First evaluation of Greenland clouds in RACMO2.4 using EarthCARE observations

Clouds present one of the major challenges for climate modeling and cause large uncertainties in climate projections. This results from the complexity involved in representing small-scale cloud microphysics in coarse-gridded climate models. Over the Greenland Ice Sheet, clouds modulate melt, but with sharply contrasting impacts for snow and ice surfaces. Therefore, accurate representation of cloud processes and cloud occurrence is essential for reliable melt projections over the ice sheet.

The recently launched Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) will provide cloud, precipitation and radiation profiles in unprecedented detail. We use these novel observations to evaluate cloud representation over Greenland in the latest version of the Regional Atmospheric Climate Model (RACMO2.4). Along-track atmospheric profiles of RACMO2.4 model output are compared with EarthCARE Level 2 cloud retrievals, as well as with Level 1 lidar and radar data, using derived backscatter and reflectivity profiles from the RACMO2.4 model output. The latter will help to explain which of the differences between observed and modeled cloud properties are due to model inaccuracies, and which are due to sensor limitations and data processing choices.

Using a selected number of case studies, our first comparison indicates that RACMO2.4 represents ice clouds reasonably well. However, we find large discrepancies regarding the representation of liquid clouds. Our analysis of cloud microphysical properties and aerosol representation will provide insights into the processes underlying these differences and will guide model development.