activity
20202024
most citedThe rise of data-driven weather forecasting

164 citations · 368 across the 5 of their papers we have counts for

collaborators

5 papers

physics.ao-ph2024★ 75 cited

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…

physics.ao-ph2023★ 164 cited

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…

physics.ao-ph2023

Domino: A new framework for the automated identification of weather event precursors, demonstrated for European extreme rainfall

Joshua Dorrington, Christian Grams, Federico Grazzini +2

A number of studies have investigated the large-scale drivers and upstream-precursors of extreme weather events, making it clear that the earliest warning signs of extreme events c…

physics.ao-ph2021★ 37 cited

What do large-scale patterns teach us about extreme precipitation over the Mediterranean at medium- and extended-range forecasts?

Nikolaos Mastrantonas, Linus Magnusson, Florian Pappenberger +1

Extreme Precipitation Events (EPEs) can have devastating consequences such as floods and landslides, posing a great threat to society and the economy. Predicting such events long i…

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…