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Using statistical emulation to quantify microphysical uncertainties for the Andreas hail storm on the Swabian Jura in 2013

Authors

Frey,  Lena
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;

Miltenberger,  Annette
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;

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Citation

Frey, L., Hoose, C., Kunz, M., Miltenberger, A., Kuntze, P. (2023): Using statistical emulation to quantify microphysical uncertainties for the Andreas hail storm on the Swabian Jura in 2013, XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG) (Berlin 2023).
https://doi.org/10.57757/IUGG23-4024


Cite as: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5021464
Abstract
Hail formation in deep convective storms depends strongly on environmental meteorological and aerosol conditions. Here we investigate the impact of uncertainty in ambient conditions and cloud microphysics representation for simulated (hail) precipitation over Southwestern Germany on 28th July 2013, the day of the Andreas hailstorm. We perform model simulations on convection-resolving scale with the numerical weather prediction model ICON coupled with the aerosol module ART. We generated a perturbed parameter ensemble with 90 ensemble members to sample uncertainties in cloud-, precipitation- and hail-related variables. Six parameters were jointly perturbed: cloud condensation nuclei (CCN) and ice nucleation particle (INP) concentrations, riming efficiency of graupel and hail, atmospheric stability, and vertical wind shear. Analysis of the ensemble with statistical emulation and variance analysis shows the importance of the CCN concentration and stability for controlling the amount of surface hail and total precipitation in the model. The geographical distribution of hail and precipitation shows a large variety among the ensemble members, with storm tracks shifted further to the north or south compared to the reference simulation. The path of the storm track is thereby mainly controlled by stability and vertical wind shear, however, aerosol parameters seem to be important for the number of storm cells.