N-ESCAP,
lication of
getation of
Dec 2001,
. B, Rao, R
tific Note,
s Centre,
Trivedi, C
,Oza, SH,
)1, Manual
shoreline
al Note,
s Centre,
rasad, K N
monitoring
h, Western
nformation
- a review.
nitoring of
ng satellite
/89 Space
A coastal
of Canada.
status and
Mangroves-
Research
monitoring.
ical aerial
n (GIS) to
uations on
A, Aquatic
IAPRS & SIS, Vol.34. Part 7, "Resource and Environmental Monitoring". Hyderabad, India,2002
INTER-COMPARISON OF SIMULTANEOUS MSMR AND SSM/I OBSERVATIONS FOR
SEA ICE ESTIMATION OVER THE ANTARCTIC REGION
Satyendra Bhandari* , Mihir Dash and N.K. Vyas
Space Applications Centre (ISRO), Ahmedabad — 380 015, INDIA
and
Amita Khanolkar, Nilay Sharma, Niloy Khare and P.C. Pandey
National Centre for Antarctic and Ocean Research (NCAOR), Goa — 403 804, INDIA
KEY WORDS : Polar Remote Sensing, Antarctic Sea Ice, OCEANSAT - MSMR, SSM/I, Sensor Inter-Calibration
ABSTRACT
With the launch of MSMR onboard OCEANSAT-1 in the polar sun-synchronous orbit, India developed the capability to
comprehensively monitor the sea ice on a regular basis, with a repetivity of two days. In view of our direct interest, we have utilised
MSMR data to observe and analyse, on apriority basis, the sea ice conditions over the Antarctic and Southern Polar Ocean region
over the last few years. MSMR data have been shown to clearly delineate the presence of sea ice, and bring out its seasonal and
long term variability in a highly consistent manner.
In this paper, we attempt an indirect validation of the brightness temperatures (Tb) observed by MSMR with near- simultaneous
measurements from SSM/I onboard DMSP series of satellites over the Antarctic and Southern Polar Ocean regions. for the present
analysis, simultaneous MSMR and SSM/I data from two contrasting seasons — summer and winter, for the 1999-2000 period have
been chosen. Analysis includes a comparison of T scatterograms to achieve confidence in the quantitative use of the T, data to
derive various geophysical parameters e.g. sea ice extent and concentration. Additionally, the Ty images produced by the two sensors
are compared to establish the capability of MSMR in reliable two -dimensional portrayal of all the sea and land ice features over the
Antarctic Region. Based on a regression analysis between MSMR observed Tbs and the SSM/I derived sea ice concentration (SIC)
values, we have developed algorithms to estimate SIC over the Southern Polar Ocean. These MSMR algorithms allow estimation of
SIC with better than 10 96 rms error. The analysis brings out the very high level of compatibility in the measurements produced by
the two sensors. The quantitative inter-comparison with the near-operational sea ice analyses from SSM/I paves thé way for
continuous and reliable monitoring of polar ice with MSMR.
*Corresponding Author: Dr. Satyendra Bhandari, Scientist — Remote Sensing, Email: space. scientist(g)rediffmail.com
1.0 INTRODUCTION
Polar regions play an important role in shaping and
influencing Earth's climate. A vast area of several millions of
square kilometers of polar oceans is perennially covered by
sea ice. The seasonally expanding and contracting extent of
sea ice profoundly impedes the ocean-atmosphere heat
exchange because sea ice is highly insulative. The presence of
sea ice also enhances the planetary albedo. Further, the salt
expulsion during formation of sea ice leads to bottom water
formation that is believed to be one of the two main sources of
global oceanic thermohaline circulation. The climate system
potentially involves many sea-ice climate feedbacks that are
extremely complex and difficult to understand (King and
Turner, 1997). This calls for detailed long term measurements
of different characteristics of sea ice.
Due to the all-weather and all-season synoptic coverage
capability, space based passive microwave radiometers
(PMRs) have played a vital and pioneering role in the study of
mapping and monitoring of ice and sea ice conditions both in
the Arctic and the Antarctic regions. In the microwave band
(1-100 GHz) distinct thermal and structural properties of sa
ice and open ocean water allow a clear delineation through the
strong emissivity contrast. Sea ice typically has an emissivity
of about 0.9 as compared to emissivity of ocean water of
about 0.4 (Ulaby et al., 1982, Massom, 1991). Exploiting this,
passive microwave sensors have been used more or less
continuously over the last 30 years to map and study sea ice
409
characteristics and sea ice variability on time scales ranging
from weekly to monthly to seasonal and inter-annual scales.
These studies have been based on almost continuous
monitoring of sea ice using PMR measurements from
Nimbus-5 ESMR, Nimbus-7 SSMR and DMSP SSM/
(Gloersen et al., 1992, Parkinson et al., 1999, Zwally, 1984).
Numerous investigations have been undertaken to
understand the observed short-term and long-term regional
and hemispheric changes in sea ice characteristics in
relation to climate and climate change (Parkinson et al.,
1999, Hanna and Bamber, 2001).
India launched its PMR, for the first time in a polar orbit, on
May 26, 1999. The Multifrequency Scanning Microwave
Radiometer (MSMR) onboard this satellite, named
OCEANSAT-1, has provided continuous polar coverage
every two days for a period of about three years. We have
used the MSMR measurements to study the spatial
distributions and seasonal variability of sea ice
characteristics over the Southern Ocean region surrounding
Antarctica. MSMR observed sea ice extent estimates were
used to analyse the long term secular trend of sea ice extent
over the southern ocean region (Dash et al, 2001).
Interesting results on the increasing — rather than
decreasing, sea ice extent over the last 25 years, as well as
the possibility of recent acceleration in this increasing rate,
were derived (Dash et al., 2001, Bhandari et al., 2002, Vyas
et al. 2002). In contrast, sea ice extent over the Arctic region
is known to be decreasing over the last two decades