雷达与雨量计同步结合区域型估算降水方程的误差分析

Error analysis of the regional radar-raingauge synchronously integrated precipitation estimation equation

中文关键词:  雷达-雨量计  同步结合  区域估算方程  误差分析

英文关键词:Radar-raingauge  Synchronous integration  Regional estimation equation  Error analysis

中文摘要:

      在明确提出云雨转换的概念和建立4个区域型雷达降水估算方程的基础上, 重点研究了A_BS区域型降水估算方程误 差估算的表示方法和评估判据, 并分析了误差产生的原因, 由此建立一种可通过设定μ_i合理区间来判别雷达和雨量计错误数据对的质量控制新方法。单站云雨转换系数A_Bi是时空的函数, 带有强烈的天气系统和地理属性。A_Bi与区域云雨转换公共 系数A_BS以b_f^-1为指数幂值的相对离差就等于单站降水误差估算因子μ_i,从而揭示了引起降水估算误差的根本原因。在μ_i的基础上扩展衍生出表示区域降水估算误差的4个量值, 即区域平均绝对误差估算因子μ_A、区域降水误差估算率μ_S、区域降水 绝对误差估算率μ_|S|及区域平均绝对误差估算量E_N,指明了各自的物理意义并分析其间的相互关系。理论和实践表明, 在 “基于准同雨团样本概念雷达和雨量计的实时同步结合方法”(RASIM)中, A_BS型区域降水估算方程对于区域各站降水总量的 估算具有μ_S=0的特点。μ_A是区域内各单站|μ_i|的平均值, 可诠释为多个单站的A_Bi相对于A_BS的聚合与离散程度的整体表示, 与天气系统的结构及演变过程特征的复杂性密切相关, 但μ_A与雨量大小无关, 无力判定降水估算的误差量。而μ_|S|和E_N 既联系着μ_A,又与雨量有关, 是较为合理而实用的降水估算误差判据。经过武汉雷达探测4次降水过程的试验评估, 总体绝 对误差率μ_T|S|小于30%,比未经过质量控制的误差减少7%.

英文摘要:

      The concepts of cloud-rain transform are presented and the four regional radar precipitation estimation equations are proposed. Our research is focused on the expression methods and evaluation criterions of errors of A_BS regional radar precipitati on estimation equations. The reason for radar precipitation estimation error is analyzed, and a new data quality control method is proposed to judge erroneous radar-raingauge data pairs through restraining μ_i,within a reasonable rang. The cloud-rain transform coefficient A_Bi of a single station is a spatial-temporal function with strong weather and geographic characteristics. The single station misestimate factor μ_i is given by the relative deviation of A_Bi to the power of b_f^-1 from A_BS to the power of b_f^-1, and it reveals that the fundamental cause of precipitation estimation error is the difference between single station observed A_Bi and the whole region common A_BS. Originated from μ_i,the four other factors describing regional precipitation estimation errors arc defined: the regional average absolute misestimate factor μ_A,the regional precipitation misestimatc ratio μ_s and the regional precipitation absolute misestimate ratio μ_|s| and the regional average absolute misestimate value E_N. The physical meanings of the four factors arc explained and their corrclations are analysed. In the RASIM method, the A_BS regional precipitation estimation equation shows the advantage of zero error of regional total precipitation estimation(μ_s=0) both in theory and prac-tice. The factor μ_A is the average value of each single station |μ_A| among the whole region, and can be interpreted as a general expression of coherence and deviation of multiple A_Bi from A_BS. The factoris μ_A is closely related to the weather system structure and the complexity of its evolution process, however, it is unrelated to the amount of precipitation and incapable to judge precipitation estimation error value. The factors μ_|s| and E_N are related to both μ_A and precipitation, and thus they are reasonable and suitable judge criterions for precipitation estimation errors. The experimental evaluations from radars at Wuhan during the four rain events give a value of total ahsolute misestimate ratio μ_T|S| less than 30%, which is a decrease of 7% compared with that without quality control.