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
MSM
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