output
19952026
most citedWeatherBench: A benchmark dataset for data-driven weather forecasting

506 citations

Showing 2020 · physics.ao-phShow all

8 papers · 2 filters

physics.ao-ph2020★ 1 cited

Machine-Learned Preconditioners for Linear Solvers in Geophysical Fluid Flows

Jan Ackmann, Peter D. Düben, Tim N. Palmer +1

It is tested whether machine learning methods can be used for preconditioning to increase the performance of the linear solver -- the backbone of the semi-implicit, grid-point mode…

physics.ao-ph2020★ 92 cited

Extreme precipitation events in the Mediterranean: Spatiotemporal characteristics and connection to large-scale atmospheric flow patterns

Nikolaos Mastrantonas, Pedro Herrera-Lormendez, Linus Magnusson +2

The Mediterranean is strongly affected by Extreme Precipitation Events (EPEs), sometimes leading to negative impacts on society, economy, and the environment. Understanding such na…

physics.ao-ph2020★ 108 cited

A comparative study of convolutional neural network models for wind field downscaling

Kevin Höhlein, Michael Kern, Timothy Hewson +1

We analyze the applicability of convolutional neural network (CNN) architectures for downscaling of short-range forecasts of near-surface winds on extended spatial domains. Short-r…

physics.ao-ph2020★ 199 cited

The 2019/20 Australian wildfires generated a persistent smoke-charged vortex rising up to 35 km altitude

Sergey Khaykin, Bernard Legras, Silvia Bucci +9

The Australian bushfires around the turn of the year 2020 generated an unprecedented perturbation of stratospheric composition, dynamical circulation and radiative balance. Here we…

physics.ao-ph2020★ 205 cited

Statistical Postprocessing for Weather Forecasts -- Review, Challenges and Avenues in a Big Data World

Stéphane Vannitsem, John Bjørnar Bremnes, Jonathan Demaeyer +21

Statistical postprocessing techniques are nowadays key components of the forecasting suites in many National Meteorological Services (NMS), with for most of them, the objective of…

physics.ao-ph2020★ 46 cited

A new low-cost technique improves weather forecasts across the world

Tim D. Hewson, Fatima M. Pillosu

Computer-generated forecasts divide the earth's surface into gridboxes, each now ~25% of the size of London, and predict one value per gridbox. If weather varies markedly within a…

physics.ao-ph2020★ 19 cited

Beyond skill scores: exploring sub-seasonal forecast value through a case study of French month-ahead energy prediction

Joshua Dorrington, Isla Finney, Tim Palmer +1

We quantify the value of sub-seasonal forecasts for a real-world prediction problem: the forecasting of French month-ahead energy demand. Using surface temperature as a predictor,…

physics.ao-ph2020★ 506 cited

WeatherBench: A benchmark dataset for data-driven weather forecasting

Stephan Rasp, Peter D. Dueben, Sebastian Scher +3

Data-driven approaches, most prominently deep learning, have become powerful tools for prediction in many domains. A natural question to ask is whether data-driven methods could al…