A Hybrid Method to Estimate Specific Differential Phase and Rainfall With Linear Programming and Physics Constraints
A Hybrid Method to Estimate Specific Differential Phase and Rainfall With Linear Programming and Physics Constraints
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DOI：
10.1109/tgrs.2016.2596295
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发表时间：
2017
影响因子：
8.2
通讯作者：
Hao Huang;Guifu Zhang;K. Zhao;S. Giangrande
中科院分区：
文献类型：
--
作者：
Hao Huang;Guifu Zhang;K. Zhao;S. Giangrande
提出了一种结合线性规划和物理约束的混合方法来估计特定差相（KDP），并改进了降雨估计。利用模拟数据对混合KDP估计器和现有的LP估计器、最小二乘拟合估计器以及极化雷达变量自一致关系估计器进行了评估和比较。仿真结果表明了该估计器的优越性，特别是在后向散射相位（δhv）占主导地位的区域。此外，对梅雨事件的自动气象站雨量计观测和基于KDP的雷达雨量估计的定量比较也证明了混合KDP估计比现有方法的优越性。
A hybrid method of combining linear programming (LP) and physical constraints is developed to estimate specific differential phase (KDP) and to improve rain estimation. The hybrid KDP estimator and the existing estimators of LP, least squares fitting, and a self-consistent relation of polarimetric radar variables are evaluated and compared using simulated data. Simulation results indicate the new estimator's superiority, particularly in regions where backscattering phase (δhv) dominates. Furthermore, a quantitative comparison between auto-weather-station rain-gauge observations and KDP-based radar rain estimates for a Meiyu event also demonstrate the superiority of the hybrid KDP estimator over existing methods.