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| 定量测量降水量的回波结构自适应算法研究 | |
| 引用本文： | 魏鸣,宋羽轩,张蕾.定量测量降水量的回波结构自适应算法研究[J].大气科学学报,2018,41(5):676-683. |
| 作者姓名： | 魏鸣 宋羽轩 张蕾 |
| 作者单位： | 南京信息工程大学 气象灾害预报预警与评估协同创新中心, 江苏 南京 210044;南京信息工程大学 中国气象局气溶胶-云-降水重点开放实验室, 江苏 南京 210044;南京信息工程大学 气象灾害预报预警与评估协同创新中心, 江苏 南京 210044;南京信息工程大学 气象灾害预报预警与评估协同创新中心, 江苏 南京 210044 |
| 基金项目： | 国家自然科学基金资助项目（41675029）；国家重点基础研究发展计划（973计划）项目（2013CB430102） |
| 摘 要： | 为提高临近预报中对流性降水估测的准确性,分析了统计法估算降水的局限性。依据降水物理机制和降水回波结构,研究雷达反射率因子定量测量降水量(QPE-Qualitative Precipitation Estimate)的自适应算法,旨在减少由于雨滴谱变化导致的Z-I关系不稳定所引起的降水量测量误差。同时考虑组合反射率因子RC和垂直液态水含量VIL两个参量对降水的影响,建立适于城市区域的动态自适应的Z-I关系,改进对强降水严重低估的问题。 |
| 关 键 词： | 雷达 定量降水估计 回波 结构 自适应 |
| 收稿时间： | 2015/4/8 0:00:00 |
| 修稿时间： | 2016/1/8 0:00:00 |
An examination of the self-adaption algorithms used in qualitative precipitation estimations |
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| WEI Ming,SONG Yuxuan and ZHANG Lei.An examination of the self-adaption algorithms used in qualitative precipitation estimations[J].大气科学学报,2018,41(5):676-683. | |
| Authors: | WEI Ming SONG Yuxuan and ZHANG Lei |
| Institution: | Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science & Technology, Nanjing 210044, China;Collaborative Innovation Center on Forecast and Evaluation of Meterological Disasters(CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing 210044, China;Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science & Technology, Nanjing 210044, China;Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science & Technology, Nanjing 210044, China |
| Abstract: | Currently, major challenges exist in the area of the quantitative precipitation estimations of convective short-term flooding caused by local heavy rainfall events. In this study, in order to improve the accuracy of the forecasting of the convective precipitation estimates, various currently used quantitative measurements methods for precipitation were summarized. Then, the limitations of these statistical methods for rainfall estimations were analyzed. It is known that different types of precipitation affect the accuracy of the precipitation estimates due to the variations in power, heat, and water vapor, which result in different micro-physical mechanisms and internal structures. Therefore, based on the physical mechanisms of the precipitation, along with the precipitation echo structures, the coefficient A and exponent b in the Z-I relationship become spatial functions rather than simple constants. Therefore, they can provide a theoretical basis for an adaptive method which can be effectively used to quantitatively estimate precipitation. In this research study, the mechanisms of convective precipitation, mixed precipitation, and stratiform precipitation were examined, and the echo structural features, precipitation micro-physical characteristics, and echo extinction laws were analyzed. It is known that multiple parameters have certain impacts on precipitation, such as composite reflectivity factors (CR) and vertical liquid water content (VIL). Therefore, it was necessary to first distinguish the three different types of precipitation from the structure, and then use statistical methods for the fitting process. The lgRC-lgI and RC-I data pairs were respectively utilized. Then, depending on the type of rain event and the corresponding Z-I relationship, the precipitation measurement errors were reduced which had resulted from the unstable Z-I relationship caused by changes in the rain events, in order to solve the problem of the serious underestimations of heavy rainfall events. The results of this study showed that the lgRC-lgI data pairs displayed better fitting results when fit by order, and RC-I data pairs exhibited better results when fit by high-order. These findings indicated that the adaptive method which was used to quantitative estimate the precipitation was reasonable. Also, the instability of the Z-I relationship caused by the physical properties and structural characteristics of the precipitation was revealed. This study also investigated the binary function relationships among the CR, VIL, and precipitation of convective and mixed precipitation. It was observed that there was a high correlation between the fitting results. The results confirmed that by taking the CR and VIL into account, the issue of significantly underestimating heavy rainfall events could be resolved. |
| Keywords: | Radar QPE echo structures self-adaption |
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