ИСПОЛЬЗОВАНИЕ АВТОМАТИЧЕСКОЙ ТИПИЗАЦИИ СИНОПТИЧЕСКОЙ СИТУАЦИИ ДЛЯ УСЛОВНОЙ ВЕРИФИКАЦИИ ЧИСЛЕННЫХ ПРОГНОЗОВ ПОГОДЫ В ПЕРМСКОМ КРАЕ

Abstract

The article discusses the possibility of verification of short-term 2-meter air temperature forecasts with the Global Forecast System and Global Environment Multiscale numerical weather prediction models depending on the observed synoptic type (a case study of the Perm region for the period 2018–2019). As part of the study, we have developed a system of automated determination of synoptic type based on a two-stage procedure, including decomposition of mean sea level pressure fields via principal component analysis and the subsequent clustering of decomposition coefficients using K-means. It has been established that GFS forecasts are more dependent on synoptic type in summer than in winter. The decline of forecast quality, expressed in systematic underestimation of forecast temperature by 0.6°–1.2°, is noted for synoptic types associated with warm air advection.: In contrast, GEM forecasts tend to lack accuracy in winter. A sharp decrease in forecast quality has been discovered in the central area of anticyclone at night, when the forecast accuracy drops to 44%. The obtained results could be useful in operational forecasting and model postprocessing.