25 th EWGLAM/10 th SRNWP Lisbon, Portugal 6-9 October 2003 Use of satellite data at Météo-France Élisabeth Gérard Météo-France/CNRM/GMAP/OBS, Toulouse,

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25 th EWGLAM/10 th SRNWP Lisbon, Portugal 6-9 October 2003 Use of satellite data at Météo-France Élisabeth Gérard Météo-France/CNRM/GMAP/OBS, Toulouse, France on behalf of: É. Gérard, F. Rabier, N. Fourrié and D. Lacroix É. Gérard, F. Rabier, N. Fourrié and D. Lacroix (ATOVS) C. Payan and F. Rabier (Météosat)

25 th EWGLAM/10 th SRNWP, Lisbon, Portugal, 6-9 October 2003 ATOVS data Operational implementation of Raw radiances instead of preprocessed radiances: 22 October 2002 (+ European & American profilers) NOAA17 on top of NOAA15 & NOAA16: 17 December 2002 AMSUA data only in operations AMSUA data denial experiments (OSEs) Research experiments with locally received data Lannion/EARS in addition to Nesdis/Bracknell Research experiments with HIRS

25 th EWGLAM/10 th SRNWP, Lisbon, Portugal, 6-9 October 2003 No more 1DVar pre-processing T s in the control variable Extrapolation above the top of the model (1 hPa) up to 0.1 hPa by regression « Rain contamination » test  observation rejected if |obs-guess| channel 4 > 1.5 K 250 km thinning Data coverage more regular, less missing orbits, less scan border pixel removal Use of more channels over land Raw radiances instead of preprocessed radiances

25 th EWGLAM/10 th SRNWP, Lisbon, Portugal, 6-9 October 2003 Raw radiances instead of preprocessed radiances Time series of rms errors and biases 24 hour forecast 200 hPa geopotential scores over 1 month 22 Aug - 22 Sep 2002 Northern Hemisphere Southern Hemisphere Preprocessed radiances Raw radiances scores computed wrt their own analysis

25 th EWGLAM/10 th SRNWP, Lisbon, Portugal, 6-9 October 2003 AMSUA data denial experiments Uniform (unstretched) ARPEGE: 4DVar analysis T107C1L41 (up to 1hPa) Forecast T359C1L41 with 1800 s time step Experiments with and without AMSUA data: 23 Dec 2002  12 Jan 2003 One forecast a day from 00 UTC analysis: Short cut-off time: 03h50 (production) Long cut-off time: 09h55 (assimilation) Impact of AMSUA data wrt cut-off time

25 th EWGLAM/10 th SRNWP, Lisbon, Portugal, 6-9 October 2003 Benefit of AMSUA data Time series of rms errors and biases 24 hour forecast 500 hPa geopotential scores over 3 weeks 23 Dec Jan 2003 Northern Hemisphere With AMSUA (long cut-off) Without AMSUA Southern Hemisphere scores wrt long cut-off analysis with AMSUA data rms difference

25 th EWGLAM/10 th SRNWP, Lisbon, Portugal, 6-9 October 2003 Positive impact of using AMSUA data More pronounced benefit over Southern Hemisphere than Northern Hemisphere, over North America than Europe, when cut-off time is long Increase of gain with forecast range more regular with long cut-off time over North America (more robust signal) When AMSUA data are used, more gain wrt cut-off time is expected if short cut-off time is shorter (i.e. 00 UTC in oper stretched ARPEGE model) AMSUA data denial experiments

25 th EWGLAM/10 th SRNWP, Lisbon, Portugal, 6-9 October 2003 Research experiments with locally received AMSUA data Nesdis/Bracknell data Data available for the operational production, 1h50 cut-off time Lannion data 45W/40E/70N/30N Even more rapidly available, but smaller area & only NOAA16/NOAA17 EARS data Eumetsat ATOVS Retransmission Service Data rapidly available No blind orbit for NOAA17 (reception centres: Greenland, Norway, Canary Islands) 13 March UTC

Impact of EARS and Lannion data in addition to Bracknell data (rms/bias wrt radiosondes) 250 hPa 12 forecast range (hour)  3648 BracknellBracknell+EARS+Lannion First step: assimilation in operational model ARPEGE Next step: assimilation in regional model ALADIN (… AROME) in research mode AMSUA, HIRS, AMSUB (observation density, bias correction, …)

25 th EWGLAM/10 th SRNWP, Lisbon, Portugal, 6-9 October 2003 Research experiments with HIRS On top of AMSUA data over 23 Dec 2002 – 12 Jan km thinning (as for AMSUA) Cloud contamination test with channel 8  rejection if x < obs-guess < y, (x,y)=f(latitude) Condition for use  Sea Land (orog<1500m) Observation error (K) water vapour channels

Forecast scores (rms & bias) over Europe with HIRS without HIRS 24 hour geopotential temperature wind rel. humidity forecast range  48 hour72 hour scores computed wrt own analysis

25 th EWGLAM/10 th SRNWP, Lisbon, Portugal, 6-9 October 2003 Results of last experiments with HIRS Occurrence of « ringing » problem in stratosphere this summer channels 5, 6, 7, 14, 15 blacklisted over seaice channels 4 & 15 (tail up to 1hPa) to be blacklisted ? only channels 11 & 12 to be assimilated ? Cloud contamination test to be revised ? First guess check to be revised ? (obs-guess) 2 <  (  o 2 +  b 2 ) … under investigation …

25 th EWGLAM/10 th SRNWP, Lisbon, Portugal, 6-9 October 2003 Assimilation of Meteosat data Use of BUFR winds produced by EUMETSAT with a quality index and disseminated every 90 minutes compared to Use of currently operational SATOB winds produced every 6 hours … as a preparation towards the use of other geostationary satellite data (GOES, etc.)…

25 th EWGLAM/10 th SRNWP, Lisbon, Portugal, 6-9 October 2003  Experiments with the uniform ARPEGE configuration  23 Dec Jan 2003  SATOB winds  Only data with QI>0.8 are transmitted  BUFR winds conditional use  Weak constraint: QI>0.6 for upper level winds and over sea for mid-level winds  Strong constraint: QI> elsewhere as a function of latitude, level, channel Vis/IR/  w Assimilation of Meteosat data

Meteosat 5&7 observation fit to first guess and analysis area=50N/50S/113E/50W Used U component Used V component BUFR versus SATOB more data used rms and bias reduction

25 th EWGLAM/10 th SRNWP, Lisbon, Portugal, 6-9 October 2003 Present time, near/next future … for satellite observations… Tuning of AMSUA data: density, rain detection HIRS use, cloud detection, obs error tuning, blacklist ATOVS bias correction wrt analysis (?) Assimilation of BUFR winds on going AIRS: screening, bias correction already performed, first assimilation experiments on going Next future: AMSUB, SeaWinds, MSG, MODIS, SSM/I(S)