潘金梅等：Comparison of the multi-layer HUT snow emission model with observations of wet snowpacks

Comparison of the multi-layer HUT snow emission model with observations of wet snowpacks
作者:Pan, JM (Pan, Jinmei)[ 1,2,3,4 ] ; Jiang, LM (Jiang, Lingmei)[ 1,2,3 ] ; Zhang, LX (Zhang, Lixing)[ 1,2,3 ]
HYDROLOGICAL PROCESSES
卷: 28  期: 3  页: 1071-1083
DOI: 10.1002/hyp.9617
出版年: JAN 30 2014

摘要
Information on snow properties plays an important role in hydrological, meteorological and climatological applications. Passive microwave remote sensing is an effective method to retrieve snowpack parameters; however, the observations can be obscured if there is wet snow in the satellite footprint. To study the emission properties of wet snow and check its response to snow wetness, this paper applies the multi-layer Helsinki University of Technology (HUT) snow emission model coupled with the Advanced Integral Equation Model to simulate the low-wetness snowpack observed at Luancheng in November 2009, and the high wetness snowpack observed at Weissfluhjoch in June 1995. Input parameters are acquired by the in-situ snow pit measurements, while the snow grain size is fitted by comparing model predictions with the observed passive microwave signals at a range of observing angles. Results show that the application of a multi-layer model is capable to consider the distribution pattern of the snow wetness along the snow profile and the refrozen ice crust of the snow surface. The multi-layer HUT model is able to reproduce the wet snow emission properties, with an rms error of 4.4 K (at Luancheng) and 5.7 K (at Weissfluhjoch) at vertical polarization, and an rms error of 7.9 K (at Luancheng) and 11.4 K (at Weissfluhjoch) at horizontal polarization. Copyright (c) 2012 John Wiley & Sons, Ltd.

通讯作者地址: Jiang, LM (通讯作者)
Beijing Normal Univ, Sch Geog, Beijing 100875, Peoples R China.
地址:
[ 1 ] Beijing Normal Univ, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China
[ 2 ] Chinese Acad Sci, Inst Remote Sensing Applicat, Beijing 100875, Peoples R China
[ 3 ] Beijing Normal Univ, Sch Geog & Remote Sensing Sci, Beijing 100875, Peoples R China
[ 4 ] Ohio State Univ, Sch Earth Sci, Columbus, OH 43210 USA