IAPRS & SIS, Vol.34, Part 7, “Resource and Environmental Monitoring”, Hyderabad, India,2002 
  
rain. As discussed in section 3, we have restricted retrieval of 
IWV and OWS, and SST up to 15 and 10 mg cm? of CLW, 
respectively. For comparison have also plotted all these GPs from 
SSM/T (except SST from SSM/I) and MSMR-operational data 
sets. In figure 1, plot of CLW from MSMR empirical algorithm 
(upper panel) from SSM/I (middle panel and MSMR- 
Operational (lower panel) algorithm is shown. 
MSMR - Integrated Water Vopor cmas2 
i. 2 que 1999 G/ 
  
SSM/I - integrated Water Vapor (g/emes2) 
:2 August 1999 
  
MSMR (Operationol) - latagraled, Water Vopor (g/cmes2) 
1-2 August 1999 
      
05 1 15 2:25 3 4 45 5 5280 6 55 
Fig.2: Global distribution of averaged IWV from MSMR 
empirical algorithm (upper panel), SSM/I (middle panel) and 
MSMR-operational algorithm (lower panel) for 1-2 Aug. 1999. 
Figure 1, shows a good comparison of SSM/I derived CLW with 
that derived using empirical algorithm. CLW from MSMR- 
operational algorithm shows a poor agreement with SSM/I 
derived CLW. Values in CLW derived using our algorithm are 
relatively underestimated as compared to SSM/I. A possible 
reason could be due to different orbital characteristics of two 
different satellites carrying these sensors. The F13 SSM/I is used 
in this study has equator crossing time (ascending at Local Solar 
Time of 17:54) closed to the peak of the known diurnal cycle of 
the cloudiness in the tropics. 
Figure 2 shows 2-day averaged IWV from MSMR empirical 
algorithm (upper panel) SSM/I (middle panel) and MSMR- 
operational algorithm (lower panel) All three are in good 
agreement. MSMR empirical algorithm very well presents all 
major features of global IWV distribution. However, As 
compared to SSM/I, the IWV from our algorithm appears to be 
marginally underestimated. 
Figure 3 shows, 2-day averaged OWS from MSMR empirical 
algorithm (upper panel) SSM/I (middle panel) and MSMR- 
operational algorithm (lower panel). All features of global winds 
are very well picked up by MSMR empirically derived OWS 
shown in the upper panel. Though there is a good qualitative 
agreement of MSMR wind speed from our algorithm with that 
from SSM/I, the OWS values from empirical algorithm are 
underestimated as compared to SSM/I, and MSMR-operational 
OWS. 
MSMR - Ocean Wind Speed (m/s) 
1-2 August 199 
    
  
SEMA ~ Qceon Wind Speed {m/s 
i= 22 id LZl e 
  
  
3 4 5 8 7 8 9 0° 11 12 
MSMR e à mg "eis Speed (m/s) 
hugus 
  
Fig.3: Global distribution of averaged OWS from MSMR 
empirical algorithm (upper panel), SSM/I (middle panel) and 
MSMR-operational algorithm (lower panel) for 1-2 Aug. 1999. 
MSWR - Seo Surface Tomparoture (Kk) 
1-2 Aet 1999 
  
  
NSMR (Operational) - Seo Surface Temperature (K) 
x na 1899 
  
14 186 18 20 22 74 20 "2 WR 
Fig.4: Global distribution of averaged SST from MSMR 
empirical algorithm (upper panel) and MSMR-operational 
algorithm (lower panel) for 1-2 Aug. 1999. 
Figure 4 shows the SST values averaged for 1-2 August 1999 
from MSMR using empirical algorithm (upper panel) and from 
    
   
   
   
   
   
   
   
  
   
    
  
    
    
     
   
   
    
  
   
  
  
  
  
  
     
    
  
  
  
   
   
    
    
    
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