Journal
ATMOSPHERIC RESEARCH
Volume 164, Issue -, Pages 210-225Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.atmosres.2015.05.010
Keywords
Numerical weather prediction; Quantitative precipitation forecast; Weather hazard; Flash floods; Cloud microphysics parameterization; Spatial verification methods
Categories
Funding
- United States Air Force Weather Agency (AFWA)
- United States National Science Foundation
- PRIN project - Italian Ministry of Education [D38C1300061000]
- Italian flagship project RITMARE
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An intercomparison of eight different microphysics parameterization schemes available in the Weather Research and Forecasting (WRF) model and an analysis of the sensitivity of predicted precipitation to horizontal resolution are presented in this paper. Three different case studies, corresponding to severe rainfall events occurred over the Liguria region (Italy) between October 2010 and November 2011, have been considered. In all the selected cases, the formation of a quasi-stationary mesoscale convective system over the Ligurian Sea interacting with local dynamical effects (orographically-induced low-level wind and temperature gradients) played a crucial role in the generation of severe precipitations. The data set used to evaluate model performances has been extracted from the official regional network, composed of about 150 professional WMO-compliant stations. Two different strategies have been exploited to assess the model skill in forecasting precipitation: a traditional approach, where forecasts and observations are matched on a point-by-point basis, and an object-based method where model success is based on the correct localization and intensity of precipitation patterns. This last method overcomes the known fictitious models performance degradation for increasing spatial resolution. As remarkable results of this analysis, a clear role of horizontal resolution on the model performances accompanied by the identification of a set of best-performing parameterization schemes emerge. The outcomes presented here offer important suggestions for operational weather prediction systems under potentially dangerous heavy precipitations triggered by the mechanisms discussed throughout the paper. (C) 2015 Elsevier B.V. All rights reserved.
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