The paper presents the algorithms for retrieving atmospheric temperature andmoisture profiles and surface skin temperature from the high-spectral-resolution AtmosphericInfrared Sounder (AIRS) with a statistical techni...The paper presents the algorithms for retrieving atmospheric temperature andmoisture profiles and surface skin temperature from the high-spectral-resolution AtmosphericInfrared Sounder (AIRS) with a statistical technique based on principal component analysis. Thesynthetic regression coefficients for the statistical retrieval are obtained by using a fastradiative transfer model with atmospheric characteristics taken from a dataset of global radiosondesof atmospheric temperature and moisture profiles. Retrievals are evaluated by comparison withradiosonde observations and European Center of Medium-Range Weather Forecasts (ECMWF) analyses. AIRSretrievals of temperature and moisture are in general agreement with the distributions from ECMWFanalysis fields and radiosonde observations, but AIRS depicts more detailed structure due to itshigh spectral resolution (hence, high vertical spatial resolution).展开更多
The physical retrieval algorithm of atmospheric temperature and moisture distribution from the Atmospheric InfraRed Sounder （AIRS） radiances is presented. The retrieval algorithm is applied to AIRS clear-sky radianc...The physical retrieval algorithm of atmospheric temperature and moisture distribution from the Atmospheric InfraRed Sounder （AIRS） radiances is presented. The retrieval algorithm is applied to AIRS clear-sky radiance measurements. The algorithm employs a statistical retrieval followed by a subsequent nonlinear physical retrieval. The regression coefficients for the statistical retrieval are derived from a dataset of global radiosonde observations （RAOBs） comprising atmospheric temperature, moisture, and ozone profiles. Evaluation of the retrieved profiles is performed by a comparison with RAOBs from the Atmospheric Radiation Measurement （ARM） Program Cloud And Radiation Testbed （CART） in Oklahoma, U. S. A.. Comparisons show that the physically-based AIRS retrievals agree with the RAOBs from the ARM CART site with a Root Mean Square Error （RMSE） of 1K on average for temperature profiles above 850 hPa, and approximately 10% on average for relative humidity profiles. With its improved spectral resolution, AIRS depicts more detailed structure than the current Geostationary Operational Environmental Satellite （GOES） sounder when comparing AIRS sounding retrievals with the operational GOES sounding products.展开更多
This paper describes briefly the sounding capabilities of TOVS/ATOVS onboard the NOAA polar-orbiting meteorological satellites,followed by a more detailed review of the retrieval schemes.The ICI physical retrieval sch...This paper describes briefly the sounding capabilities of TOVS/ATOVS onboard the NOAA polar-orbiting meteorological satellites,followed by a more detailed review of the retrieval schemes.The ICI physical retrieval scheme with some adaptations is implemented in our experiment.The analyses of the Chinese regional NWP model are utilized to create a rolling library of initial guess field.Retrieval results validated against both NWP analyses and radiosondes indicate good agreement between ICI retrievals and conventional observations.Preliminary result from the PC-ATOVS Windows display system of NSMC will also be shown.展开更多
A three-dimensional variational method is proposed to simultaneously retrieve the 3-D atmospheric temperature and moisture profiles from satellite radiance measurements. To include both vertical structure and the hori...A three-dimensional variational method is proposed to simultaneously retrieve the 3-D atmospheric temperature and moisture profiles from satellite radiance measurements. To include both vertical structure and the horizontal patterns of the atmospheric temperature and moisture, an EOF technique is used to decompose the temperature and moisture field in a 3-D space. A number of numerical simulations are conducted and they demonstrate that the 3-D method is less sensitive to the observation errors compared to the 1-D method. When the observation error is more than 2.0 K, to get the best results, the truncation number for the EOF＇s expansion have to be restricted to 2 in the 1-D method, while it can be set as large as 40 in a 3-D method. This results in the truncation error being reduced and the retrieval accuracy being improved in the 3-D method. Compared to the 1-D method, the rms errors of the 3-D method are reduced by 48% and 36% for the temperature and moisture retrievals, respectively. Using the real satellite measured brightness temperatures at 0557 UTC 31 July 2002, the temperature and moisture profiles are retrieved over a region （20°-45°N, 100°- 125°E） and compared with 37 collocated radiosonde observations. The results show that the retrieval accuracy with a 3-D method is significantly higher than those with the 1-D method.展开更多
基金Supported by the National Natural Science Foundation of China under Grant No. 49775255.
文摘The paper presents the algorithms for retrieving atmospheric temperature andmoisture profiles and surface skin temperature from the high-spectral-resolution AtmosphericInfrared Sounder (AIRS) with a statistical technique based on principal component analysis. Thesynthetic regression coefficients for the statistical retrieval are obtained by using a fastradiative transfer model with atmospheric characteristics taken from a dataset of global radiosondesof atmospheric temperature and moisture profiles. Retrievals are evaluated by comparison withradiosonde observations and European Center of Medium-Range Weather Forecasts (ECMWF) analyses. AIRSretrievals of temperature and moisture are in general agreement with the distributions from ECMWFanalysis fields and radiosonde observations, but AIRS depicts more detailed structure due to itshigh spectral resolution (hence, high vertical spatial resolution).
基金This research was supported by the Navy MURI Grant N00014-01-1-0850the 973 Proiect No,2001CB309400.
文摘The physical retrieval algorithm of atmospheric temperature and moisture distribution from the Atmospheric InfraRed Sounder （AIRS） radiances is presented. The retrieval algorithm is applied to AIRS clear-sky radiance measurements. The algorithm employs a statistical retrieval followed by a subsequent nonlinear physical retrieval. The regression coefficients for the statistical retrieval are derived from a dataset of global radiosonde observations （RAOBs） comprising atmospheric temperature, moisture, and ozone profiles. Evaluation of the retrieved profiles is performed by a comparison with RAOBs from the Atmospheric Radiation Measurement （ARM） Program Cloud And Radiation Testbed （CART） in Oklahoma, U. S. A.. Comparisons show that the physically-based AIRS retrievals agree with the RAOBs from the ARM CART site with a Root Mean Square Error （RMSE） of 1K on average for temperature profiles above 850 hPa, and approximately 10% on average for relative humidity profiles. With its improved spectral resolution, AIRS depicts more detailed structure than the current Geostationary Operational Environmental Satellite （GOES） sounder when comparing AIRS sounding retrievals with the operational GOES sounding products.
基金Supported by National"973"Project No.4(G1998040909#).
文摘This paper describes briefly the sounding capabilities of TOVS/ATOVS onboard the NOAA polar-orbiting meteorological satellites,followed by a more detailed review of the retrieval schemes.The ICI physical retrieval scheme with some adaptations is implemented in our experiment.The analyses of the Chinese regional NWP model are utilized to create a rolling library of initial guess field.Retrieval results validated against both NWP analyses and radiosondes indicate good agreement between ICI retrievals and conventional observations.Preliminary result from the PC-ATOVS Windows display system of NSMC will also be shown.
基金the 973 Program (Grant No. 2004CB418305)the National Natural Science Foundation of China(Grant No. 40575049).
文摘A three-dimensional variational method is proposed to simultaneously retrieve the 3-D atmospheric temperature and moisture profiles from satellite radiance measurements. To include both vertical structure and the horizontal patterns of the atmospheric temperature and moisture, an EOF technique is used to decompose the temperature and moisture field in a 3-D space. A number of numerical simulations are conducted and they demonstrate that the 3-D method is less sensitive to the observation errors compared to the 1-D method. When the observation error is more than 2.0 K, to get the best results, the truncation number for the EOF＇s expansion have to be restricted to 2 in the 1-D method, while it can be set as large as 40 in a 3-D method. This results in the truncation error being reduced and the retrieval accuracy being improved in the 3-D method. Compared to the 1-D method, the rms errors of the 3-D method are reduced by 48% and 36% for the temperature and moisture retrievals, respectively. Using the real satellite measured brightness temperatures at 0557 UTC 31 July 2002, the temperature and moisture profiles are retrieved over a region （20°-45°N, 100°- 125°E） and compared with 37 collocated radiosonde observations. The results show that the retrieval accuracy with a 3-D method is significantly higher than those with the 1-D method.
