METOP星载干涉式超高光谱分辨率红外大气探测仪(IASI)及其产品

为了深入了解国际卫星红外大气探测仪器的新特点,以欧洲METOP卫星装载的超高光谱红外大气探测仪(IASI:Infrared Atmospheric Sounding Interferometer)为例,介绍卫星红外探测仪研发背景、仪器特征和数据产品处理,并与第1个高光谱大气红外探测仪(AIRS:Atmosphenic Inftared Sounder)作了比较分析.采用干涉分光技术的IASI为地球大气遥感提供了丰富的研究资料,可用于反演大气、海洋、云和大气成分,对我国风云卫星的高光谱红外大气垂直探测仪器的研发具有重要参考价值.     

风云三号卫星红外高光谱探测技术及潜在应用

高光谱大气探测仪具有高光谱分辨率、高灵敏度和高精度光谱辐射定标等特点,在大气温湿度廓线反演、数值天气预报同化、气候变化研究以及大气痕量气体探测等应用上有显著的优势。我国风云三号极轨气象卫星的FY-3A/B/C三颗卫星上成功装载了自主研制的通道式红外探测仪器—红外分光计(IRAS),获取了从可见光到红外波长范围内26个通道的辐射观测,并应用于资料同化、全球大气温度和水汽廓线反演等。从FY-3D星开始将装载红外高光谱大气探测仪以替代IRAS,标志着红外高光谱大气垂直探测系统新纪元的开始。以风云三号卫星红外高光谱大气探测仪为例,介绍了卫星红外高光谱探测技术的进展和地面应用系统预处理过程的关键技术环节,给出了红外高光谱资料的潜在应用,并对在数值天气预报同化和大气探测应用方面的难点问题进行了分析和探讨。     

利用高光谱红外探测资料反演大气参数

文章介绍了红外高光谱的卫星探测技术以及利用现有的机载和星载高光谱资料的反演方法，着重讨论了美国NASA地球观测系统上携带的大气红外探测仪AIRS的反演方法。     

人工神经网络法反演晴空大气湿度廓线的研究

高光谱分辨率大气红外探测器AIRS(Atmospheric Infrared Sounder)作为第一个超高光谱大气红外探测仪,开辟了卫星大气探测的新时代.以无线电探空值与SARTA(Stand-Alone Radiative Transfer Algorithm辐射传输模式)v1.05版的前向模式模拟出的AIRS辐射...     

AIRS晴空大气温度廓线反演试验

2002年5月发射的Aqua是美国地球观测系统中的第2颗卫星EOS-2(Earth Observing System),它携带的大气红外探测仪AIRS(Atmospheric Infrared Sounder)是目前国际上最先进的超高光谱分辨率红外大气垂直探测仪.1200的光谱分辨率和全球覆盖能力使其可以观测全球大气状态及其变化.对其超高光谱分辨率资料的处理和应用的研究既有科学意义,又有实用价值.利用AIRS实际观测资料反演大气温度,本文使用的是便于处理大数据量的统计反演方法中的特征向量法,计算回归系数使用的是AIRS观测辐射值和T213数值预报分析场.本文从通道个数、地形及地表发射率影响、增加预报因子、国外同类产品比较等4个方面进行了大气温度反演试验研究.研究结果表明:(1)在利用超高光谱分辨率仪器进行反演时,合理选择通道是非常必要的;(2)AIRS反演的大气温度在对流层顶和中上层具有较高的精度,在对流层低层,尤其是近地面反演精度不够理想;(3)增加地表温度,地表发射率和地形3个预报因子,可以提高近地面的反演精度;(4)文中反演的大气温度精度与国外同类产品精度基本一致.     

基于高光谱资料对FY-1C/1D气象卫星进行交叉定标

介绍了利用AQUA卫星高光谱AIRS资料对FY-1C、FY-1D气象卫星热红外通道进行交叉定标的方法及定标结果。首先利用卫星轨道预报软件预报出AQUA与FY-1C以及AQUA与FY-1D卫星交叉点,再对交叉区域卫星资料进行像元投影和像元匹配,像元匹配包括时间、观测角度、环境均匀性等检验。以AIRS探测结果作为辐射基准,利用其观测值和FY-1卫星热红外通道光谱响应函数进行光谱匹配,最终得到FY-1卫星热红外通道的准真值并与FY-1卫星的业务产品进行比较分析。对FY-1C、FY-1D两年多卫星资料进行多次交叉比对,结果表明FY-1C通道4比AIRS观测亮温低1.3K左右,通道5低3.6K左右;而FY-1D通道4比AIRS观测亮温低0.3K左右,通道5低3.6K左右。这个准真值与FY-1观测的计数值进行再定标得到新的定标系数。     

红外高光谱资料近地面通道应用

由于下垫面的复杂性,卫星近地面通道的辐射率资料没有得到充分开发和利用。就我国自主研发的GRAPES 3DVar而言,红外高光谱近地面通道资料还没有应用于陆地,即使在下垫面相对简单的海洋,由于背景场海表温度估计不够准确,红外高光谱资料的使用效果也不甚理想。针对GRAPES模式的背景场海表温度估计不够准确这一问题,本文利用大气红外探测仪器AIRS(The Atmospheric Infrared Sounder)辐射率观测资料通过一维变分（1DVar）方法对其晴空视场点内的背景场海表温度进行调整,再运用GRAPES全球分析预报系统进行同化分析,研究了海表温度调整后对分析场的影响。结果表明,利用一维变分调整后的海表温度不仅使得低层通道的模拟亮温与观测亮温更加匹配,而且有效地改进了分析场,对位势高度场高、中、低层均有不错的改进,对低层湿度场以及风场的改进也较为明显。     

红外高光谱资料近地面通道应用技术研究:海洋地区观测资料同化试验

由于下垫面的复杂性,卫星近地面通道的辐射率资料没有得到充分开发和利用.就我国自主研发的GRAPES-3DVar而言,红外高光谱近地面通道资料还没有应用于陆地,即使在下垫面相对简单的海洋,由于背景场海表温度估计不够准确,红外高光谱资料的使用效果也不甚理想.针对GRAPES模式的背景场海表温度估计不够准确这一问题,本文利用大气红外探测仪器AIRS(The Atmospheric Infrared Sounder)辐射率观测资料通过一维变分(1DVar)方法对其晴空视场点内的背景场海表温度进行调整,再运用GRAPES全球分析预报系统进行同化分析,研究了海表温度调整后对分析场的影响.结果表明,利用一维变分调整后的海表温度不仅使得低层通道的模拟亮温与观测亮温更加匹配,而且有效地改进了分析场,对位势高度场高、中、低层均有不错的改进,对低层湿度场以及风场的改进也较为明显.     

利用神经网络方法从高光谱分辨率红外遥感资料反演大气温度廓线

采用主分量分解数据压缩技术和基于误差反传学习算法的三层前馈神经网络(BP神经网络),使用AUQA/AIRS(Atmospheric Infrared Sounder)高光谱分辨率红外观测资料,对不同光谱通道组合,在中纬度复杂地形上反演了垂直空间分辨率为1 km的大气温度廓线,并与相匹配的ECWMF分析场资料进行了比较。结果表明,从AIRS资料能够获得1 K/km垂直分辨率的对流层温度反演精度。但是青藏高原对反演结果有明显的影响,并且这种影响与光谱波段有关。消除这种影响的途径之一是增加非卫星观测的附加预报因子。同时改进了神经网络反演策略,采用逐层反演的方法,缩短了所需要的网络训练时间。     

利用AIRS卫星资料反演大气廓线Ⅰ.特征向量统计反演法

引进美国威斯康星大学的IMAPP（International MODIS／AIRS Preprocessing Package）软件包，介绍了利用高光谱分辨率大气红外探测器AIRS（Atmospheric Infrared Sounder）观测辐射值，用特征向量统计法反演大气温度、湿度等垂直廓线的算法，采用亮度温度分类和扫描角分类回归后，减小了反演误差。并将其应用到中国地区，通过与无线电探空值及欧洲中期天气预报中心ECMWF（European Center of Medium-range Weather Forecasts）客观分析场的比较，结果表明：该方法所获得的温度、水汽反演结果与探空观测及ECMWF大气廓线分布一致，且AIRS因其高光谱分辨率（即高垂直空间分辨率）显示了精细的大气结构。     

气象卫星可见光红外光学成像仪发展沿革

该文回顾了环境气象卫星可见光红外光学成像遥感仪器50多年的发展历程,从不同时期在轨运行的近百台 (套) 仪器中选择了12种作为代表,结合仪器功能性能技术指标和应用需求梳理分析了其历史发展脉络和主流业务发展趋势,并初步探讨了创新发展方向。50多年的发展可以分为3个阶段:早期探索20年, 美国第1代探索性仪器,开创了气象卫星对地观测的先河;初步应用20年, 基本形成初步应用格局,欧洲、中国等开始发展自己的环境气象卫星光学成像遥感仪器;稳定应用和进步发展10多年。新一代极轨卫星可见光红外光学成像遥感仪器,其典型特征是光谱波段20个以上,谱段带宽窄,光谱范围全面覆盖0.4~15 μm,辐射测量精度高,空间分辨率为200~1000 m,其改进型仪器代表了未来极轨气象卫星主流业务发展趋势。静止气象卫星可见光红外光学成像遥感仪器未来主流业务发展方向的典型特点是光谱波段15个以上,谱段带宽较窄,光谱范围全面覆盖0.4 ~15 μm,辐射测量精度高,空间分辨率为500~2000 m,圆盘图成像速度可达到分钟级,区域扫描速度更快。     

Quality Assessment and Forecast Sensitivity of Global Remote Sensing Observations

The satellite-derived wind from cloud and moisture features of geostationary satellites is an important data source for numerical weather prediction(NWP) models. These datasets and global positioning system radio occultation(GPSRO)satellite radiances are assimilated in the four-dimensional variational atmospheric data assimilation system of the UKMO Unified Model in India. This study focuses on the importance of these data in the NWP system and their impact on short-term24-h forecasts. The quality of the wind observations is compared to the short-range forecast from the model background. The observation increments(observation minus background) are computed as the satellite-derived wind minus the model forecast with a 6-h lead time. The results show the model background has a large easterly wind component compared to satellite observations. The importance of each observation in the analysis is studied using an adjoint-based forecast sensitivity to observation method. The results show that at least around 50% of all types of satellite observations are beneficial. In terms of individual contribution, METEOSAT-7 shows a higher percentage of impact(nearly 50%), as compared to GEOS, MTSAT-2and METEOSAT-10, all of which have a less than 25% impact. In addition, the impact of GPSRO, infrared atmospheric sounding interferometer(IASI) and atmospheric infrared sounder(AIRS) data is calculated. The GPSRO observations have beneficial impacts up to 50 km. Over the Southern Hemisphere, the high spectral radiances from IASI and AIRS show a greater impact than over the Northern Hemisphere. The results in this study can be used for further improvements in the use of new and existing satellite observations.     

Application of an artificial neural network for a direct estimation of atmospheric instability from a next-generation imager

Atmospheric instability information derived from satellites plays an important role in short-term weather forecasting,especially the forecasting of severe convective storms. For the next generation of weather satellites for Korea's multi-purpose geostationary satellite program, a new imaging instrument has been developed. Although this imaging instrument is not designed to perform full sounding missions and its capability is limited, its multi-spectral infrared channels provide information on vertical sounding. To take full advantage of the observation data from the much improved spatiotemporal resolution of the imager, the feasibility of an artificial neural network approach for the derivation of the atmospheric instability is investigated.The multi-layer perceptron model with a feed-forward and back-propagation training algorithm shows quite a sensitive response to the selection of the training dataset and model architecture. Through an extensive performance test with a carefully selected training dataset of 7197 independent profiles, the model architectures are selected to be 12, 5000, and 0.3 for the number of hidden nodes, number of epochs, and learning rate, respectively. The selected model gives a mean absolute error,RMSE, and correlation coefficient of 330 J kg~(-1), 420 J kg~(-1), and 0.9, respectively. The feasibility is further demonstrated via application of the model to real observation data from a similar instrument that has comparable observation channels with the planned imager.     

Validation of IASI-Retrieved Atmospheric Water Vapor Data over the Tibetan Plateau Region

The Infrared Atmospheric Sounding Interferometer (IASI) is a new-generation ultraspectral atmospheric sounding instrument mounted on the MetOp-A, the first operational polar-orbiting satellite developed by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT). It is an ultrahigh spectral-resolution atmospheric detector which can detect atmospheric chemical composition, temperature, and humidity profiles with high accuracy and resolution. In the present study, through comparative analyses of the similarities and differences between the IASI and the radiosonde observation (RAOB) water vapor data, and between the IASI and the Aqua-AIRS water vapor retrievals, a detailed and systematic assessment of the credibility of the IASI water vapor retrievals over the plateau region was made. A comparison of the IASI retrievals with the AIRS retrievals and the RAOB measurements over the Tibetan Plateau revealed that the IASI retrieval data are reliable and can be used for conducting further studies.     

基于往返式平漂探空的FY-3D卫星反演温度检验

往返式平漂探空观测（以下简称平漂探空）可实现对流层至平流层低层大气温度廓线垂直探测以及平流层低层内持续4 h的水平温度分布探测。该文介绍利用平漂探空试验数据对风云3号气象卫星D星（FY-3D）反演温度数据的检验评估算法,基于该算法和2021年3—9月长江中下游平漂探空试验数据完成对卫星反演大气温度数据的检验。结果显示:FY-3D卫星反演的温度数据准确度总体较高,与平漂探空上升段数据平均绝对偏差约为1.34℃,与下降段数据平均绝对偏差约为1.93℃;卫星反演的100 hPa以上和850 hPa以下温度误差分别偏大0.59℃和0.33℃;卫星反演平流层温度准确度低于温度廓线,平均绝对偏差约为3.92℃;与平漂探空数据相比,卫星大气温度廓线分辨率较低、趋势较平滑,无法显示大气温度垂直分布和平流层温度水平分布的细节特征。     

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.     

Satellite Data Assimilation of Upper-Level Sounding Channels in HWRF with Two Different Model Tops

The Advanced Microwave Sounding Unit-A(AMSU-A) onboard the NOAA satellites NOAA-18 and NOAA-19 and the European Organization for the Exploitation of Meteorological Satellites(EUMETSAT)Met Op-A, the hyperspectral Atmospheric Infrared Sounder(AIRS) onboard Aqua, the High resolution Infra Red Sounder(HIRS) onboard NOAA-19 and Met Op-A, and the Advanced Technology Microwave Sounder(ATMS) onboard Suomi National Polar-orbiting Partnership(NPP) satellite provide upper-level sounding channels in tropical cyclone environments. Assimilation of these upper-level sounding channels data in the Hurricane Weather Research and Forecasting(HWRF) system with two different model tops is investigated for the tropical storms Debby and Beryl and hurricanes Sandy and Isaac that occurred in 2012. It is shown that the HWRF system with a higher model top allows more upper-level microwave and infrared sounding channels data to be assimilated into HWRF due to a more accurate upper-level background profile. The track and intensity forecasts produced by the HWRF data assimilation and forecast system with a higher model top are more accurate than those with a lower model top.