| 2013年汛期华中区域业务数值模式降水预报检验 |
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| 引用本文： | 陈超君,李俊,王明欢.2013年汛期华中区域业务数值模式降水预报检验[J].气象与环境学报,2015,31(2):1-8. |
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| 作者姓名： | 陈超君 李俊 王明欢 |
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| 作者单位： | 中国气象局武汉暴雨研究所 暴雨监测预警湖北省重点实验室，湖北 武汉 430074 |
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| 基金项目： | 水利部公益行业专项，国家自然科学基金(41275107、41405106)共同资助。 |
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| 摘 要： | 为充分了解华中区域中尺度业务数值预报模式更新为WRF后的预报性能，对该模式2013年汛期24 h和48 h的累积降水预报产品，采用TS评分、预报正确率、漏报率、空报率、偏差及ETS评分等统计量对其进行了较详细的评估。结果表明：从日平均降水率分布来看，24 h预报的降水中心位置和强度与实况更接近，48 h的预报明显偏大、偏强；汛期总体降水检验表明，该模式的降水预报以偏大为主，随着降水量级的增大，TS和ETS评分逐渐减小，且ETS评分逐渐靠近TS；逐月降水检验结果发现，该区域汛期月晴雨预报正确率与雨日率呈正相关；通过梅雨期WRF与GRAPES_Meso的预报对比检验可见，两个模式都表现出了较好的预报性能。值得指出的是，随着降水量级的增大，WRF模式降水预报优势逐渐显现。总的来说，该模式的降水预报产品具有一定的参考价值。
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| 关 键 词： | 检验评估 数值模式 降水预报 |
Verification of precipitation forecast using an operational numerical model during flooding season of 2013 in the middle area of China |
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| CHEN Chao-jun,LI Jun,WANG Ming-huan.Verification of precipitation forecast using an operational numerical model during flooding season of 2013 in the middle area of China[J].Journal of Meteorology and Environment,2015,31(2):1-8. |
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| Authors: | CHEN Chao-jun LI Jun WANG Ming-huan |
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| Institution: | Hubei Key Laboratory for Heavy Rain Monitoring and Warning Research, Institute of Heavy Rain, China Meteorological Administration, Wuhan 430074, China |
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| Abstract: | The meso-scale numerical weather prediction system in the middle region of China has been updated recently with WRF model. In order to evaluate the prediction performance of the updated forecasting system, 24 and 48 hours precipitation prediction during the flood season of 2013 were analyzed in terms of TS score, forecast accuracy rate, missing alarm rate, false alarm rate, bias and ETS score. The results show that for 24 hours forecast, the distribution of daily mean precipitation rate, precipitation intensity and center position are closer to those of observation, while those from the 48 hours forecasts are significantly overestimated. Precipitation verification during the flood season suggests that most precipitation forecasts are overestimated, and TS and ETS scores decrease gradually and ETS score is gradually close to TS score with the increase of precipitation grade. Monthly precipitation verification suggests that accuracy rate of rainy and shine weather forecast is in a positive correlation with rainy day rate. Verification of forecasts from two models (WRF and GRAPES_Meso) shows that both have good prediction scores. It is worth noting that forecast results by the WRF are getting better with the increase of precipitation grade. In general, precipitation prediction products of this model are of a certain references to the precipitation forecast. |
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| Keywords: | Verification Numerical weather prediction model Precipitation prediction |
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