205 citations · 510 across the 10 of their papers we have counts for
12 papers
HourGlass: A probabilistic data-driven temporal downscaler for global and regional weather forecasting
Magnus Sikora Ingstad, Mariana C. A. Clare, Olav Ersland +16
Many forecast applications require high frequency temporal resolution, yet most state-of-the-art data-driven weather forecasting systems operate at 6-hourly resolution. Although di…
WP-MIP: An Artificial Intelligence, Hybrid, and Physically Based Model Intercomparison Project for Weather Prediction
Ron McTaggart-Cowan, Linus Magnusson, Inna Polichtchouk +57
Rapid progress in the field of machine-learning for weather prediction has led to the emergence of algorithms whose forecasting skill can exceed that of traditional physically base…
"What is a realistic forecast?" Assessing data-driven weather forecasts, a journey from verification to falsification
Zied Ben Bouallègue
The artificial intelligence revolution is fuelling a paradigm shift in weather forecasting: forecasts are generated with machine learning models trained on large datasets rather th…
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…
Prévisions météorologiques basées sur l'intelligence artificielle : une révolution peut en cacher une autre
Zied Ben-Bouallegue, Mariana C A Clare, Matthieu Chevallier
Artificial intelligence (AI), based on deep-learning algorithm using high-quality reanalysis datasets, is showing enormous potential for weather forecasting. In this context, the E…
Seamless prediction of high-impact weather events: a comparison of actionable forecasts
Zied Ben-Bouallegue
A new index for high-impact weather forecasting is introduced and assessed in comparison with the well-established extreme forecast index (EFI). Two other ensemble summary statisti…
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…
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…
Generation of scenarios from calibrated ensemble forecasts with a dual ensemble copula coupling approach
Zied Ben Bouallegue, Tobias Heppelmann, Susanne E. Theis +1
Probabilistic forecasts in the form of ensemble of scenarios are required for complex decision making processes. Ensemble forecasting systems provide such products but the spatio-t…
Assessment and added value estimation of an ensemble approach with a focus on global radiation forecasts
Zied Ben Bouallegue
The assessment of the high-resolution ensemble weather prediction system COSMO-DE-EPS is achieved with the perspective of using it for renewable energy applications. The performanc…
Quantile forecast discrimination ability and value
Zied Ben Bouallegue, Pierre Pinson, Petra Friederichs
While probabilistic forecast verification for categorical forecasts is well established, some of the existing concepts and methods have not found their equivalent for the case of c…