An Active/Passive Microwave Retrieval Algorithm for Inferring Ocean Vector Winds from TRMM

Alamgir Hossan, M. Jacob, W. Linwood Jones, Harriet Medrozo
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引用次数: 5

Abstract

This paper describes a novel ocean vector wind (OVW) retrieval algorithm that uses Ku-band Precipitation Radar (PR) and the multi-frequency TRMM Microwave Imager (TMI), both on board the Tropical Rainfall Measuring Mission (TRMM) satellite. The basis of this algorithm is the anisotropic nature of ocean backscatter (sig-0) and brightness temperature (Tb), which are used in a maximum likelihood estimation procedure to infer wind speed and wind direction. For this paper, we leverage from previous research that characterized the Geophysical Model Functions (GMF) for both TMI and PR observations. NOAA Numerical Weather Product (GDAS) was used as a nature run, to perform a Monte Carlo simulation to conduct trade studies and predict the OVW retrieval performance over the TRMM orbit. Examples of retrieved ocean winds and statistics of WS and WD differences are presented.
一种从TRMM推断海洋矢量风的主动/被动微波检索算法
本文介绍了一种利用热带降雨测量任务(TRMM)卫星上的ku波段降水雷达(PR)和多频TRMM微波成像仪(TMI)进行海洋矢量风(OVW)反演的新算法。该算法的基础是海洋后向散射(sig-0)和亮度温度(Tb)的各向异性特性,这两个特性被用于最大似然估计过程中来推断风速和风向。在本文中,我们利用了以前的研究,描述了TMI和PR观测的地球物理模型函数(GMF)。使用NOAA数值天气产品(GDAS)作为自然运行,执行蒙特卡罗模拟以进行贸易研究并预测TRMM轨道上的OVW检索性能。给出了海风反演的实例以及WS和WD差异的统计数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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