidence of dLEGOS empirical skill.", "access": "Primary source text or institutional guidance retrieved", "identifier": "https://doi.org/10.1007/s10236-003-0036-9", "identity": "Not independently resolved against publication metadata" }, { "id": "G08", "title": "Bocquet and Sakov (2013) Joint state and parameter estimation with an iterative ensemble Kalman smoother", "area": "Joint inverse state and parameter estimation", "category": "Primary methodological or regional evidence", "summary": "Tests iterative smoothing for joint inference in low-order nonlinear systems; informs identifiability and controlled observing-system experiments.", "application": "Apply within the stated physical and inference assumptions.", "limitation": "No direct evidence of dLEGOS empirical skill.", "access": "Primary source text or institutional guidance retrieved", "identifier": "https://doi.org/10.5194/npg-20-803-2013", "identity": "Not independently resolved against publication metadata" } ]