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

Abstract

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.

Optimal ship tracking on a navigation route between two ports: a hydrodynamics approach

“…The analysis scheme is mainly based on the Lorenc [15] concept of minimizing a cost function in terms of the deviation of desired analysis from the first guess field, which is taken as the 6-h forecast, and the observations, weighted by the inverse of the forecast and observation errors. The detailed methodology for computing vector winds is available in Kamineni et al [16]. The objective analysis scheme in SSI takes care of generating six-hourly wind fields from 48 h satellite wind data gaps.…”

Inner harbour wave agitation using boussinesq wave model

“…Surface winds over global oceans are critical for driving numerical sea state prediction models. Hence, use of analyzed wind fields (Lorenc, 1986;Kamineni et al, 2002) assimilating to third generation wave models is the only solution for deriving long term wave conditions. In the present study, wave conditions are based on 10 years (1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004) six hourly model hindcasts using deep water wave model WAM (WAMDI Group, 1988).…”

Application of Oceansat-1 MSMR analysed winds to marine navigation

“…The detailed methodology for computing vector winds is available in Kamineni et al (2002). The objective analysis scheme in SSI takes care of generating 6-hourly wind fields from 48 h satellite wind data gaps.…”