The comparative impact of the assimilation of SSM/I and TMI brightness temperatures in the ECMWF 4D‐Var system

This paper studies the impact of assimilating TRMM (Tropical Rainfall Measuring Mission) Microwave Imager (TMI) brightness temperatures in the European Centre for Medium-Range Weather Forecasts fourdimensional variational assimilation system (4D-Var). The methodology is similar to the one developed operationally for Special Sensor Microwave/Imager (SSM/I) radiometers. First, a one-dimensional variational (1D-Var) approach is used to retrieve specific-humidity profiles, sea-surface wind speed and cloud liquid-water path. Then, the first two quantities are assimilated in the 4D-Var analysis system. Results show an improvement of 1D-Var product accuracy when using TMI instead of SSM/I brightness temperatures. This is related to the characteristics of the TMI radiometer which allow a better estimate of surface parameters and of water vapour in tropical conditions. Consequently, 4D-Var analyses of the total column water vapour are improved using TMI data. The experiment with TMI observations gives a smaller increase in global humidity than the experiment with SSM/I data, leading to a reduction of the model precipitation spin-down at the beginning of the forecasts. The impact on the low-level wind analysis is small with either SSM/I or TMI data. Forecast performance with TMI data is generally improved compared with a control experiment without any SSM/I or TMI data. The TMI experiment scores are better than those obtained in the SSM/I experiment for the 1000 hPa geopotential in the northern hemisphere and for tropical winds at 200 hPa.

[1]  C. Rodgers,et al.  Retrieval of atmospheric temperature and composition from remote measurements of thermal radiation , 1976 .

[2]  Laurence Eymard,et al.  Remote sensing of integrated cloud liquid water: Development of algorithms and quality control , 1998 .

[3]  M. A. Goodberlet,et al.  Ocean surface wind speed measurements of the Special Sensor Microwave/Imager (SSM/I) , 1990 .

[4]  J. Mahfouf,et al.  The ecmwf operational implementation of four‐dimensional variational assimilation. III: Experimental results and diagnostics with operational configuration , 2000 .

[5]  P. Courtier,et al.  A strategy for operational implementation of 4D‐Var, using an incremental approach , 1994 .

[6]  S. A. Snyder,et al.  Determination of oceanic total precipitable water from the SSM/I , 1990 .

[7]  Robert F. Adler,et al.  On the Tropical Rainfall Measuring Mission (TRMM) , 1996 .

[8]  Christian Kummerow,et al.  A simplified scheme for obtaining precipitation and vertical hydrometeor profiles from passive microwave sensors , 1996, IEEE Trans. Geosci. Remote. Sens..

[9]  C. Kummerow,et al.  The Tropical Rainfall Measuring Mission (TRMM) Sensor Package , 1998 .

[10]  James P. Hollinger,et al.  SSM/I instrument evaluation , 1990 .

[11]  Peter Bauer,et al.  Rainfall, total water, ice water, and water vapor over sea from polarized microwave simulations and Special Sensor Microwave/Imager data , 1993 .

[12]  Fuzhong Weng,et al.  An eight-year (1987-1994) time series of rainfall, clouds, water vapor, snow cover, and sea ice derived from SSM/I measurements , 1996 .

[13]  Clemens Simmer,et al.  Remote sensing of cloud liquid water , 1994 .

[14]  L. Phalippou,et al.  Variational retrieval of humidity profile, wind speed and cloud liquid‐water path with the SSM/I: Potential for numerical weather prediction , 1996 .