基于RTTOV模式的大气二氧化碳反演参数敏感性分析

大气二氧化碳是开展全球气候变化和碳循环研究的关键数据。卫星遥感技术与模式模拟相结合的反演方法已成为获取该数据的重要手段,但模式输入参数本身的误差会对大气二氧化碳反演精度产生影响,须在反演算法设计中加以关注。本文利用RTTOV10快速辐射传输模式模拟Aqua/AIRS红外探测仪17个大气二氧化碳反演通道,计算了这些通道上大气顶出射辐射对温度廓线、臭氧廓线、水汽廓线、地表温度和地表发射率的参数误差的不确定性,并与二氧化碳增加0.5%时造成的不确定性进行对比,分析二氧化碳对上述参数误差的敏感性。结果表明,温度廓线误差是干扰AIRS大气二氧化碳反演的主要因素,其次是臭氧廓线误差,而水汽廓线、地表温度和地表发射率的误差对二氧化碳反演的影响在除去个别通道后可忽略不计。最后,本文以通道为单位,确定了各通道上的高敏感参数、敏感参数和不敏感参数,为二氧化碳反演通道的选择和反演算法的设计提供了参考。     

AN ERROR ANALYSIS ON THE SIMULATED DATA OF TOVS HIRS BY RTTOV5 MODEL

The sounding data of meteorological satellites provide not only the real time weatherinformation about the distribution of both cloud and rainfall,but also some others about themovement and state of atmosphere.They are important variables and parameters for NWP modelused to simulate and predict atmospheric state.In order to introduce remote sensing informationfrom satellites into NWP model,there is an efficient way of establishing an RT model by use of theatmosphere radiation sounding data of meteorological satellites to get the variables and parametersvaluable to NWP model.In this paper,we set up profiles of air temperature and water vapor fromthe surface to upper (0.1 hPa) using the radiosounding data and the surface data from May toAugust 1998 atmosphere East Asia.A TOVS RT model (RTTOV5) is provided to compute thevalue of radiation value of HIRS channels in NOAA14.Then the radiation values of 19 HIRSchannels are gotten.After matching these data computed by the RT model and the correspondingvalues coming from satellite sounding in time,the statistic distribution of bias between tile modeloutput and the satellite sounding at each sounding channel can be gotten.At the same time.thedistribution of RMS to every TOVS HIRS channel,the standard biases to different scanning angleto each channel are also obtained.     

A new weighting function for estimating microwave sounding unit channel 4 temperature trends simulated by CMIP5 climate models

A new static microwave sounding unit (MSU) channel 4 weighting function is obtained from using Coupled Model Inter-comparison Project, Phase 5 (CMIP5) historical multimodel simulations as inputs into the fast Radiative Transfer Model for TOVS (RTTOV v10). For the same CMIP5 model simulations, it is demonstrated that the computed MSU channel 4 brightness temperature (T4) trends in the lower stratosphere over both the globe and the tropics using the proposed weighting function are equivalent to those calculated by RTTOV, but show more cooling than those computed using the traditional UAH (University of Alabama at Huntsville) or RSS (Remote Sensing Systems in Santa Rosa, California) static weighting functions. The new static weighting function not only reduces the computational cost, but also reveals reasons why trends using a radiative transfer model are different from those using a traditional static weighting function. This study also shows that CMIP5 model simulated T4 trends using the traditional UAH or RSS static weighting functions show less cooling than satellite observations over the globe and the tropics. Although not completely removed, this difference can be reduced using the proposed weighting function to some extent, especially over the tropics. This work aims to explore the reasons for the trend differences and to see to what extent they are related to the inaccurate weighting functions. This would also help distinguish other sources for trend errors and thus better understand the climate change in the lower stratosphere.     

Landsat 8地表温度反演及验证—以黑河流域为例

地表温度是区域和全球尺度地表物理过程的一个重要参数,目前已有的地表温度产品空间分辨率较低,缺乏高空间分辨率的地表温度产品。Landsat系列卫星提供了大量免费的高空间分辨率遥感数据,然而对应的高空间分辨率地表温度产品还未见到,为了获取长时间序列的高空间分辨率地表温度数据,针对Landsat 8 TIRS数据提出了一个物理单通道地表温度反演算法。该算法首先利用ASTER全球地表发射率产品(ASTER GED)结合Landsat 8地表反射率产品计算Landsat 8影像的地表发射率,然后利用快速辐射传输模型RTTOV结合MERRA大气廓线数据对热红外影像进行大气校正,最后利用物理单通道地表温度反演算法得到地表温度。利用黑河流域HiWATER试验2013年—2015年15个站点的实测地表温度数据对本文方法和普适性单通道算法进行了验证,同时对验证站点的空间异质性进行了分析。结果表明,本文方法和普适性单通道算法估算的地表温度整体精度均较高,能够获取高精度、高空间分辨率的地表温度数据,可以服务于城市热岛效应、地表蒸散发估算等相关研究。     

RTTOV和CRTM对“罗莎”台风卫星微波观测的模拟研究与比较

快速辐射传输模式中水成物辐射效应的考虑对卫星观测模拟具有重要的影响。利用区域中尺度数值模式WRF预报输出水成物含量和温湿廓线等参数,使用欧洲中期数值天气预报中心和美国卫星资料同化联合中心发展建立的快速辐射传输模式RTTOV和CRTM,结合雅可比模式计算得到的响应函数,分析了各种水成物辐射效应对AMSUA/B卫星微波观测各通道亮温模拟的影响,并比较了RTTOV和CRTM结果间的异同。结果表明,RTTOV和CRTM两个快速辐射传输模式计算得到的水成物响应函数和水成物辐射效应对模拟亮温影响特征基本一致,但量级上存在差异。雅可比表征的水成物响应函数和水成物本身的分布层次对应关系良好,云水和雨水的响应函数主要分布在中下层,冰水和雪则分布在中上层。相对于RTTOV,CRTM计算得到的水成物响应函数要大一些。对AMSUA,云水和雨水的辐射效应对通道模拟亮温主要以增温为主,尤其是在低频的窗区通道,冰晶和雪则体现散射效应为主的降温作用。对AMSUB,水成物辐射效应的考虑使得模拟亮温降低,尤其是通道2降温幅度最大。CRTM计算出的水成物辐射效应带来的模拟亮温变化幅度大于RTTOV。目前,CRTM除了考虑云、雨、冰和雪4种水成物外,还考虑霰和雹的辐射效应,对水成物辐射效应的考虑比RTTOV更完善一些。     

AN ERROR ANALYSIS ON THE SIMULATED DATA OF TOVS HIRS BY RTTOV5 MODEL*

The sounding data of meteorological satellites provide not only the real time weather information about the distribution of both cloud and rainfall,but also some others about the movement and state of atmosphere.They are important variables and parameters for NWP model used to simulate and predict atmospheric state.In order to introduce remote sensing information from satellites into NWP model,there is an efficient way of establishing an RT model by use of the atmosphere radiation sounding data of meteorological satellites to get the variables and parameters valuable to NWP model.In this paper,we set up profiles of air temperature and water vapor from the surface to upper (0.1 hPa) using the radiosounding data and the surface data from May to August 1998 atmosphere East Asia.A TOVS RT model (RTTOV5) is provided to compute the value of radiation value of HIRS channels in NOAA14.Then the radiation values of 19 HIRS channels are gotten.After matching these data computed by the RT model and the corresponding values coming from satellite sounding in time,the statistic distribution of bias between tile model output and the satellite sounding at each sounding channel can be gotten.At the same time.the distribution of RMS to every TOVS HIRS channel,the standard biases to different scanning angle to each channel are also obtained.     

应用SVM技术模拟前向辐射传输模式

提出了一种利用支持向量机(SVM)模拟前向辐射传输模式的方法.利用欧洲中期天气预报中心(ECMWF)的RTFOV_8_7前向辐射传输模式和60L-SD廓线集牛成了AMSU-A模拟亮温资料,用模拟亮温和相应的廓线集资料组成训练样本和检验样本,采用SVM方法进行训练.对检验样本的模拟显示,SVM可以用于描写前向辐射传输模式中的非线性映射关系,较好地由大气廓线集资料模拟出与其相关的AMSU-A仪器5-14通道亮温,其中通道6-14的均方根误差在0.1K以内,平均误差算术平均值在0.01K以内.通过多元线件同归方法对温度廓线进行反演试验,发现用SVM模拟的亮温可以用于温度廓线反演,其反演精度可以达到甚至高于RTTOV_8_7计算的亮温.