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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

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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

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Data management system: Soprano Architecture

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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

Models configuration

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ARPEGE horizontal resolution (km)

70km

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Assimilation and forecast cycles

ARPEGE-Métropole, very short cut-off ( 1H05 at 00UTC )

54H run based on 3DVAR FGAT and P6 from previous short cut-off forecast P24H forecast avalaible at 0145 UTC

Guess

Analysis

Short cut-off18UTC Forecast

60H

Analysis

long cut-off18UTC

Guess

Analysis

Short cut-off00UTC

Forecast102H

Analysis

long cut-off00UTC

Guess

3DVAR ARPEGE

Very Short cut-off 00UTC

Forecast 54H

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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

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ALADIN : 24 operationnal domains

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Coupling files for assimilation ALADIN

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AROME-France operational since Dec 18 2008

AROME 600x512pts, Dx=2.5km, 41L, Dt=1mnAnd ALADIN-France 300x300 domain

four 30-h forecasts per day over France3-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

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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

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Op. d’obs ARPEGE

Hu2m, T2m

V10m

SEVIRI HR

ALADIN (+ SEVIRI HR, Hu2m,T2m,V10m) AROME (+ radar)

GPSRO

GPS sol

IASI, AIRS

SEVIRI CSR

Données assimilées dans les modèles

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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.

SYNOP / BUOY [5000-6000] / a few units

RADAR Doppler winds [0-1000]

Ground GPS [150-170]

Radiosondes (TEMP, PILOT) [700-4000]

Various Aircraft messages [500-5000]

Cloud motion winds [0-20]

Scatterometer winds [0-80]

ATOVS pixels [100-200]

SEVIRI [150-300]

total [7000-15000]

Radar data Assimilation AROMERadar data Assimilation AROME

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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)

.. ..

.. . .

.. ..... ... ..

0 100 km

10 km Observations used as profiles

Radar products from AROME

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Explicit observation perturbations, andimplicit (but effective) background perturbations.

Ensemble assimilation (operational with 6 members…) : simulation of the error evolution

Flow-dependent B

b = M a (+ m )

a

3DVAR FGATT359C1L60

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SIGMAB’s

« CLIMATOLOGY »

SIGMAB’s

« OF THE DAY »

8 dec 2006 r0

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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 T538L65 C2.4 or C3.6 (~15km or 10km over France)

OTI (h) résolutionEURAT 12 Tl95

HNC and HS 24 Tl44TROP 12 Tl44

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

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Targeted area for singular vectors

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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

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Operational Suite on SX9 (96 procs)

Hour

Nb proc

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Changes in NWP systemChanges 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 a Prognostic 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

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Evolution RMSE Z500 EuropeRegular improvment over 23 years

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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, 19AMSU-A NOAA15, 16, 18, 19, AQUAAMSU-B/MHS from NOAA15, 16, 18, 19: 700 MbytesSSM/I and IS from DMSP F13->F15, F16, F17: 280 MbytesSeawind from Quikscat 240 Mbytes?AIRS from Aqua 500 Mbytes

RMDCN = ECMWF + GTS

8Mb/s

Lannion 4Mb/s

Recent advances in the use of observations in the French NWP models

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

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Evolution in obs number

H. Bénichou

Since July 2008, more than 2 million data per day

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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

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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

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–SSMI (DMSP-F13): 7 channels

– AIRS (Aqua) : 54 channels over 324

– IASI (Metop): 51 channels over 314

Radiances:SSMI, AIRS and IASI

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

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Assimilation of MSG SEVIRI Clear Sky Radiances

10

.8

m c

han

nel

Associated percentage of cloud

free

CSR product from Meteosat-8/-9 (MSG/MSG-2) Hourly product Assimilation of

– 2 WV channels in 4DVar

250 km thinning

CSR

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Ground-based GPS: Station selection

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Radio Occultation GPS

Before screening

After screening10% data used

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Evolution in managed/used data ratio

75% satellite data / 25% in situ data used

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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

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Assimilation of AMSUB over land

surface

upper atmosphere

observation structure function

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

AMSUB channels already assimilated over land

channel 3 (183+/-1 GHz, where orog > 1500 m) channel 4 (183+/-3 GHz, where orog > 1000 m)

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Impact on total column water vapour (TCWV) Average over the period 1 Aug-14 Sep’06

EXP = CTR + additional AMSUB channels over land

EXP-CTR

CTR

TCWV diurnal cycle at TOMB

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Assimilation of SSM/I over land

surface

upper atmosphere

observation structure function

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)

– “Ts” instead of “Ts” as one of the predictors – Emissivity dynamically retrieved from 19V channel

Only used over sea for the moment

Water vapour (TCWV & specific humidity profile) Average over the period 15 Jul-13 Sep’06

Control TCWV increments Mean= 0.027 kg.m-2 (0.1%)

Experiment TCWV increments Mean= 0.041 kg.m-2 (0.2%)

EXP-CTR TCWV analysis difference Mean= 0.165 kg.m-2 (0.6%)

EXP-CTR q analysis difference iso = 0.05 g.kg-1

500 hPa

20°N

more humidity in EXP

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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

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1. Current operational configuration1. 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

Sept, 06 → Jul, 08 1 Jul. 08 → 4 Feb. 09 Since 4 Feb. 09

Clear 19 channels (stratos) 54 channels (+35 tropos) 54 channels

Cloudy Ø Ø 54 channels

Sept, 06 → Jul, 08 1 Jul. 08 → 4 Feb. 09 Since 4 Feb. 09

Open sea Ø 50 channels 64 channels

Land Ø Ø 50 channels

Sea ice Ø Ø 32 channels

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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

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2.a. Use of IASI data2.a. Use of IASI dataChannels selectionChannels selection

Sea 64 channels Land 50 channels sea-ice32 channels

Weighting functions

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Geopotential: RMSE(noIASI wrt ECMWF) –RMSE(OPER wrt ECMWF)

Positive impact in mid-latitude and polar region in the troposphere

2.a. Use of IASI data2.a. Use of IASI dataImpact of IASI on forecastImpact of IASI on forecast 100

50

40

30

20

10

-10

-20

-30

-100

96h forecast range

NH SH

SH

72h forecast range

NH

NH

SH

SH

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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

2.a. Increase IASI density

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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 / 125km box

1 profile / 250km box

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2.b. 2.b. Impact of IASI density increaseImpact of IASI density increase

250 km 125 km Positive impact mainly for

southern hemisphere72h forecast range

NH SH

96h forecast range

NH SH

Geopotential:

RMSE(noIASI wrt ECMWF) – RMSE(OPER wrt ECMWF)

100

50

40

30

20

10

-10

-20

-30

-100

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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)

2.c. Extension to WV channels:2.c. Extension to WV channels:(Settings + impact on the analysis) (Settings + impact on the analysis)

Slight improvement of the innovation (obs- first guess) for other satellite humidity observations (MHS, HIRS 11 & 12)

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2.c. Extension to WV channels:2.c. Extension to WV channels:impact on forecasts impact on forecasts

Positive impact on forecast wrt ECMWF analysis for large domains

Statistically significant

• for geopotential in the upper-troposhere for 72-96 hour for NH

Geopotential at 96h forecast range

IASIWV

REF

rmseBias

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Relative humidity (12h forecast) wrt ECMWF analysis

Statistically significant in the whole troposphere until 24h forecast range for NH

IASIWV

REF

2.c. Extension to WV channels:2.c. Extension to WV channels:impact on forecasts impact on forecasts

rmseBias

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3.a. 3.a. Cloud-affected radiances:Cloud-affected radiances:Method (Pangaud et al, 2009, MWR)Method (Pangaud et al, 2009, MWR)

CO2-SlicingCO2-Slicing

Cloud parameters retrieval (CTP et Ne)

Use of CTP and Ne into RTTOV

Simulation of cloudy radiance

Cloud-DetectCloud-Detect

Flag cloudy channels

Assimilation of cloudy channels• 600hPa<CTP<950hPa• AIRS: sigma_o(cloudy) = sigma_o(clear) = 1

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3.b. 3.b. Cloud-affected radiances:Cloud-affected radiances:Impact on AIRS analysisImpact on AIRS analysis

EXP: assim clear + cloudy observations REF: assim clear observations only

Cloudy obs assimilated

Clear obs assimilated

More observations are assimilated, particularly for tropospheric channels (potentially more contaminated by clouds).

Geographical coverage of assimilated observations for the channel 239 (478 hPa:mid-troposphere). 01/09/06 à 00UTC

Bath 21-25 september 2009, EUMETSAT Meteorological Satellite Conference

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3.b. 3.b. Cloud-affected radiances:Cloud-affected radiances:Impact on forecasts from AIRSImpact on forecasts from AIRS

blue:positive = reduction of RMSE red :negative = increase of RMSE

Statistics accumulated from 01/09/06 to 04/10/06RMSE difference with respect to radiosonde data

Altitude(hPa)

Forecast range (h)

GEOPOTENTIAL TEMPERATURE

Forecast range (h)

Significant up to 72h forecast range

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Data monitoring

•http://www.meteo.fr/special/minisites/monitoring/menu.html

User/password available upon request herve.benichou@meteo.fr

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News on upper-air observations

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TEMP/TEMPSHIP

Nancy (12UTC) : stop end 2010 Lyon : 06UTC only Rapa : 18UTC only Takaroa: Stopped in August 2009 Tubuai and Amsterdam: impact study

Nimes :Robotsonde (MODEM) in 2010– Autosonde (Vaissala) at Bordeaux

One more ASAP end 2009 A fourth one in early 2010

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Windprofilers network

La Ferté Vidame available on GTS

Marignane, Clermont Ferrand and Lannemezan Available on bilateral basis

End of Nice profiler

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GPS surface network

IGN : RGP about 170 stations in January 2009

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E-suite in research environnement

• Cycle 35T2_op1 (including RTTOV9)

• New resolution : T798 C2.4 L70 (10km over France) Dt=600s (first version : 720s)

• 2 loops of minimization in 4DVAR: T107 C=1 L70 Dt=1800s 25iter T323 C=1 L70 Dt=1350s 30 iter

• Use of a stratiform precipitation scheme in second minimization

• Use of a 6-member assimilation ensemble with 4D-VAR T399 C1 L70 , use of background error variances depending on the flux for all parameters (only vorticity in oper version) with a tuned spatial filter

• Evolution of turbulence scheme

•ALADIN-France:• Change of resolution: 7.5 km, 70 levels• Switch off Aladin-France as intermediate coupling model between global and

convective scale systems beg•AROME L60 direct coupling with ARPEGE

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E-suite observation part

Reduction to 125 km of box sizes used to select satellite data instead of 250 km in oper version. (P. Moll …)

9 additional chanels Water Vapor IASI (land + sea) and 4 surface IASI channels de surface (sea)

Assimilation of humidity observations in low troposphere with AMSU-B over land

New RTTOVS coefficients for AIRS

Use of clear sky MODIS CMW

improved sea-ice mask

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(A. Joly)

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Change of horizontal thinning for radiances in ARPEGE

Operational horizontal thinning presently is 250 km

In E-suite, horizontal thinning is decreased to 125 km => ~ 3.5 times more radiances are assimilated

More impact in Southern Hemis.because this area has less conventional data& because we assimilate more data over sea than over land

Geopotential height1 isoline = 1 m

Wind 1 isoline = 0.2 m/s

Example: increased density only for IASI

Scores with respect to ECMWF analysesover a 3-week periodRMS(250km) – RMS(125km)

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125km (instead of 250km) thinning (P. Moll)

• Multiplication by 4 of data incoming the screening more expensive !

• In screening output, observations really used :

Numbre in million

Total Sat % sat obs

Oper 1,3 0,95 73%

New 3,8 3,48 92%

3H background errors statistics,given by new assimilation ensemble Arpege

assim. d’ens. 4D-Var

assim. d’ens. 3D-Var Fgat

Klaus storm, maxim error variances better forecasted

(position+amplitude) with 4D-Var version

24/01/2009 à 00h/03h

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Preliminary Results …

scores (70 cases) with respect to radiosondes (TP) and IFS analysis (AC):

Geopotential Temperature VentTP TP TPAC AC AC

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New vertical resolution

0

1000

2000

3000

4000

5000

6000

7000

0 20 40 60 80 100120140160180200220240260280300320340360380400

épaisseur de la couche (en m)

altit

ude

(en

m)

60 niveaux

41 niveaux

AROME From L41 to L60 (+ 37% CPU) :Increased vertical resolution mainly in the boundary layer:-1st level from 17mto 10m-27 level below 3000m (instead of 15)Spectral coupling above 100hPa

–Vorticité, divergence et temperature–20 first wave numbers (scale > 100 km)

-

alt L41 ARO L60 ARO L70 ARP/ALA (m) oper dbl dbl

)()()1()( tXtXtX coupleuraromearome

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24 radars: 16 in C band (yellow circles) + 8 in S band (green circles). Volumes reflectivity (from 2 to 13 elevations).

22 Doppler radars (red circles), 2 planned (dashed red circles)

Radar data assimilation : French network

70

Radar data assimilation : Inversion method of reflectivity profiles

Caumont, 2006: use of model profiles in the vicinity of the observation as representative database

Consistency between the retrieved profile and clouds/precipitations that the model is able to create Possibility of wrong solution if the model is too far from reality… needs check

2

0

20

21

exp

21

exp

||xyy||

||xyy||x=xE

jsj

js

jj

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Données utilisées

RADAR AROME Guess AROME ANALYSEZpseudo-anZobs

• Important for increments alance in convective situations• High departure to first guess allowed• Thinning:1 obs. on 15 kms boxes to avoid correlated observations and representaivity

erros • Sigma Obs increasing linearly up to 160 kms

dbZthresNielev

listenoirespatiale

thresthres ZZZZsimZZZZobs

0,1

#/

)()(

Retrieved profiles when

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Future plans

PEARP with 35 members at 06 and 18 UTC

Spring 2010:

Nec phase 2 (2* 10 nodes)

ARPEGE 10km L70, AROME 2.5km L60 (direct coupling with ARPEGE), ALADIN 7.5km L70,

high density radiances, more IASI and AIRS channels, extended condition of use, NOAA-19, radar reflectivity (AROME only)

Late 2010

ALADIN 3D-VAR Outre-Mer (Polynesia, New Caledonia, Antilles-Guyana) Configuration coupled with IFS using LBC project

New data : SSM/IS F16 and F17, AVHRR winds, GRAS on Metop, Iscat

Thanks for

your attention