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

Wellmann, Constanze; Barrett, Andrew I.; Johnson, Jill S.; Kunz, Michael; Vogel, Bernhard; Carslaw, Ken S.; Hoose, Corinna

Abstract:
Severe hailstorms have the potential to damage buildings and crops. However, important processes for the prediction of hailstorms are insufficiently represented in operational weather forecast models. Therefore, our goal is to identify model input parameters describing environmental conditions and cloud microphysics, such as the vertical wind shear and strength of ice multiplication, which lead to large uncertainties in the prediction of deep convective clouds and precipitation. We conduct a comprehensive sensitivity analysis simulating deep convective clouds in an idealized setup of a cloud-resolving model. We use statistical emulation and variance-based sensitivity analysis to enable a Monte Carlo sampling of the model outputs across the multi-dimensional parameter space. The results show that the model dynamical and microphysical properties are sensitive to both the environmental and microphysical uncertainties in the model. The microphysical parameters lead to larger uncertainties in the output of integrated hydrometeor mass contents and precipitation variables. In particular, the uncertainty in the fall velocities of graupel and hail account for more than 65% of the variance of all considered precipitation variables and for 30 %–90% of the variance of the integrated hydrometeor mass contents. ... mehr

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Verlagsausgabe §
DOI: 10.5445/IR/1000117850
Veröffentlicht am 24.03.2020
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung - Forschungsbereich Troposphäre (IMK-TRO)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2020
Sprache Englisch
Identifikator ISSN: 1680-7324
KITopen-ID: 1000117850
Erschienen in Atmospheric chemistry and physics
Band 20
Heft 4
Seiten 2201–2219
Bemerkung zur Veröffentlichung Gefördert durch den KIT-Publikationsfonds
Vorab online veröffentlicht am 26.02.2020
Nachgewiesen in Scopus
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