Impact of MSMR data on NCMRWF global data assimilation system

Abstract

It is very essential to make use of non-conventional remotely sensed data mainly from various satellites for numerical weather prediction. IRS series of Indian satellites have been found very useful for various types of studies. Recently IRS-P4 was successfully launched and its Multi-frequency Scanning Microwave Radiometer (MSMR) sensor is giving near surface wind speed and total precipitable water content over oceanic region. An attempt has been made to assimilate directly these two geophysical parameters derived at 150 km resolution, along with other global meteorological data, in the National Center for Medium Range Weather Forecasting (NCMRWF), New Delhi Global Data Assimilation System. (GDAS). The paper describes the development work done in utilizing the surface wind speed and the total precipitable water content data in the NCMRWF operational GDAS. The basic algorithms for assimilating the MSMR data directly in the global analysis scheme have been described. The analyzed fields produced after running the six hourly GDAS cycle have been examined and various aspects of the impact of this data set on the global analysis especially for Indian oceanic region have been evaluated. Other aspects like, penalty contributions, root mean square (rms) errors of various types of data both with respect to the analysis and the background field, etc. have been examined. The impact of additional IRS-P4 data on assimilation and model simulation is found to be positive and beneficial.