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Concordiasi Satellite data assimilation at high latitudes

Concordiasi Satellite data assimilation at high latitudes. F. Rabier, A. Bouchard, F. Karbou, V. Guidard, S. Guedj, A. Doerenbecher, E. Brun, D. Puech + other participants to Concordiasi. Overview. Rationale: Analyses over Antarctica important for weather, climate and ozone chemistry.

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Concordiasi Satellite data assimilation at high latitudes

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  1. Concordiasi Satellite data assimilation at high latitudes F. Rabier, A. Bouchard, F. Karbou, V. Guidard, S. Guedj, A. Doerenbecher, E. Brun, D. Puech + other participants to Concordiasi

  2. Overview Rationale: Analyses over Antarctica important for weather, climate and ozone chemistry. Try to optimize the use of satellite data to compensate for the lack of conventional observations. • Data Assimilation over Antarctica • 1. Infrared sensor assimilation • 2. Microwave sensor assimilation • 3. Assimilation and forecast Results • Field campaign: Additional in situ data < 16km

  3. Data Assimilation over Antarctica

  4. Assimilation of infrared sensors Assimilation of IASI and AIRS over polar areas (sea ice and land) Example of the increase of data over polar areas IASI channels 167 (100hPa) and 306 (300hPa) Black dots: pixels assimilated in operations Color dots (Tb) : assimilation of IASI over land and sea ice for high peaking channels

  5. 2. Assimilation of microwave sensors Improved representation of surface emissivity • Old emissivity operational scheme : Grody (1998) or Weng(2001) depending on frequency, used until July 2008 • Dynamical approach for the estimation of the emissivity from Satellite observations over land (Karbou 2006) • Emissivity derived from AMSU/A ch3 and AMSU/B-ch1 are assigned to the temperature & humidity soundings channels respectively • The estimation of emissivity has been adapted to Antarctica : snow and sea ice surfaces

  6. 2. Assimilation of microwave sensors Comparison of the new emissivity calculation with the old one, over sea ice New Old Fg-departure (K) (obs- first guess) histograms for AMSU-A, ch4 (July 2007) Fg-departure (K) (obs- first guess) histograms for AMSU-B, ch2 (July 2007)

  7. 2. Assimilation of microwave sensors Use of additional microwave data CONTROL Density of data EXP AMSUB- Ch3 AMSUA- Ch5

  8. 3. Assimilation and forecast results Overall number of data over area

  9. 3. Assimilation and forecast results Fit of short-range forecasts to Antarctic radiosondes Temperature Zonal wind 0hPa 200hPa 400hPa Nobs RMS 600hPa 800hPa 1000hPa Data South of 65 S

  10. 3. Assimilation and forecast results Impact of the data assimilation on forecast over high latitudes Comparison of RMSE for forecasts at 48h and 72h Error (experiment with additional data (AMSUA/B, AIRS, IASI)) – Error (Control) 48h 72h Blue: Positive impact of additional data 40°S 50°S EQ EQ Average over latitude, over 20 days (20/07/07--> 8/08/07), Geopotential data

  11. Field campaignAdditional in situ data

  12. Overview of the field experiment 2008 • 150 radiosoundings from Concordia, • 75 from Dumont d’Urville • Were provided on GTS • High resolution profiles available on demand • In situ measurements at Concordia • 18 Stratospheric balloons • Meteorological sensors, ozone sensors • Particle counter to study stratospheric clouds • GPS radio-occultations • 12 driftsondes with 50 dropsondes in each • ACAR-like data and dropsonde data will be provided on GTS http://www.cnrm.meteo.fr/concordiasi/ 2010

  13. Concordia and Dumont d’Urville soundings Statistics Dumont d’Urville(66,40°S;140°E) Concordia on DomeC(75°S;123°E) • Usual hour of RS launch : 0hTU • Addiational RS for Concordiasi : 12hTU • Statistics of meteorological conditions over 149 cases: • 35% cirrus • 39% Ac/As • 48% Stratocumulus • 19% clear • Usual hour of RS launch : 12hTU • Additional RS for Concordiasi : 0hTU • Stat meteo over 120 cases: • 62% clear • 29% almost cloudy • 10% cloudy Concordiasi Website: http://www.cnrm.meteo.fr/concordiasi-dataset/

  14. Concordiasi • 2008: • Preparatory data assimilation studies • In situ radiosonde data • 2009: • 1D-Var studies with radiosonde data as validation • Test campaign for stratospheric balloons (elsewhere) • 2010: • Stratospheric balloons over Antarctica • Data impact studies

  15. Balloon data Trajectories for late winter/ early spring (Austral) Vorcore 2005 Sept-Oct 2005 Dec 2005-Feb 2006 NWP users encouraged to use the data, available on the GTS Nov 2005

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