提高“К分布法”计算遥感通道透过率精度的方法

卫星测量地面或云面反射的氧气0.76μm吸收带一些通道的太阳辐亮度，可遥测洋面或地面气压场及云顶气压。由于洋面或地面气压相对变化约10-3量级，用“К分布法”计算氧气通道透过率要求较高的精度和速度。提高“К分布法”计算精度的途径是:①减少产生误差的简化计算；②增加截点数，特别是波段内吸收线较多、吸收系数变化较复杂的通道。假设在卫星上用干涉光谱仪测量氧气0.76μm吸收带一些通道的带宽均为1cm-1，在12930~13220cm-1范围内，选190个波段，计算不同温度廓线下通道的平均透过率。大部分通道“К分布法”的截点数N≤20，个别通道氧气吸收线较多，吸收系数变化较复杂，为了使“К分布法”通道平均透过率的计算误差小于10-4，需增加通道内截点数N，N最多为136，与逐线计算结果相比，通道垂直透过率的最大均方差小于3×10-5。计算透过率的速度和精度都满足反演计算的要求。     

从118.75 GHz附近六通道亮温反演大气温度廓线的数值模拟研究

为了能在静止气象卫星上实现微波被动遥感探测大气温度廓线,并保持一定的地面空间分辨率(如视场小于60 km),就需要使用高频微波及大天线.欧洲和美国下一代静止气象卫星上都已考虑采用118.75 GHz附近通道.为了充分了解118.75 GHz附近通道遥感反演温度廓线的能力,为仪器研制及今后资料的解释反演提供必要的基础数据,作者开展了采用118.75 GHz附近六个通道遥感反演大气温度廓线的数值模拟研究.统计反演的数值试验表明,118.75 GHz附近六通道对温度垂直分布有一定的遥感反演能力;温度反演较好的层次对应于权重函数峰值所在的位置.     

毫米/亚毫米波探测大气温度和湿度的通道选择

利用热带大气温湿廓线计算了热带地区毫米/亚毫米波段微波大气透过率权重函数。对权重函数峰值高度的分析结果显示:对流层低层的大气温度可以选择118 GHz通道的远翼频率来探测,而对高层大气温度进行探测时,选择425 GHz通道的远翼频率较为合适;在大气湿度探测方面,183 GHz通道组合适合探测对流层中层大气的湿度,高层大气湿度探测应该首先考虑380 GHz通道组合来实现。根据大气温度探测通道和大气湿度探测通道的权重函数分布,鉴于国内现有遥感仪器的制造水平,建议选择118 GHz 3个通道与425 GHz 8个通道共11个大气温度探测通道和183 GHz 3个通道与380 GHz 5个通道共8个大气湿度探测通道作为未来静止轨道微波探测的候选通道。     

利用气象卫星资料反演大气温度廓线的初步试验

气象卫星垂直探测资料在国外已广泛用于数值天气预报中,本文介绍了由气象卫星垂直探测资料反演大气温度廓线的方法及回归反演系数的计算。最后给出了利用NOAA-7 TOVS资料反演大气温度廓线的试验结果。试验结果与常规探测温度的比较表明:绝对平均偏差和均方根误差在各等压面上大致为2—3℃。     

晴空卫星红外模拟资料反演大气温度廓线的研究

HIRS／3资料的反演是一个典型的非适定问题,而奇异值分解法（SVD）是一种解病态线性代数方程组的有效方法,它在遇到矩阵的不适定问题时依然可以保持其数值稳定性并能尽量多地利用各探测通道的有效信息。将SVD方法应用于卫星资料的温度反演问题中可以将资料空间和参数空间分型,从中提取有效信息来反演大气温度廓线。通过理想资料试验,分析了温度廓线初猜值、水汽廓线误差等因素对温度反演结果的影响。结果表明：对HIRS／3资料来说,用SVD法反演大气温度廓线时只能截取一定的阶数,以取4～7为宜;温度廓线初猜值的选取对反演结果的影响较大,当模式层的中层误差较大时得到的反演结果最稳定;水汽廓线的扰动对中低层的温度反演结果和第5,8,10,11和16通道的亮温值有较大影响。     

应用ATOVS资料反演大气温湿廓线

本文用牛顿迭代的方法反演NOAA-15极轨气象卫星ATOVS资料，求解大气温度廓线和水汽廓线，本文利用一阶变分原理从辐射传输方程中得到了大气温度、水汽权重函数的解析形式，并改进了传统使用的线性迭代方法，利用牛顿非线性迭代方法求解大气表层温度，大气温度廓线及大气水汽廓线，并根据大气参量的自相关性，将大气温度廓线、大气水汽廓线用经验正交函数（EOF）的线性组合表示，减少了要反演的参数，提高了反演稳定性和迭代速度。     

云参数对RTTOV5模式模拟误差的影响分析

该文根据1998年8月的业务TOVS反演的温度、水汽垂直廓线资料以及其它资料, 利用RTTOV5模式模拟NOAA14极轨气象卫星上相应红外探测 (HIRS) 通道的辐射亮温值, 将模拟值对比实测TOVS探测资料, 结果表明, 晴空模式模拟亮温与实测值的误差小于部分有云时的误差, 模拟误差受云的影响呈反相变化, 对水汽敏感的中低层探测通道在晴空时的误差小于部分有云情况; 通过对比白天和夜间短波窗区探测通道模拟误差, 分析了其受地面反射太阳光辐射的影响的大小及其原因所在; 并利用RTTOV5的伴随模式和Jacobine模式分析了模式模拟误差对初始场云参数的敏感性。该研究为TOVS/ATOVS探测资料在3DR或4DR变分同化中的直接应用奠定了基础。     

边界层温度廓线遥感反演的本地化改进研究

采用MODIS资料和美国发展的MODIS大气温、湿度廓线统计反演算法,估算大气温度、湿度廓线作为初始场,应用101层快速透过率模式(PFAAST)估算了大气透过率,并采用Newton非线性迭代算法反演中国西北荒漠戈壁地区大气温度廓线。结果表明:该方法对边界层高度及以上部分的大气温度反演得比较好,误差基本都在2 K范围内,边界层范围内的温度反演误差较大,反演误差与气溶胶光学厚度增量和地表温度估算误差呈显著正相关关系,与大气水汽混合比的关系较差。文中从敏感性试验和理论分析角度阐述了地表温度和气溶胶光学厚度估算误差对大气温度反演误差的影响,发现不同光谱波段的地表温度权重均随地表温度的增加有不同程度增加,地表温度反演误差增加将增加地表温度权重,提高地表温度估算误差有助于提高地表温度权重的精度;荒漠戈壁地区大气边界层中气溶胶浓度较高,光学厚度较大,使边界层大气透过率降低,进而降低卫星红外遥感波段的地表温度权重和空气温度权重。由于该模式没有很好地考虑边界层中沙尘气溶胶的影响,使卫星反演的大气透过率偏高,以至于高估地表温度权重和大气温度权重,使得反演的表面温度和空气温度偏低。该研究结合太阳光度计获得的光学厚度资料,采用统计方法对气溶胶效应引起的大气透过率误差和表面温度估算误差进行校正,并对物理算法进行本地化改进,实现了边界层温度廓线的反演。     

七通道微波辐射计遥感大气温度廓线的性能分析

文中首先分析了大气参数分布的垂直分辨率对模拟七通道微波温度探测器各通道亮温的影响，通过对比计算表明，大气参数的垂直分辨率对微波测温通道亮温计算的影响为0．2K～0．7K；随后分析了各通道亮温测量误差对温度廓线反演性能的影响，当测量误差在0．2K～2．0K范围内变化时，反演结果的总体均方根误差为2．1K～3．1K；同时还分析了单通道缺损、单通道发生漂移及所有通道发生漂移等情况对温度廓线反演性能的影响。当仪器缺损一个通道时，对所缺通道权重函数峰值附近高度上的大气温度反演有不同程度的影响，对其他高度上的大气温度反演的影响可忽略；单通道漂移0．5K时，对反演结果的影响较小；各通道整体漂移达到1．0K时，对温度廓线反演有明显影响；最后，考虑了云雾对微波测温通道亮温的影响，数值计算表明，雾层、浓霾和卷云对各通道亮温几乎没有影响，层云和积云对50．50GHz通道亮温有明显的影响。     

预估临边探测大气温度和水汽廓线的反演精度

针对在研仪器——大气辐射超高光谱探测仪的临边探测模式,模拟计算了大气温度和水汽的权重函数。以此为基础,利用信息量和权重函数线性化方法,结合仪器的可探测亮温阈值0.3 K,计算并分析6种大气状态下,大气温度和水汽混合比廓线在不同反演精度条件下可获得的光谱通道数,在满足最佳光谱通道数200的要求下,理论上预估其反演精度。温度廓线整体反演精度为0.6 K,水汽混合比廓线反演精度可达到5%,但热带大气在16~20 km高度的水汽廓线反演精度仅为10%。反演精度预估,仅提供了一种全面认识仪器性能的方法,精度的确定还有赖于真实探测数据的获取和反演方法。     

Analysis of the ability of infrared water vapor channel for moisture remote sensing in the lower atmosphere

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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.     

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.     

Study of TOVS applications in monitoring atmospheric temperature,water vapor,and cloudiness in East Asia

Summary A new Statistical-Physical Retrieval Method (STPRM) has been developed for applications with TIROS Operational Vertical Sounder (TOVS) measurements. The method uses physical modeling combined with statistical regression to develop straightforward retrieval expressions for temperature, moisture content, and tropopause height based on brightness temperature measurements from both the HIRS and MSU instruments used in the TOVS system. The selection of HIRS and MSU channels used in the various retrievals is based on channel sensitivity coefficients which relate to the amplitude of the change of a given channel's brightness temperature to a given change in a retrieval parameter. The temperature retrieval procedure is designed for all-weather situations, and emphasizes the use of MSU microwave channels including linear combinations of these channels to improve vertical resolution. Cloud parameters are retrieved using radiances from HIRS channels to generate clear column radiances for the moisture and tropopause height retrievals, which depend almost exclusively on the HIRS channels. The STPRM scheme is then used to obtain and evaluate distributions of temperature, mixing ratio, and tropopause height. Distributions of ozone content are also retrieved from an independent iterative retrieval procedure using the cloud corrected radiances from the STPRM scheme as input. The retrievals are compared to in situ measurements obtained from radiosonde observations and ground-based Dobson spectrometer measurements situated throughout East Asia with generally good results. The temperature retrievals are also used in a synoptic analysis of a winter storm situation that developed over northern China in January 1989, giving a geopotential height distribution which is confirmed by aerological observations.With 16 Figures     

云参数对微波亮温模拟计算的影响试验

利用CRTM (Community Radiative Transfer Model) 快速辐射传输模式对NOAA-K系列卫星的AMSU-A通道亮温进行正演模拟,重点研究云粒子类型、云高、云厚度等云参数对微波亮温模拟的影响。结果表明:改变云粒子类型时,云水和雨水对模拟亮温影响较大,模拟亮温值比晴空高1 K;霰、雪、冰、雹等固态粒子对模拟亮温的影响较小,模拟亮温值略低于晴空无云情况;云层光学厚度较大时,各通道亮温受云层影响的情况取决于权重函数峰值高度和云顶高度的配置;多个高度存在云时,若最上层云较厚 (2 km),光学厚度大,相应通道亮温取决于最上层云,较低层云对亮温不产生影响;云层变薄,光学厚度减小,高度低于云层或略高于云顶的通道亮温随云层厚度的变化明显,若通道高度远高于云顶,云层厚度的变化对于其亮温模拟的影响很小。     

基于FY-4A卫星探测区域模式背景误差和观测误差估计的长波红外通道选择研究

中国新一代静止气象卫星风云四号A星（FY-4A）上搭载的干涉式大气垂直探测仪GIIRS（Geostationary Interferometric Infrared Sounder）是世界上首台在静止轨道运行的高光谱红外探测仪器,拥有1650个通道,其中长波通道689个,中波通道961个。由于计算机存储能力、数据传输和变分同化时效性等限制,目前很难在业务环境中同化全部通道,并且多通道卫星信息往往存在一定的空间相关和光谱相似,故在实际应用中必须降低高光谱资料的通道维数,去除数据冗余和观测相关性,挑选出对特定目标起主要作用的通道子集,进而利用有限的通道来最大限度地提供观测信息。考虑GRAPES（Global/Regional Assimilation and Prediction Enhanced System）数值预报系统估计得到的FY-4A观测范围内的背景误差协方差矩阵,并且在GIIRS观测误差后验重估计的基础上,结合通道权重函数峰值和信息熵分步迭代法对其长波通道进行了通道选择研究和试验。结果表明,在给定选择通道个数时,权重函数法和信息熵方法得到的通道组合进行温度和湿度误差分析时误差整体比单一方法小,在给定通道个数（40个）少于单一方案（50个）时,误差分析结果相当。GIIRS最优通道选择的研究为该资料的同化应用建立了基础。      

Estimating the Retrievability of Temperature Profiles from Satellite Infrared Measurements

A method is developed to assess retrievability, namely the retrieval potential for atmospheric temperature profiles, from satellite infrared measurements in clear-sky conditions. This technique is based upon generalized linear inverse theory and empirical orthogonal function analysis. Utilizing the NCEP global temperature reanalysis data in January and July from 1999 to 2003, the retrievabilities obtained with the Atmospheric Infrared Sounder （AIRS） and the High Resolution Infrared Radiation Sounder/3 （HIRS/3） sounding channel data are derived respectively for each standard pressure level on a global scale. As an incidental result of this study, the optimum truncation number in the method of generalized linear inverse is deduced too. The results show that the retrievabilities of temperature obtained with the two datasets are similar in spatial distribution and seasonal change characteristics. As for the vertical distribution, the retrievabilities are low in the upper and lower atmosphere, and high between 400 hPa and 850 hPa. For the geographical distribution, the retrievabilities are low in the low-latitude oceanic regions and in some regions in Antarctica, and relatively high in mid-high latitudes and continental regions. Compared with the HIRS/3 data, the retrievability obtained with the AIRS data can be improved by an amount between 0.15 and 0.40.     

Using longwave HIRS radiances to test climate models

A ‘model-to-radiance’ comparison of simulated brightness temperatures from the Hadley Centre Global Environmental Model 2 with measurements from the High Resolution Infrared Radiation Sounder/4 (HIRS/4) instrument onboard the MetOp-A satellite is presented. For the all-sky, the model overestimates brightness temperatures in the atmospheric window region with the greatest biases over areas associated with deep convective cloud. In contrast to many global climate models, much smaller clear-sky biases are found indicating that model clouds are the dominating source of error. Simulated values in upper atmospheric CO₂ channels approximate observations better as a result of compensating cold biases at the poles and warm biases at lower latitudes, due to a poor representation of the Brewer Dobson circulation in the 38 level ‘low-top’ configuration of the model. Simulated all and clear-sky outgoing longwave radiation (OLR) evaluated against the Clouds and the Earth’s Radiant Energy System (CERES) and HIRS OLR products reveal good agreement, in part due to cancellation of positive and negative biases. Through physical arguments relating to the spectral energy balance within a cloud, it is suggested that broadband agreement could be the result of a balance between positive window biases and unseen negative biases originating from the water vapour rotational band in the far infrared (not sampled by HIRS).     

The study of in-orbit calibration accuracy of NOAA satellite infrared sounder and its effect on temperature profile retrievals

The calibration accuracy of High Resolution Infrared Radiation Sounder Mod. 2 (H1RS / 2) on NOAA-10 sat-ellite is analyzed in this paper. The non-linear effect in the linear calibration curve induces a deviation of 1.5 degrees (k) of brightness temperature in the tenth channel (8.3 urn, water vapor absorption) of the HIRS / 2 and the non-linear effect affects the other channels to a different extent. Based on analyzing non-linearity in two-point calibration curve, a tri-point calibration equation is given. A numerical test of effects of the linear and non-linear calibration models on the accuracy of atmospheric temperature retrievals is carried out.