Terrestrial snow cover has largest geographic extent in the northern hemisphere. Melting snow supplies most of
California’swater supply. Recent analyses of long-term surface observations show a good relationship between the
snow depth and AMSR-E (Advanced Microwave Scanning Radiometer - Earth Observing System) swath brightness
temperature. In this work, we employ one snow season (AMSR-E) dataset and the retrieved snow cover area (SCA) to
analyze the snow microwave emission and gradient algorithm ability. The time series analysis shows that the
relationship between SCA and the SWE. The result show that when the ground was covered with a light fall of snow,
the SCA increase immediately and the bright temperature is well indicate the snow exist. When the snow become
deeper, the SCA reach the maximum and bright temperature become not sensitivity. All the date show that the SCA
and ground observation is consistent in the whole snow season, but when the snow is more than 0.5m or snow is begin
to melt, the bright temperature have less useful information.
The Chinese HY-2, a satellite designed for ocean dynamic environment monitoring, was launched on August 16, 2011. The onboard scanning microwave radiometer (RM) is primarily designed for sea surface temperature and wind speed mapping. However, our objective of this investigation is to exploit the large amount of land observations of RM and to extend the mission scope to the retrieval of surface soil moisture, which is also an essential boundary condition for coupling with atmospheric dynamics. The single-channel algorithm (SCA) was implemented using only the RM observed brightness temperature to estimate the surface soil moisture. Ancillary data of a normalized difference vegetation index were processed and used as inputs for the SCA to calculate the vegetation water content, which is a required parameter for estimating the vegetation optical depth. The retrieved soil moisture results agree with the global climate pattern of wet and dry regions. Initial assessments were performed using soil moisture measurements by in situ underground sensors over two selected networks: REMEDHUS in Spain and CTP-SMTMN network over the Tibetan Plateau. Results showed a good performance of soil moisture estimation for these land surface conditions for the year 2012, with the lowest root mean square error of 0.047 m3/m3. This product will contribute to continuous soil moisture information on a global scale for global change studies.