International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B3 
  
  
  
   
   
   
  
  
  
   
   
  
   
  
    
   
forest factor F and time- and space-varying c in (2) is 
to correct the systematic errors in (1) so that only 
  
random errors remain. 
  
  
  
Figure 4: Difference maps between the new and old SSM/I SWE algorithms for October 1990 through May 1991. 
3.3 Comparisons between the new and old 
algorithm for SWE retrieval 
Figure 4 shows maps of monthly biases, i.e., 
difference between SWE estimate from the new (2) 
and old algorithm (1). Shades of blue indicate that the 
new algorithm is estimating less snow than the 
original global snow algorithm, while shades of red 
indicate that the new algorithm is estimating more. 
The pale blue and sage colors in Figure 6 indicate 
areas where there is little difference in SWE estimates 
by the two algorithms. Because snow crystals are 
typically larger in tundra regions than in forested 
regions, snow thickness and SWE were overestimated 
using the original algorithm. Snow was under- 
estimated using (1) in forested areas because the 
microwave emission from the trees was overwhelming 
scattering from the underlying snowpack. The most 
noticeable negative values are found in the northern 
portion of the Mackenzie River basin and on the north 
slope of Alaska. With the inclusion of a forest factor in 
. Istanbul 2004 
   
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