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The Impact of AIRS Atmospheric Temperature and Moisture Profiles on Hurricane Forecasts: Ike(2008) and Irene(2011)

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Advances in Atmospheric Sciences 2015年第3期32卷 319-335页

作者： ZHENG Jing Jun LI Timothy J.SCHMIT Jinlong LI Zhiquan LIU Cooperative Institute for Meteorological Satellite Studies University of Wisconsin-MadisonWisconsin 53706 USA National Satellite Meteorological Center China Meteorological Administration Advanced Satellite Products Branch Center for Satellite Applications and ResearchNESDIS/NOAA Madison WI 53706 USA National Center for Atmospheric Research Boulder Colorado 80305 USA

Atmospheric InfraRed Sounder （AIRS） measurements are a valuable supplement to current observational data,especially over the oceans where conventional data are sparse.In this study,two types of AIRS-retrieved temperature and moisture profiles,the AIRS Science Team product （SciSup） and the single field-of-view （SFOV） research product,were evaluated with European Centre for Medium-Range Weather Forecasts （ECMWF） analysis data over the Atlantic Ocean during Hurricane Ike （2008） and Hurricane Irene （2011）.The evaluation results showed that both types of AIRS profiles agreed well with the ECMWF analysis,especially between 200 hPa and 700 hPa.The average standard deviation of both temperature profiles was approximately 1 K under 200 hPa,where the mean AIRS temperature profile from the AIRS SciSup retrievals was slightly colder than that from the AIRS SFOV retrievals.The mean SciSup moisture profile was slightly drier than that from the SFOV in the mid troposphere.A series of data assimilation and forecast experiments was then conducted with the Advanced Research version of the Weather Research and Forecasting （WRF） model and its three-dimensional variational （3DVAR） data assimilation system for hurricanes Ike and Irene.The results showed an improvement in the hurricane track due to the assimilation of AIRS clear-sky temperature profiles in the hurricane environment.In terms of total precipitable water and rainfall forecasts,the hurricane moisture environment was found to be affected by the AIRS sounding assimilation.Meanwhile,improving hurricane intensity forecasts through assimilating AIRS profiles remains a challenge for further study.

关键词： AIRS data assimilation temperature profile moisture profile hurricane forecast WRF 3DVAR

Ensemble Retrieval of Atmospheric Temperature Profiles from AIRS

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Advances in Atmospheric Sciences 2014年第3期31卷 559-569页

作者： ZHANG Jie Zhenglong LI Jun LI Jinglong LI Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Key Laboratory of Meteorological Disaster of Ministry of EducationNanjing University of Information Science & Technology Cooperative Institute for Meteorological Satellite Studies University of Wisconsin-Madison

ABSTRACT Satellite-based observations provide great opportunities for improving weather forecasting. Physical retrieval of atmo spheric profiles from satellite observations is sensitive to the uncertainty of the first guess and other factors. In order to improve the accuracy of the physical retrieval, an ensemble methodology was developed with an emphasis on perturbing the first guess. In the methodology, a normal probability density function （PDF） is used to select the optimal profile from the ensemble retrievals. The ensemble retrieval algorithm contains four steps：（1） regression retrieval for original first guess; （2） perturbation of the original first guess to generate new first guesses （ensemble first guesses）; （3） using the ensemble first guesses and nonlinear iterative physical retrieval to generate ensemble physical results; and （4） the final optimal profile is selected from the ensemble physical results by using PDE Temperature eigenvectors （EVs） were used to generate the pertur- bation and generate the ensemble first guess. Compared with the regular temperature profile retrievals from the Atmospheric InfraRed Sounder （AIRS）, the ensemble retrievals RMSE of temperature profiles selected by the PDF was reduced between 150 and 320 hPa and below 400 hPa, with a maximum improvement of 0.3 K at 400 hPa. The bias was also reduced in many layers, with a maximum improvement of 0.69 K at 460 hPa. The combined optimal （CombOpt） profile and a mean optimal （MeanOpt） profile of all ensemble physical results were improved below 150 hPa. The MeanOpt profile was better than the CombOpt profile, and was regarded as the final optimal （FinOpt） profile. This study lays the foundation for improving temperature retrievals from hyper-spectral infrared radiance measurements.

关键词： ensemble retrieval perturbation eigenvectors PDF AIRS

Global consistency check of AIRS and IASI total CO2 column concentrations using WDCGG ground-based measurements

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Frontiers of Earth Science 2017年第1期11卷 1-10页

作者： Anyuan DIAO Jiong SHU Ci SONG Wei GAO Key Laboratory of Geographic Information Science (Ministry of Education) School of Geographic Sciences East China Normal University Shanghai 200241 China Colorado State University Department of Ecosystem Science and Sustainability Fort Collins Colorado 80523 USA Colorado State University Natural Resource Ecology Laboratory Fort Collins Colorado 80523 USA

This article describes a global consistency check of CO2 satellite retrieval products from the Atmospheric Infrared Sounder （AIRS） and Infrared Atmospheric Sounding Interferometer （IASI） using statistical analysis and data from the World Data Centre for Greenhouse Gases （WDCGG）. We use the correlation coefficient （r）, relative difference （RD）, root mean square errors （RMSE）, and mean bias error （MBE） as evaluation indicators for this study. Statistical results show that a linear positive correlation between AIRS/IASI and WDCGG data occurs for most regions around the world. Temporal and spatial variations of these statistical quantities reflect obvious differences between satellite-derived and ground-based data based on geographic position, especially for stations near areas of intense human activities in the Northern Hemisphere. It is noteworthy that there appears to be a very weak correlation between AIRS/IASI data and ten ground- based observation stations in Europe, Asia, and North America. These results indicate that retrieval products from the two satellite-based instruments studied should be used with great caution.

关键词： CO2 consistency check AIRS IASI WDCGG

Assimilation of atmospheric infrared sounder radiances with WRF-GSI for improving typhoon forecast

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Frontiers of Earth Science 2018年第3期12卷 457-467页

作者： Yan-An LIU Zhibin SUN Maosi CHEN Hung-Lung Allen HUANG Wei GAO Key Laboratory of Geographic Information Science (Ministry of Education) East China Normal University Shanghai 200241 China School of Geographic Sciences East China Normal University Shanghai 200241 China ECNU-CSU Joint Research Institute for New Energy and the Environment East China Normal University Shanghai 200062 China Joint Laboratory for Environmental Remote Sensing and Data Assimilation East China Normal University Shanghai 200241 China Natural Resource Ecology Laboratory Colorado State University Fort Collins CO 80523 United States Cooperative Institute for Meteorological Satellite Studies University of Wisconsin-Madison Madison WI 53706 United States

The Atmospheric Infrared Sounder （AIRS） can provide the profile information on atmospheric temperature and humidity in high vertical resolution. The assimilation of its radiances has been proven to improve the Numerical Weather Prediction （NWP） in global models. In this study, regional assimilation of AIRS radiances was carried out in a community assimilation system, using Gridpoint Statistical Interpolation （GSI） coupled with the Weather Research and Forecasting （WRY） model. The AIRS channel selection, quality control, and radiances bias correction were examined and illustrated for optimized assimilation. The bias correction scheme in the regional model showed that corrections on most of the channels produce satisfactory results except for several land surface channels. The assimilation and forecast experiments were carried out for three typhoon cases （Saola, Damrey, and Haikui in 2012） with and without including AIRS radiances. Results show that the assimilation of AIRS radiances into the WRF/GSI model improves both the typhoon track and intensity in a 72-hour forecast.

关键词： AIRS WRF/GSI model radiance assimilation typhoon forecast

Validation of AIRS-Retrieved atmospheric temperature data over the Taklimakan Desert

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Research in Cold and Arid Regions 2020年第4期12卷 242-251页

作者： YuFen Ma RuQi Li Men Zhang MinZhong Wang Mamtimin Ali Institute of Desert Meteorology China Meteorological AdministrationUrumqiXinjiang 830002China Center of Central Asia Atmospheric Science Research UrumqiXinjiang 830002China Xinjiang Meteorological Observatory UrumqiXinjiang 830002China

The Taklimakan Desert, the world's second largest desert, plays an important role in regional climate change. Previousstudies on its spatial temperature features suffered from sparse conventional detection data, but the Atmospheric InfraredSounder (AIRS) provides excellent temperature retrievals with high spatiotemporal resolution. Validation of AIRS temperatureretrievals over desert regions with high land-surface emissivity, the key contributor to inversion error, is essential beforeusing these data in regional weather/climate modeling. This paper examines the correlation coefficients, root meansquare error (RMSE) and mean BIAS between AIRS-retrieved atmospheric temperature data and radiosonde observations(RAOBs) in the Taklimakan Desert hinterland and oases in the morning and at dusk. Firstly, the AIRS retrievals are consistentwith RAOBs and are more consistent in the morning than at dusk. The consistency is better over a small-scale desert oasisthan over a large-scale oasis in the morning and exhibits the opposite trend at dusk. The correlation coefficient over thehinterland is high in the morning but negative at dusk due to high desert-surface emissivity. Second, the RMSEs, which areall smaller than 3 K, are generally higher over desert sites than over oasis sites and slightly lower over a small-scale oasisthan over a large-scale oasis in the morning. At dusk, the RMSEs are higher over desert sites than over oases and slightlyhigher over a small-scale oasis than over a large-scale oasis. Furthermore, the RMSEs are generally higher in the morningthan at dusk over a large-scale oasis and lower in the morning than at dusk over a small-scale oasis. Third, the absolutemean BIAS values are mostly lower than 1 K. In the morning, relative to RAOB temperatures, the retrieval temperaturesare higher over desert sites but lower over oasis sites. At dusk, the retrieval temperatures are lower than RAOB temperaturesover both desert and oasis sites. The retrieval temperatures are higher than RAOB temperatures over desert sit

关键词： AIRS Taklimakan Desert temperature quality validation

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中国可降水量时空分布及其变化趋势分析

长江科学院院报 2023年第4期40卷 37-43页

作者：黄双庆唐超礼黄友锐安徽理工大学计算机科学与工程学院安徽淮南232001 安徽理工大学电气与信息工程学院安徽淮南232001

为了探究2003—2021年中国可降水量时空分布及其变化趋势特点,采用美国国家航空航天局地球观测系统卫星Aqua上AIRS探测仪反演的AIRS3STM中可降水量数据,通过线性拟合、Mann-Kendall检验和经验正交函数分析法,分析其时空变化影响因素。... 详细信息

为了探究2003—2021年中国可降水量时空分布及其变化趋势特点,采用美国国家航空航天局地球观测系统卫星Aqua上AIRS探测仪反演的AIRS3STM中可降水量数据,通过线性拟合、Mann-Kendall检验和经验正交函数分析法,分析其时空变化影响因素。结果表明:(1)中国日间、夜间年际可降水量呈上升趋势,日间上升速率为0.044 (kg/m^(2))/a,夜间上升速率为0.062 (kg/m^(2))/a,并得出日间、夜间突变点发生时间分别是2014年和2008年。(2)中国日间、夜间四季变化均为上升趋势,夏季变化速率最大,春季、冬季变化速率较低,仅日间夏季和夜间的夏、秋和冬季通过了α=0.05的显著性检验。(3)中国日间可降水量和地表温度空间分布与纬度呈负相关,纬度越低,可降水量、地表温度越高,华南地区可降水量较高,西北地区偏低,利用EOF分析法选取部分典型区域也验证了以上规律。(4)可降水量与地表温度呈正相关,地表温度越高,其上升趋势越明显。研究成果对中国的气候、地形分布以及自然灾害预警均有一定参考意义。

关键词：可降水量地表温度时空规律 MK趋势分析 AIRS

Use of Total Precipitable Water Classification of A Priori Error and Quality Control in Atmospheric Temperature and Water Vapor Sounding Retrieval

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Advances in Atmospheric Sciences 2012年第2期29卷 263-273页

作者： Eun-Han KWON Elisabeth WEISZ School of Earth and Environmental Sciences Seoul National University Seoul 151-747 Korea Cooperative Institute for Meteorological Satellite Studies University of Wisconsin-Madison1225 West Dayton Street Madison WI 53706 USA

This study investigates the use of dynamic a priori error information according to atmospheric moistness and the use of quality controls in temperature and water vapor profile retrievals from hyperspectral infrared （IR） sounders. Temperature and water vapor profiles are retrieved from Atmospheric InfraRed Sounder （AIRS） radiance measurements by applying a physical iterative method using regression retrieval as the first guess. Based on the dependency of first-guess errors on the degree of atmospheric moistness, the a priori first-guess errors classified by total precipitable water （TPW） are applied in the AIRS physical retrieval procedure. Compared to the retrieval results from a fixed a priori error, boundary layer moisture retrievals appear to be improved via TPW classification of a priori first-guess errors. Six quality control （QC） tests, which check non-converged or bad retrievals, large residuals, high terrain and desert areas, and large temperature and moisture deviations from the first guess regression retrieval, are also applied in the AIRS physical retrievals. Significantly large errors are found for the retrievals rejected by these six QCs, and the retrieval errors are substantially reduced via QC over land, which suggest the usefulness and high impact of the QCs, especially over land. In conclusion, the use of dynamic a priori error information according to atmospheric moistness, and the use of appropriate QCs dealing with the geographical information and the deviation from the first-guess as well as the conventional inverse performance are suggested to improve temperature and moisture retrievals and their applications.

关键词： atmospheric sounding AIRS total precipitable water a priori error quality control

Ozone Profile Retrieval from Satellite Observation Using High Spectral Resolution Infrared Sounding Instrument

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Advances in Atmospheric Sciences 2001年第5期18卷 959-971页

作者： Yanni Qu, Mitchell D. Goldberg and Murty Divakarla Research and Data System Corporation, 7833 Walker Dr Greenbelt. MD 20770 National Eivironment Satellite Data and Information Service, Office of Research and Application, World Weather Building. 5200 Auth Research and Data System Corporation Greenbelt USA National Environment Satellite Data and Information Service Office of Research and Application Camp Springs USA

This paper presents a preliminary result on the retrieval of atmospheric ozone profiles using an im- proved regression technique and utilizing the data from the Atmospheric InfraRed Sounder (AIRS), a hyper-spectral Instrument expected to be flown on the EOS-AQUA platform in 20D2. Simulated AIRS spectra were used to study the sensitivity of AIRS radiance on the tropospheric and stratospheric ozone changes, and to study the impact of various channel combinations on the ozone profile retrieval. Sensitivity study results indicate that the AIRS high resolution spectral channels between the wavenumber 650- 800 cm-1 provide very useful information to accurately retrieve tropospheric and stratospheric ozone pro- files Eigenvector decomposition of AIRS spectra indicate that no more than 100 eigenvectors are needed to retrieve very accurate ozone profiles. The accuracy of the retrieved atmospheric ozone profile from the pres- ent technique and utilizing the AIRS data was compared with the accuracy obtained from current Advanced TIROS Operational Vertical Sounder (ATOVS) data aboard National Oceanic and Atmospheric Admini- stration (NOAA) satellites As expected, a comparison of retrieval results confirms that the ozone profile re- trieved with the AIRS data is superior to that of ATOVS

关键词： AIRS ATOVS Regression Eigenvector Principal component

Comparisons of cloud detection among four satellite sensors on severe haze days in eastern China

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Atmospheric and Oceanic Science Letters 2018年第1期11卷 86-93页

作者： TAN Sai-Chun ZHANG Xiao WANG Hong CHEN Bin SHI Guang-Yu SHI Chong State Key Laboratory of Numerical Modeling of Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of Sciences Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Nanjing University of Information Science and Technology College of Earth Science University of Chinese Academy of Sciences State Key Laboratory of Severe Weather/Institute of Atmospheric Composition Chinese Academy of Meteorological Sciences China Meteorological Administration Key Laboratory of Cloud-Precipitation Physics and Severe Storms Institute of Atmospheric Physics Chinese Academy of Sciences

云在天气、气候和地球能量平衡中非常重要。雾霾地区不同卫星云探测精度如何的研究较少。本论文详细比较了中国东部地区2015–2016年冬季2次严重雾霾天气时,"A-Train"星群上四个遥感器的云探测。结果显示,在雾霾区域,MODIS/Aqua真彩色图... 详细信息

云在天气、气候和地球能量平衡中非常重要。雾霾地区不同卫星云探测精度如何的研究较少。本论文详细比较了中国东部地区2015–2016年冬季2次严重雾霾天气时,"A-Train"星群上四个遥感器的云探测。结果显示,在雾霾区域,MODIS/Aqua真彩色图和CALIOP/CALIPSO清楚地观测到气溶胶层时,AIRS/Aqua、CALIOP和CPR/CloudSat没有观测到云,而MODIS则观测到云顶高度接近地面的云,表明MODIS将气溶胶误判为云。更多雾霾天气个例结果显示,在雾霾区域,MODIS云量比AIRS云量高13%–49%,平均高36%.

关键词：云探测气溶胶雾霾 MODIS AIRS CloudSat CALIPSO