Influence of cloud microphysics schemes on weather model predictions of heavy precipitation

  • Cloud microphysics is one of the major sources of uncertainty in numerical weather prediction models. In this work, the ability of a numerical weather prediction model to correctly predict high-impact weather events, i.e., hail and heavy rain, using different cloud microphysics schemes is evaluated statistically. Polarimetric C-band radar observations over 30 convection days are used as the observation dataset. Simulations are made using the regional-scale Weather Research and Forecasting (WRF) model with five microphysics schemes of varying complexity (double moment, spectral bin (SBM), and Predicted Particle Properties (P3)). Statistical characteristics of heavy-rain and hail events of varying intensities are compared between simulations and observations. All simulations, regardless of the microphysics scheme, predict heavy-rain events (15, 25, and 40 mm h−1) that cover larger average areas than those observed by radar. The frequency of these heavy-rain events is similar toCloud microphysics is one of the major sources of uncertainty in numerical weather prediction models. In this work, the ability of a numerical weather prediction model to correctly predict high-impact weather events, i.e., hail and heavy rain, using different cloud microphysics schemes is evaluated statistically. Polarimetric C-band radar observations over 30 convection days are used as the observation dataset. Simulations are made using the regional-scale Weather Research and Forecasting (WRF) model with five microphysics schemes of varying complexity (double moment, spectral bin (SBM), and Predicted Particle Properties (P3)). Statistical characteristics of heavy-rain and hail events of varying intensities are compared between simulations and observations. All simulations, regardless of the microphysics scheme, predict heavy-rain events (15, 25, and 40 mm h−1) that cover larger average areas than those observed by radar. The frequency of these heavy-rain events is similar to radar-measured heavy-rain events but still scatters by a factor of 2 around the observations, depending on the microphysics scheme. The model is generally unable to simulate extreme hail events with reflectivity thresholds of 55 dBZ and higher, although they have been observed by radar during the evaluation period. For slightly weaker hail/graupel events, only the P3 scheme is able to reproduce the observed statistics. Analysis of the raindrop size distribution in combination with the model mixing ratio shows that the P3, Thompson two-moment (2-mom), and Thompson aerosol-aware schemes produce large raindrops too frequently, and the SBM scheme misses large rain and graupel particles. More complex schemes do not necessarily lead to better results in the prediction of heavy precipitation.show moreshow less

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Metadaten
Author:Gregor Köcher, Tobias Zinner, Christoph KnoteORCiDGND
URN:urn:nbn:de:bvb:384-opus4-1047529
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/104752
ISSN:1680-7324OPAC
Parent Title (English):Atmospheric Chemistry and Physics
Publisher:EGU
Place of publication:Katlenburg-Lindau
Type:Article
Language:English
Year of first Publication:2023
Publishing Institution:Universität Augsburg
Release Date:2023/06/12
Tag:Atmospheric Science
Volume:23
Issue:11
First Page:6255
Last Page:6269
DOI:https://doi.org/10.5194/acp-23-6255-2023
Institutes:Medizinische Fakultät
Medizinische Fakultät / Lehrstuhl für Model-based Environmental Exposure Science
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Licence (German):CC-BY 4.0: Creative Commons: Namensnennung (mit Print on Demand)