Complex forecasts of heavy snowfalls in the Urals with global and mesoscale numerical models

International Conference and Early Career Scientists School on Environmental Observations, Modeling and Information Systems: ENVIROMIS-2018

生态环境科学;计算机科学

Pischalnikova, E.V.^1,2 ; Kalinin, N.A.^2 ; Shikhov, A.N.^3 ; Bykov, A.V.^2

Department of Meteorological Forecasts, Perm Center for Hydrometeorology and Environmental Monitoring, 70 Novogayvinskaya Street, Perm, 614030, Russia^1

Department of Meteorology and Atmosphere Protection, Perm State University

15 Bukireva Street, Perm, 614990, Russia^2

Department of Cartography and Geoinformatics, Perm State University

15 Bukireva Street, Perm, 614990, Russia^3

关键词: Frontal precipitation;    Geographical locations;    Heavy snowfall;    Mesoscale numerical model;    Model forecasting;    Number of false alarms;    Reliability level;    Seasonal patterns;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/211/1/012057/pdf
DOI  :  10.1088/1755-1315/211/1/012057

来源: IOP

【 摘 要 】

This paper presents an assessment of short-term numerical forecasts of precipitation in the cold period of the Urals. The use of global (GEM and GFS) and mesoscale (WRF) models in forecasting of heavy snowfalls is considered. The reliability levels of the 15-h and 27-h forecasts with the GEM, GFS, and WRF models are approximately equal. The 39-h forecasts with the WRF model are least accurate. The dependences of the quality of model forecasting on synoptic-scale environments, seasonal patterns, geographical location, and topography are obtained. The heavy snowfall events formed by a warm front, a cold front, and in the northern part of a cyclone are predicted with satisfactory accuracy. The least successful numerical forecasts are obtained for non-frontal precipitation in the warm sector of a cyclone. All three models tend to overestimate the precipitation amount during the cold period: the number of false alarms exceeds the number of missed events. The numerical forecasts of precipitation during the cold period have higher reliability levels for the territory of Western Urals than for the Eastern Urals region.