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Impact study of AMSU-A/B data over land and sea-ice in the Météo-France global assimilation system

This study evaluates the impact of assimilating AMSU-A/B data on land and sea-ice in the Météo-France global assimilation system. It focuses on the emissivity and surface temperature uncertainties over snow and sea-ice surfaces and proposes methods to improve the assimilation process. The study also examines the frequency parameterization for sea-ice emissivity.

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Impact study of AMSU-A/B data over land and sea-ice in the Météo-France global assimilation system

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  1. Impact study of AMSU-A/B data over land and sea-ice in the Météo-France global assimilation system Fatima Karbou and Florence Rabier CNRM-GAME, Météo-France & CNRS

  2. Energy source (1) Upwelling radiation Top of Atmosphere (2) Downwelling radiation Signal attenuated by the atmosphere (3) Surface emission Surface (emissivity, temperature) Assimilation of AMSU-A & AMSU-B over land • Since July 2008, a “dynamical retrieval method” is used in ARPEGE to estimate the land surface emissivity at microwave frequencies (Karbou et al. 2006): • Instantaneous emissivity retrieval at one surface surface channel (89 GHz for AMSU-B and 50 GHz for AMSU-A) • The emissivity is then given to sounding channels (with no frequency dependency) Plane parallel non scattering atmosphere, specular surface

  3. AMSU-A & AMSU-B observations Indirect measurements of temperature and humidity

  4. More humidity in EXP Assimilation of AMSU-B (low peaking humidity channels) over land Evaluation wrt GPS data from AMMA TCWV (EXP-REF) Correlations with GPS

  5. More humidity in EXP Assimilation of AMSU-B over land operational in April 2010 TCWV (EXP-REF) Diurnal cycle of TCWV, Timbuktu (MALI)

  6. AMSU-A & AMSU-B observations over sea-ice Current usage of AMSU-B channel 5 (183.31  7.0 GHz) in ARPEGE, dec 2008 One of the limitations: large uncertainties about the surface description (emissivity and surface temperature) over snow and sea-ice

  7. Assimilation of observations over sea-ice Emissivity at 89 GHz Difficult modelling of sea-ice emissivity OPER Emis=0.99 January 2009 July 2009

  8. Assimilation of AMSU-A & AMSU-B over sea-ice • (a) For AMSU-B in particular, can we still use the 89 GHz emissivities for sounding channels without any frequency dependence parameterization ? • (b) Can we safely use the specular assumption over sea ice ? January 2009 July 2009

  9. Assimilation of AMSU-A & AMSU-B over sea-ice • (a) For AMSU-B in particular, can we still use the 89 GHz emissivities for sounding channels without any frequency dependence parameterization ? • (b) Can we safely use the specular assumption over sea ice ? • Introduction of frequency parameterization for sea ice: to describe the emissivity change from 89 GHz to 183.31 GHz (AMSU-B) Emissivity (~183 GHz) = Emissivity at 89 GHz + f (Tb 89, Tb150, Ts) (AMSU-A) Emissivity (~52-60 GHz) = Emissivity at 50 GHz • Data impact studies for evaluation: • Period: 15/12/2009 to 04/02/2010 • CTL: the operational system • EXP: CTL + emissivity model over sea ice + assimilation of AMSU-A/-B over sea ice

  10. Data impact results Usage of AMSU-B channel 5 (183.31  7.0 GHz) in ARPEGE CTL EXP

  11. Data impact results Usage of AMSU-B channel 5 (183.31  7.0 GHz) in ARPEGE Snow (effect of specular approximation ?, Harlow, 2009, Guedj et al. 2010) CTL EXP

  12. Assimilation of observations over sea-ice Operational in Nov 2010 Wind scores wrt radiosondes (January 2009)

  13. Assimilation of observations over sea-ice Scores: Plutôt positifs en particulier sur l’Hémisphère Nord

  14. Summary Objective: extend the use of AMSU observations over sea ice Method to calculate the sea ice emissivity to be used to assimilate humidity and temperature observations Beneficial for ARPEGE: data usage, RTTOV performances, Fit to all available observations, quality of analyses/forecasts Issues: the use of AMSU data over snow surfaces

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