基于CMA-TYM和SCMOC的嫩江流域暴雨检验北大核心CSCD

选取2021年嫩江流域9个暴雨日,利用降水融合产品,采用CRA空间检验,对区域台风数值预报系统(CMATYM)和国家级智能网格指导预报(SCMOC)20:00起报的24 h降水预报产品进行检验。结果表明:CMA-TYM和SCMOC预报的最大降水量位置均偏西、偏北,CMA-TYM和SCMOC预报的降水落区均偏西,但前者偏北,后者略偏南,SCMOC预报优于CMA-TYM。误差分析表明:CMA-TYM和SCMOC预报的暴雨落区最大降水量和平均降水量比实况偏小,格点数、面积较实况偏大,但整体上,CMA-TYM预报更接近实况。CRA空间检验显示,CMA-TYM预报的降水强度和落区形态、SCMOC预报的降水落区位置和形态较接近实况,具有一定指示意义。

Verification of Rainstorm Based on Numerical Model About CMA-TYM and SCMOC in Nenjiang Basin

The Nenjiang is the north source of the Songhua River. Nenjiang Basin is an important commodity grain base in China. The change of water level in Nenjiang Basin during the flood season is closely related to the precipitation, especially the continuous rainstorm and heavy rainstorm are very easy to cause flood disaster. For example, Nenjiang Basin is affected by the continuous rainstorm and heavy rainstorm weather on 18 July 2021, the Yong'an Reservoir bursted, the Xin'an Reservoir collapsed, residents across the towns are hit by the flood disaster. The flood in Nenjiang Basin has great impacts on the national economy and people's lives. Therefore, in order to improve the accuracy of rainstorm prediction in Nenjiang Basin, the deviation between CMA-TYM and SCMOC precipitation products are analyzed from the aspects of rainstorm area and intensity, and the correction ability is improved, which has certain practical significance for agricultural production, reservoir storage, and water resource allocation in the basin. At the same time, it also provides a strong guarantee for forecast warning, people's lives and property security, and sustainable healthy development of social. Nine rainstorm days are selected in 2021, using merged precipitation, based on numerical model products by CMA-TYM and SCMOC, the contiguous rain area (CRA) technique is used to test 24 h precipitation predicted at 2000 BT. The results show that maximum precipitation position deviation of rainstorm days predicted by CMA-TYM and SCMOC are west and north, but precipitation location of rainstorm days tested by CRA technique are west, the former is north, the latter is slightly south. SCMOC prediction preforms better than CMA-TYM. Error analysis show that, it is smaller than the precipitation observation that maximum precipitation value and average precipitation of observed rainstorm area predicted by CMA-TYM and SCMOC, but the grid numbers and area are larger than the observation. On the whole, CMA_TYM forecast is closer to the observation. CRA technique shows that the intensity and pattern of precipitation location predicted by CMA-TYM, location and pattern of precipitation predicted by SCMOC are close to the observation, and it has certain instructive significance.