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ACP | Articles | Volume 20, issue 4
Atmos. Chem. Phys., 20, 2201–2219, 2020
https://doi.org/10.5194/acp-20-2201-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Atmos. Chem. Phys., 20, 2201–2219, 2020
https://doi.org/10.5194/acp-20-2201-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

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.

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Cited articles

Adams-Selin, R. D., van den Heever, S. C., and Johnson, R. H.: Impact of Graupel Parameterization Schemes on Idealized Bow Echo Simulations, Mon. Weather Rev., 141, 1241–1262, https://doi.org/10.1175/MWR-D-12-00064.1, 2013. a
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Barrett, A. I., Wellmann, C., Seifert, A., Hoose, C., Vogel, B., and Kunz, M.: One Step at a Time: How Model Time Step Significantly Affects Convection-Permitting Simulations, J. Adv. Model. Earth Sy., 11, 641–658, https://doi.org/10.1029/2018MS001418, 2019. a, b
Bastos, L. S. and O'Hagan, A.: Diagnostics for Gaussian Process Emulators, Technometrics, 51, 425–438, https://doi.org/10.1198/TECH.2009.08019, 2009. a
Bigg, E. K.: The formation of atmospheric ice crystals by the freezing of droplets, Q. J. Roy. Meteor. Soc., 79, 510–519, https://doi.org/10.1002/qj.49707934207, 1953. a
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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.
Severe hailstorms may cause damage to buildings and crops. Thus, the forecast of numerical...
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