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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
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

Computing platform
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

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:


    • 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


    • SST 1/12 degree from NCEP/NESDIS + SSM/I sea ice mask

Arpege m tropole very short cut off 1h05 at 00utc






long cut-off


long cut-off





Short cut-off


Very Short cut-off


Short cut-off









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 )

Models configuration follow up
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

Arome france operational since dec 18 2008
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

Arome operational configuration
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





Hu2m, T2m


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

AROME (+ radar)

Données assimilées dans les modèles


GPS sol

Op. d’obs ARPEGE

Number of observations counts of bits of info
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.












10 km










100 km


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

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

eb = M ea (+ em )



Flow-dependent B


Explicit observation perturbations, and

implicit (but effective) background perturbations.





8 dec 2006 r0


  • 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)

Assimilation forecast suites
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

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

Evolution rmse z500 europe regular improvment over 23 years
Evolution RMSE Z500 EuropeRegular improvment over 23 years

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

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

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

Evolution in obs number
Evolution in obs number

Since July 2008, more than 2 million data per day

H. Bénichou

Radiances atovs received with long cut off
Radiances: ATOVSreceived with long cut-off

  • NOAA15 (AMSU-A)



  • NOAA18 (AMSU-A, MHS)

  • Aqua (AMSU-A)

  • Metop (HIRS, AMSU-A, MHS)

H. Bénichou

Radiances atovs used with long cut off
Radiances: ATOVSused with long cut-off

  • NOAA15 (AMSU-A)



  • NOAA18 (AMSU-A, MHS)

  • Aqua (AMSU-A)

  • Metop (HIRS, AMSU-A, MHS)

H. Bénichou

Radiances ssmi airs and iasi
Radiances:SSMI, AIRS and IASI

  • SSMI (DMSP-F13): 7 channels

  • AIRS (Aqua) : 54 channels over 324

  • IASI (Metop): 51 channels over 314

Winds cmw all in bufr modis seawind ami ascat
Winds: CMW (all in BUFR), MODIS, Seawind, AMI, ASCAT

Assimilation of msg seviri clear sky radiances


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

Radio occultation gps
Radio Occultation GPS

Before screening

After screening

10% data used

Evolution in managed used data ratio
Evolution in managed/used data ratio

75% satellite data / 25% in situ data used

Land surface emissivity at microwave frequencies
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

Assimilation of amsub over land

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)


observation structure function

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


EXP = CTR + additional AMSUB channels over land


TCWV diurnal cycle at TOMB

Assimilation of ssm i over land
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


observation structure function

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%)

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


500 hPa

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

more humidity in EXP

Impact of advanced infrared sounder radiances in the french global nwp arpege model
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

1 current operational configuration
1. Current operational configuration global NWP ARPEGE model

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

Iasi assimilation general features
IASI assimilation: general features global NWP ARPEGE model

  • 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

2 a use of iasi data channels selection
2.a. Use of IASI data global NWP ARPEGE modelChannels selection

Sea 64 channels

Land 50 channels

sea-ice32 channels

Weighting functions

2 a use of iasi data impact of iasi on forecast
2.a. Use of IASI data global NWP ARPEGE modelImpact of IASI on forecast







Positive impact in mid-latitude

and polar region in the



72h forecast range








96h forecast range







2 a increase iasi density
2.a. Increase IASI density global NWP ARPEGE model

  • 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 global NWP ARPEGE model

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 

2 b impact of iasi density increase
2.b. global NWP ARPEGE modelImpact of IASI density increase





  • 250 km 125 km

  • Positive impact mainly for southern hemisphere

72h forecast range








96h forecast range






2.c. Extension to WV channels: global NWP ARPEGE model

(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)

2 c extension to wv channels impact on forecasts
2.c. Extension to WV channels: global NWP ARPEGE modelimpact 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

2 c extension to wv channels impact on forecasts1
2.c. Extension to WV channels: global NWP ARPEGE modelimpact on forecasts



  • Relative humidity (12h forecast) wrt ECMWF analysis

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



3.a. global NWP ARPEGE modelCloud-affected radiances:

Method (Pangaud et al, 2009, MWR)



Cloud parameters retrieval (CTP et Ne)

Flag cloudy channels

Use of CTP and Ne into RTTOV

Simulation of cloudy radiance

  • Assimilation of cloudy channels

  • 600hPa<CTP<950hPa

  • AIRS: sigma_o(cloudy) = sigma_o(clear) = 1

3 b cloud affected radiances impact on airs analysis
3.b. global NWP ARPEGE modelCloud-affected radiances:Impact on AIRS analysis

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

EXP: assim clear + cloudy observations

REF: assim clear observations only

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

Cloudy obs assimilated

Clear obs


Bath 21-25 september 2009, EUMETSAT Meteorological Satellite Conference

3 b cloud affected radiances impact on forecasts from airs
3.b. global NWP ARPEGE modelCloud-affected radiances:Impact 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



Significant up to 72h forecast range



Forecast range (h)

Forecast range (h)

Data monitoring
Data monitoring global NWP ARPEGE model

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

News on upper air observations
News on upper-air observations global NWP ARPEGE model

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

Windprofilers network global NWP ARPEGE model

La Ferté Vidame available on GTS

Marignane, Clermont Ferrand and Lannemezan

Available on bilateral basis

End of Nice profiler

GPS surface network global NWP ARPEGE model

IGN : RGP about 170 stations in January 2009

E suite in research environnement
E-suite in research environnement global NWP ARPEGE model

  • 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

E suite observation part
E-suite observation part global NWP ARPEGE model

  • 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

(A. Joly) global NWP ARPEGE model

Change of horizontal thinning for radiances in arpege
Change of horizontal thinning global NWP ARPEGE modelfor radiances in ARPEGE

Example: increased density only for IASI

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

  • Operational horizontal thinning presently is 250 km

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

125km instead of 250km thinning p moll
125km (instead of 250km) thinning (P. Moll) global NWP ARPEGE model

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

  • In screening output, observations really used :

3h background errors statistics given by new assimilation ensemble arpege
3H background errors statistics, global NWP ARPEGE modelgiven by new assimilation ensemble Arpege

assim. d’ens. 3D-Var Fgat

Klaus storm, maxim error variances better forecasted

(position+amplitude) with 4D-Var version

assim. d’ens. 4D-Var

24/01/2009 à 00h/03h

Preliminary results
Preliminary Results … global NWP ARPEGE model

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










New vertical resolution global NWP ARPEGE model

alt L41 ARO L60 ARO L70 ARP/ALA

(m) oper dbl dbl

  • 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)

Radar data assimilation french network
Radar data assimilation : French network global NWP ARPEGE model

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 inversion method of reflectivity profiles
Radar data assimilation : global NWP ARPEGE modelInversion 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

AROME Guess global NWP ARPEGE model





Données utilisées

Retrieved profiles when

  • 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

Future plans global NWP ARPEGE model

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
Thanks global NWP ARPEGE modelfor your attention