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利用FY-3A近红外资料反演水汽总量
引用本文:胡秀清,黄意玢,陆其峰,郑婧.利用FY-3A近红外资料反演水汽总量[J].应用气象学报,2011,22(1):46-56.
作者姓名:胡秀清  黄意玢  陆其峰  郑婧
作者单位:1.中国气象局中国遥感卫星辐射测量和定标重点开放实验室 国家卫星气象中心,北京 100081
摘    要:该文介绍了利用搭载在FY-3A卫星上的中分辨率光谱成像仪 (MERSI) 的近红外 (NIR) 通道反演大气水汽总量 (PWV) 的方法。根据预先建立的查找表,大气水汽总量可以通过水汽通道与窗区通道的卫星测值相比反演得到。对MERSI近红外水汽通道灵敏度进行估算,结果表明:处于吸收带两翼的905 nm和980 nm通道对不同水汽量的敏感性表现比较接近,对较大水汽含量最为敏感;当水汽较弱时,强吸收的940 nm通道非常敏感。基于这3个通道对水汽含量敏感性的不同表现,采用3个通道水汽总量的加权平均值作为PWV产品的最终反演值。文中设计了水汽总量业务算法反演流程,并基于FY-3A/MERSI最新观测资料进行晴空大气水汽总量的业务处理生成试验,顺利生成MERSI单轨道水汽总量产品及日拼图中国区域产品和全球产品,同时生成多天合成产品,产品反映出MERSI具有较好的近红外水汽探测能力。将卫星反演结果与探空数据进行初步比对检验,显示卫星反演值有20%~30%系统性偏低,需要进一步改进反演查找表。

关 键 词:中分辨率光谱成像仪    近红外通道    水汽总量
收稿时间:2009-12-28

Retrieving Precipitable Water Vapor Based on the Near-infrared Data of FY-3A Satellite
Hu Xiuqing,Huang Yibin,Lu Qifeng and Zheng Jing.Retrieving Precipitable Water Vapor Based on the Near-infrared Data of FY-3A Satellite[J].Quarterly Journal of Applied Meteorology,2011,22(1):46-56.
Authors:Hu Xiuqing  Huang Yibin  Lu Qifeng and Zheng Jing
Institution:1.Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, National Satellite Meteorological Center, China Meteorological Administration (LRCVES/CMA), Beijing 1000812.Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing 100101
Abstract:The technique of retrieving precipitable water vapor (PWV) based on near-infrared (NIR) data of Medium Resolution Spectral Imager (MERSI) on board FY-3A satellite is introduced. Five NIR channels are designed on the MERSI instrument for PWV observation, three of which are water vapor absorption channels centered near 905 nm, 940 nm and 980 nm respectively and others are atmospheric window channels at 865 nm and 1030 nm. The method adopted here for PWV retrieval is based on the ratio of reflected solar radiance (or apparent reflectance) detected by satellite between water vapor absorption channels and atmospheric window channels. By employing channel ratios, the aerosol extinction distribution and the variation effect of surface reflectance are partially removed, and the atmospheric transmittance of water vapor channels is approximately obtained. The PWV is derived from the atmospheric transmittance based on a Look-up Table which is pre-calculated using a radiation transfer model. The sensitivities of atmospheric transmission in each NIR water vapor channels of MERSI to the total precipitable water vapor are also simulated. It is found that 905 nm channel is more sensitive under humid conditions while the strong absorption channel at 940 nm is sensitive under dry conditions. And the two weak absorption channels have similar sensitivity to total water vapor amount. In this case, under a given atmosphere condition, the derived PWV values from three water vapor channels may be a little different. The weighted average of three derived PWV values is regarded as the final PWV product and the weighing coefficients are determined by their sensitivity.The procedure of the operational PWV product generation is designed and conducted for experimental retrieval. Based on the global data of MERSI, FY-3A Products Generation System (PGS) can successfully generate the daily global and regional PWV L2 products and multi-day integrated L3 products, which can clearly display the spatial distribution of water vapor amounts over global land area. The result indicates that FY-3A/MERSI has an excellent ability in detecting NIR water vapor, and can demonstrate fine characteristic of PWV spatial distributions. As 940 nm channel shows good application under dry atmosphere conditions and 905 nm or 980 nm channel work well under humid situation, acceptable retrieval accuracy can always be achieved by combining these channels. In order to assess the accuracy, the retrieved PWV from MERSI NIR are compared with the ground-based sounding data. Over cloud free area, there is a good agreement between them in variation trend and spatial distribution. The MERSI PWV results are steady but 20%—30% lower than sounding, so the retrieval algorithm and the Look-up Table need to be updated to reduce this bias in the near future.
Keywords:Medium Resolution Spectral Imager  near infrared bands  precipitation water vapor
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