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1,223 claims from 771 papers are on the record. 45 have been checked so far; the other 1,178 have no check with a result yet.
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Keyword: FourCastNet Clear all
8 claims from 4 papers
Earth and Planetary Sciences › Meteorological Phenomena and Simulations
FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators
Pathak, Subramanian, Harrington et al. · arXiv (Cornell University) · 2022
Unchecked2 claimsShow 2 claims
- Unchecked“FourCastNet matches the forecasting accuracy of the ECMWF Integrated Forecasting System (IFS), a state-of-the-art Numerical Weather Prediction (NWP) model, at short lead times for large-scale variables, while outperforming IFS for variables with complex fine…
- Unchecked“FourCastNet generates a week-long forecast in less than 2 seconds, orders of magnitude faster than IFS.”
Earth and Planetary Sciences › Meteorological Phenomena and Simulations
Do AI models produce better weather forecasts than physics-based models? A quantitative evaluation case study of Storm Ciarán
Charlton-Perez, Dacre, Driscoll et al. · npj Climate and Atmospheric Science · 2024
Unchecked2 claimsShow 2 claims
- Unchecked“The four machine learning models considered (FourCastNet, Pangu-Weather, GraphCast and FourCastNet-v2) produce forecasts that accurately capture the synoptic-scale structure of the cyclone including the position of the cloud head, shape of the warm sector an…
- Unchecked“All of the machine learning models underestimate the peak amplitude of winds associated with the storm, only some machine learning models resolve the warm core seclusion and none of the machine learning models capture the sharp bent-back warm frontal gradien…
Earth and Planetary Sciences › Meteorological Phenomena and Simulations
Validating Deep Learning Weather Forecast Models on Recent High-Impact Extreme Events
Pasche, Wider, Zhang, Zscheischler and Engelke · Artificial Intelligence for the Earth Systems · 2024
Unchecked1 claimEarth and Planetary Sciences › Meteorological Phenomena and Simulations
FourCastNet: Accelerating Global High-Resolution Weather Forecasting using Adaptive Fourier Neural Operators
Kurth, Subramanian, Harrington et al. · arXiv (Cornell University) · 2022
Unchecked3 claimsShow 3 claims
- Unchecked“We report that a data-driven deep learning Earth system emulator, FourCastNet, can predict global weather and generate medium-range forecasts five orders-of-magnitude faster than NWP while approaching state-of-the-art accuracy.”
- Unchecked“FourCast-Net is optimized and scales efficiently on three supercomputing systems: Selene, Perlmutter, and JUWELS Booster up to 3,808 NVIDIA A100 GPUs, attaining 140.8 petaFLOPS in mixed precision (11.9%of peak at that scale).”
- Unchecked“The time-to-solution for training FourCastNet measured on JUWELS Booster on 3,072GPUs is 67.4minutes, resulting in an 80,000times faster time-to-solution relative to state-of-the-art NWP, in inference.”
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