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Journal of Atmospheric and Oceanic Technology

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Article Type:
Research Article

Identification of Large-Scale Atmospheric and Oceanic Features from IRS-P4 Multifrequency Scanning Microwave Radiometer: Preliminary Results

Rashmi Sharma1, K. N. Babu1, A. K. Mathur1, and M. M. Ali1
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  • 1 Oceanic Sciences Division, Meteorology and Oceanography Group, Space Applications Centre, Ahmedabad, India
Print Publication:
01 Jul 2002
DOI:
https://doi.org/10.1175/1520-0426(2002)019<1127:IOLSAA>2.0.CO;2
Page(s):
1127–1134
Restricted access

Abstract

Large-scale features of sea surface temperature, wind speed, water vapor, and cloud liquid water, derived from multifrequency scanning microwave radiometer (MSMR) on board Indian oceanographic satellite IRS-P4 could be identified during 15 June–23 August 1999. This is the period during which extensive validation was carried out. MSMR is the only sensor in orbit operating at 6.6 GHz. Average distribution of these parameters brings out large-scale atmospheric and oceanographic features. Zonal averages of these parameters were also studied to examine the consistency of MSMR data over larger spatial scales. Linear correlations between all parameters were also computed to check for the interconsistency of these parameters. The present analysis shows the potential use of MSMR products in studying the oceanographic and atmospheric phenomena.

Corresponding author address: Dr. M. M. Ali, Oceanography Group, National Remote Sensing Agency, Hyderabad 500 037, India. Email: mmali73@yahoo.com

Abstract

Large-scale features of sea surface temperature, wind speed, water vapor, and cloud liquid water, derived from multifrequency scanning microwave radiometer (MSMR) on board Indian oceanographic satellite IRS-P4 could be identified during 15 June–23 August 1999. This is the period during which extensive validation was carried out. MSMR is the only sensor in orbit operating at 6.6 GHz. Average distribution of these parameters brings out large-scale atmospheric and oceanographic features. Zonal averages of these parameters were also studied to examine the consistency of MSMR data over larger spatial scales. Linear correlations between all parameters were also computed to check for the interconsistency of these parameters. The present analysis shows the potential use of MSMR products in studying the oceanographic and atmospheric phenomena.

Corresponding author address: Dr. M. M. Ali, Oceanography Group, National Remote Sensing Agency, Hyderabad 500 037, India. Email: mmali73@yahoo.com

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