Assimilation of AIRS/IASI data at ECMWF · Data assimilation system (4D-Var) The observations are...
Transcript of Assimilation of AIRS/IASI data at ECMWF · Data assimilation system (4D-Var) The observations are...
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
Assimilation of AIRS/IASI data atECMWF
PeterBauer,EuropeanCentreforMedium-RangeWeatherForecasts
TonyMcNally,AndrewCollard,MarcoMatricardi,WeiHan,CarlaCardinali,NielsBormann
•Initialperformance/impactassessment•Upgrades:Additionofwatervapourchannels,cloud-affectedradiances,ozone•Comprehensiveobservingsystemexperiments•Futureupgrades•Summary
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
Data assimilation system (4D-Var)
The observations are used to correct errors in the shortforecast from the previous analysis time.
Every 12 hours we assimilate 4 – 8,000,000 observations tocorrect the 100,000,000 variables that define the model’svirtual atmosphere.
This is done by a careful 4-dimensional interpolation inspace and time of the available observations; this operationtakes as much computer power as the 10-day forecast.
~3,000,000 from AIRS& IASI!
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
Radiances (→ brightness temperature = level 1):• AMSU-A on NOAA-15/18/19, AQUA, Metop• AMSU-B/MHS on NOAA-17/18/19, Metop• SSM/I on F-15, AMSR-E on Aqua• HIRS on NOAA-17/19, Metop• AIRS on AQUA, IASI on Metop• MVIRI on Meteosat-7, SEVIRI on Meteosat-9, GOES-11/12, MTSAT-1R imagers
Bending angles (→ bending angle = level 1):• COSMIC (6 satellites), GRAS on Metop
Ozone (→ total column ozone = level 2):• Total column ozone from SBUV on NOAA-17/18, OMI on Aura
Atmospheric Motion Vectors (→ wind speed = level 2):• Meteosat-7/9, GOES-11/12, MTSAT-1R, MODIS on Terra/Aqua
Sea surface parameters (→ wind speed and wave height = level 2):• Near-surface wind speed from Seawinds on QuikSCAT, ERS-2 scatterometer,
ASCAT on Metop• Significant wave height from RA-2/ASAR on Envisat, Jason altimeter
Data sources: Satellites
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
Initial performance assessment
Upgrades: Addition of water vapourchannels, cloud-affected radiances
Comprehensive observing systemexperiments
Future upgrades
Summary
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
• AIRSCO2andH2OchannelsassimilatedsinceOctober2003(324channels,1/9FOV).• IASICO2/H2OchannelsassimilatedsinceJune2007/March2009(8461channels,1/4FOV).• Assimilatedinclear-skyareasandaboveclouds;sinceSeptember2009infullyovercastsituations,AIRS(notIASI)overlandsurfaces/sea-ice.• Continuousrevisionofchannelusage,qualitycontrol:Ozonechannels,PCRT.
Current use of AIRS/IASI data
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
λ[μm]
ΔTB[K]
IASI(afterApril2007calibrationchange)
AIRS
FG-departurestandarddeviation
MeanFG-departureafterbiascorrection
MeanFG-departurebeforebiascorrection
λ[μm]
Noise: AIRS vs. IASI data
(A.Collard)
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
First-guessdeparturestandarddeviationsin15μmCO2-band
ObservedCalculated
IASI: Model minus observations
(A.Collard)
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
First-guessdeparturestandarddeviationsinH2O-band
ObservedCalculated
IASI: Model minus observations
(A.Collard)
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
Initial performance assessment
Upgrades: Addition of water vapourchannels, cloud-affected radiances
Comprehensive observing systemexperiments
Future upgrades
Summary
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
Greychannelsarethe120H2OchannelsdistributedviatheGTS
10IASIwatervapourchannels
IASI H2O channel impact
(A.Collard)
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
Best value at ~1.5K Normalisedto unity here
10IASIwatervapourchannels:Fittoothermoisturesounderradiances
IASI H2O channel impact
(A.Collard)
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
CLOUD
AIRSchannel226at13.5micron(peakabout600hPa)
AIRSchannel787at11.0micron(surfacesensingwindowchannel)
TemperatureJacobian(K)
Pressure(hPa)
unaffectedchannelsassimilated
contaminatedchannelsrejected
Anon-linearpatternrecognitionalgorithmisappliedtodeparturesoftheobservedradiancespectrafromacomputedclear-skybackgroundspectra.
Thisidentifiesthecharacteristicsignalofcloudinthedataandallowscontaminatedchannelstoberejected.
obs-calc(K)
Verticallyrankedchannelindex
IASI/AIRS cloud detection
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
• byaddingcloudtoppressureandeffectivecloudfractiontocontrolvector(viasinkvariable),forretrievedeffectivecloudcover=1;• nocloudyRTcalculationsrequired,conservativelinearizationpoint.
SinglecycleHIRS,AIRS,IASIovercast/clear
Assimilation of cloud-affected channels
(T.McNally)
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
TemperatureforecasterrorRMSEdifference(EXP-CTRL,77cases,ownanalyses)200hPa
500hPa 700hPa
Positive: deteriorationNegative: improvement
0.2+ K shading
Assimilation of cloud-affected channels
(T.McNally)
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
Initial performance assessment
Upgrades: Addition of water vapourchannels, cloud-affected radiances
Comprehensive observing systemexperiments
Future upgrades
Summary
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
NH
SH
EU
AIRS/IASI impact
CTRL plus AIRS
(T.McNally)
US
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
NH
SH
CTRL plus IASI
(T.McNally)
EU
US
AIRS/IASI impact
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
NH
SH
CTRL plus both
(T.McNally)
EU
US
AIRS/IASI impact
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
0 2 4 6 8 10 12 14 16 18 20
SYNOP-windAIREP-windDRIBU-windTEMP-windPILOT-windGOES-AMV
MTSAT-AMVMET-AMV
MODIS-AMVSCAT-wind
SYNOP-massAIREP-massDRIBU-massTEMP-mass
HIRSAMSU-A
AIRSIASI
GPS-ROSSMI
AMSR-EMHS
AMSU-BMET 7-RadMET 9-Rad
MTSAT-RadGOES-Rad
FEC %
0 5 10 15 20 25 30
SYNOP-windAIREP-windDRIBU-windTEMP-windPILOT-windGOES-AMV
MTSAT-AMVMET-AMV
MODIS-AMVSCAT-wind
SYNOP-massAIREP-massDRIBU-massTEMP-mass
HIRSAMSU-A
AIRSIASI
GPS-ROSSMI
AMSR-EMHS
AMSU-BMET 7-RadMET 9-Rad
MTSAT-RadGOES-Rad
FEC per OBS %
Relative FC error reduction per system
Relative FC error reduction per observation
(C.Cardinali)
Advanced diagnostics
The forecast sensitivity(Cardinali, 2009, QJRMS,135, 239-250) denotes thesensitivity of a forecast errormetric (dry energy norm at 24or 48-hour range) to theobservations. The forecastsensitivity is determined bythe sensitivity of the forecasterror to the initial state, theinnovation vector, and theKalman gain.
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
0 1 2 3 4 5 6 7 8 9
SYNOP
AIREP
DRIBU
TEMP
PILOT
GOES-
Met-AMV
SCAT
HIRS
AMSU-A
AIRS
IASI
GPS-RO
SSMI
MHS
AMSU-B
Met-Rad
Met-Rad
MERIS
MTSAT-
GOES-Rad
O3
FEC %
black cntrl3 AMSU-A, 2 MHS vs 1 AMSU-A, 0 MHS
(C.Cardinali)
Advanced diagnostics – MW sounder denial
Forecast error reduction [%]
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
Initial performance assessment
Upgrades: Addition of water vapourchannels, cloud-affected radiances
Comprehensive observing systemexperiments
Future upgrades
Summary
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
Active IASI ozone channel assimilationJacobians of 321 O3channels in 9.6µmband (black: 16selected channels)
Ozone analysis vs.sonde observations(01-02/2009, N.H.)
Observed vs.simulated biasacross O3spectrum (biascorrected), N.H.
(W.Han)
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
IASI O3-channels
• Baseline System: T511 (40 km) full operational data (no O3 observations)
• UV System: As Baseline plus UV data from SBUV and OMI
• IASI System: As Baseline plus 16 IASI ozone channels (LW cloud detection andchannel 1585 anchored to zero bias correction, other channels VarBC)
Zonal mean cross section of fullozone field (shaded) and meananalysis difference with andwithout IASI ozone channels(units are mass mixing ratio)
(W.Han)
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
Verification against MLS(2 weeks, 20090615-20090630)
BASELINE = No O3Observations
BASELINE
+ SBUV + OMI
BASELINE
+ IASI 16 O3channels
BIAS: <AN-MLS> Std. dev.: <AN-MLS>
(W.Han)
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
Impact on T-channels with O3-sensitivityExperiment with anchoring channel 1585 and 15 bias-corrected channels
# 1585 50 hpa (O3)
# 290 340 hPa (T)
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
IASI data compression
Objective:• DevelopmentofPCradiativetransfermodeltobeabletoassimilatePC-scorecompresseddatafromadvancedinfraredsounders.
• EvaluatemodelwithfocusonshortwaveIASIchannelsandthepotentialofefficientnoisereduction.
IASIchannel6982at4.2μmoriginal reconstructedusing200PCs
(A.Collard)
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
Fit of RTTOV and PC_RTTOV(400 PCs, 600 predictors) toline-by-line radiances for a5165 profile independent set
(M.Matricardi)
Accuracy of PC radiative transfer
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
… and the latest …
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
IASI: Observation errors (σO)
Temperature soundingLW
Window WV
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
IASI: Spatial error correlations
Temperature soundingLW
Window WV
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
IASI: Inter-channel error correlations (Desroziers)
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
4D-Var experiments
• Use Desroziers-estimated observation errors in 4DVAR, with correlations,and scaling factor (July/August 2009).
• Standard deviations of Obs-FG, normalised to 1 for no-IASI experiment:
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
Chessboard pattern apparent inbackground departurecovariances for almost allassimilated IASI channels.
Pixel numbering:At ECMWF: Only pixel 1 of 4IASI pixels within AMSU-A FOVis currently considered.
ECMWF O-B covariance [K2]for channel 360 (734.750 cm-1)
1
2
4
3Flightdirection
IASI Pixel 1 spatial covariance
(N.Bormann)
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
Initial performance assessment
Upgrades: Addition of water vapourchannels, cloud-affected radiances
Comprehensive observing systemexperiments
Future upgrades
Summary
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
Summary
Advancedsounders(AIRS/IASI)representthemostvaluablesingleinstrumenttypeforNWP
Ideally,AIRS/IASIobservationsarecomplementedbypassivemicrowave(clouds/precipitation),conventionalandradiooccultationobservations(anchoringofbiascorrection)
AtECMWF,IASIobservationusagehasbeenconstantlyimproved/extendedsinceinitialimplementationon12June2007:Clouddetection,qualitycontrol,watervapourchannels,cloud-affectedradiances
Nextdevelopments:• Usageoverland,improvedusageoversea-ice• Moreaggressiveusageofcloud-affectedchannels• Activeusageofozonechannels• TestofPrincipalComponentmodelwithrealobservationsforIASIband3(andfullspectrum)• InclusionofvariableCO2(andothertracegases)
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
IASI spatial covariance - summary
• Background departure covariances for IASI suggest a smallerror that is correlated between different scan-positions andscan-lines, with alternating positive and negative correlations.
• Similar patterns observed at ECMWF and Met Office.• Effect largest for pixels 1 and 2, little effect for pixels 3 and 4.• The size of the error is small and of no concern to the
assimilation of the data.
• Error appears to be correlated to the direction of themovement of the corner-cube mirror.
• Possibly a signature of micro-vibrations affecting spectralcharacteristics (Denis Blumstein)?
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
Model grids for T799 and T1279
25 km843,490 points
16 km2,140,704 points
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
OPS(35r2)
980 hPa
(35r3) Use ofimproved QC(Huber norm)
961 hPa
(36r1) High-res systemT1279+T159/T255/T255
945 hPa
Hurricane Bill,
20 Aug. 2009
Observed MSLpressure~944 hPa
T1279 Tropical cyclone analyses improvedImproved Huber norm QC also beneficial
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
Impact of resolution upgrade
10 meter wind gustoccurrence probability:
> 24 m/s
> 35 m/s
%
T399L62 T639L62 (T319L62 10days+)
(R.Buizza)
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
IASIForecastScores
IASIbetterIASI
worse
IASIbetterIASI
worseSH
NH
500hPageopotentialanomalycorrelation(56cases,spring2007,normalizedRMSEdifference,ownanalysis)
Meanerrordifference uncertainty
IASI NWP impact prior to implementation (12/06/07)
(A.Collard)
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
ECMWF model forecast performance
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
ECMWF model forecast performance
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
ECMWF model suites
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
Analysis Observationwindow Observationfile Extractionstart00DA 21-03 21-03 04:0000DCDA 21-09 21-03 13:45
03-09 14:0012DA 09-15 09-15 16:0012DCDA 09-21 09-15 01:45
15-21 02:0006SCDA 03-09 03-09 10:0018SCDA 15-21 15-21 22:00
ECMWF model suites
Delayedcut-offsuiteprovidesshort-rangeforecastfor…
Earlydeliverysuitethatinitializes…
Medium-rangeforecast
Dataextractionstarttimesforeachsuite:
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
Data sources: ConventionalSYNOP/SHIP/METAR:
• Meteorological/aeronautical land surface weather stations (2m-temperature,dew-point temperature, 10m-wind)
• Ships→ temperature, dew-point temperature, wind (land: 2m, ships: 25m)
BUOYS:• Moored buoys (TAO, PIRATA)• Drifters→ temperature, pressure, wind
TEMP/TEMPSHIP/DROPSONDES:• Radiosondes• ASAPs (commercial ships replacing stationary weather ships)• Dropsondes released from aircrafts (NOAA, Met Office, tropical cyclones,
experimental field campaigns, e.g., FASTEX, NORPEX)→ temperature, humidity, pressure, wind profiles
PROFILERS:• UHF/VHF Doppler radars (Europe, US, Japan)→ wind profiles
Aircraft:• AIREPS (manual reports from pilots)• AMDARs, ACARs, etc. (automated readings)→ temperature, pressure, wind profiles
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
Experiment verification
Forecasts:•verificationagainstexperiment’sownanalyses,•verificationagainstoperationalanalyses,•verificationagainstobservations,incl.informationonstatisticalsignificance.
→Accuracy(anomalycorrelation,root-mean-squareerror)ofselectedmeterologicalparameter(T,q,z,R)forecastsatsignificantmodelheights(1000,750,500,200hPa):Betterobservingsystemshouldimproveanalysisandmedium-rangeforecast,i.e.beclosertomeansofverification.
NormalizedRMSEdifference:(RMSEexp–RMSEctrl)/RMSEctrl
Meanerrordifference uncertainty
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
Experiment verification
Analyses:→Fit(biasandstandarddeviation)ofobservations(in-situandremotelysensed)tomodelfirstguessandanalysis:Betterobservingsystemshouldimproveanalysisandshort-rangeforecast,i.e.drawclosertoentireobserveddataset.
Single-levelobservation
Multiplelevel/channelobservation
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
ECMWF model forecast performance - NH
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
RTTOV PC-RTTOV
Simulatederrorcorrelationspectrum:
Principal component radiative transferObjective:FastradiativetransfercalculationsandexploitationofthefullinformationcontentcontainedintheIASIspectrum
Method:• DevelopmentofPCcalculationinsideRTTOVfastmodelwithminimalcodestructuremodification(includingtangent-linearandadjointmodel)• Testaccuracywithrespecttoline-by-lineandconventionalRTTOVradiancecalculations(alsoagainstradianceobservations)• Plans:
• ApplyPC-RTTOVtoIASIshortwaveband(denoising)• Furtherextendtofullspectrum(potentialissueswith:Jacobians,clouddetection,landsurfaces,etc.)
(M.Matricardi)
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
FirstcycleovercastHIRS,AIRS,IASI•800-600hPa,•600-300hPa,o300-100hPa
FirstcycletemperatureincrementdifferenceEXP-CTRL
250hPa
700hPa
positivenegative
0.2 K intervals
Assimilation of cloud-affected channels
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
Firstcycletemperatureincrement250hPa(0.2,0.5,1Kintervals)
Experiment Experiment-Control
Control(dotsareovercastdata)
Assimilation of cloud-affected channels
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
Supporting States and Co-operation
Belgium Ireland PortugalDenmark Italy SwitzerlandGermany Luxembourg FinlandSpain The Netherlands SwedenFrance Norway TurkeyGreece Austria United Kingdom
Co-operation agreements or working arrangements with:Czech Republic Montenegro ACMADCroatia Morocco ESAEstonia Romania EUMETSATHungary Serbia WMOIceland Slovakia JRC Latvia Slovenia CTBTOLithuania CLRTAP
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
COUNCIL18 Member States
Organisation of ECMWF
DIRECTORD. Marbouty(France) (230)
MeteorologicalDivision
E. Andersson(Sweden) (42)
ComputerDivisionI. Weger
(Austria) (65)
OperationsW. Zwieflhofer
(Austria) (111)
ResearchE. Källén
(Sweden) (90)
AdministrationU. Dahremöller
(Germany) (25)
DataDivision
J.-N. Thépaut(France) (37)
ModelDivisionM. Miller(UK) (24)
Probabilistic Forecastingand Diagnostics Division
T. Palmer(UK) (19)
FinanceCommittee7 Members
Technical AdvisoryCommittee18 Members
Scientific AdvisoryCommittee12 Members
Policy AdvisoryCommittee
7-18 Members
Advisory Committeeof Co-operating States
12 Members
Advisory Committeeon Data Policy
8-31 Members
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
ECMWF Budget 2009
Germany 20.20%
Denmark1.87%Belgium2.71%
United Kingdom16.43%
Turkey 2.38%
Sweden 2.66%
Finland 1.42%
Switzerland 2.89%Portugal1.29%
Austria 2.16%
Norway 2.13%
Netherlands 4.61%
Italy12.66%
Ireland1.23%
Greece1.74%
France 15.46%
Spain 7.95%Main Revenue 2009
Member States’contributions £35,593,300
Co-operating States’contributions £847,400
Other Revenue £1,169,500
Total £37,610,200
GNI Scale 2009–2011
Luxembourg0.23%
Main Expenditure 2009Staff £14,450,100Leaving Allowances& Pensions £2,965,200ComputerExpenditure £15,690,600Buildings £3,634,300Supplies £870,000
Total £37,610,200
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AssimilationofAIRS/IASIdataatECMWF P.Bauer ⒸECMWF
ECMWF model forecast performance - Europe