A high wind geophysical model fuction for Quik SCAT wind retrievals and application to Typhoon IOKE  

作　　者：ZOU Juhong ZENG Tao CUI Songxue 

机构地区：[1]National Satellite Ocean Application Service,State Oceanic Administration

出　　处：《Acta Oceanologica Sinica》2015年第7期65-73,共9页海洋学报（英文版）

基　　金：The National Natural Science Foundation of China under contract No.41106152;the National Science and Technology Support Program under contract No.2013BAD13B01;the National High Technology Research and Development Program(863 Program)of China under contract No.2013AA09A505;the International Science and Technology Cooperation Program of China under contract No.2011DFA22260;the National High Technology Industrialization Project under contract No.[2012]2083;the Marine Public Projects of China under contract Nos 201105032,201305032 and 201105002-07

摘　　要：The geophysical model function （GMF） describes the relationship between a backscattering and a sea surface wind, and enables a wind vector retrieval from backscattering measurements. It is clear that the GMF plays an important role in an ocean wind vector retrieval. The performance of the existing Ku-band model function QSCAT-1 is considered to be effective at low and moderate wind speed ranges. However, in the conditions of higher wind speeds, the existing algorithms diverge alarmingly, owing to the lack of in situ data required for developing the GMF for the high wind conditions, the QSCAT-1 appears to overestimate the a0, which results in underestimating the wind speeds. Several match-up QuikSCAT and special sensor microwave/imager （SSM/I） wind speed measurements of the typhoons occurring in the west Pacific Ocean are analyzed. The results show that the SSM/I wind exhibits better agreement with the ＂best track＂ analysis wind speed than the QuikSCAT wind retrieved using QSCAT-1. On the basis of this evaluation, a correction of the QSCAT-1 model function for wind speed above 16 m/s is proposed, which uses the collocated SSM/I and QuikSCAT measurements as a training set, and a neural network approach as a multiple nonlinear regression technologytechnology.In order to validate the revised GMF for high winds, the modified GMF was applied to the QuikSCAT observations of Hurricane IOKE. The wind estimated by the QuikSCAT for Typhoon IOKE in 2006 was improved with the maximum wind speed reaching 55 m/s. An error analysis was performed using the wind fields from the Holland model as the surface truth. The results show an improved agreement with the Holland model wind when compared with the wind estimated using the QSCAT-1. However, large bias still existed, indicating that the effects of rain must be considered for further improvement.The geophysical model function （GMF） describes the relationship between a backscattering and a sea surface wind, and enables a wind vector retrieval from backscattering measurements. It is clear that the GMF plays an important role in an ocean wind vector retrieval. The performance of the existing Ku-band model function QSCAT-1 is considered to be effective at low and moderate wind speed ranges. However, in the conditions of higher wind speeds, the existing algorithms diverge alarmingly, owing to the lack of in situ data required for developing the GMF for the high wind conditions, the QSCAT-1 appears to overestimate the a0, which results in underestimating the wind speeds. Several match-up QuikSCAT and special sensor microwave/imager （SSM/I） wind speed measurements of the typhoons occurring in the west Pacific Ocean are analyzed. The results show that the SSM/I wind exhibits better agreement with the ＂best track＂ analysis wind speed than the QuikSCAT wind retrieved using QSCAT-1. On the basis of this evaluation, a correction of the QSCAT-1 model function for wind speed above 16 m/s is proposed, which uses the collocated SSM/I and QuikSCAT measurements as a training set, and a neural network approach as a multiple nonlinear regression technologytechnology.In order to validate the revised GMF for high winds, the modified GMF was applied to the QuikSCAT observations of Hurricane IOKE. The wind estimated by the QuikSCAT for Typhoon IOKE in 2006 was improved with the maximum wind speed reaching 55 m/s. An error analysis was performed using the wind fields from the Holland model as the surface truth. The results show an improved agreement with the Holland model wind when compared with the wind estimated using the QSCAT-1. However, large bias still existed, indicating that the effects of rain must be considered for further improvement.

关 键 词：geophysical model function high wind QUIKSCAT neural network wind retrieval 

分 类 号：P732[天文地球—海洋科学] P714.2