ERA5
Emerging18papers using it
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2020first seen
ERA5 is a multi-decadal reanalysis dataset that contains atmospheric, oceanic, and land surface data used to evaluate deep learning models for short-term precipitation prediction.
Papers using ERA5 (18)
- Adaptive Spatio-Temporal Graphs with Self-Supervised Pretraining for Multi-Horizon Weather ForecastingDeep Learning for Short-Term Precipitation Prediction in Four Major Indian Cities: A ConvLSTM Approach with Explainable AIResolution-Aware Retrieval Augmented Zero-Shot ForecastingSynergistic Neural Forecasting of Air Pollution with Stochastic SamplingNon-collective Calibrating Strategy for Time Series ForecastingTowards Accurate Forecasting of Renewable Energy : Building Datasets and Benchmarking Machine Learning Models for Solar and Wind Power in FranceVA-MoE: Variables-Adaptive Mixture of Experts for Incremental Weather ForecastingForecasting Global Weather with Graph Neural NetworksPangu-Weather: A 3D High-Resolution Model for Fast and Accurate Global
Weather ForecastA Deep Learning Method for Real-time Bias Correction of Wind Field
Forecasts in the Western North PacificSea Ice Forecasting using Attention-based Ensemble LSTMMT-IceNet -- A Spatial and Multi-Temporal Deep Learning Model for Arctic
Sea Ice ForecastingRainBench: Towards Global Precipitation Forecasting from Satellite
ImageryRegional data-driven weather modeling with a global stretched-gridPhysics-based vs. data-driven 24-hour probabilistic forecasts of
precipitation for northern tropical AfricaGenerating Fine-Grained Causality in Climate Time Series Data for
Forecasting and Anomaly DetectionDUNE: A Machine Learning Deep UNet++ based Ensemble Approach to Monthly,
Seasonal and Annual Climate ForecastingPredicting Landfall's Location and Time of a Tropical Cyclone Using
Reanalysis Data