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Found 4 papers, 1 papers with code
WeatherBench 2: A benchmark for the next generation of data-driven global weather models
WeatherBench 2 is an update to the global, medium-range (1-14 day) weather forecasting benchmark proposed by Rasp et al. (2020), designed with the aim to accelerate progress in data-driven weather modeling.
A Generative Deep Learning Approach to Stochastic Downscaling of Precipitation Forecasts
Despite continuous improvements, precipitation forecasts are still not as accurate and reliable as those of other meteorological variables.
Machine learning emulation of gravity wave drag in numerical weather forecasting
By training on an increased complexity version of the existing parameterisation scheme we build emulators that produce more accurate forecasts.
Weather Forecasting
Atmospheric and Oceanic Physics
Computational Physics
RainBench: Towards Global Precipitation Forecasting from Satellite Imagery
Extreme precipitation events, such as violent rainfall and hail storms, routinely ravage economies and livelihoods around the developing world.
