Nowcasting Rainfall Fields Derived from Specific Differential Phase
Nowcasting Rainfall Fields Derived from Specific Differential Phase
复制标题
由特定微分相位得出的临近预报降雨场
DOI：
10.1175/jamc-d-11-081.1
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发表时间：
2012
影响因子：
3
通讯作者：
V. Chandrasekar
中科院分区：
文献类型：
--
作者：
E. Ruzanski;V. Chandrasekar
短期自动预报（nowcasting）的降水传统上是使用雷达反射率数据，但最近的研究表明，使用特定的差分相位Kdp有几个优点，使用反射率估计降雨。本文提出了一种评估的nowcastingKdp为基础的降雨场的特点，使用协作自适应传感的大气Kdp估计和临近预报方法，适用于约42小时的X波段雷达网络数据。结果表明，在连续意义下（基于互相关），Kdp降水场的寿命约为17 min，而反射率Zh降水场的寿命约为15 min。分类（技能评分为基础）的寿命为~26分钟观察到Kdp为基础的降雨场相比，~30分钟Zh为基础的降雨场。雷达雨量计的验证表明，kdp为基础的降雨量估计始终performedZh-based的估计了30分钟的提前时间，但两个估计之间的差异减少的归一化标准误差增加提前时间。
Short-term automated forecasting (nowcasting) of precipitation has traditionally been done using radar reflectivity data; recent research, however, indicates that using specific differential phaseKdphas several advantages over using reflectivity for estimating rainfall. This paper presents an evaluation of the characteristics of nowcastingKdp-based rainfall fields using the Collaborative Adaptive Sensing of the AtmosphereKdpestimation and nowcasting methods applied to approximately 42 h of X-band radar network data. The results show thatKdp-based rainfall fields exhibit lifetimes of ~17 min as compared with ~15 min for rainfall fields derived from reflectivityZhin a continuous (cross correlation based) sense. Categorical (skill score based) lifetimes of ~26 min were observed forKdp-based rainfall fields as compared with ~30 min forZh-based rainfall fields. Radar–rain gauge verification showed thatKdp-based rainfall estimates consistently outperformedZh-based estimates out to a lead time of 30 min, but the difference between the two estimators decreased in terms of normalized standard error with increasing lead time.