摘要
利用风云三号C星(FY-3C)微波温湿探测仪(MWHTS)的实测亮温数据,开展了中低纬度(40°S-40°N)区域海面气压反演研究.MWHTS 118.75 GHz氧气通道的辐射亮温测量值与氧气气柱总量密切相关,可用于反演海面气压.根据辐射传输方程分析了MWHTS 8个氧气通道对海面气压的敏感性.结果表明,与位于氧气吸收带中心的通道相比,位于吸收带翼区的探测通道对海面气压的变化更敏感.基于神经网络方法建立了中低纬度海面气压反演算法,通过将反演结果与ERA-Interim再分析数据以及原位观测数据进行对比分析,发现建立的反演算法在中低纬度晴空、云天、雨天条件下,对海面气压的估计精度分别为2.0,3.0和3.5 hPa.最后,开展了生成初期热带气旋的反演试验,结果表明反演的海面气压资料对热带低压的判别有一定帮助.
Sea level pressure is an important meteorological factor and plays a key role in Numerical Weather Prediction(NWP),tropical cyclone forecasting and solar activity studies.However,until recently,sea level pressure data have mainly been provided by in-situ measurements.It is of great significance to obtain sea level pressure with a high spatial and temporal resolution by means of remote sensing.In this study,we investigated the retrieval of sea level pressure over mid-to-low latitude(40°S-40°N)regions using the observations from the Microwave Humidity and Temperature Sounder(MWHTS)onboard the Fengyun-3 C(FY-3 C)satellite.Sea level pressure sounding is achieved by MWHTS 118.75 GHz channels due to their ability to measure the total columnar oxygen absorption.The sensitivity of the MWHTS 118.75 GHz channels to surface pressure was analyzed using the radiative transfer equation.Compared with the channels far into the oxygen absorption band,the channels lie on the wing of the band are more sensitive to the change of surface pressure.A statistical retrieval algorithm based on the Back-Propagation(BP)neural networks was established.In-situ buoy measurements and reanalysis data were used to assess the retrieval performance.Results showed that the proposed retrieval algorithm can estimate sea level pressure over mid-to-low latitude areas(40°S-40°N)with the accuracy of 2.0,3.0,and 3.5 hPa for clear-sky,cloudy and rainy conditions,respectively.In addition,several tropical cyclone retrieval experiments showed that the proposed method was useful in the early identification of tropical depression.
作者
张子瑾
董晓龙
ZHANG Zijin;DONG Xiaolong(Key Laboratory of Microwave Remote Sensing,National Space Science Center,Chinese Academy of Sciences,Beijing 100190;University of Chinese Academy of Sciences,Beijing 100049;International Space Science Institute-Beijing,Beijing 100190)
出处
《空间科学学报》
CAS
CSCD
北大核心
2020年第3期364-375,共12页
Chinese Journal of Space Science
基金
国家重点研发计划项目资助(2017YFB0502800,2017YFB0502802)。