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Oceansat-1 was successfully launched by India in 1999, with two payloads, namely Multi-frequency Scanning Microwave Radiometer (MSMR) and Ocean Color Monitor (OCM) to study the biological and physical parameters of the ocean. The MSMR sensor is configured as an eight-channel radiometer using four frequencies with dual polarization. The MSMR data at 75 km resolution from the Oceansat-I have been assimilated in the National Centre for Medium Range Weather Forecasting (NCMRWF) data assimilation forecast system. The operational analysis and forecast system at NCMRWF is based on a T80L18 global spectral model and Spectral Statistical Interpolation (SSI) scheme for data analysis. The impact of the MSMR data is seen globally, however it is significant over the oceanic region where conventional data are rare. The dry-nature of the control analyses have been removed by utilizing the MSMR data. Therefore, the total precipitable water data from MSMR has been identified as a very crucial parameter in this study. The impact of surface wind speed from MSMR is to increase easterlies over the tropical Indian Ocean. Shifting of the positions of westerly troughs and ridges in the south Indian Ocean has contributed to reduction of temperature to around 30 • S.

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Assimilation of IRS-P4 (MSMR) meteorological data in the NCMRWF global data assimilation system

Kamineni

Rizvi

Kar

et al. 2002

J Earth Syst Sci

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Impact of Oceansat-I MSMR data on analyzed oceanic winds and wave predictions

et al. 2004

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Impact of high resolution water vapor cross‐sectional data on hurricane forecasting

Kamineni

Krishnamurti

Ferrare

et al. 2003

Geophysical Research Letters

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This paper addresses the impact of moisture profile data sets derived from the Lidar Atmospheric Sensing Experiment (LASE) for the assimilation and forecasts of hurricanes. LASE is a vertical profiler for moisture measurements that was developed at NASA Langley Research Center. LASE was deployed on board the NASA DC‐8 research aircraft and provided vertical profiles of moisture in a hurricane environment during the Convection and Moisture Experiment‐4, which occurred in August and September 2001. In this preliminary study we show results from two types of experiments (with and without LASE data) that show improvements in track and intensity forecasts of hurricanes, Erin, Humberto and Gabrielle. When the LASE moisture profiles are assimilated, track errors are reduced by 100 km and intensity errors are reduced by 20–25% for 3 day forecasts.

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Cited by 4 publications

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Assimilation of IRS-P4 (MSMR) meteorological data in the NCMRWF global data assimilation system

Assimilation of IRS-P4 (MSMR) meteorological data in the NCMRWF global data assimilation system

Impact of Oceansat-I MSMR data on analyzed oceanic winds and wave predictions

Impact of high resolution water vapor cross‐sectional data on hurricane forecasting

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