1.Chengdu Universiy ofInformation Technology;2.Climate Center of Fujian Province;3.Numerical Weather Prediction Center,China MeteorologicalAdministration;4.Chinese Academy of Meteorological Sciences
National Science and Technology Major Project of the Ministry of Science and Technology of China (2018YFC1507405)
为深入了解GRAPES（Global/Regional Assimilation and Prediction System）3km对流尺度区域模式对华南前汛期精细化降水的预报性能,为模式改进及业务应用提供参考依据，针对广东省复杂地形特点，根据距离海岸线的远近将站点分为沿海东部、沿海西部和内陆地区三个子区域，利用广东省86个站点逐小时观测降水资料和国家气象信息中心多源融合降水资料，采用二分类降水预报检验方法，定量评估了2020年5月18日-6月18日华南前汛期降水预报效果。结果显示，GRAPES_Meso 3km精细化降水预报技巧受广东复杂地形影响较大，广东沿海东部和内陆地区24小时累积降水小雨、中雨、大雨预报成功指数评分（Threat Score， TS）、公平成功指数（Equitable Threat Score，ETS）评分高于沿海西部地区，尽管暴雨预报评分具有此相同特征，但三个子区域暴雨预报技巧总体较低；从 3h累积降水预报评分看，沿海东部、沿海西部及内陆地区等三个子区域预报评分存在明显的日变化特征，但是沿海东部和西部与内陆地区表现有所不同，沿海东部和西部预报技巧表现为夜间较低（预报偏差偏高），白天相对较高（预报偏差偏低），而内陆地区则是夜间预报技巧较高（预报偏差偏低），白天相对较低（预报偏差偏高）。沿海西部预报技巧相对较低的原因是由于检验时段内广东地区存在一个弱的风切变，而沿海西部大部分地区正好处于切变线南侧的温度高值区控制，但模式模拟该地区日平均温度较实况偏低，使得相对湿度较实况偏大，导致沿海西部模式预报降水空报较多，降低其降水预报技巧。
To learn more about the performance of GRAPES_Meso 3km (Global/Regional Assimilation and Prediction System) model for precipitation prediction in the first flood season of South China and to provide reference for improvement and operational application, the hourly precipitation data of 86 stations in Guangdong Province were selected. According to the distance to the coastline, the stations were divided into three sub-regions: the eastern coastal region, the western coastal region and the inland region. By using the Threat score (TS), the Equitable Threat Score(ETS), the forecast bias score and other indicators, the quantitative evaluation was carried out from 18 to 6 may 2020 The forecast effect of precipitation in the first flood season of South China on June 18. On the whole, the TS and ETS scores of light rain, moderate rain, heavy rain and rainstorm in the eastern coastal area and inland area are higher than those in the western coastal area, but the rainstorm forecasting skills of the three sub regions are lower; from the 3H cumulative precipitation score, the forecasting scores of the three sub regions have obvious diurnal variation characteristics, but the performance of the eastern coastal area and the western coastal area is different from that of the inland area In the eastern and western coastal areas, the night forecast skill is relatively low (the bias is high), and the daytime forecast skill is relatively high (the bias is low), while the daily variation in inland areas is relatively high (the bias is low), and the daytime forecast skill is relatively low (the bias is high); the reason for the relatively low forecast skill in the western coastal areas is due to the verification period There is a weak wind shear in Inner Guangdong, and most of the western coastal areas are just controlled by the high temperature area on the south side of the shear line. However, the daily average temperature in this area simulated by the model is lower than the actual situation, and the relative humidity is higher, which leads to more air forecasts of precipitation in the western coastal areas, and reduces the skills of precipitation forecast.
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