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22 nd North America/Europe Data Exchange Meeting Reading December 9-11, 2009

22 nd North America/Europe Data Exchange Meeting Reading December 9-11, 2009. Status report Bruno Lacroix (DPrévi/COMPAS) With contributions from CNRM/GMAP. Outlines Operational suite(s) current configurations (Computers, Models) Use of data Issues under development French data

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22 nd North America/Europe Data Exchange Meeting Reading December 9-11, 2009

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  1. 22nd North America/Europe Data Exchange Meeting Reading December 9-11,2009 Status report Bruno Lacroix (DPrévi/COMPAS) With contributions from CNRM/GMAP • Outlines • Operational suite(s) • current configurations (Computers, Models) • Use of data • Issues under development • French data • E-suite • Future plans

  2. Computing platform • NEC Configuration • NEC SX9 13 nodes of 16 processors • 102.4 Gflops/CPU , • 1 To mem / node • 2 machines: • Operations 6 nodes since 22nd September 2009 • Research 7 nodes • Next (and last) step 2010 Q1 • 20 nodes (2*10) : • 32,7 Tflops • + SX8 32 nodes / 8 processors 9.1 Tflops max • Until February 2012, 2013 or 2014

  3. Data management system: Soprano Architecture

  4. Models configuration • Global model up to 102H at 00UTC (cut off 2H20), 72H at 06 (3H), 84H at 12UTC(1H50), 60H at 18UTC (3H) • ARPEGE global spectral model TL538 C2.4 L60 • 60 levels, from 17m to 5Pa, horizontal resolution from 15km (over France) to 87km • Linear grid with T360 C2.4 orography (1080x540 pts) • 12 processors for ARPEGE forecast (10’ for 24H forecast) 4DVAR assimilation : • 2 loops of minimization T107 C1 L60(25 it.), T224 (30 it.) • 16 processors (1 SX9 node) for assimilation (40’ between cut-off and P0) data used: • SYNOP, SHIP, BUOY, AIREP, AMDAR, ACARS, TEMP, PILOT • CMW winds GOES 11, 12 + Meteosat 7, 9 + MTSAT-1R, Modis • SEVIRI radiances (Meteosat 9) • AMI (ERS2), Seawind (Quickscat) and ASCAT (Metop) winds • HIRS, AMSU-A, AMSU-B/MHS NOAA15, 16, 17, 18, Metop & AQUA • SSM/I (DMSP F13), AIRS AQUA, GPS ZTD, GPS RO, IASI (Metop) • SST 1/12 degree from NCEP/NESDIS + SSM/I sea ice mask

  5. ARPEGE horizontal resolution (km)‏ 70km

  6. Assimilation and forecast cycles

  7. Analysis Analysis Guess Guess Guess long cut-off 18UTC long cut-off 00UTC Analysis Analysis 3DVAR ARPEGE Short cut-off 18UTC Very Short cut-off 00UTC Short cut-off 00UTC Forecast 60H Forecast 54 H Forecast 102H 54H run based on 3DVAR FGAT and P6 from previous short cut-off forecast P24H forecast avalaible at 0145 UTC ARPEGE-Métropole, very short cut-off ( 1H05 at 00UTC )

  8. Models configuration (follow up) • Regional model up to D2 06UTC (at 00, 06, 12 and 12UTC) • ALADIN spectral limited area model • 9.5 km resolution on 2740kmx2740km domain, 60 levels (289x289 pts) • 3DVAR data assimilation: same data as ARPEGE plus SEVIRI radiances • Idem as dynamical adaptation of IFS • Many coupling files • Tropical model 72H range at 00 and 12 UTC • ARPEGE uniform model (TL539 C1 L60) ~37km • No own data assimilation (interpolation of stretched model analysis) • To be stopped in 2010 • Short Range Ensemble Prediction System 102H range • 11 runs ARPEGE TL358 C2.4 L55 (23 to 133km) • Based on singular vector perturbation

  9. ALADIN : 24 operationnal domains

  10. Coupling files for assimilation ALADIN

  11. AROME-France operational since Dec 18 2008 • four 30-h forecasts per day over France • 3-hourly 3DVar assimilation cycle including radar doppler radial winds, Meteosat radiances, synop T, Hu, wind • NH model with 5-species "ICE3" microphysics, 1D TKE scheme, "EDKF" shallow convection, ECMWF radiation • "SURFEX" surface model with tiles: soil/vegetation, sea, lake, town AROME 600x512pts, Dx=2.5km, 41L, Dt=1mn And ALADIN-France 300x300 domain

  12. AROME operational configuration • the ALADIN-FRANCE operational suite provides : • Lateral boundary conditions • Surface initial conditions : CANARI analysis (OI) at 00, 06, 12 and 18 UTC (the previous AROME forecast is used otherwise). ALADIN cycle AROME cycle time

  13. SEVIRI CSR SEVIRI HR IASI, AIRS Hu2m, T2m V10m ALADIN (+ SEVIRI HR, Hu2m,T2m,V10m) AROME (+ radar) Données assimilées dans les modèles GPSRO GPS sol Op. d’obs ARPEGE

  14. Number of observations (counts of bits of info.) • The number of observations depends on the assimilation time • SYNOP, RADAR Doppler winds, Aircraft measurements and SEVIRI radiances are of great interest to supply information to the data assimilation system.

  15. Radar data Assimilation AROME

  16. . . . . . . . . . . . 10 km . . . . . . . . . 100 km 0 Radar products from AROME • 24 radars , 17 Doppler bande-C giving between 2 and 11 PPIs / 15’ • BUFR (Z,Vr,statut) archived into BDM (a file /elevation, 1km res.) • Data center Opera in January 2011 with UK Met Office (about 70 radars over 29 countries) Observations used as profiles

  17. Ensemble assimilation (operational with 6 members…) :simulation of the error evolution eb = M ea (+ em ) 3DVAR FGAT T359C1L60 Flow-dependent B ea Explicit observation perturbations, and implicit (but effective) background perturbations.

  18. SIGMAB’s « CLIMATOLOGY » SIGMAB’s « OF THE DAY » 8 dec 2006 r0

  19. PEARP2 • PEARP2 is based on ARPEGE model • Two runs : at 06TU range 72h / 18TU range 108h • 35 members : 1 control member and 34 pertubated membres • Initial state Perturbation : • Singulars vectors over 4 zones > > > • Use f 6 analyses from AEARP (Assimilation Ensemble ARPege, L. Berre & G. Deroziers) • Amplitude limited by variance-covariance matrix coming from assimilation cycle • Mdel Errors :multi-physics (physic ARPEGE operationnal scheme+ 7 schem validated by GMAP/PROC) • Resolution PEARP2 T358L65 C2.4 / augmentation en 2010 T538L65C2.4 or C3.6 (~15km or 10km over France)

  20. PEARP T358L55 C2.4 (~23km over France)

  21. Targeted area for singular vectors

  22. Assimilation/Forecast Suites • Operational suites Atmospheric models: • Limited-Area ALADIN • La Réunion 3100x4600km with 3DVAR assimilation, • several research, commercial and transportable dynamical adaptation versions • Chemical Transport Model MOCAGE, Forecasts of air quality up to 96H • 3 domains:Global/Europe/France, Horz. resolutions: 4°, 0.5°, 0.1° • Observations currently only used for validation • Ocean Wave Models, Forecasts up to 102H • Global (2), Europe, France, Horz. resolutions: 1°, 1°, 0.25°, 0.1° • assimilate Jason-1 and Envisat altimeter wave height data

  23. Operational Suite on SX9 (96 procs) Nb proc Hour

  24. Changes in NWP system 07-2008 : IASI, SSM/I F14, statistics from ensemble assimilation cycle (6 members 3DVAR with T359C1L60 forecast) 04/02/2009 Arpège/Aladin: new physical parameterizations, in operation using aPrognostic Turbulent Kinetic Energy (TKE) scheme March 2009 move to SOPRANO data managment environment April 2009 : new ALADIN-France configuration, coupled with IFS at 00 and 12UTC, without data assimilation (dynamical adaptation). 22/09/2009: move to SX9 supercomputer

  25. Evolution RMSE Z500 EuropeRegular improvment over 23 years

  26. Telecom and data received (files) link to Toulouse relevant to US/Europe data exchange: Daily volume of satellite data files received from Exeter : HIRS NOAA16, 17, 19 AMSU-A NOAA15, 16, 18, 19, AQUA AMSU-B/MHS from NOAA15, 16, 18, 19: 700 Mbytes SSM/I and IS from DMSP F13->F15, F16, F17: 280 Mbytes Seawind from Quikscat 240 Mbytes? AIRS from Aqua 500 Mbytes

  27. September 2006: 20 stratospheric AIRS channels, SSM/I F13 and F15, Ground-based GPS data over Europe September 2007: GPS radio-occultation, ATOVS on MetOp (AMSU-A, MHS), ERS scatterometer, February 2008: Variational Bias Correction for radiances, ASCAT assimilation June 2008: HIRS on Metop, SSM/I F14, Emissivity parametrisation over land for micro-wave, CSR Meteosat, IASI Recent advances in the use of observations in the French NWP models

  28. Evolution in obs number Since July 2008, more than 2 million data per day H. Bénichou

  29. Radiances: ATOVSreceived with long cut-off • NOAA15 (AMSU-A) • NOAA16 (AMSU-A, AMSU-B) • NOAA17 (HIRS, AMSU-B) • NOAA18 (AMSU-A, MHS) • Aqua (AMSU-A) • Metop (HIRS, AMSU-A, MHS) H. Bénichou

  30. Radiances: ATOVSused with long cut-off • NOAA15 (AMSU-A) • NOAA16 (AMSU-A, AMSU-B) • NOAA17 (HIRS, AMSU-B) • NOAA18 (AMSU-A, MHS) • Aqua (AMSU-A) • Metop (HIRS, AMSU-A, MHS) H. Bénichou

  31. Radiances:SSMI, AIRS and IASI • SSMI (DMSP-F13): 7 channels • AIRS (Aqua) : 54 channels over 324 • IASI (Metop): 51 channels over 314

  32. Winds: CMW (all in BUFR), MODIS, Seawind, AMI, ASCAT

  33. CSR Assimilation of MSG SEVIRI Clear Sky Radiances • CSR product from Meteosat-8/-9 (MSG/MSG-2) • Hourly product • Assimilation of • 2 WV channels in 4DVar • 250 km thinning 10.8 mm channel Associated percentage of cloud free

  34. Ground-based GPS: Station selection

  35. Radio Occultation GPS Before screening After screening 10% data used

  36. Evolution in managed/used data ratio 75% satellite data / 25% in situ data used

  37. Land surface emissivity at microwave frequencies • Developments to assimilate surface sensitive satellite channels over land (Karbou et al., 2009) • Use of a dynamically retrieved emissivity to better assimilate AMSUA/B sounding channels over land in operations since July 2008

  38. Assimilation of AMSUB surface sensitive channels over land • channels 2 (150 GHz) and 5 (183+/-7 GHz) • where orog > 1000 m • Emissivity • dynamically derived from 89 GHz channel • assigned to those channels Assimilation of AMSUB over land upper atmosphere • AMSUB channels already assimilated over land • channel 3 (183+/-1 GHz, where orog > 1500 m) • channel 4 (183+/-3 GHz, where orog > 1000 m) surface observation structure function

  39. Impact on total column water vapour (TCWV) Average over the period 1 Aug-14 Sep’06 EXP-CTR EXP = CTR + additional AMSUB channels over land CTR TCWV diurnal cycle at TOMB

  40. Assimilation of SSM/I over land Only used over sea for the moment • Assimilation of SSM/I channels 3 to 7 over land • 22V / 37V / 37H / 85V / 85H • Emissivity • dynamically retrieved from 19V/19H channels • assigned to channels of same polarization with a frequency parameterization • Quality control • no coastal point, no land point with | lat | > 60° • Variational bias correction (VarBC) • “eTs” instead of “Ts” as one of the predictors • Emissivity dynamically retrieved from 19V channel upper atmosphere surface observation structure function

  41. Control TCWV increments Mean= 0.027 kg.m-2 (0.1%) EXP-CTR TCWV analysis difference Mean= 0.165 kg.m-2 (0.6%) Experiment TCWV increments Mean= 0.041 kg.m-2 (0.2%) EXP-CTR q analysis difference iso = 0.05 g.kg-1 20°N 500 hPa Water vapour (TCWV & specific humidity profile) Average over the period 15 Jul-13 Sep’06 more humidity in EXP

  42. Impact of advanced infrared sounder radiances in the french global NWP ARPEGE model 1. Overview • Current operational configuration 2. Use of IASI data • Channels selection + Impact on forecasts • Increase of IASI density • Extension to Water Vapour channels 3. Cloud-affected Radiances • Method • Impacts from AIRS (analysis + forecasts

  43. 1. Current operational configuration IASI operationally assimilated in : - ''long wave''temperature channels are assimilated, - clear condition (1 flag/channel, McNally & Watts, 2003): AIRS operationally assimilated in : - ''long wave'' temperature channels are assimilated, - Clear and cloudy conditions - Over open sea

  44. IASI assimilation: general features • Level 1C radiances are received via EumetCast in Toulouse(whole BUFR including 8461 channels) • A subset of 314 channels is retained in the Operational Observational DataBase (commonly chosen with other NWP centres)‏ • Radiances are bias corrected using VarBC

  45. 2.a. Use of IASI dataChannels selection Sea 64 channels Land 50 channels sea-ice32 channels Weighting functions

  46. 2.a. Use of IASI dataImpact of IASI on forecast 100 NH SH Geopotential: RMSE(noIASI wrt ECMWF) – RMSE(OPER wrt ECMWF)‏ Positive impact in mid-latitude and polar region in the troposphere 50 72h forecast range 40 30 NH SH 20 SH NH 96h forecast range 10 -10  -20 SH -30 -100

  47. 2.a. Increase IASI density • In operational configuration: • Pre-selection: • Only data from detector #1 • 1 fov AMSUA over 2 • 1 scanline over 2 • Selection during screening:1 profile per 250km box • In order to increase density • Pre-selection: • Only data from detector #1 • More complex pattern  • Selection during screening: 1 profile per 125km box • Between 3.5 and 4 more profiles are assimilated

  48. 2.a. Increase IASI density Typical data coverage over a 6-hour assimilation window(# of used channels / profile)example for 4th March 2009, 00UTC analysis time  1 profile / 250km box 1 profile / 125km box 

  49. 2.b. Impact of IASI density increase 100 NH SH 50 • 250 km 125 km • Positive impact mainly for southern hemisphere 72h forecast range 40 30 20 10 NH SH -10 96h forecast range Geopotential: RMSE(noIASI wrt ECMWF) – RMSE(OPER wrt ECMWF)‏ -20 -30 -100

  50. 2.c. Extension to WV channels: (Settings + impact on the analysis) Add 9 WV channels (1320, 1349.5 and between 1392.5 and 1401.5 cm-1) • Everywhere (sea, land, sea ice). • sigma_o(WV) = 4 K • (sigma_o(LW) = 0.5 – 1 K) Slight improvement of the innovation (obs- first guess) for other satellite humidity observations (MHS, HIRS 11 & 12)

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