Météo-France status report Hervé Roquet (DP/CMS) & Bruno Lacroix (DPrévi/COMPAS)

Montréal 26/5/2004

17th North America / Europe Data Exchange Meeting

ԌModels� Last modifications Impact of Cut-off time on forecast Use of data Meteosat data (geowinds) AMSU-A data HIRS radiances added to AMSU-A AMSU-B AIRSPlans

FUJITSU VPP5000:Second half-year 2003 a new configuration with 124 processors (instead of 31) = ex ECMWF computer.

2 separate machines:

–60 processors for operations

–64 processors for research

Supercomputer configuration

•June 2003•increase of average model resolution TL199 to TL358•reduction of stretching factor 3.5 to 2.4•reduction of minimisation resolution TL161 to TL149

•December 2003•Use of HIRS raw radiances in 4DVAR•Tuning of AMSU-A

•+ weekly run up to 120H based on 00UTC long cut-off (MFSTEP)•January 2004

•New solver for 4DVAR minimization •reduction of iteration numbers (45->40, 20->15)

•March 2004 New very short cut-off (1H)•May 2004

•New radiation scheme (FMR15)

Last modifications : ARPEGE model

Global model up to 102H at 00UTC, (72H at 06 and 12UTC, 60H at 18UTC)

ARPEGE global spectral model TL358 C2.4 L4141 levels, up to 1hPa, resolution 23km to 133kmLinear grid with T240 C2.4 orography3processors for ARPEGE forecast (20’ for 24H forecast)

4DVAR assimilation : 2 loops of minimization T107 C1 L41 (40 it.), T149 (15 it.) Last loop with simplified physics16 processors for assimilation (30’ between cut-off and P0)

data used: SYNOP, SHIP, BUOY, AIREP, AMDAR, ACARS, TEMP, PILOTSATOB GOES 9, 10, 12 + BUFR Meteosat 5, 7HIRS NOAA16 & 17, AMSU-A NOAA15 & 16SST 0.5 degree from NCEP/NESDIS + SSM/I sea ice mask

Models configuration

Previous configuration T298 C3.5 from 19 to 233km

Since June 2003, T358 C2.4 from 23 to 133 km

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

5 runs a day and 9 analyses on 6 hour windows [H-3h ; H+3h[

•4 short cut-off analyses to run short range forecasts•1h50 at 00UTC (P102H) and 12UTC (P72H)•3h at 06UTC (P72H) and 18UTC (P60H)

•4 long cut-off analyses to produce first guess (7-8h)

•1 very short cut-off 1H at 00UTC (P36H)

Guess

Analysis

Short cut-off18UTC Forecast

60H

Analysis

long cut-off18UTC

Guess

Analysis

Short cut-off00UTC

Forecast102H

Analysislong cut-off00UTC

Guess

Analysis

Very Short cut-off 00UTC

Forecast 36H

Impact of 1H cut-off on the forecasts

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experiment :46 forecast runs at 00h up to 36 Hwith a 1-hour cut-offand short cut-off first guess compared to 1H50 operationnal run

geopotential, verified against radiosondes data No significant degradation over Europe

Soundings available for 1H50 and 8H cut-off period 1998-2004

Number of available soundings since 1993

Impact of 8H cut-off on the forecasts

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experiment :23 forecast runs at 00h (once a week from 1/12/2004) with a 8-hour cut-offcompared to 1H50 operationnal run(same assimilation)

geopotential, verified against radiosondes data Significant improvement over Europe

The improvement can be seen almost every day.

It is mainly given by the late ATOVS data

Importance of the EARS data

Regional model up to J+2 06UTC (at 00, 06, 12 and 12UTC)ALADIN spectral limited area model

9.5 km resolution on 2740kmx2740km domain.No data assimilation: it is a dynamical adaptation model.

Many coupling filesTropical model 72H range at 00 and 12 UTC

ARPEGE uniform model (TL358 C1 L41) ~55km4D-VAR analysis configuration TL107 L41 (40/15 it.)

Use of simple bogussing and more SATOB data Seasonal Forecast 4 months range

ARPEGE T63 C1 L31 configuration ARPEGE-Climat 9 runs a month from ECMWF analysis + SST forcing

Experimental Short Range Ensemble Prediction System 60H range

10 runs ARPEGE TL358 C2.4 L41 (control = oper)Based on singular vector perturbation

Models configuration (follow up)

Area for verification

Short range ensemble Forecast (ARPEGE)

•Targetting over Atlantic Ocean and Western Europe•Optimization time window : 0-12hTotal Energy norm (initial and final)

16 first SVs

No physics

SV computation with a T63 regular truncation

Analyse Controle

ARPEGE CEP Tropiques AVARC

Vignettes

Brier Skill Score on wind speed (ref. : ECMWF EPS) Tested over a sample of 85 cases (Western Europe)

Comparison T199 C3.5 L 31 / T 358 C2.4 L41Rank diagram – T199 – Z500 – 24h Rank diagram – T358 – Z500– 24h

Rank diagram – T358 - Z500 – 48hRank diagram – T199 - Z500 – 48h

Telecom and data received (files)links relevant to US/Europe data exchange:

Daily volume of satellite data files received from Exeter :HIRS, AMSU-A, AMSU-B from NOAA15, 16 and 17: total 350MbSSM/I from DMSP F13 and F15: total 130 MbSeawind (240 Mbytes) from QuikscatAIRS+AMSU-A (250 Mbytes) from Aqua

Lannion to suitland (CIR 128 kbit/s, MIR 256 kbit/s):–IODC data from Meteosat 5 all channels, full resolution every 30 minutes, and AVHRR data received at Lannion

Suitland to Lannion (CIR 128 kbit/s, MIR 256 kbit/s): –GOES-W data for FSDS of Eumetsat

PVC from Toulouse to CIR (kbps) in CIR (kbps) out

United Kingdom 256 128

French West Indies 128 128

Assimilation of Meteosat data(Chistophe Payan)

Use of BUFR winds produced by EUMETSAT with a quality index and disseminated every 90 minutes

compared to

Use of previously operational SATOB winds produced every 6 hours

Experiments with the uniform ARPEGE configuration, over the period 23 Dec 2002 - 5 Jan 2003

SATOB experiment, the operational use Blacklist north of the 30° North on land

BUFR experiment with conditional use QI>0.85 (0.90 for HWW in tropics area) Satob Blacklist plus : - on land for p > 700hPa - in extra-tropics for 350 < p < 800 hPa (data too biased)

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

BUFR winds : present time, near/next future

Meteosat BUFR winds assimilated since december 2003

Use of BUFR winds of the other satellites on going

Structure of the observation errors as a function of the quality indicator and spatial correlation

Bias correction

Status of ATOVS data at Météo-France

• Operational use of AMSUA raw radiances• Raw radiances instead of preprocessed radiances: 22 October 2002 (+ European & American profilers)• NOAA17 on top of NOAA15 & NOAA16 : 17 December 2002• Research on locally received data (EARS)

• Operational suite with HIRS data(+ revision of rain detection for AMSUA) : December 2003

• Pre-operational suite with AMSUB data : Summer 2004

Assimilation of AMSUA raw radiances (Elisabeth GERARD and Florence Rabier)

– Ts in the control variable– T extrapolation above the model top (1 hPa) up to 0.1 hPa by regression– 250 km thinning

99

Sea ice (Ts < 271.45 K)

3<scan position<28

Cloudy |ob-fg| ch 4 > 1.5 K |lat|>30 for channel 8

Clear |ob-fg| ch 4 1.5 K

Land orog<500m/1500 m for channels 5/6

Open sea (Ts 271.45 K)

151413121211111010887766554321Conditions for use

0.7 K

0.7 Kor CLWP(ch1; ch2) > 0.1

mm

Assimilation of AMSUA raw radiances

Time series of rms errors and biases24 hour forecast 200 hPa geopotential scores over 1 month 22 Aug - 22 Sep 2002

Preprocessed radiancesRaw radiances

scores computed wrt own analysis

Northern Hemisphere

Southern Hemisphere

rms difference

rms difference

Experiments with HIRS radiances(Elisabeth Gérard and Delphine Lacroix)

– On top of AMSUA data over 3 weeks (23 Dec 2002 – 12 Jan 2003)– 250 km thinning (as for AMSUA)

3<scan position<54

(ob-fg) ch 11/12 > -3 K

x(lat)<(ob-fg) ch 8<y(lat)

Land (orog<1500 m)

Sea (Ts > 271.45 K)

15151414131212111110877665544321Conditions for use

water vapour channels

Forecast scores (rms & bias) over Europewith HIRS & without HIRS

24 hour

geopotential

temperature

wind

rel. humidity

forecast range

48 hour

72 hour

TCWV time series

-4.7

-8.0

-3.0

-6.1

Global

-0.1-7.4Globe

0.5-3.2S. Hem

-0.6-9.6Tropics

0.8-4.3N. Hem

LandSea%

WINTER

SUMMER

-3.3

-7.1

1.1

-3.9

Global

-0.3-5.1Globe

0.7-3.7S. Hem

-0.7-8.7Tropics

-0.1 1.9N. Hem

LandSea%

Scores (winter) Time series of rms errors and biases

48 hour forecast - 500 hPa geopotential 2 weeks - 26 Dec 2002 – 10 Jan 2003

without HIRSwith HIRS

scores computed wrt own analysis

Northern Hemisphere

Southern Hemisphere

Tropics

Test suite with HIRS and Meteosat BUFR

44 runs in Autumn 2003

Preparation for assimilation of OBS

• AMSU-B•EARS

•QuikSCAT•AIRS

•MODIS winds

Assimilation of AMSUB data

9 < scan position < 82

Ts > 278 K and |ob-fg|ch 2 < 5 K

Land orog<1000m/1500m for channels 4/5

Sea

55443321Conditions for use

In a similar way as for AMSUA & HIRS data: Scan and air-mass bias correction 250 km horizontal thinning

Effect of assimilating AMSUB data on TCWV (Total Column Water Vapour) field

Win

ter

perio

dSp

ring

perio

d

Winter scoreswrt radiosondes (27 Nov – 7 Dec 2003)

RMS, std dev. and bias errors (without minus with AMSUB data) for geopotential [m] as a function of forecast and vertical rangesRed: degradation from AMSUB

Green: improvement from AMSUB

Tropics

Northern Hemispher

e

Southern Hemisphere

RMS Std dev. Bias

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Spring scoreswrt radiosondes (17 Mar – 3 Apr 2004)

RMS, std dev. and bias errors (without minus with AMSUB data) for geopotential [m] as a function of forecast and vertical rangesRed: degradation from AMSUB

Green: improvement from AMSUB

Tropics

Northern Hemisphere

Southern Hemisphere

RMS Std dev. Bias

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Assimilation of AMSUB data - Conclusion

• Increase of humidity over land in Tropics and Southern Hem. and slightly in Northern Hem.

• Positive impact on the forecast scores (for geopotential, temperature and slightly for wind)

• Experiments ongoing• Spring period to be run again with adjusted bias

correction– Bias correction tuning necessary as assimilating

AMSUB data modifies the background, i.e. the way AMSUA/AMSUB/HIRS data are being used

Research experiments with locally received AMSUA data. (N. Fourrié)

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 dataEumetsat ATOVS Retransmission Service• Data rapidly available• No blind orbit for NOAA17

13 March 2003 12 UTC

« EARS-Lannion » hybrid product since February 2004 :Recalibrated level 1c radiances computed from level 1a ATOVS data received from EARS HRPT stations and locally at Lannion

Impact of EARS and Lannion data in addition to Bracknell data (rms/bias wrt radiosondes)

Temperature @ 250 hPa1

2

forecast range (hour)

36

48

Bracknell Bracknell+EARS+LannionFirst step: assimilation in operational model ARPEGENext step: assimilation in regional model ALADIN (… AROME) in research modeAMSUA, HIRS, AMSUB (observation density, bias correction, …)

Towards an assimilation of the Quikscat data

First test to be set up : - preprocessing (like ECMWF) of the raw data, (inversion at 50km of resolution). - choice of the most likely solution, produced by the inversion, and her opposite - final choice among the deviation against the first guess - quality control against rain, sea-ice and land contamination - thinning at 100km

AIRS : Atmospheric InfRared Sounder Thomas Auligné

324 out of 2378 channels 1 spot out of 18

Flat bias correction for each channel calculated over all active data

Basic definition for o:0.6 K for upper temperature

channels1 K for lower temperature

channels2 K for water-vapor channels

AIRS : assimilation suite

Bias correction

Observation error estimation

Assimilation period of 19 days : 2003.08.01 2003.08.19

CTRL = latest ARPEGE suite (including HIRS)

EXP = CTRL + AIRS (all data in 6h assim window)

+ more iterations in the 2nd 4D-Var minimisation

- Gross check : 150 < Tb < 350 & (obs - fg) < 20- First-guess check : (obs - fg)² < (o² + b²)- Channels in O3 and SW bands, over land, peaking above/near model cloud top (1hPa), at edges of scan are blacklisted

176 channels used

AIRS : assimilation suite

Channel selectio

n

Mitch Goldberg cloud detection scheme: based on thresholds recomputed for ARPEGE model LW window channel: Tb(965.43cm-1) > 270 K Model SST versus SW window channel (2616.095cm-1) (night only) Model SST versus predicted SST (from channels 918.65, 965.32, 1228.09, 1236.40 cm-1) VIS/NIR imager: less than 10 % cloud in pixel (day only)

Information on a pixel basis

Cloud detectio

n

Geopotential Temperature

VERIF = ECMWF analysis

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Forecast range Pressure

RMSCTRL - RMSEXP

Geopotential Temperature

Humidity

VERIF = TEMP observations

“Conservative” assimilation

(only 176 channels, over clear pixels, flat bias correction)

is neutral/slightly positive for summer experiment

To be confirmed/improved with more extensive testing

Pre-operational by summer 2004

Conclusion for AIRS data

Use of MODIS winds at Météo-France

First experiment with a 3-weeks data set of Terra Modis winds

Basic - Modis winds used "as is“Terra Modis only17 march – 5 april 2004Horizontal density thinning: average of ~250 kmNo use of quality index

Example of AMVs distribution for one analysis16 may 00 UTC

Quality indicator-based selection : only Modis winds with qi larger than 0.80 will be used

“ECMWF filtering”: over land winds used above 400 hPa, over sea, IR winds above 700 hPa and WV winds above 550 hPa

Horizontal density thinning: average of ~250 km (priority: obs time, qi)

Further experimentMODIS winds

Scores of the first experiment (9 days of assimilation)

Towards meso-scale assimilation

AROME Forecast 2.5km / 2008

MSG/Seviri WV 6,2 Tb on 12 Feb 2003, 1330

3DVar specific humidity increments

3DVAR ALADIN Assimilation of Water Vapor radiances MSG clear sky (resolution 10km)

Plans

Summer 2004: AMSU-B, AIRS, EARS,Quikscat

Autumn 20043DVAR ALADIN + Meteosat8 WV radiances

Spring 2005GOES BUFR winds, MODIS winds