| 基于S波段双极化雷达的变分法的定量降水估计算法 |
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| 引用本文： | 刘陈帅,张阿思,陈生. 基于S波段双极化雷达的变分法的定量降水估计算法[J]. 热带气象学报, 2022, 38(3): 422-432. DOI: 10.16032/j.issn.1004-4965.2022.036 |
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| 作者姓名： | 刘陈帅 张阿思 陈生 |
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| 作者单位： | 1.中山大学大气科学学院，广东 珠海 519082 |
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| 基金项目： | 国家自然科学基金项目41875182广州科技局计划项目201904010162中山大学“百人计划”项目74110-18841203广东省气候变化与自然灾害研究重点实验室2020B1212060025 |
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| 摘 要： | 基于比差分传播相移(KDP)的降水估计算法R(KDP)相较于传统基于水平反射率因子(ZH)的算法R(ZH)的表现更优。在雷达实际运行中，由于随机误差和后向散射相位(backscattering phase)的影响，可能出现负的KDP。运用一种基于变分的雷达定量降水估计混合算法(V-RQPE)。该算法用变分拟合方法重构差分相位(ΦDP)，用一种新的稳健的边界条件求解方法，在消除随机误差的同时获得非负的KDP，进而进行降水估计。随后我们使用2017年5月7日广州S波段雷达的回波数据和地面雨量站观测数据进行验证，同时使用了六种不同的算法进行对比，结果显示，在1小时累计降水估计中，V-RQPE表现最好，在24小时累计降水估计中，V-RQPE和基于变分拟合的KDP的降水估计算法(R-VKDP)表现最好，实验结果表明变分拟合方法对雷达降水估计能力有显著提升。
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| 关 键 词： | 变分拟合 雷达定量降水估计 比差分传播相移 边界条件 |
| 收稿时间： | 2021-02-04 |
A VARIATIONAL APPROACH FOR RETRIEVING QUANTITATIVE PRECIPITATION WITH S-BAND DUAL-POLARIZATION RADAR |
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| LIU Chenshuai,ZHANG Asi,CHEN Sheng. A VARIATIONAL APPROACH FOR RETRIEVING QUANTITATIVE PRECIPITATION WITH S-BAND DUAL-POLARIZATION RADAR[J]. Journal of Tropical Meteorology, 2022, 38(3): 422-432. DOI: 10.16032/j.issn.1004-4965.2022.036 |
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| Authors: | LIU Chenshuai ZHANG Asi CHEN Sheng |
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| Affiliation: | 1. School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai, Guangdong 519082, China;2. Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, Sun Yat-sen University, Zhuhai, Guangdong 519082, China;3. Key Laboratory of Tropical Atmosphere-Ocean System Sun Yat-sen University, Ministry of Education, Zhuhai, Guangdong 519082, China;4. Southern Laboratory of Ocean Science and Engineering, Zhuhai, Guangdong 519082, China;Guangdong Meteorological Observatory, Guangzhou 510641, China; Key Laboratory of Remote Sensing of Gansu Province, Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China |
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| Abstract: | Compared with the traditional radar quantitative precipitation estimation (QPE) algorithm R(ZH) based on reflectivity factor (ZH), the radar QPE algorithm based on specific differential phase shift (KDP) performs better. In the actual operation of radar, the random error and backscattering phase observed in the differential phase (ΦDP) result in negative KDP estimates. In this study, an improved variational hybrid radar QPE algorithm (V-RQPE) is used to quantitatively estimate the rainfall rate (R) from the KDP. In this algorithm, the ΦDP is reconstructed by using the improved variational approach based on a new robust boundary condition solution method. The reconstructed ΦDP may eliminate the random error and obtain the non-negative KDP at the same time. The approach is assessed with a real rainfall case on May 7, 2017 observed by an operational S-band dual-polarization radar in Guangzhou and compared with the other five different algorithms. The results show that: (1) V-RQPE performs best for the 1-hour cumulative precipitation estimation; (2) the quantitative estimate of R with the KDP derived from the optimized ΦDP based on variational approached (R-VKDP) demonstrates best performance for the 24-hour cumulative precipitation estimation; (3) the experimental results indicate that the variational approach to reconstruct the ΦDPcan help significantly improve radar precipitation estimation. |
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| Keywords: | variational approach quantitative precipitation estimation specific differential phase shift boundary condition |
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