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Moisture budget perspective on impact of cloud microphysics, soil moisture, and initial condition uncertainties for predicting strongly forced deep convection

Authors

Miltenberger,  Annette
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Barthlott,  Christian
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Takumi,  Matsunobu
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Puh,  Matjaž
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Keil,  Christian
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Kuntze,  Patrick
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Hoose,  Corinna
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Kunz,  Michael
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

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Citation

Miltenberger, A., Barthlott, C., Takumi, M., Puh, M., Keil, C., Kuntze, P., Hoose, C., Kunz, M. (2023): Moisture budget perspective on impact of cloud microphysics, soil moisture, and initial condition uncertainties for predicting strongly forced deep convection, XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG) (Berlin 2023).
https://doi.org/10.57757/IUGG23-3069


Cite as: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5020467
Abstract
Precipitation formation by deep convective storms is controlled by a complex interplay of larger-scale forcing, available moist static energy, cloud dynamics, and cloud microphysical processes. The representation of the related atmospheric properties and processes is subject to large uncertainties in numerical weather prediction models, even at the kilometer-scale resolution. Quantifying the impact of different uncertainty sources for the prediction of deep convective systems as well as understanding the propagation and growth of moisture error is essential for our physical understanding of deep convection but also the design of ensemble forecasting systems.Based on a supercell hailstorm event close to Munich in June 2019, we quantify the impact of meteorological initial (and lateral boundary) condition, soil moisture content, and cloud microphysics perturbations on precipitation and surface hail prediction in a 420-member high-resolution ensemble dataset. The joint initial conditions and perturbed physics ensemble allows us to also investigate interaction effects of different model perturbations. Further, we investigate the impact of the various sources of uncertainty on the regional moisture budget in the vicinity and downstream of the simulated deep convective storms.Our results indicate that cloud microphysics perturbations and initial condition uncertainties are equally important for hail resulting in a strongly enhanced spread in the joint ensemble. For total precipitation, initial condition uncertainty is more important. Cloud microphysical perturbations are further found to modify the water content in the deep convective outflow and enhance variability in the upper-tropospheric moisture fluxes to downstream regions compared to the initial condition only ensemble.