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Hu W.,University of Saskatchewan | Hu W.,CAS Beijing Institute of Geographic Sciences and Nature Resources Research | Shao M.A.,CAS Beijing Institute of Geographic Sciences and Nature Resources Research | Hou M.T.,China Meteorological Administration Training Center | And 2 more authors.
Journal of Hydrology

Quick and accurate estimates of spatial mean volumetric soil water content (θ) are essential for validating remotely-sensed soil water content and water budget analyses. The objective of this study was to test and validate a methodology that utilizes measured θ from the Most Time Stable Locations (MTSLs) to estimate mean θ in an adjacent or distant area while negating the impact of variability in soil, vegetation and topographic properties. Soil water content measured by a neutron probe at depths of 0.1, 0.2, 0.4, 0.6 and 0.8. m in Laoyemanqu watershed on the Chinese Loess Plateau was used to test our methodology. This method predicts mean θ of one area with measured θ at the MTSL from another area. Estimation errors depend on size of the study areas, number of measurement times in the target area and soil depth. A more accurate estimation of mean θ was found when using larger areas and deeper soils. Our method was also validated by predicting mean θ of a larger watershed (Liudaogou watershed) using the θ measurement at the MTSL at Laoyemanqu watershed. The proposed method has great potential for soil water upscaling with socio-economic, environmental and geo-political values. © 2013 Elsevier B.V. Source

Yang P.,China Meteorological Administration Training Center | Ren G.,National Climate Center | Liu W.,Institute of Urban Meteorology
Journal of Applied Meteorology and Climatology

An hourly dataset of automatic weather stations over Beijing Municipality in China is developed and is employed to analyze the spatial and temporal characteristics of urban heat island intensity (UHII) over the built-up areas.Atotal of 56 stations that are located in the built-up areas [inside the 6th Ring Road (RR)] are considered to be urban sites, and 8 stations in the suburban belts surrounding the built-up areas are taken as reference sites. The reference stations are selected by using a remote sensing method. The urban sites are further divided into three areas on the basis of the city RRs. It is found that the largest UHII generally takes place inside the 4th RR and that the smallest ones occur in the outer belts of the built-up areas, between the 5th RR and the 6th RR, with the areas near the northern and southern 6th RR experiencing the weakest UHI phenomena. On a seasonal basis, the strongest UHII generally occurs in winter and weak UHII is dominantly observed in summer and spring. The UHII diurnal variations for each of the urban areas are characterized by a steadily strong UHII stage from 2100 local solar time (LST) to 0600 LST and a steadily weak UHII stage from 1100 to 1600 LST, with the periods 0600-1100 LST and 1600-2100 LST experiencing a swift decline and rise, respectively. UHII diurnal variation is seen throughout the year, but the steadily strong UHII stage at night is longer (shorter) and the steadily weak UHII stage during the day is shorter (longer) during winter and autumn (summer and spring). © 2013 American Meteorological Society. Source

Zhao J.,China Meteorological Administration Training Center | Zou X.,Florida State University | Zou X.,Nanjing University of Information Science and Technology | Weng F.,National Oceanic and Atmospheric Administration
IEEE Transactions on Geoscience and Remote Sensing

A detection of radio-frequency interference (RFI) in the space-borne microwave radiometer data is difficult under snow and sea ice-covered conditions. The existing methods such as a spectral difference technique or a principal component analysis (PCA) of RFI indices produce many false RFI signals near the boundary of Greenland and Antarctic ice sheets. In this paper, a double PCA (DPCA) method is developed for RFI detection over Greenland and Antarctic regions. It is shown that the new DPCA method is effective in detecting RFI signals in the C- and X-band radiometer channels of WindSat while removing the false RFI signals over Greenland and Antarctic. It also worked well in other snow-free or snow-rich regions such as winter data over the United States. The proposed DPCA can be applied to satellite radiometer data orbit-by-orbit or granule-by-granule and is thus applicable in an operational environment for fast processing and data dissemination. © 1980-2012 IEEE. Source

Zou X.,Florida State University | Zhao J.,China Meteorological Administration Training Center | Weng F.,National Oceanic and Atmospheric Administration | Qin Z.,Florida State University | Qin Z.,Nanjing University of Information Science and Technology
IEEE Transactions on Geoscience and Remote Sensing

The MicroWave Radiation Imager (MWRI) onboard the FengYun (FY)-3B satellite has five frequencies at 10.65, 18.7, 23.8, 36.5, and 89.0 GHz, each having dual channels at vertical and horizontal polarization states, respectively. It is found that radio-frequency interference (RFI) is present in MWRI data over land. The RFI signals are, in general, detectable from a spectral difference method and a principal component analysis (PCA) method. In particular, the PCA method is applied to derive RFI signals from natural radiations by using the characteristics of natural radiation measurements having all-channel correlations. In the area where data have a higher projection onto the first principle component (PC) mode, RFI is, in general, present. However, both the spectral and PCA methods cannot detect RFI reliably over frozen grounds and scattering surfaces, where the brightness temperature difference between 10.65 and 18.7 GHz is large. Thus, detection is improved through the use of normalized PCA. The new RFI detection algorithm is now working reliably for MWRI applications. It is found that RFI at 10.65 GHz distributes widely over Europe and Japan, and is less popular over the United States and China. © 2012 IEEE. Source

Hu Y.,CAS Institute of Atmospheric Physics | Hu Y.,China Meteorological Administration Training Center | Dong W.,Beijing Normal University | He Y.,National Climate Center
Journal of Geophysical Research: Atmospheres

The "observation minus reanalysis" (OMR) method is used to estimate the impact of land surface forcings on surface temperature by computing the difference of trends between the observations and reanalysis data set. The basis of this method is that if observed surface temperature, moisture, and wind over land are not used in reanalysis, the reanalysis data set should not be sensitive to urbanization and other land use change. In this study, the OMR method is used to estimate the impacts of land surface change on surface temperature trends during the period from 1979 to 2008 in eastern China, and the difference time series of extreme temperature indices between the observations and the reanalysis data sets is also analyzed. The OMR trends of annual cold (warm) nights exhibit generally decrease (increase), it means that land surface change is likely to enhance the decreasing (increasing) trends of annual cold (warm) nights. The decreasing (increasing) OMR trends of annual cold (warm) days is found in semiarid region in northern China, while the increasing (decreasing) of cold (warm) days occurs in eastern agricultural area. For eastern China as a whole, the land surface change impact may explain about one third of the observed increase for the annual warm nights and nearly half of the observed decrease for the annual cold nights, and the impacts on the annual cold days and warm days are relatively small. The land surface change may reduce the diurnal temperature range significantly. The impact of land surface forcings on extreme temperature demonstrates obviously annual variation. Copyright © 2010 by the American Geophysical Union. Source

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