Preprints
https://doi.org/10.5194/egusphere-2025-5192
https://doi.org/10.5194/egusphere-2025-5192
14 Nov 2025
 | 14 Nov 2025
Status: this preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).

Significance of microphysical processes for uncertainties in ensemble forecasts of summertime convection over central Europe

Christian Barthlott, Beata Czajka, Christoph Gebhardt, and Corinna Hoose

Abstract. Accurately forecasting summertime convection remains a challenge for convection-permitting ensemble prediction systems, which often show insufficient spread in precipitation forecasts. This study examines the role of microphysical uncertainties using the ICOsahedral Non-hydrostatic (ICON) model for four representative convective cases over central Europe. A 108-member cloud microphysics ensemble (MPHYS-ENS) was generated by perturbing cloud condensation nuclei (CCN) and ice-nucleating particle (INP) concentrations, graupel sedimentation velocity, and the cloud droplet size distribution. Microphysical perturbations alone produced substantial variability in convective intensity and location, despite identical initial and boundary conditions. Precipitation totals were highly sensitive to CCN and graupel sedimentation, with deviations of 17–33 % across cases, while the timing of convection onset was only weakly affected. Rapid domain-wide error growth indicated strong thermodynamic impacts even in cloud-free regions. Process diagnostics showed that water–ice and vapor–liquid phase changes dominate mean hydrometeor mass rates, while the most frequent processes involved evaporation. Cold-rain pathways consistently governed precipitation; higher CCN and INP concentrations enhanced this dominance, whereas faster graupel sedimentation weakened it. The ratio of cold- to warm-rain processes emerged as a potential diagnostic for identifying regimes in which increased aerosol loading enhances, rather than suppresses, precipitation. Comparison with operational ensembles highlighted the importance of ensemble size. The 108-member MPHYS-ENS generated the largest spread, while bootstrapped 20-member subsets approached operational ensemble system levels. This study demonstrates that cloud microphysics is a major source of forecast uncertainty in summertime convection and should be explicitly represented in ensemble design.

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Christian Barthlott, Beata Czajka, Christoph Gebhardt, and Corinna Hoose

Status: open (until 26 Dec 2025)

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Christian Barthlott, Beata Czajka, Christoph Gebhardt, and Corinna Hoose
Christian Barthlott, Beata Czajka, Christoph Gebhardt, and Corinna Hoose
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Latest update: 14 Nov 2025
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Short summary
The study uses the ICON model to examine how microphysical uncertainties affect summertime convection in central Europe. A 108-member ensemble varying aerosol and cloud parameters showed strong differences in precipitation intensity and location but little impact on convection onset. Results highlight that cloud microphysics is a key source of forecast uncertainty in convective weather prediction.
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