两种双偏振雷达降水估测算法对比检验评估

Comparative verification and evaluation of two dual-polarization radar quantitative precipitation estimation algorithms

摘要

【目的】CSU-HIDRO算法和WSR88D算法是业务中主要的双偏振雷达定量降水估测算法，但两者在不同气候背景下的可用性存在一定差异，为详细评估2种算法在环上海地区的具体适用情况。【方法】利用上海青浦S波段双偏振雷达和雷达扫描范围内的自动站分钟雨量数据，基于2023—2024年环上海地区的46次典型降水过程，采用不分级、降水实况强度分级(雨强分级)、站点与雷达距离分级(距离分级)、影响系统分型4种方式对CSU-HIDRO算法和WSR88D算法进行检验评估。【结果】其结果显示：(1)CSU-HIDRO算法在不分级检验、雨强分级检验和距离分级检验评估中，其准确度均要高于WSR88D算法。且CSU-HIDRO算法在小时雨强35~50 mm区间内和距离雷达10~75 km范围内的降水估测效果最优。(2)影响系统分型检验显示，2种算法对高空冷平流强迫类天气的降水估测能力相当，但在低层暖平流强迫类天气、准正压类天气和斜压锋生类天气样本中，CSU-HIDRO算法的定量降水估测效果要优于WSR88D算法。【结论】总体上，CSU-HIDRO算法在环上海地区的综合适用性更强，尤其在中等雨强和中等距离范围内估测精度更高，可为该区域的雷达降水反演提供更优选择。

Abstract

[Objective] The CSU-HIDRO and WSR88D algorithms are the primary dual-polarization radar quantitative precipitation estimation(QPE) algorithms used in operational meteorology. However, their applicability varies under different climatic conditions, necessitating a detailed evaluation of the suitability of these two algorithms in the peri-Shanghai region.[Methods] Data from the S-band dual-polarization radar in Qingpu, Shanghai, and minute-level rainfall data from automatic stations within the radar coverage were utilized. Based on 46 typical precipitation events in the peri-Shanghai region from 2023 to 2024, the CSU-HIDRO and WSR88D algorithms were evaluated and verified using four method: non-stratified assessment, stratification by observed rainfall intensity(rain rate stratification), stratification by station-to-radar distance(distance stratification), and classification of influencing weather systems.[Results] The result showed that:(1) the accuracy of the CSU-HIDRO algorithm was higher than that of the WSR88D algorithm in unstratified, rain rate-stratified, and distance-stratified evaluation. Moreover, the CSU-HIDRO algorithm achieved the best precipitation estimation performance within the range of hourly rainfall intensity between 35 and 50 mm and within distances of 10 to 75 km from the radar.(2) Verification based on weather system types revealed that both algorithms demonstrated comparable precipitation estimation performance for weather systems forced by upper-level cold advection. However, for samples of weather systems forced by low-level warm advection, quasi-barotropic systems, and baroclinic frontogenesis systems, the CSU-HIDRO algorithm outperformed the WSR88D algorithm in quantitative precipitation estimation.[Conclusion] Overall, the CSU-HIDRO algorithm demonstrates stronger applicability in the peri-Shanghai region. It provides higher estimation accuracy, especially for moderate rainfall intensity and medium distances, thereby providing a better option for radar-based precipitation retrieval in this region.

关键词

双偏振雷达 / WSR88D / CSU-HIDRO / 降水估测 / 检验评估 / 分钟雨量 / 天气分型 / 影响因素

Key words

dual-polarization radar / WSR88D / CSU-HIDRO / precipitation estimation / verification and evaluation / minute-scale rainfall / weather pattern classification / influencing factors

基金资助

国家重点研发计划项目(2022YFC3003905)

上海市科委自然科学基金(23ZR1447300)

中国气象局创新发展专项(CXFZ2024J001)

中国气象局气象能力提升联合研究专项(23NLTSZ002)

中国气象局青年创新团队(CMA2023QN06)

中国气象局青年创新团队(CMA2024QN02)

上海市气象局科技人才类项目(KJRC202403)

上海市气象局科技人才类项目(KJRC202411)