- 1Montefiore institute - Big Data, Uliege, Liege, Belgium
- 2Cilmatology and topoclimatology , Uliege, Liege, Belgium
Regional Climate Models (RCMs) provide high-resolution, physics-based fields, but they face three main limitations. First, they are computationally expensive and hence difficult to scale across scenarios or ensembles. Second, they lack uncertainty quantification. Third, they usually take only coarse data from Earth System Models (ESMs) or reanalysis to predict fields, without assimilating real observations. In response to these problems, neural emulators of RCMs have been developed over different regions.
In this work, we present MAR.ia, a diffusion-based emulator of MAR, an RCM developed at ULiège tailored to Belgium (Doutreloup et al., 2019). Our approach maps coarse atmospheric and surface reanalysis variables (ERA5 at 0.25° and 1° resolution) to key surface variables (temperature, precipitation and wind speed) at the resolution of MAR (5 km). The emulator is conditioned on ERA5 reanalysis every six hours (as the forcing of MAR) in order to give hourly MAR-like fields. We assess the sensitivity of the emulator to the choice of ERA5 fields, identifying the key drivers to reproduce MAR dynamics.
We solve the three main limitations initially stated: we reduce computational costs by several orders of magnitude, we estimate uncertainty by sampling several times for the same coarse inputs (generation of ensembles), and we incorporate observational constraints from ground stations and satellites directly during sampling, while showing competitive metrics, i.e. correlation of ~0.99 for the temperature at 2m.
Future work will attempt to use ESM outputs (weather forecast or CMIP future projections) as context variables instead of reanalysis, enabling both short-term meteorological predictions and long-term climate projections up to 2100, over Belgium.
Doutreloup, S., Wyard, C., Amory, C., Kittel, C., Erpicum, M., and Fettweis, X. (2019). Sensitivity to Convective Schemes on Precipitation Simulated by the Regional Climate Model MAR over Belgium (1987–2017), Atmosphere, 10( 1), 34. https://doi.org/10.3390/atmos10010034.
How to cite: Faulx, E., Peters, S., Fettweis, X., and Louppe, G.: MAR.ia: a diffusion-based emulator for high-resolution climate downscaling over Belgium, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18397, https://doi.org/10.5194/egusphere-egu26-18397, 2026.