166 citations · 529 across the 13 of their papers we have counts for
13 papers
Machine learning is revolutionizing weather forecasting -- the next step is a change in how we work
Peter Dueben, Peter Bauer, Oliver Fuhrer +2
Following the success of machine learning in producing weather predictions with competitive skill compared to complex traditional systems, this article shifts attention from foreca…
Representing the Surface Ocean in ECMWF's data-driven forecasting system AIFS
Sara Hahner, Lorenzo Zampieri, Jean-Raymond Bidlot +22
Machine-learning (ML) models, such as the AIFS at the ECMWF, have revolutionised weather forecasting in recent years. We present an extension of the AIFS that jointly models the at…
Hybrid ensemble forecasting combining physics-based and machine-learning predictions through spectral nudging
Inna Polichtchouk, Simon Lang, Sarah-Jane Lock +2
We present the first application of spectral nudging in a probabilistic ensemble forecasting framework, combining the physics-based ECMWF Integrated Forecasting System ensemble (IF…
High-Resolution Probabilistic Data-Driven Weather Modeling with a Stretched-Grid
Even Marius Nordhagen, Håvard Homleid Haugen, Magnus Sikora Ingstad +9
We present a probabilistic data-driven weather model providing ensembles of high spatial resolution realizations of 87 variables at arbitrary ensemble size and forecast length. The…
AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score
Simon Lang, Mihai Alexe, Mariana C. A. Clare +15
Over the last three decades, ensemble forecasts have become an integral part of forecasting the weather. They provide users with more complete information than single forecasts as…
AIFS -- ECMWF's data-driven forecasting system
Simon Lang, Mihai Alexe, Matthew Chantry +13
Machine learning-based weather forecasting models have quickly emerged as a promising methodology for accurate medium-range global weather forecasting. Here, we introduce the Artif…
WeatherBench 2: A benchmark for the next generation of data-driven global weather models
Stephan Rasp, Stephan Hoyer, Alexander Merose +15
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 dat…
The rise of data-driven weather forecasting
Zied Ben-Bouallegue, Mariana C A Clare, Linus Magnusson +14
Data-driven modeling based on machine learning (ML) is showing enormous potential for weather forecasting. Rapid progress has been made with impressive results for some application…
Improving medium-range ensemble weather forecasts with hierarchical ensemble transformers
Zied Ben-Bouallegue, Jonathan A Weyn, Mariana C A Clare +3
Statistical post-processing of global ensemble weather forecasts is revisited by leveraging recent developments in machine learning. Verification of past forecasts is exploited to…
ENS-10: A Dataset For Post-Processing Ensemble Weather Forecasts
Saleh Ashkboos, Langwen Huang, Nikoli Dryden +5
Post-processing ensemble prediction systems can improve the reliability of weather forecasting, especially for extreme event prediction. In recent years, different machine learning…
Probabilistic Forecasting with Generative Networks via Scoring Rule Minimization
Lorenzo Pacchiardi, Rilwan Adewoyin, Peter Dueben +1
Probabilistic forecasting relies on past observations to provide a probability distribution for a future outcome, which is often evaluated against the realization using a scoring r…
Bridging observation, theory and numerical simulation of the ocean using Machine Learning
Maike Sonnewald, Redouane Lguensat, Daniel C. Jones +3
Progress within physical oceanography has been concurrent with the increasing sophistication of tools available for its study. The incorporation of machine learning (ML) techniques…
Machine learning emulation of gravity wave drag in numerical weather forecasting
Matthew Chantry, Sam Hatfield, Peter Duben +2
We assess the value of machine learning as an accelerator for the parameterisation schemes of operational weather forecasting systems, specifically the parameterisation of non-orog…