HR: 0800h
AN: H21B-0511    [Abstracts]
TI: New Multi-Day Snow Cover Products From Combination Of Terra And Aqua MODIS Daily Snow Cover Data
AU: * wang, x
EM: xianwei.wang@utsa.edu
AU: xie, h
EM: hongjie.xie@utsa.edu
AB: This study develops an algorithm and automated scripts to produce multi-day Terra or Aqua, and Terra-Aqua snow cover image composites, with flexible starting and ending dates and a user-defined cloud cover threshold. Taking the northern Xinjiang, China and the 2003-2004 hydrologic year as an example, and using a cloud cover of 10% as a user-defined threshold, the algorithm generated 152 multi-day Terra-Aqua composite images in the test area, an average of 2.4 days (composite period) per image. Compared with the annual mean snow cover ~30% from standard MODIS 8-day Terra or Aqua composite product (only 47 images per year), the new multi-day Terra-Aqua composite product gives a mean snow cover of 18.7%, while both having similar percentage of annual mean cloud cover (~5%) and similar snow classification accuracy (~94%). In addition, some lake ices were misclassified as snow in the standard 8-day Terra or Aqua composite images. This suggests that the standard algorithm for producing 8-day composite products for the study area may have some limitations. Further investigations for other regions are needed. In any case, the new multi-day composite algorithm, however, correctly combine the daily images into composite images. Therefore, those new composite products generated from our algorithm and scripts are a significant contribution to the current MODIS snow cover product series and future NPOESS snow cover products.
DE: 1835 Hydrogeophysics
SC: Hydrology [H]
MN: 2007 Fall Meeting