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FY-3 IRAS水汽通道亮温正演精度改进方法
引用本文:曹玥瑶,张鹏,马刚,白文广,廖蜜.FY-3 IRAS水汽通道亮温正演精度改进方法[J].应用气象学报,2016,27(6):698-708.
作者姓名:曹玥瑶  张鹏  马刚  白文广  廖蜜
作者单位:1.中国气象科学研究院, 北京 100081
基金项目:资助项目: 公益性行业(气象)科研专项(201506074),国家高技术研究发展计划(2015AA123704),国家自然科学基金面上项目(41475031)
摘    要:卫星大气探测仪器的正演模拟是卫星资料同化和定量遥感的基础, 同CO2吸收通道相比, 目前红外水汽探测通道的亮温正演模拟误差较大。利用国际上通用的TIGR (thermodynamic initial guess retrieval database) 43廓线库作为训练样本, NESDIS (national environment satellite, data and information service) 35廓线库作为独立检验样本, 对水汽廓线按照整层大气水汽总量为阈值进行分组训练, 基于RTTOV (radiative transfer for TOVS) 模型训练获得风云三号气象卫星红外分光计的正演回归系数并模拟计算观测亮温。以0.045 kg·m-2作阈值进行分组训练为例, 结果表明:该方法可有效改进水汽通道亮温的正演精度, 特别是对低水汽含量廓线的模拟精度改进比较明显, 最大可达0.17 K。进一步分析表明:分组训练方法改进水汽通道辐射模拟精度的原因是提高了水汽光学厚度的计算精度。

关 键 词:风云三号气象卫星    红外分光计    分段模拟    正演    水汽通道
收稿时间:3/7/2016 12:00:00 AM
修稿时间:6/3/2016 12:00:00 AM

An Improvement of Brightness Temperature Simulation of FY 3 IRAS Infrared Water Vapor Channel
Cao Yueyao,Zhang Peng,Ma Gang,Bai Wenguang and Liao Mi.An Improvement of Brightness Temperature Simulation of FY 3 IRAS Infrared Water Vapor Channel[J].Quarterly Journal of Applied Meteorology,2016,27(6):698-708.
Authors:Cao Yueyao  Zhang Peng  Ma Gang  Bai Wenguang and Liao Mi
Affiliation:1.Chinese Academy of Meteorological Sciences, Beijing 1000812.National Satellite Meteorological Center, Beijing 100081
Abstract:Forward modeling of satellite atmospheric sounding instruments is the foundation of satellite data assimilation and inversion. Currently, more uncertainties on the accuracy of infrared water vapor channel are still exist compared with temperature detection channel. A method based on the group training of profiles which are classified by their water content of air column is used, to try to improve the forward modeling accuracy in the water vapor channel. Determination of threshold value is based on principles of basic balance profile numbers after group classification. Many threshold values are utilized to classify profiles, only results of threshold for 0.045 kg·m-2 are detailed and analyzed, which lead to quite similar experiment results. TIGR 43 profile library is used as the training sample to get coefficients for fast radiative transfer computation and NESDIS 35 profile library is used to test the precision improvement as the independent sample.Different coefficients got from the group training are used to establish RTTOV forward model of FY-3 IRAS and the channel brightness temperature is calculated using the corresponding profile and coefficients. The forward modeling accuracy of the FY-3 IRAS brightness temperature is get by comparison with line-by-line results, which are considered as accurate and reliable. Research results show accuracy improvement of the brightness temperature after group training. Improvement shows better in the low water content profile case, which up to 0.17 K in the 0.045 kg·m-2 threshold experiment. Further analysis is executed to find the cause for the improvement in the group training experiment. The layer water vapor predictor optical depth of channel 11-13 are calculated and comparison is done between the forward model with and without group training. Results show better consistency of water vapor absorption and channel weighting function distribution, besides, the absorption of water vapor line and continuum is adjusted more reasonable considering the weighting function height. These provide positive influence on the improvement of forward modeling results.It puts forward a method which can improve the fast radiative calculation accuracy of infrared water vapor channel, further work should be done in respect of bias caused by the precision of water vapor molecule absorption line parameters and the input water vapor profile self error. Furthermore, it merely considers the water content of air column, the potential influence caused by the shape of the profile is out of consideration, which may be the cause for the negative effect in channel 13 and research direction of future work.
Keywords:FY 3 meteorological satellite  infrared spectrometer  group training  forward calculation  water vapor channel
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