Advances in Earth Science ›› 2004, Vol. 19 ›› Issue (2): 204-210. doi: 10.11867/j.issn.1001-8166.2004.02.0204

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THE DEVELOPMENT AND PROSPECT OF ESTIMATING SNOW WATER EQUIVALENT USING PASSIVE MICROWAVE REMOTE SENSING DATA

CHE Tao, LI Xin   

  1. Cold and Arid Regions Environmental and Engineering Research Institute, CAS, Lanzhou 730000, China
  • Received:2003-02-09 Revised:2003-08-04 Online:2004-12-20 Published:2004-04-01

CHE Tao, LI Xin. THE DEVELOPMENT AND PROSPECT OF ESTIMATING SNOW WATER EQUIVALENT USING PASSIVE MICROWAVE REMOTE SENSING DATA[J]. Advances in Earth Science, 2004, 19(2): 204-210.

Snow water equivalent (SWE) is an important factor in the variable study of snow storage. However, the only adequately way to estimate the spatial coverage and temporal changes of snow cover in a regional scale is via remote sensing. Passive microwave data, as a complement for visible remote sensing data, despite of its coarse resolution, have the capability to penetrate clouds and snow cover and to provide dual polarization information at different frequencies. In fact, passive microwave remote sensing has played a key role in cryosphere research field in past three decades. This paper reviews the researches of monitoring snow using passive microwave remote sensing data at home and abroad. The applicability of existing algorithms (and models) to estimate snow water equivalent is assessed. Then, the retrieval of SWE in the QinghaiTibetan plateau is discussed in detail, to illustrate the complexity of the estimating SWE using SSM/I data in the special region, and to clarify the reasons that lead to the complexity. Finally, a series of methods and solutions are offered, which provide the theory basis for the further dynamic monitoring on snow in the QinghaiTibetan plateau regions. For improving the retrieval accuracy, several aspects should be taken into account, such as detecting wet snow and dry snow, distinguishing the snow cover and frozen soil in the SSM/I subpixel, and comparison of retrieval results and observation data.

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