Research On Testing And Revision Of Cloud And Atmospheric Products For AIRS

Since the 1960s when the first weather satellite was successfully launched, Satellites played a major role in weather analysis and atmospheric science research. With the development of meteorological science, satellite detection accuracy of the increasingly high demand. The development and application of hyperspectral atmospheric sounder data has become an inevitable trend in the development of future satellite and meteorological research professional work. The AIRS as the first real sense of hyperspectral infrared atmospheric sounder, it will provide high vertical resolution data retrieval accuracy. This study will tests and analysis effective cloud fraction in cloud products, temperature(atmospheric heat resources in climate rescoure elements) and water vapor (atmospheric water resources in climate rescoure elements) in atmospheric inversion product for AIRS inversion in Central and East China and the surrounding areas in summer(May to August), and try to improve the accuracy of AIRS products, improve its use in weather analysis, weather warnings and so on.On testing and use for AIRS cloud products, selecting each fifteen samples in Central and East China (95～130°E,20～60°N) in the afternoon at the same time for the corresponding AIRS and MODIS data. Selecting some cloud detection algorithms based on brightness temperature in infrared wavelengths for MODIS are used to identify clear sky pixel and different cloud phase in cloud pixel for AIRS, and count to the brightness temperature differences for AIRS different types of pixel in the cloud recognition algorithms. According to the brightness temperature differences for AIRS in the different phases for clear sky, water cloud and ice cloud, determine the threshold to achieve clear sky and cloud phase identification for AIRS. On the basis of the above it is test and improved the AIRS effective cloud fraction for retrieval in the different phase. The results showed that:Applying brightness temperature threshold method to AIRS cloud phase identification can better reflect the characteristics of clear sky and cloud phase for AIRS, cloud phase distribution corresponds with MODIS cloud phase product is better, especially in the edge region of the cloud. Analysis the comparison and deviation for AIRS effective cloud fraction in different cloud phases can get a conclusion:When effective cloud fraction lower under water clouds and effective cloud fraction higher under ice clouds, the effective cloud fraction error that AIRS inversion is larger. On the basis of the error analysis present an effective cloud fraction deviation correction algorithm for AIRS. It can increase to a certain extent for AIRS effective cloud fraction and provide a reference for application AIRS cloud products.On inspection in temperature and water vapor and application in the instability index calculated atmospheric product for AIRS, utilize the temperature and water vapor from AIRS atmospheric products, calculated the K index and the SI index of these two indices of atmospheric instability. The statistical analysis to these two atmospheric instability indexes which are applied to the rainstorm before about 6 hours occurred. Statistical results show that the rainstorm disasters oc(?) in about 80% of the case K> 27.5 ℃ or SI<3 ℃ before 6 hours. In order to better describe the characteristics of atmospheric instability before the storm occurred, the index K and the index SI calculated from AIRS made the appropriate combination of indices obtained KS and apply it to a case of rainstorm for certification. From verify the effects of view: region occurred rainstorm basically in the KS index high before 6 hours, the instability index calculated AIRS atmospheric products have a certain significance in indicating rain. Based on the temperature and water vapor examine with the statistical samples for AIRS atmospheric products through the ECMWF can be drawn:The applicability for temperature and water vapor on 500hPa height as well as temperature on 700hPa height inversion. When effective cloud fraction in the cloud pixels higher, deviations for water vapor on 700hPa and 850hPa height inversion by AIRS are larger. K index and SI index calculation errors mainly by AIRS water vapor inversion error on 700hPa and 850hPa height at higher effective cloud fraction caused. Finally, based on the error distribution of temperature and water vapor for statistical case, and combined with the radiance corresponds to the peak level for weighting function to establish the appropriate revisions for these three AIRS inversion temperature and water vapor. From the revised effect for examined case, The temperature and water vapor for AIRS has certain improvements, instability index error calculated by temperature and water vapor after revised is further reduced and Instability index of high value area can better correspond to heavy rain areas than before revised on spatial distribution.