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Fang Y.,Beijing Climate Center | Zhang Y.,Nanjing University | Huang A.,Nanjing University | Li B.,Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites
Advances in Atmospheric Sciences | Year: 2013

The performance of a regional air-sea coupled model, comprising the Regional Integrated Environment Model System (RIEMS) and the Princeton Ocean Model (POM), in simulating the seasonal and intraseasonal variations of East Asian summer monsoon (EASM) rainfall was investigated. Through comparisons of the model results among the coupled model, the uncoupled RIEMS, and observations, the impact of air-sea coupling on simulating the EASM was also evaluated. Results showed that the regional air-sea coupled climate model performed better in simulating the spatial pattern of the precipitation climatology and produced more realistic variations of the EASM rainfall in terms of its amplitude and principal EOF modes. The coupled model also showed greater skill than the uncoupled RIEMS in reproducing the principal features of climatological intraseasonal oscillation (CISO) of EASM rainfall, including its dominant period, intensity, and northward propagation. Further analysis indicated that the improvements in the simulation of the EASM rainfall climatology and its seasonal variation in the coupled model were due to better simulation of the western North Pacific Subtropical High, while the improvements of CISO simulation were owing to the realistic phase relationship between the intraseasonal convection and the underlying SST resulting from the air-sea coupling. © 2013 Chinese National Committee for International Association of Meteorology and Atmospheric Sciences, Institute of Atmospheric Physics, Science Press and Springer-Verlag Berlin Heidelberg. Source

Hou P.,Satellite Environment Center | Hou P.,Beijing Normal University | Chen Y.,Beijing Normal University | Qiao W.,Satellite Environment Center | And 3 more authors.
Theoretical and Applied Climatology | Year: 2013

Near-surface air temperature (NSAT) directly reflects the thermal conditions above the ground and has been considered as a relevant indicator of resident health in urban regions. The rapid retrieval of NSAT data is necessary to assess urban environments. In this paper, a method of NSAT retrieval is developed that employs Landsat Thematic Mapper images using an Energy Balance Bowen Ratio model. This model is established based on the energy balance over land and the Bowen ratio. The degree of retrieval error obtained when using this model is determined on the basis of a comparison with the observed values obtained from weather stations; the mean error is approximately 2. 21 °C. Moreover, the spatial relationship between NSAT and urban wetlands is analyzed using Geographical Information System technology. The results show that wetlands have an obvious influence on atmospheric temperature and that this influence decreases as the distance from the wetland increases. When that distance is less than 300 m, its influence on the NSAT is significant. © 2012 Springer-Verlag. Source

Zhang X.,Nanjing University of Information Science and Technology | Guo Y.,Nanjing University of Information Science and Technology | Yang C.,Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites
Journal of Computational Information Systems | Year: 2013

In order to study the effect of clouds on meteorological satellite communications under cloudy conditions, the shadowing effect and multipath effect of the clouds on meteorological satellite signal are as a static composite channel effect, the probability density function and bit error rate function of the static composite channel are given. Meteorological satellite composite channel simulation model is established, the fading of the reception signal in the composite channel is divided into three cases of mild fading, moderate fading and severe fading. The results of computer experiments indicate that the probability density curves and bit error rate curves function of the received signal in the simulation model are quite consistent with the theory model, and demonstrate it is an accurate and efficient method. © 2013 by Binary Information Press. Source

Hou P.,Satellite Environment Center | Hou P.,Beijing Normal University | Jiang W.,Beijing Normal University | Cao G.,Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites | Li J.,Beijing Normal University
International Journal of Remote Sensing | Year: 2012

Human activity is one of the most important aerosol sources. Because the underlaying surface feature records most human activities, it is important to recognize the correlation between aerosol distribution and the underlaying surface. In this research, the dark object algorithm and a second-generation operational algorithm of Moderate-Resolution Imaging Spectroradiometer (MODIS) aerosol retrieval are used to estimate aerosol optical depth from Enhanced Thematic Mapper Plus (ETM+) images acquired by the Landsat 7 satellite system in urban regions, and the correlations between aerosol distribution and urban underlaying surface features (including landform, land cover and urbanization level) is analysed. Results show that (1) it is feasible to apply a second-generation algorithm to retrieve aerosol optical depth with ETM+ images. When a validation is performed with the ground observation meteorological range converted into aerosol optical depth with the correlation model acquired by a Moderate-Resolution Atmospheric Transmission (MODTRAN) simulation, the retrieval error is about 0.0094. For higher spatial resolution of an ETM+ image, it is better to study the aerosol distribution features in the urban regions. Additionally, (2) there are obvious variations in spatial distribution of aerosol over the different features of the underlaying surface. For the landform, aerosol optical depth is mountain < hill > plain; for the land cover, aerosol optical depth is dense vegetation < sparse vegetation < water < bare soil > residential area; for the different urbanization-level regions, there is bigger and bigger aerosol optical depth with increasing of the urbanization level. On the whole, as human activities increase, so too does the aerosol optical depth. © 2012 Taylor and Francis Group, LLC. Source

Hou P.,Satellite Environment Application Center | Wang Q.,Satellite Environment Application Center | Cao G.,Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites | Wang C.,Satellite Environment Application Center | And 2 more authors.
Journal of Geographical Sciences | Year: 2012

Terrestrial ecosystem and climate system are closely related to each other. Faced with the unavoidable global climate change, it is important to investigate terrestrial ecosystem responding to climate change. In inland river basin of arid and semi-arid regions in China, sensitivity difference of vegetation responding to climate change from 1998 to 2007 was analyzed in this paper. (1) Differences in the global spatio-temporal distribution of vegetation and climate are obvious. The vegetation change shows a slight degradation in this whole region. Degradation is more obvious in densely vegetated areas. Temperature shows a general downward trend with a linear trend coefficient of -1.1467. Conversely, precipitation shows an increasing trend with a linear trend coefficient of 0. 3896. (2) About the central tendency response, there are similar features in spatial distribution of both NDVI responding to precipitation (NDVI-P) and NDVI responding to AI (NDVI-AI), which are contrary to that of NDVI responding to air temperature (NDVI-T). Typical sensitivity region of NDVI-P and NDVI-AI mainly covers the northern temperate arid steppe and the northern temperate desert steppe. NDVI-T typical sensitivity region mainly covers the northern temperate desert steppe. (3) Regarding the fluctuation amplitude response, NDVI-T is dominated by the lower sensitivity, typical regions of the warm temperate shrubby, selui-shrubby, bare extreme dry desert, and northern temperate meadow steppe in the east and temperate semi-shrubby, dwarf arboreous desert in the north are high response. (4) Fluctuation amplitude responses between NDVI-P and NDVI-AI present a similar spatial distribution. The typical sensitivity region mainly covers the northern temperate desert steppe. There are various linear change trend responses of NDVI-T, NDVI-P and NDVI-AI. As to the NDVI-T and NDVI-AI, which are influenced by the boundary effect of semi-arid and semi-humid climate zones, there is less correlation of their linear change tendency along the border. There is stronger correlation in other regions, especially in the NDVI-T in the northern temperate desert steppe and NDVI-AI in the warm temperate shrubby, selui-shrubby, bare, extreme and dry desert. © 2012 Science China Press and Springer-Verlag Berlin Heidelberg. Source

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