| 同化风廓线雷达资料对浙江降水预报改进评估 |
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| 引用本文： | 余贞寿,冀春晓,杨程,黎玥君.同化风廓线雷达资料对浙江降水预报改进评估[J].应用气象学报,2018,29(1):97-110. |
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| 作者姓名： | 余贞寿 冀春晓 杨程 黎玥君 |
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| 作者单位： | 浙江省气象科学研究所, 杭州 310008 |
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| 基金项目： | 浙江省科技计划项目（2014C33056），浙江省气象科技计划项目（2013ZD01），华东区域高分辨数值预报众创平台项目“非常规资料分析及同化应用（风廓线）” |
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| 摘 要： | 采用中尺度模式WRF和美国俄克拉荷马大学风暴分析预测中心的资料同化系统开展中国东部地区35部风廓线雷达资料同化试验研究，在同化1 h平均采样产品前，对其进行气候极值检查、一致性检查、垂直稀疏化等质量控制，选取2014年5月16-17日暴雨过程评估同化风廓线雷达资料对降水预报的影响，探讨其对初始场改进作用，之后，通过批量试验再次确认同化风廓线雷达资料可有效提高降水预报能力。个例同化试验对比分析表明:同化风廓线雷达资料后，暴雨区及其上游地区850 hPa的风速增强20%~30%，水汽通量增加30%~50%，大气层结不稳定性增强，小雨和大雨TS评分分别提高0.06和0.07，暴雨漏报率和空报率分别降低0.04和0.05，降水预报得到改进。
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| 关 键 词： | 风廓线雷达 数值天气预报 资料同化 降水 |
| 收稿时间： | 2017/6/30 0:00:00 |
| 修稿时间： | 2017/10/9 0:00:00 |
Impacts of Assimilating Wind Profiler Radar Observations on Precipitation Prediction in Zhejiang Province |
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| Yu Zhenshou,Ji Chunxiao,Yang Chen and Li Yuejun.Impacts of Assimilating Wind Profiler Radar Observations on Precipitation Prediction in Zhejiang Province[J].Quarterly Journal of Applied Meteorology,2018,29(1):97-110. |
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| Authors: | Yu Zhenshou Ji Chunxiao Yang Chen and Li Yuejun |
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| Institution: | Zhejiang Institute of Meteorological Sciences, Hangzhou 310008 |
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| Abstract: | Wind profiler radar (WPR) is a new type of wind measuring radar, which has advantages of high spatial resolution, continuity and good instantaneity. With the increase of wind profile radar year by year, it is meaningful to apply this kind of wind field observations to the numerical model to improve the model prediction ability. The meso-scale numerical prediction model WRF and the assimilation system ADAS developed by Center for Analysis and Prediction of Storms, University of Oklahoma, is used to study effects of assimilating observations of 35 wind profiler radars in eastern China on precipitation prediction over Zhejiang. Prior to assimilation, 1 h average sampling product data are subjected to climate extreme inspection, consistency check and vertical thinning for quality control. A spring rainstorm process on 16-17 May 2014 is selected as an example to evaluate effects of WPR data assimilation on the quality of precipitation forecast in detail. And effects of WPR data are also verified by batch experiments starting from 0000 UTC and 1200 UTC during the whole June of 2015. Results show that the model precipitation TS and ETS scores are improved, especially for heavy rainfalls. At the same time, the false alarm ratio (FAR) and frequency of misses (FOM) for heavy and torrential rain decrease after WPR data assimilation, but the FAR of moderate rain increase. The case study shows that WPR data assimilation can adjust the initial field of low layer wind field, increase small scale weather information, and improve the horizontal wind prediction on the whole layers. For 12 h wind forecast field, the result of assimilation of WPR is obviously better than that without the assimilation. In addition, the improvement of the zonal wind is more obvious than that of the meridional wind after WPR data assimilation. The case study shows that 850 hPa wind speed is enhanced by 20%-30%, water vapor flux is increased by 30%-50%, and the atmospheric instability in the rainstorm area and its upstream region is also enhanced after WPR data assimilation. As a result, TS of light rain and heavy rain is increased by 0.06-0.07, and FAR and FOM of rainstorm is reduced by 0.04-0.05. Although the assimilation of wind profiler data can improve the precipitation prediction quality, there are still some problems, such as an unexplained overestimation of regional average precipitation, which needs further investigation. |
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| Keywords: | wind profiler radar numerical weather prediction data assimilation precipitation |
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