Comparison of Gaussian, logarithmic transform and mixed Gaussian–log‐normal distribution based 1DVAR microwave temperature–water‐vapour mixing ratio retrievals
Comparison of Gaussian, logarithmic transform and mixed Gaussian–log‐normal distribution based 1DVAR microwave temperature–water‐vapour mixing ratio retrievals
复制标题
基于 1DVAR 微波温度-水蒸气混合比反演的高斯、对数变换和混合高斯-对数正态分布的比较
DOI：
10.1002/qj.2651
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发表时间：
2016
影响因子：
8.9
通讯作者：
J. Forsythe
中科院分区：
文献类型：
--
作者：
A. Kliewer;S. Fletcher;A. S. Jones;J. Forsythe
高斯分布假设在遥感反演和同化数值天气预报中得到了广泛的应用。由于许多地球物理变量服从对数正态分布而不是高斯分布，在合作大气研究所(CIRA)一维最优估计(C1DOE)反演系统中实施了对数正态和高斯混合分布的数据同化方案，将与温度有关的背景误差模拟为高斯分布，将与混合比有关的背景误差模拟为对数正态分布。将新的混合分布与传统的高斯分布和水汽混合比的对数变换在两种情况下进行了比较：(I)由对数正态分布产生的合成亮温和(Ii)2005年9月在西太平洋上空观测到的高级微波探测单元(AMSU)，在那里以前探测到了湿度的对数正态信号。对于情况1，假设对数正态分布的先验状态是一致的，基于对数正态分布的检索是最好的反转真实状态的方法。对于情况2，混合分配方案的最终创新是最小的。与微波地面和降水产品系统(MSPPS)的反演值进行了比较，与其他两种方法相比，对数正态方法始终更接近于这些值。
The assumption of a Gaussian distribution is widely used in remote sensing retrievals and data assimilation for numerical weather prediction. Since many geophysical variables follow a log‐normal distribution rather than a Gaussian distribution, a mixed log‐normal and Gaussian distribution data assimilation scheme is implemented in the Cooperative Institute for Research in the Atmosphere (CIRA) one‐dimensional optimal estimation (C1DOE) retrieval system to model the background errors associated with the temperature as a Gaussian and those with respect to the mixing ratio as log‐normal. The new mixed distribution is compared against the traditional Gaussian configuration and a logarithmic transformation for the water‐vapour mixing ratio for two situations: (i) synthetic brightness temperatures generated from a log‐normal distribution and (ii) Advanced Microwave Sounding Unit (AMSU) observations from the month of September 2005 over the west Pacific, where a log‐normal signal for moisture had previously been detected. It is shown for Case 1 that, given a consistent a priori state for a log‐normal distribution, the log‐normal distribution based retrieval is the best at inverting the true state back. For Case 2, the final innovations are smallest for the mixed distribution scheme. The retrieval values are compared against the Microwave Surface and Precipitation Products System (MSPPS) and the log‐normal approach is consistently closer to the values compared with these other two approaches.