Effect of Natural Variations in Rain Drop Size Distributions on Rain Rate Estimators of 3 cm Wavelength Polarimetric Radar
Effect of Natural Variations in Rain Drop Size Distributions on Rain Rate Estimators of 3 cm Wavelength Polarimetric Radar
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雨滴尺寸分布自然变化对 3 cm 波长极化雷达雨率估算器的影响
DOI：
10.2151/jmsj.83.871
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发表时间：
2005
影响因子：
3.1
通讯作者：
V. Bringi
中科院分区：
文献类型：
--
作者：
M. Maki;Sang;V. Bringi
本文研究了3厘米波长偏振雷达雨滴谱的自然变化对降雨率估计的统计误差。四种类型的估计：一个经典的估计R（ZH），和三种类型的极化雷达估计R（KDP），R（ZH，ZDR），和R（KDP，ZDR），其中R是降雨率，ZH是在水平偏振的反射率因子，KDP是特定的微分相位，和ZDR是微分反射率。采用T矩阵方法计算了7,664个用Joss-Waldvogel型雨滴谱仪测量的1min雨滴谱，计算结果表明，R（ZH）、R（KDP）、R（KDP，ZDR）和R（ZH，ZDR）的归一化误差分别为25%、14%、9%和10%。除R（ZH）外，所有估计的净误差均随降雨率的增加而减小。对于大于10 mmh − 1的降雨率，例如，R（ZH）、R（KDP）、R（KDP，ZDR）和R（ZH，ZDR）的平均NE分别为25%、9%、5%和7%。模拟结果表明，经典估计量R（ZH）对DSD的变化最敏感，而估计量R（KDP，ZDR）对DSD的变化最不敏感，而降雨量估计量R（KDP，ZDR）对DSD的变化最不敏感的原因是：在水平和垂直偏振的前向散射振幅的差异，这有助于KDP，是成比例的4.78次幂的液滴直径。另一方面，对ZH有贡献的后向散射截面的指数与液滴直径的6.38次方成比例。由于降雨率R与水滴直径的3.67次方成正比，因此KDP对DSD变化的敏感性低于ZH。然而，DSD光谱与异常大的中值体积直径D0可以增加R（KDP）的估计误差。差分反射率ZDR减小了异常D0的影响，并且对于进一步改进估计器R（KDP）是有用的。这是因为ZDR本身是D0的一个很好的度量。
Statistical errors of rain rate estimators due to natural variations in raindrop size distribution (DSD) are studied for 3-cm wavelength polarimetric radar. Four types of estimators are examined: A classical estimator R(ZH), and three types of polarimetric radar estimators R(KDP), R(ZH, ZDR), and R(KDP, ZDR), where R is the rain rate, ZH is the reflectivity factor at horizontal polarization, KDP is the specific differential phase, and ZDR is the differential reflectivity. The T-matrix method is employed for the scattering calculations, and a total of 7,664 one-minute raindrop size spectra, measured with a Joss-Waldvogel type disdrometer are used.According to simulation results, the normalized errors (NEs) of R(ZH), R(KDP), R(KDP,ZDR), and R(ZH,ZDR) for all DSD samples are 25%, 14%, 9%, and 10%, respectively. The NEs of all estimators, except R(ZH), tend to decrease with increasing rain rate. For rain rates larger than 10 mmh−1, e.g., the average NEs of R(ZH), R(KDP), R(KDP, ZDR), and R(ZH,ZDR) are 25%, 9%, 5%, and 7%, respectively. The simulation results show that the classical estimator R(ZH) is the most sensitive to variations in DSD and the estimator R(KDP, ZDR) is the least sensitive.The lowest sensitivity of the rain estimator R(KDP, ZDR) to variations in DSD can be explained by the following facts. The difference in the forward-scattering amplitudes at horizontal and vertical polarizations, which contributes KDP, is proportional to the 4.78th power of the drop diameter. On the other hand, the exponent of the backscatter cross section, which contributes to ZH, is proportional to the 6.38th power of the drop diameter. Because the rain rate R is proportional to the 3.67th power of the drop diameter, KDP is less sensitive to DSD variations than ZH. However, DSD spectra with unusually large median volume diameter D0 can increase the estimation error of R(KDP). The differential reflectivity ZDR reduces the effect of unusual D0 and is useful for further improvement of the estimator R(KDP). This is due to the fact that ZDR itself is a good measure of D0.