SOTAVerified

Weather Forecasting

Weather Forecasting is the prediction of future weather conditions such as precipitation, temperature, pressure and wind.

Source: MetNet: A Neural Weather Model for Precipitation Forecasting

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 326–350 of 420 papers

TitleStatusHype
Explainable AI-Based Interface System for Weather Forecasting Model—0
Explainable Graph Neural Networks for Observation Impact Analysis in Atmospheric State Estimation—0
Exploring the design space of deep-learning-based weather forecasting systems—0
Exploring the Use of Machine Learning Weather Models in Data Assimilation—0
Extreme Solar Flare Prediction Using Residual Networks with HMI Magnetograms and Intensitygrams—0
FABLE: A Localized, Targeted Adversarial Attack on Weather Forecasting Models—0
FengWu-4DVar: Coupling the Data-driven Weather Forecasting Model with 4D Variational Assimilation—0
FlowDAS: A Stochastic Interpolant-based Framework for Data Assimilation—0
FNP: Fourier Neural Processes for Arbitrary-Resolution Data Assimilation—0
FourCastNet: Accelerating Global High-Resolution Weather Forecasting using Adaptive Fourier Neural Operators—0
From Cities to Series: Complex Networks and Deep Learning for Improved Spatial and Temporal Analytics*—0
FuXi-ENS: A machine learning model for medium-range ensemble weather forecasting—0
FuXi-Extreme: Improving extreme rainfall and wind forecasts with diffusion model—0
FuXi-RTM: A Physics-Guided Prediction Framework with Radiative Transfer Modeling—0
FuXi-S2S: A machine learning model that outperforms conventional global subseasonal forecast models—0
General Information Metrics for Improving AI Model Training Efficiency—0
Generalized Mixture Model for Extreme Events Forecasting in Time Series Data—0
Generative Modeling of High-resolution Global Precipitation Forecasts—0
Global atmospheric data assimilation with multi-modal masked autoencoders—0
Global spatio-temporal downscaling of ERA5 precipitation through generative AI—0
Global Vegetation Modeling with Pre-Trained Weather Transformers—0
GNSS Radio Occultation on Aerial Platforms with Commercial Off-The-Shelf Receivers—0
Graph-enabled Reinforcement Learning for Time Series Forecasting with Adaptive Intelligence—0
Graph Neural Network for spatiotemporal data: methods and applications—0
Gridded Transformer Neural Processes for Large Unstructured Spatio-Temporal Data—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1PhyDNetMSE4.82—Unverified
2E3D-LSTMMSE4.17—Unverified
3UNetMSE4.11—Unverified
4RainformerMSE4.03—Unverified
5PredRNNMSE3.9—Unverified
6ConvLSTMMSE3.75—Unverified
7EarthformerMSE3.7—Unverified
8IAM4VPMSE2.94—Unverified
#ModelMetricClaimedVerifiedStatus
1CatBoost with RMSEWithUncertaintyR-AUC MSE1.34—Unverified
2SNN Ens U MT Np SpecFER-AUC MSE1.14—Unverified