This study investigates the capability of the dynamic downscaling method （DDM） in an East Asian climate study for June 1998 using the fifth-generation Pennsylvania State University-National Center for Atmospheric Re...This study investigates the capability of the dynamic downscaling method （DDM） in an East Asian climate study for June 1998 using the fifth-generation Pennsylvania State University-National Center for Atmospheric Research non-hydrostatic Mesoscale Model （MM5）.Sensitivity experiments show that MM5 results at upper atmospheric levels cannot match reanalyses data,but the results show consistent improvement in simulating moisture transport at low levels.The downscaling ability for precipitation is regionally dependent.During the monsoon season over the Yangtze River basin and the pre-monsoon season over North China,the DDM cannot match observed precipitation.Over Northwest China and the Tibetan Plateau （TP）,where there is high topography,the DDM shows better performance than reanalyses.Simulated monsoon evolution processes over East Asia,however,are much closer to observational data than reanalyses.The convection scheme has a substantial impact on extreme rainfall over the Yangtze River basin and the pre-monsoon over North China,but only a marginal contribution for Northwest China and the TP.Land surface parameterizations affect the locations and pattern of rainfall bands.The 10-day re-initialization in this study shows some improvement in simulated precipitation over some sub-regions but with no obvious improvement in circulation.The setting of the location of lateral boundaries （LLB） westward improves performance of the DDM.Including the entire TP in the western model domain improves the DDM performance in simulating precipitation in most sub-regions.In addition,a seasonal simulation demonstrates that the DDM can also obtain consistent results,as in the June case,even when another two months consist of no strong climate/weather events.展开更多
Remote measurements of Earth’s surface from ground, airborne, and spaceborne instruments show that its albedo is highly variable and is sensitive to solar zenith angle（SZA） and atmospheric opacity. Using a validate...Remote measurements of Earth’s surface from ground, airborne, and spaceborne instruments show that its albedo is highly variable and is sensitive to solar zenith angle（SZA） and atmospheric opacity. Using a validated radiative transfer calculating toolbox, DISORT and a bidirectional reflectance distribution function library, AMBRALS, a land surface albedo（LSA） lookup table（LUT） is produced with respect to SZA and aerosol optical depth. With the LUT, spectral and broadband LSA can be obtained at any given illumination geometries and atmospheric conditions. It provides a fast and accurate way to simulate surface reflectance over large temporal and spatial scales for climate study.展开更多
The multi-source data fusion methods are rarely involved in VNIR and thermal infrared remote sensing at present. Therefore, the potential advantages of the two kinds of data have not yet been adequately tapped, which ...The multi-source data fusion methods are rarely involved in VNIR and thermal infrared remote sensing at present. Therefore, the potential advantages of the two kinds of data have not yet been adequately tapped, which results in low calculation precision of parameters related with land surface temperature. A new fusion method is put forward where the characteristics of the high spatial resolution of VNIR （visible and near infrared） data and the high temporal resolution of thermal infrared data are fully explored in this paper. Non-linear fusion is implemented to obtain the land surface temperature in high spatial resolution and the high temporal resolution between the land surface parameters estimated from VNIR data and the thermal infrared data by means of GA-SOFM （genetic algorithms ＆ self-organizing feature maps）-ANN （artificial neural net-work）. Finally, the method is verified by ASTER satellite data. The result shows that the method is simple and convenient and can rapidly capture land surface temperature distribution of higher resolution with high precision.展开更多
基金supported by the funding of the Key Program of the Chinese Academy of Sciences (Grant No.KZCX2-YW-328)the National Key Basic Research Program (2005CB422003)+1 种基金National Science Foundation Center of China (NSFC) (40871001)the US JPL Grant No. 1278492,NOAA Grant Nos NA07OAR4310226 and NA08OAR4310591
文摘This study investigates the capability of the dynamic downscaling method （DDM） in an East Asian climate study for June 1998 using the fifth-generation Pennsylvania State University-National Center for Atmospheric Research non-hydrostatic Mesoscale Model （MM5）.Sensitivity experiments show that MM5 results at upper atmospheric levels cannot match reanalyses data,but the results show consistent improvement in simulating moisture transport at low levels.The downscaling ability for precipitation is regionally dependent.During the monsoon season over the Yangtze River basin and the pre-monsoon season over North China,the DDM cannot match observed precipitation.Over Northwest China and the Tibetan Plateau （TP）,where there is high topography,the DDM shows better performance than reanalyses.Simulated monsoon evolution processes over East Asia,however,are much closer to observational data than reanalyses.The convection scheme has a substantial impact on extreme rainfall over the Yangtze River basin and the pre-monsoon over North China,but only a marginal contribution for Northwest China and the TP.Land surface parameterizations affect the locations and pattern of rainfall bands.The 10-day re-initialization in this study shows some improvement in simulated precipitation over some sub-regions but with no obvious improvement in circulation.The setting of the location of lateral boundaries （LLB） westward improves performance of the DDM.Including the entire TP in the western model domain improves the DDM performance in simulating precipitation in most sub-regions.In addition,a seasonal simulation demonstrates that the DDM can also obtain consistent results,as in the June case,even when another two months consist of no strong climate/weather events.
基金supported by the National Natural Science Foundation of China(No.41305019)the Anhui Provincial Natural Science Foundation(No.1308085QD70)
文摘Remote measurements of Earth’s surface from ground, airborne, and spaceborne instruments show that its albedo is highly variable and is sensitive to solar zenith angle（SZA） and atmospheric opacity. Using a validated radiative transfer calculating toolbox, DISORT and a bidirectional reflectance distribution function library, AMBRALS, a land surface albedo（LSA） lookup table（LUT） is produced with respect to SZA and aerosol optical depth. With the LUT, spectral and broadband LSA can be obtained at any given illumination geometries and atmospheric conditions. It provides a fast and accurate way to simulate surface reflectance over large temporal and spatial scales for climate study.
基金Supported by the Key Laboratory of Mapping from Space of State Bureau of Surveying and Mapping（No.200815）, the Natural Science Foundation of China （NSFC 40371087, 40701119）, the Major State Basic Research Development Program of China （973 Program） （No. 2007CB714401）, the National High Technology Research and Development Program of China （863 Program） （No. 2007AA10Z201 ）.
文摘The multi-source data fusion methods are rarely involved in VNIR and thermal infrared remote sensing at present. Therefore, the potential advantages of the two kinds of data have not yet been adequately tapped, which results in low calculation precision of parameters related with land surface temperature. A new fusion method is put forward where the characteristics of the high spatial resolution of VNIR （visible and near infrared） data and the high temporal resolution of thermal infrared data are fully explored in this paper. Non-linear fusion is implemented to obtain the land surface temperature in high spatial resolution and the high temporal resolution between the land surface parameters estimated from VNIR data and the thermal infrared data by means of GA-SOFM （genetic algorithms ＆ self-organizing feature maps）-ANN （artificial neural net-work）. Finally, the method is verified by ASTER satellite data. The result shows that the method is simple and convenient and can rapidly capture land surface temperature distribution of higher resolution with high precision.
