Impact of Rain Effects on L-Band Passive Microwave Satellite Observations Over the Ocean

被引:0
|
作者
Jin, Xuchen [1 ,2 ]
He, Xianqiang [2 ,3 ,4 ,5 ]
Wang, Difeng [2 ]
Ying, Jianyun [6 ]
Gong, Fang [2 ]
Zhu, Qiankun [2 ]
Zhou, Chenghu [1 ]
Pan, Delu [2 ]
机构
[1] Southern Marine Sci & Engn Guangdong Lab Guangzho, Guangzhou 511458, Peoples R China
[2] Minist Nat Resources MNR, State Key Lab Satellite Ocean Environm Dynam SOED, Inst Oceanog SIO 2, Hangzhou 310012, Peoples R China
[3] Donghai Lab, Zhoushan 316021, Peoples R China
[4] Shanghai Jiao Tong Univ, Sch Oceanog, Shanghai 200030, Peoples R China
[5] Zhejiang Univ, Ocean Coll, Zhoushan 316000, Peoples R China
[6] Minist Nat Resources MNR, Inst Oceanog SIO 2, Lab Ocean Engineer, Hangzhou 310012, Peoples R China
基金
中国国家自然科学基金;
关键词
Rain; Atmospheric modeling; Sea surface; Ocean temperature; L-band; Atmosphere; Atmospheric measurements; microwave remote sensing; radiometer; rain;
D O I
暂无
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
L-band passive microwave remote sensing of ocean surfaces is hampered by uncertainties due to the contribution of precipitation. However, modeling and correcting rain effect are complicated because all the precipitation contributions from the atmosphere and sea surface, including the rain effect in the atmosphere, water refreshing, rain-perturbed sea surface, and rain-induced local wind, are coupled. These rain effects significantly alter L-band microwave satellite measurements. This study investigates the impact of precipitation on the satellite measured brightness temperature (TB) and proposes a correction method. The results show that the rain-induced TB increase is approximately 0.5-1.4 K in the atmosphere, depending on the incidence angle and polarization. Moreover, the rain effect on sea surface emissions is more significant than that in the atmosphere. The result shows that rain effects on sea surface emissions are higher than 3 K for both polarizations when the rain rate is higher than 20 mm/h. We validate the rain effect correction model based on Soil Moisture Active Passive (SMAP) observations. The results show that the TBs at the top of the atmosphere (TOA) simulated by the model are in a good agreement with the SMAP observations, with root-mean-square errors (RMSEs) of 1.137 and 1.519 K for the horizontal and vertical polarizations, respectively, indicating a relatively high accuracy of the established model. Then, a correction model is applied to sea surface salinity (SSS) retrieval for analysis, and the results show that the developed model corrects the underestimation in SSS retrieval. Finally, the rain effect correction model is validated with Aquarius observations in three regions, and it is found that the RMSEs of the corrected TOA TBs range from 1.013 to 1.608 K, which is higher than those without rain effect correction (RMSEs range from 2.078 to 3.894 K). Overall, the model developed in this study provides relatively a good accuracy for rain effect correction.
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页数:16
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