derived OWS 
ood qualitative 
rithm with that 
algorithm are 
MR-operational 
  
  
  
om MSMR 
le panel) and 
-2 Aug. 1999. 
  
  
m MSMR 
operational 
99, 
) August 1999 
inel) and from 
IAPRS & SIS, Vol.34, Part 7, “Resource and Environmental Monitoring", Hyderabad, India,2002 
  
MSMR-operational algorithm (lower panel). SSM/I is not able to 
provide SST. There is a good comparison of SST using empirical 
and operational algorithms. All features of global SST as depicted 
by 2-days averaged map from MSMR operational algorithm are 
very well picked up by SST map for the same period using 
empirical algorithm. Despite of closeness of two SSTs, it may be 
noted that SST operational algorithm requires 6.6 GHz and the 
other higher frequency channels, and hence provides SST only at 
150 km resolution grid, whereas, empirical algorithm developed 
by us do not use 6 GHz channels and hence can be retrieved at 75 
km resolution grid. 
MSMR - Cloud Liquid Water {mg /cmese2 
September sega s 
     
SSMA - Claud Liquid Wotes (mg/emee2) 
September 1999 
  
MSWR (Operational) - Cloud Liquid Woler (mqg/crmee2) 
Il 1999 v/ 
     
  
   
a + 10 1h 20 2) 30 35 40 45 50 
   
Fig 5: Global distribution of averaged CLW from MSMR 
empirical algorithm (upper panel), SSM/I (middle panel) and 
MSMR-operational algorithm (lower panel) for Sept. 1999. 
Further, we have compared monthly averaged fields of CLW, 
IWV, OWS and SST from MSMR empirical algorithm with those 
from SSM/I and MSMR operational algorithms. Figure 5-8 shows 
the monthly fields for September 1999 for all GPs. In these 
figures the monthly GPs derived from MSMR empirical 
algorithm are shown in the upper panel, from SSM/I are shown in 
the middle panel and from MSMR operational algorithm are 
shown in the lowest panel. The SSM/I does not provide SST and 
hence it is not shown in figure 8. 
Figure 5 gives rise to the conclusions similar to that drawn with 2- 
days averaged CLW maps (fig. 1). The CLW from empirical 
algorithm is much closer to CLW from SSM/I than that from 
MSMR-operational product. Some underestimation by our 
algorithm is possibly due to the reason stated earlier. 
The figure 6 is showing a good match of IWV for September 
1999 in all three panels. This was expected as the 2-days fields as 
shown in figure 2 were also in good agreement. There appears to 
be some underestimation by our empirical algorithm but that is 
not very significant. 
Figure 7 shows the monthly map of OWS from MSMR using 
empirical algorithm, SSM/I, and MSMR operational algorithm. 
The OWS from MSMR empirical algorithm very well brings out 
the wind speed gradients and the global wind patterns, 
quantitative values seem to be underestimated. 
MSMR - Integrated Water Vopor (g/cmes2) 
September 1999 
D 
   
   
  
  
  
SSM/I - Integrated Water Vapor emes2 
/ me 1999 (a/ : 
T 
  
b BüE ^3 180 1200 Wow 39 
MSMR (Operauonol) - Integroled Woter Vopor {g/cmes2 
September 1999 ) 
     
       
9.5 15 2 25 3 4 45 S 553 6 65 
  
Fig.6: Global distribution of averaged IWV from MSMR 
empirical algorithm (upper panel), SSM/I (middle panel) and 
MSMR-operational algorithm (lower panel) for Sept. 1999. 
MSMR - Qcean Wind Speed (m/s 
Septemebr 1999 ) 
  
  
  
  
  
SSM/l - Qceon Wind Speed (m/s 
Septemebr 1999 {m/s} 
  
    
3 4 5 5 7 8 9 10 11 12 
MSMR (Operational) - Oceon Wind Speed (m/s 
{ a ce 1999 (m/s)