多波段微波辐射计反演大气温湿廓线性能分析

为了为星载、机载以及地基微波大气温湿廓线探测仪通道的设置、大气参数反演指标的论证、反演算法的开发以及反演产品的质量评定提供参考依据,基于快速辐射传输模式(RTTOV10)和大气参数廓线库,建立了基于神经网络的微波大气温湿廓线反演性能分析方法,分析了反演方法、通道选择、亮温观测误差和地表比辐射率等因素对大气温湿廓线反演性能的影响。模拟试验分析表明:1神经网络反演算法显著优于线性统计回归反演算法,特别是对亮温观测噪声的敏感性相对较弱;2183.31GHz附近的水汽探测通道能够为大气温度廓线反演提供一定的信息;118.75GHz附近的温度探测通道对整个大气的温度反演均有明显影响,在200hPa附近误差的影响量达0.4K;350~60GHz和118.75GHz附近的温度探测通道对基于183.31GHz附近通道的湿度廓线反演具有重要影响,而且存在一定的互补性;4微波亮温观测误差以及地表比辐射率假定对大气温湿廓线反演有着显著影响。

Analysis of Atmospheric Parameter Retrievals from Multi-band Microwave Sounding Instruments

Using the RTTOV10 forward model and atmospheric parameter profile datasets,a numerical simulation scheme was developed based on artificial neural networks,which provides a reference for the selection of channels,requirements analysis,development of retrieval algorithm and evaluation of the retrieval products for atmospheric soundings from satellite\|borne,airborne or ground\|based microwave radiometers.Then,the impact of retrieval method,channel selection and observation error of bright temperatures were analyzed by a series of retrieval experiments.The results show:(1) The neural networks provide better reproductions of the profiles than the statistical inversion,and especially show less sensitivity to the bright temperature observation errors;(2) The humidity detection channels near 183.31 GHz can provide some information for temperature retrievals,which is about 0.2 K between 400~800 hPa.The channels near 118.75 GHz can provide additional information for temperature soundings in the whole atmosphere,and the largest positive impact is about 0.4 K occurring near 200 hPa;(3) The temperature sounding channels near 50 GHz and 118.75 GHz are not only important but complementary for humidity profile retrievals with 183.31 GHz channels;(4) The retrievals of temperature and humidity profiles are sensitive to the brightness temperature observation errors and the surface emissivity assumptions.