Articles | Volume 20, issue 4
Atmos. Chem. Phys., 20, 2201–2219, 2020
https://doi.org/10.5194/acp-20-2201-2020
Atmos. Chem. Phys., 20, 2201–2219, 2020
https://doi.org/10.5194/acp-20-2201-2020

Research article 26 Feb 2020

Research article | 26 Feb 2020

Comparing the impact of environmental conditions and microphysics on the forecast uncertainty of deep convective clouds and hail

Constanze Wellmann et al.

Data sets

Training data and emulators for the analysis of sensitivity of deep convective clouds and hail to environmental conditions and microphysics M.-C. Wellmann https://doi.org/10.5445/IR/1000099232

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Short summary
Severe hailstorms may cause damage to buildings and crops. Thus, the forecast of numerical weather prediction (NWP) models should be as reliable as possible. Using statistical emulation, we identify those model input parameters describing environmental conditions and cloud microphysics which lead to large uncertainties in the prediction of deep convection. We find that the impact of the input parameters on the uncertainty depends on the considered output variable.
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