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Sensitivity of Rain-Rate Estimates Related to Convective Organization: Observations from the Kwajalein, RMI, Radar

机译:与对流组织有关的雨率估计的敏感性:KWAJALEIN,RMI,RADAR的观察

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Ground radar rainfall, necessary for satellite rainfall product (e.g., TRMM and GPM) ground validation (GV) studies, is often retrieved using annual or climatological convective/stratiform Z-R relationships. Using the Kwajalein, Republic of the Marshall Islands (RMI), polarimetric S-band weather radar (KPOL) and gauge network during the 2009 and 2011 wet seasons, the robustness of such rain-rate relationships is assessed through comparisons with rainfall retrieved using relationships that vary as a function of precipitation regime, defined as shallow convection, isolated deep convection, and deep organized convection. It is found that the TRMM-GV 2A53 rainfall product underestimated rain gauges by -8.3% in 2009 and -13.1% in 2011, where biases are attributed to rainfall in organized precipitation regimes. To further examine these biases, 2A53GV rain rates are compared with polarimetrically tuned rain rates, in which GV biases are found to be minimized when rain relationships are developed for each precipitation regime, where, for example, during the 2009 wet-season biases in isolated deep precipitation regimes were reduced from -16.3% to -4.7%. The regime-based improvements also exist when specific convective and stratiform Z-R relationships are developed as a function of precipitation regime, where negative biases in organized convective events (-8.7%) are reduced to -1.6% when a regime-based Z-R is implemented. Negative GV biases during the wet seasons lead to an underestimation in accumulated rainfall when compared with ground gauges, suggesting that satellite-related bias estimates could be underestimated more than originally described. Such results encourage the use of the large-scale precipitation regime along with their respective locally characterized convective or stratiform classes in precipitation validation endeavors and in development of Z-R rainfall relationships.
机译:卫星降雨量的地面雷达降雨,卫星降雨产品(例如,TRMM和GPM)地面验证(GV)研究通常使用年度或气候对流/层状Z-R关系来检索。在2009年和2011年潮湿的季节使用Kwajalein(RMI),Polariemetric S频段天气雷达(KPOL)和仪表网络,通过利用关系检索降雨的比较来评估这种雨率关系的鲁棒性随着降水制度的函数而变化,定义为浅对流,孤立的深度对流和深组织对流。有人发现,2011年,2009年的降雨量高估了-8.3%的降雨量-8.3%,偏差归因于有组织降水制度的降雨。为了进一步检查这些偏差,将2A53GV雨率与极性调谐雨率进行比较,其中发现GV偏差在为每个降水状态开发雨部关系时,例如,在孤立的2009年湿季偏差期间深度降水制度从-16.3%降低至-4.7%。当特异性对流和层状Z-R关系作为沉淀制度的函数开发时,基于政权的改进也存在于组织对流事件(-8.7%)中的负偏差减少到-1.6%时,当实施制度的Z-R时。与地板仪相比,湿季期间的负GV偏差导致累积降雨量的低估,表明卫星相关的偏差估计可以低于最初描述的。这种结果鼓励使用大规模降水制度以及各自的局部表征的对流或层状阶段,以及Z-R降雨关系的发展。

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