Comparative analysis of SCMOC and various numerical models for precipitation forecasting
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    Abstract:

    Based on the three-source fusion grid precipitation analysis data from CMPAS and using the dichotomy classical verification method, a comprehensive map of precipitation forecast score, and the Method for Object-Based Diagnostic Evaluation (MODE), we compare and analyzed the precipitation forecast performance of the fine-gridded SCMOC, ECMWF global, and CMA-Meso models in Qinling and its surrounding areas in 2021, and observe the following: 1) The ECMWF model can well describe the spatial distribution characteristics of daily average precipitation, daily precipitation standard deviation, and daily precipitation frequency under the influence of terrain. However, the precipitation frequency of more than 0.1 mm is much higher than the observation, and the torrential rain frequency is lower than the observation. SCMOC and CMA-Meso have better forecasts of precipitation of different grades. The deficiency of SCMOC is that its ability to describe the fine spatial distribution characteristics of precipitation is relatively weak. 2) The occurrence time of the daily peak of precipitation frequency greater than 0.1mm in the ECMWF model is about 3 hours earlier than the observation, and CMA-Meso and SCMOC are more consistent with the observation. 3) The TS scores of the three products with 24-hour precipitation greater than or equal to 0.1 mm are basically the same, but the characteristics of the precipitation forecast are significantly different. SCMOC has a high success rate, a low hit rate, more missed hits, and fewer false alarms than ECMWF and CMA-Meso models which are the opposite of SCMOC. SCMOC's TS score, success rate, and hit rate for 24 h, 3 h heavy rain, and above are better than the other two products. 4) The verification results of the MODE method show that SCMOC has the highest similarity between the forecast and observation of large-area precipitation objects, and its forecast ability is better than ECMWF and CMA-Meso. However, there is a high risk of missing a hit for scattered, small-area torrential rain objects. The east-west distance deviation of SCMOC and ECMWF is greater than that of the north-south direction, and the proportion of the west position is higher than that of the east position.

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潘留杰,张宏芳,刘静,刘嘉慧敏,梁绵,祁春娟,戴昌明,李培荣,2023.智能网格SCMOC及多模式降水预报对比[J].大气科学学报,46(2):217-229.
PAN Liujie, ZHANG Hongfang, LIU Jing, LIU Jiahuimin, LIANG Mian, QI Chunjuan, DAI Changming, LI Peirong,2023. Comparative analysis of SCMOC and various numerical models for precipitation forecasting[J]. Trans Atmos Sci,46(2):217-229. DOI:10.13878/j. cnki. dqkxxb.20220213001

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History
  • Received:February 13,2022
  • Revised:May 01,2022
  • Adopted:
  • Online: April 19,2023
  • Published: March 28,2023
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