Skip to main content
Log in

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

  • Published:
Journal of Earth System Science Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Chang S W and Holt T R 1994 Impact of assimilating SSM/I rainfall rates on numerical prediction of winter cyclones;Mon. Weather Rev. 122 151–164

    Article  Google Scholar 

  • Eymard L, Bernard R and Lojou J Y 1993 Validation of microwave radiometer geophysical parameters using meteorological model analysis;Int. J. Rem. Sens. 14 1945–1963

    Article  Google Scholar 

  • Goswami B N and Rajagopal E N 2002 Comparison of NCMRWF surface winds over the Indian Ocean within situ observations and quick-scat winds. (Manuscript under preparation)

  • Kanamitsu M 1989 Description of the NMC global data assimilation and forecast system;Weather Forecasting 4 335–342

    Article  Google Scholar 

  • Ledvina D V and Pfaendtner J 1995 Inclusion of special sensor microwave/ imager (SSM/I total precipitable water content estimates into the GEOS-1 data assimilation system;Mon. Weather Rev. 123 3003–3015

    Article  Google Scholar 

  • Lorenc A C 1986 Analysis methods for numerical weather prediction;Quart. J. Roy. Meteor. Soc. 112 1177–1194

    Article  Google Scholar 

  • Parrish D F and Derber J C 1992 The National Meteorological Center’s spectral statistical interpolation analysis system;Mon. Weather Rev. 120 1747–1763

    Article  Google Scholar 

  • Rizvi S R H and Parrish D F 1995 Documentation of the Spectral Statistical Interpolation (SSI) Scheme;Technical Report. 1/1995, DST, NCMRWF, New Delhi, India.

    Google Scholar 

  • Rizvi S R H, Rupa K and Mohanty U C 2000 Report on the utilization of MSMR data in the NCMRWF global data assimilation system;Report no. 1/2000. NCMRWF, New Delhi.

    Google Scholar 

  • Rizvi S R H, Rupa K and Mohanty U C 2002 Impact of MSMR data on NCMRWF Global Data Assimilation System;Metero. Atmos. Phys. (accepted)

  • Schluessel P and Emery W J 1990 Atmospheric water vapour over oceans from SSM/I measurements;Int. J. Remote Sens. 11(5) 753–766

    Article  Google Scholar 

  • Schluessel P and Luthardt H 1991 Surface wind speeds over the north sea from special sensor microwave/Imager observations;J. Geophys. Res. 96 (c3) 4845–4853

    Google Scholar 

  • Varma A K, Gairola R M, Basu S, Singh K P and Pandey P C 1998 A comparative study of near concurrent DMSP-SSM/I and geosat-altimeter measurements of ocean winds over the Indian oceanic region;Int. J. Remote Sens. 19 717–730

    Article  Google Scholar 

  • Weng F, Grody N C, Ferraro R, Basisi A and Forsyth D 1997 Cloud liquid water climatology from the special sensor microwave imager;J. Climate 1086-1098

  • Xiao Q, Zou X and Kuo Y H 2000 Incorporating the SSM/I derived precipitable water and rainfall rate into a numerical model: A case study for the ERICA IOP-4 cyclone;Mon. Weather Rev. 128 87–128

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Kamineni, R., Rizvi, S.R.H., Kar, S.C. et al. Assimilation of IRS-P4 (MSMR) meteorological data in the NCMRWF global data assimilation system. J Earth Syst Sci 111, 351–364 (2002). https://doi.org/10.1007/BF02701980

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02701980

Keywords

Navigation