Comparative Analysis of SCMOC and Models Rainstorm Forecasting Performance in Qinling Mountains and Their Surrounding Areas

Abstract

Taking CMPA (CMA Multi-source Merged Precipitation Analysis System) analysis data as a reference, the research analyzes the forecast performance of ECMWF, CMA-Meso, and SCMOC (National Meteorological Center grid precipitation forecast guidance product) in 74 rainstorm cases in 2020 and 2021 in Qinling Mountains and their surrounding areas by using the dichotomy classical verification score comprehensive diagram and the object-oriented MODE spatial verification method, based on the circulation classification in rainstorm weather. The research conclusions are as follows: (1) based on the high- and low-altitude circulation situation and focused on the direct impact system, rainstorms in the Qinling Mountains and their surrounding areas can be divided into five patterns. (2) Point-to-point verification shows that SCMOC has obvious advantages in rainstorm forecast, but the disadvantage is that the Bias is relatively high. CMA-Meso has advantages in RST (weak weather system) decentralized rainstorm forecast. (3) MODE verification shows that the number of ECMWF and SCMOC independent objects is significantly lower than that of observation, the forecast area of regional rainstorm objects of SCMOC is significantly larger, the SCMOC scattered rainstorm objects are missed, and the number of independent precipitation objects of CMA-Meso is higher than that of the other two precipitation products. (4) The forecast object area and intensity of SCMOC and observation match best in the XFC (westerly trough) circulation situation, while ECMWF has the best results for the forecast of FGXFC (subtropical high westerly trough) rainstorms.