Publications

Wang, XW, Xie, HJ (2009). New methods for studying the spatiotemporal variation of snow cover based on combination products of MODIS Terra and Aqua. JOURNAL OF HYDROLOGY, 371(4-Jan), 192-200.

Abstract
Based on multi-day combination of Terra and Aqua MODIS snow cover products (cloud cover less than 10%), this study developed new snow cover index (SCI), snow-covered duration/days (SCD) map, snow cover onset dates (SCOD) map and snow cover melting dates (SCMD) map, one each per hydrological year, to further examine the spatiotemporal variations of snow cover. Daily in situ snow depth observations in northern Xinjiang, China from 2001 to 2005 were used to validate the new maps. Our results indicate that the SCD maps had an overall agreement of 90% with in situ observations of snow cover days at 20 stations in the study area, and the SCOD and SCMD maps also had good agreements with the in situ measurements, with a mean value of 1 week forward shift and 1 week back-ward shift, respectively, due to transient snowfall events in early fall and in late spring. The snow cover index (SCI) (km(2) day), first proposed here, contains both snow cover duration and extent for 1 hydrological year and indicates that the 2001-2002 hydrologic year had the most snow cover while the 2005-2006 had the least. While the SCD map provides the snow cover duration/days of each pixel in a hydrologic year, the SCOD and SCMD maps give specific dates when the snow cover begins and when it melts away at the pixel. Together, SCD, SCI, SCOD and SCMD can provide crucial information on spatiotemporal variation of snow cover conditions for any region of interest. This could potentially be critical information for local water agencies for planning water use and for mitigating snow-caused disaster. Long term availability of MODIS type of snow cover data for producing such datasets is key to study the connection between snow cover change and global climate change. (C) 2009 Elsevier B.V. All rights reserved.

DOI:
10.1016/j.jhydrol.2009.03.028

ISSN:
0022-1694