numerical weather prediction
PulseAugur coverage of numerical weather prediction — every cluster mentioning numerical weather prediction across labs, papers, and developer communities, ranked by signal.
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Physics-informed ML enhances satellite cloud detection
Researchers have developed a physics-informed feature engineering approach for 1D-CNN models to improve multilayer cloud detection from geostationary satellites. This method embeds channel selections derived from thresh…
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New AI framework integrates weather and turbine data for wind power forecasting
Researchers have developed a new multimodal framework for short-term wind power forecasting that integrates SCADA data from wind turbines with numerical weather prediction (NWP) forecasts. This approach addresses the ch…
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New framework assesses AI forecasting model robustness against weather prediction errors
A new framework for evaluating the robustness of AI forecasting models in photovoltaic (PV) power generation has been developed. This framework addresses the challenge of numerical weather prediction (NWP) errors, which…
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Deep learning models show resilience to weather forecast errors in PV power prediction
A new study evaluates the robustness of various deep learning models, including PatchTST, GRU, N-HITS, and LightGBM, when subjected to errors in numerical weather prediction (NWP) data. The research introduces a physica…
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AI model enhances extreme precipitation forecasts using station and gridded data
Researchers have developed a novel two-stage framework using a U-Net architecture to improve extreme precipitation forecasting. This method combines probability classification with value reconstruction, blending forecas…
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New AI framework enhances regional weather downscaling efficiency
Researchers have developed a novel framework for regional weather downscaling that leverages a pretrained global weather foundation model. This approach uses lightweight prediction heads operating in the model's latent …
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Machine learning enhances uncertainty quantification in data assimilation
A new research paper explores the application of conformal prediction (CP), a machine learning technique, for quantifying uncertainty in data assimilation, particularly within numerical weather prediction. The study eva…
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Otter Weather AI model offers efficient, skillful medium-range forecasting
Researchers have developed Otter Weather, a new AI model for medium-range weather forecasting that aims to be more efficient and accessible than current state-of-the-art methods. The model significantly improves the ski…
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SIMBA framework enhances weather prediction with bidirectional radiance modeling · 2 sources tracked
Researchers have developed SIMBA, a novel bidirectional framework for modeling hyperspectral infrared radiances from the FY-4A GIIRS instrument. This framework uniquely integrates atmospheric profile retrieval and radia…
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Neural fields improve weather prediction data assimilation
Researchers have developed a novel neural field-based approach to Four-Dimensional Variational Data Assimilation (4DVAR), a critical but computationally intensive process in numerical weather prediction. This new method…
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Extreme Weather Bench: New AI framework aids high-impact weather forecasting
Researchers have introduced Extreme Weather Bench (EWB), a new open-source benchmark suite designed to evaluate AI and Numerical Weather Prediction (NWP) models. EWB provides a standardized set of case studies, observat…
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PINN-Cast transformer uses Neural ODEs and physics loss for weather forecasting
Researchers have developed PINN-Cast, a novel continuous-depth transformer model for short-term weather forecasting. This model integrates Neural Ordinary Differential Equations (Neural ODEs) within its encoder blocks t…