activity
20202026
most citedA Generative Deep Learning Approach to Stochastic Downscaling of Precipitation Forecasts

201 citations · 606 across the 34 of their papers we have counts for

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Showing 2025Show all

5 papers · 1 filter

physics.ao-ph2025

Improved rainfall forecasts in daily use over East Africa

Fenwick C. Cooper, Shruti Nath, Andrew T. T. McRae +21

Ensemble forecasting has proven to be a vital tool for predicting extreme, life-threatening or only partially predictable weather events. As well as providing probabilistic product…

cs.LG2025

On Global Applicability and Location Transferability of Generative Deep Learning Models for Precipitation Downscaling

Paula Harder, Christian Lessig, Matthew Chantry +2

Deep learning offers promising capabilities for the statistical downscaling of climate and weather forecasts, with generative approaches showing particular success in capturing fin…

physics.ao-ph2025★ 1 cited

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…

physics.ao-ph2025★ 1 cited

An update to ECMWF's machine-learned weather forecast model AIFS

Gabriel Moldovan, Ewan Pinnington, Ana Prieto Nemesio +18

We present an update to ECMWF's machine-learned weather forecasting model AIFS Single with several key improvements. The model now incorporates physical consistency constraints thr…

cs.CV2025

RainShift: A Benchmark for Precipitation Downscaling Across Geographies

Paula Harder, Luca Schmidt, Francis Pelletier +5

Earth System Models (ESM) are our main tool for projecting the impacts of climate change. However, running these models at sufficient resolution for local-scale risk-assessments is…