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QIN Bangyong,ZHOU Xuan,ZHANG Honglei,YANG Xiaofeng,LU Rong,YU Yang,SHI Lijian. 2014. An improved wind speed algorithm for “Jason-1” altimeter under tropical cyclone conditions. Acta Oceanologica Sinica, 33(7):83-88
An improved wind speed algorithm for “Jason-1” altimeter under tropical cyclone conditions
台风条件下改进的Jason-1海面风速反演算法
Received:March 04, 2013  Revised:September 06, 2013
DOI:10.1007/s13131-014-0500-z
Key words:altimeter  wind speed  rain effect  tropical cyclone
中文关键词:  高度计  风速  降雨影响  热带气旋
基金项目:The National Natural Science Foundation of China under Nos 41201350 and 41228007;the International Scientific and Technological Cooperation Projects of State Oceanic Adminstration under contact No. 2011DFA22260;the Knowledge Innovation Program of the Chinese Academy of Sciences under contact No. Y0S04300KB.
Author NameAffiliationE-mail
QIN Bangyong State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China  
ZHOU Xuan State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China
P. O. Box 5111, Beijing 100094, China 
zhouxuan@radi.ac.cn 
ZHANG Honglei State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China  
YANG Xiaofeng P. O. Box 5111, Beijing 100094, China  
LU Rong State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China  
YU Yang P. O. Box 5111, Beijing 100094, China  
SHI Lijian National Satellite Ocean Application Service, State Oceanic Administration, Beijing 100081, China  
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Abstract:
      Rain effect and lack of in situ validation data are two main causes of tropical cyclone wind retrieval errors. The National Oceanic and Atmospheric Administration's Climate Prediction Center Morphing technique (CMORPH) rain rate is introduced to a match-up dataset and then put into a rain correction model to remove rain effects on "Jason-1" normalized radar cross section (NRCS);Hurricane Research Division (HRD) wind speed, which integrates all available surface weather observations, is used to substitute in situ data for establishing this relationship with "Jason-1" NRCS. Then, an improved "Jason-1" wind retrieval algorithm under tropical cyclone conditions is proposed. Seven tropical cyclones from 2003 to 2010 are studied to validate the new algorithm. The experimental results indicate that the standard deviation of this algorithm at C-band and Ku-band is 1.99 and 2.75 m/s respectively, which is better than the existing algorithms. In addition, the C-band algorithm is more suitable for sea surface wind retrieval than Ku-band under tropical cyclone conditions.
中文摘要:
      台风条件下现场观测资料十分稀少,Young等人、Gu等人利用台风模式风速代替现场观测数据,通过与高度计观测的后向散射截面进行对比分析,建立高风速反演算法。但台风模式自身的缺陷,以及降雨的衰减、体后向散射和雨表面扰动作用,影响了这些算法的精度。HRD海面风速再分析数据融合了所有的现场观测数据,其精度明显优于台风模式风速数据。为了改进台风条件下海面风速反演算法的精度,本文首先利用CMORPH降雨数据和降雨订正模型对Jason-1后向散射截面进行降雨订正,并通过HRD海面风速再分析数据代替台风模式风速数据建立匹配数据集,推导高度计在无雨、高风速条件下海面风速反演算法;然后,利用无雨条件下C和Ku波段高度计后向散射截面的关系,给出了台风条件下海面风速反演的技术流程;最后,利用Irene飓风对本文算法进行了验证,试验结果表明,本文算法在C和Ku波段的均方根误差分别为1.99和2.75m/s,精度明显优于Gu算法和Jason-1业务化算法,且C波段比Ku波段更适合台风条件下海面风速的反演。
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