1 code implementation • 29 Aug 2023 • Stephan Rasp, Stephan Hoyer, Alexander Merose, Ian Langmore, Peter Battaglia, Tyler Russel, Alvaro Sanchez-Gonzalez, Vivian Yang, Rob Carver, Shreya Agrawal, Matthew Chantry, Zied Ben Bouallegue, Peter Dueben, Carla Bromberg, Jared Sisk, Luke Barrington, Aaron Bell, Fei Sha
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.
no code implementations • 6 Jun 2023 • Marcin Andrychowicz, Lasse Espeholt, Di Li, Samier Merchant, Alexander Merose, Fred Zyda, Shreya Agrawal, Nal Kalchbrenner
The ability of neural models to make a prediction in less than a second once the data is available and to do so with very high temporal and spatial resolution, and the ability to learn directly from atmospheric observations, are just some of these models' unique advantages.
no code implementations • 28 Mar 2023 • Shreya Agrawal, Rob Carver, Cenk Gazen, Eric Maddy, Vladimir Krasnopolsky, Carla Bromberg, Zack Ontiveros, Tyler Russell, Jason Hickey, Sid Boukabara
Post-processing typically takes the outputs of a Numerical Weather Prediction (NWP) model and applies linear statistical techniques to produce improve localized forecasts, by including additional observations, or determining systematic errors at a finer scale.
no code implementations • 23 May 2022 • Ignacio Lopez-Gomez, Amy McGovern, Shreya Agrawal, Jason Hickey
We find that training models to minimize custom losses tailored to emphasize extremes leads to significant skill improvements in the heat wave prediction task, compared to NWMs trained on the mean squared error loss.
2 code implementations • 14 Nov 2021 • Lasse Espeholt, Shreya Agrawal, Casper Sønderby, Manoj Kumar, Jonathan Heek, Carla Bromberg, Cenk Gazen, Jason Hickey, Aaron Bell, Nal Kalchbrenner
An emerging class of weather models based on neural networks represents a paradigm shift in weather forecasting: the models learn the required transformations from data instead of relying on hand-coded physics and are computationally efficient.
2 code implementations • 24 Mar 2020 • Casper Kaae Sønderby, Lasse Espeholt, Jonathan Heek, Mostafa Dehghani, Avital Oliver, Tim Salimans, Shreya Agrawal, Jason Hickey, Nal Kalchbrenner
Weather forecasting is a long standing scientific challenge with direct social and economic impact.
no code implementations • 11 Dec 2019 • Shreya Agrawal, Luke Barrington, Carla Bromberg, John Burge, Cenk Gazen, Jason Hickey
High-resolution nowcasting is an essential tool needed for effective adaptation to climate change, particularly for extreme weather.