meteorological service of canada status report josée morneau and nicolas wagneur data assimilation...

Meteorological Service of Canada Status Report

Josée Morneau and Nicolas WagneurJosée Morneau and Nicolas WagneurData Assimilation and Quality ControlData Assimilation and Quality ControlCanadian Meteorological CentreCanadian Meteorological CentreMeteorological Service of CanadaMeteorological Service of Canada

www.ec.gc.ca

APSDEU-8 MeetingMontréal, Canada.10-12 October 2007

APSDEU-8 Montréal – October 10-12, 2007Metorological Service of Canada Status Report

Computers and Telecoms

• Electrical capacity problem solved• IBM: 2 x 600 P5+ clusters, to reach 4512 P5+ by mid 2009• Upgrade to SGI-FE’s: 2 x capacity• New CFS: 2 PB tape capacity• Links to NOAA-TOC (GTS), UKMetO (Sat data + GTS

back-up), EUMETSAT (EARS)• Link to NOAA-NESDIS soon• Internet still used for much satellite data


CMC OPERATIONAL RUNS: MAIN COMPONENTS

GEM modelGlobal (100km) : 0-10/15 days Regional (15km) : 0-48 hoursHIMAP (10km) : 0-24 hours

air quality (CHRONOS)

Environmental EmergencyTransport model (CANERM)

Trajectory model

monthly and seasonalforecasts

global assimilation cycle

4D-Var Analysis (data collection and

assimilation)

Models,9-hour forecast

(trial field)

Wave model (WAM)

regional data assimilation

ensemble forecasts(20 members)

surface analysesGEM model

Global (35 km) : 0-10/15 days Regional (15 km) : 0-48 hours

LAM (2.5 km) : 0-24 hours


• Atmosphere (4D-Var)– Wind (U,V)– temperature + Ps– Moisture (ln Q)

• Surface (OI)

– air temperature– dew point depression– precipitation amount– sea surface temperature (also lakes)– mean sea level pressure– snow depth– ice cover– ice thickness– deep soil temperature– soil moisture– albedo– and other geophysical fields based on climatology

Data Assimilation – Fields Analyzed

4-D analyses fromsurface up to 10 hPa

(58 Levels)

2-D analyses at surface

Global and Regional grids (some on LAM)


Observations assimilated in 4D-Var

(750 m) Verticalhourly

U,VProfiler

(NOAA Network)

~180 km boxes11 layers, per time step

U,VMODIS polar winds

(Aqua, Terra)

1.5o x 1.5o

11 layers, per time step

U,V

(IR, WV, VI channels)

AMV’s(METEOSAT 7-9, GOES 11-12, MTSAT-1R)

2o x 2o

3-hourlyIM3

(6.7 m)

Water vapor channel

GOES 11-12

250 km x 250 km

per time step

Ocean Land

AMSU-A 3-10 6-10

AMSU-B / MHS 2-5 3-4

ATOVS

NOAA 15-16-17-18, AQUA

1o x 1o x 50 hPaper time step

U, V, TAircraft

(BUFR, AIREP, AMDAR, ADS)

1 report / 6hT, (T-Td), ps, (U, V over water)Surface report

28 levelsU, V, T, (T-Td), psRadiosonde/dropsonde

ThinningVariablesType


Availability of aircraft data

ADS data collected by NavCanada: UANT01 CWAO (on GTS since July 05)Some ADS data now collected in Northern Canada

ADS data East of 30° W now available.Thanks to UK-Nats.


Canadian AMDAR - Status

• AC Jazz: 33 CRJ and 42 DHC-8 on GTS, 1 CRJ and 7 DHC-8 retained due to problems with data quality. More CRJ to be added. CRJ data very good.

• Still issues with DHC-8 TT data, although improved. Problem is related to data averaging aspects in avionics.

• Some data from AMS (DHC-8 and B737) but not used nor transmitted due to data quality issues.

• Some progress with First Air (B737 or B727 with TAMDAR), and data quality improving after TAMDAR calibration. To be distributed and assimilated after positive evaluation, including RH.

• Data from NavCanada CRJ’s (2) to be this fall.• Negotiations progressing well with WestJet.• MSC-ADAS ready to replace former C-ADAS software.• Monitoring of data is on-going and showing importance of good

monitoring before distribution of data.


Canadian AMDAR coverage


Monitoring of AMDAR Humidity Obs.

GLFE TAMDAR MDCRS WVSS-IIDiff.

Scales


Monitoring of RAOBS Humidity Obs.

O - BO - A

TAMDAR and RAOBS haveSimilar STD

TAMDAR hasMore bias than RAOBS

TAMDAR arebetter than WVSS-II


Other Canadian observations

• “Synoptic” observations from CTBTO network, using SYNOP MOBIL code, header: SNCN19 CWAO. Observations every 10-min, 10 stations for now but should increase, received at CMC by e-mail.

• Canadian radar data - now available centrally at CMC, NRP (National Radar Processor) operational, full volume scans available.

• Forestry and Road weather stations in British Columbia - data received at CMC, in old SA format. Data redistribution restrictions currently apply…should eventually be available in BUFR.

• Co-operative network in Quebec (Province, Hydro-Quebec, etc), received at CMC, also redistribution restrictions…problems with BUFR data.

• Some research wind profilers in Southern Ontario and Quebec: operated by Universities, data not yet available to CMC but should be provided to USA MADIS coop profiler hub.

• Some soil TT data now available, eventually in BUFR.• New equipment for radiosondes. Should improve wind quality, also includes provision

for 4D data in BUFR.• Ozone soundings on GTS (KULA01 CWAO) and total column ozone.• Major data management project in MSC, should lead to all data available in BUFR.• Potential development of surface GPS Network. Lead: Godelieve Deblonde.• Surface Weather stations for 2010 Olympics (Whistler) already on GTS.


575 X 641 grid (66% in 15-km uniformarea), 58 levels

Regionalmodel


Currently 4 GEM LAM 2.5 km domains, plus MAP D-Phase over the Alps (until November 2007)

Topography at 2.5 km


Changes to CMC NWP System since last meeting

Minor changes :• AMV’s : GOES-10 to GOES-11 (Jul. 2006), METEOSAT-8 to METEOSAT-9 (Oct. 2006),

METEOSAT-5 to METEOSAT-7 (Feb. 2007)• Radiances: GOES-10 to GOES-11 : Jul 2006• Blacklisting AMSU-A Ch. 4 from NOAA-16 : Jan 2007

Major changes to Global System on October 31, 2006 :• 35 km, 58 levels• ISBA land surface scheme• Improvements to physical parameterization• Kain-Fritsch deep convection• Assimilation: new B statistics, 58 levels (still T108), 40% more efficient 4D-Var code, new

SST and snow analyses.

Migration to New IBM : March 07• Some compiler issues• Some reproducibility issues

New assimilation setup for regional system on July 5, 2007• 6 hour spinup cycle (previously 12)• 3D FGAT analysis 58 levels

Major upgrade of the ensemble prediction system on July 15, 2007• 20 members up to 16 days at 0.9 deg (400x200) and 28 levels


Horizontal Grid of new global GEMPrevious model New Global-meso

400X200 -> 100 km 800X600 -> 33 km at 45o N


Vertical Levels of new global GEMPrevious model

10hPa

28 eta levelsDZ (km)

New Global-meso

58 eta levelsDZ (km)

10hPa


Objective Evaluation Against AnalysesAnomaly Correlation

Geopotential Height – 500 hPaNorthern Hemisphere Southern Hemisphere

120 Winter (DJF 2005) Cases


Case Study - Hurricane Katrina

72 hours 120 hours


Case Study: Radar Echoes for Hurricane Rita

(Michel Roch)


Hurricane Rita: MESO vs OPER.Observed trajectory

MESO

OPER

Other models

(MR)


Recent NWP verification

• http://iweb.cmc.ec.gc.ca/~afsisio/CMOI/verification/images/omm/special_cases/runningmean/noam_vs_obs_24h_rmse.gif

GEM-15

New Sat data

4D-Var

Meso Global


New Assimilation set-up for Regional System

• Update to 58 Levels and B Stats of meso-global GEM (from 28L, B stats from 100-km Global GEM)

• Spin-up shortened to 6 hours (from 12) with 3D-Var FGAT, more benefit from Global 4D-Var

• Snow depth anal. on 15-km model grid• New ice climatology, forcing a southern limit to the ice line

(monthly)• Easy extension to 4 cycles per day


Regional 12 hr spin-up cycle

L’analyse est transmise

Champ d’essai est produit

L’analyse est produiteG200

G218

G212

G206

R200 R206 R112

R212R218R100

R312 R118

R106 R300

G100

G112


Regional 6 hr spin-up cycle

L’analyse est transmise

Champ d’essai est produit

L’analyse est produite

R206

R218R100

R312 R118

R106 R300

R112

G200

G218

G212

G206

R200

R112

R212

G100

G112

R206

R312 R118

R218R100

R106 R300

R318

R306


Summer O-P 48h Winter(42 cases) (42 cases


42 winter cases– synop and shef (00-24h)


Evaluation of possible gain with 4 regional runs per day

(42 winter cases)

zonal wind std

temperature

zonal wind


New EPS implemented July 2007

a) New physics / New dynamics / Horizontal resolution

• 20 GEM members (SEF not used in the new EPS)

• Horizontal resolution: 0.9°

• Model lid: 10 hPa

• Forecasts up to 16 days

• Inclusion of two stochastic components in the physics

• Multi-parameterization approach...

• ENKF – True 4D with FGAT like innovations, 0.9°


New Set-up for EPS

b) Stochastic physical tendency perturbations

• All physical tendencies on horizontal winds, temperature, and humidity of each member are multiplied by a random function:– Defined in the range [0.5 , 1.5]– With a decorrelation time scale of 3 hours– And a decorrelation length scale of ~1700 km


New Set-up for EPS

c) Stochastic kinetic energy backscatter algorithm

• Numerical models are over-dissipative near the truncation limit• This likely inhibits upscale energy transfer that can affect the large

scale flow• It is thought that this phenomenon can be a cause of under-

dispersion in EPSs• Parameterization: Inject energy near the truncation limit to

compensate for the over-dissipation


Comparison between the former and new EPS

Mean of errors

Error of the meanEnsemble spread

Glo

bal R

MS

Sco

res

Thin lines : New EPSThick lines: Old EPS

Globe


Comparison between the former and new EPS

Mean of errors

Error of the mean

Ensemble spread

Tro

pica

l RM

S S

core

s

Thin lines : New EPSThick lines: Old EPS

Tropics


Next increment to assimilation system:more observations in 4D-Var

(parallel suite scheduled to start in october, 2007)AIRS & SSMI radiances3 hourly sfc dataDynamic bias correction for all radiance dataRevised background & observation error statistics✓More low level AMV’sMore levels from radiosondes and aircraftSSMI/S radiances✓QuikSCAT⌚Metop ATOVS: AMSUA & MHSGPS Occultations from COSMIC, CHAMP and GRACE (during later

phase of parallel testing)


Summary of the new components to be implemented

• AIRS radiance data (87 channels).• SSM/I radiance data (+ eliminating AMSU-A ch3 and new cloud mask for AMSU-B).• Going from RTTOV7 to RTTOV8.7 (and new vertical interpolation) • Inclusion of high scan angle AMSU data.• QuikScat oceanic surface winds (from KNMI).• 3.9 micron AMV (nighttime low level winds).• Dynamical bias correction for all radiance data.

Current operational assimilation and forecast system • ~35 km resolution global forecast model (GEM with 800x600 points and 58 eta levels)

.• 4DVAR global assimilation with 6 hour window .• 15 km regional forecast model over North America (58 eta levels). • 3DVAR FGAT regional assimilation with 6 hour spin-up cycle launched from global

cycle every 12 hours.


Data volumes (typical for 6 hour)

~50% Increase of assimilated data

Operational System New data

RAOBS 50000

Aircraft 55000

Profilers 8000

Surface 13000

GOES 5000

SatWind 40000

AMSU-A 50000

AMSU-B 20000

SSMI 14000

QuikScat 10000

AIRS 75000

SatWind 1500

AMSU-A 14000

AMSU-B 5000

Total ~240000 Total ~120000


Global model 500 hPa geopotential forecast anomaly correlation

156 summer cases 160 winter cases 160 winter cases

hours hours hours

Global model 500 hPa geopotential forecast anomaly correlation

156 summer cases 160 winter cases 160 winter cases

hours hours hours


Verification against Radiosondes for winter 2007

5 day global forecast – 160 cases verified over Southern Hemisphere

Pre

ssur

e hP

a

m/s m/s

degrees

degrees

dam

2 day regional forecast – 40 cases verified over North America

UUUV UU

UV

GZ TT

ESES

GZTT

degreesdam

Pre

ssur

e hP

a

m/s m/s

degrees

OPE in blue versus NEW in red

BIASSTD DEV STD DEV

BIAS

Verification against Radiosondes for winter 2007

5 day global forecast – 160 cases verified over Southern Hemisphere

Pre

ssur

e hP

a

m/s m/s

degrees

degrees

dam

2 day regional forecast – 40 cases verified over North America

UUUV UU

UV

GZ TT

ESES

GZTT

degreesdam

Pre

ssur

e hP

a

m/s m/s

degrees

OPE in blue versus NEW in red

BIASSTD DEV STD DEV

BIAS


Summer time series Winter time series





Schematic description of Observations Impact (OI) calculation

t= -6 hrs

eg

t= 24 hrs

ef

ForecastError (J/Kg)

Observations

e f,g

• Estimation of Observation Impact (OI) on the quality of a short-range forecast. OI is defined as efg = ef – eg

efg < 0 , the assimilation of observations is reducing the 24h forecast error. The observations are beneficial.

efg > 0 , the assimilation of observations is increasing the 24h forecast error. The observations are non-

beneficial.


Estimation of ef,g

g

gT

b

g

f

fT

a

f

ee

ee

xL

x

xL

x

)( bH x

b

g

a

fTbgfgf ee

Heeexx

Kxy ),(,

Sensitivity gradient in observation space

Innovation

: background variable at observation location

y : observation

KT: adjoint of the analysis gain matrix, i.e. )( bba H xyKxx


eg

t= -6 hrs

e f,g) UA

t= 24 hrst=0

ef

ForecastError (J/Kg)

Calculation of the impact of observation groups to the reduction of forecast error

e f,g) AI

.

...


Sensitivity of 24-hr fcst errors to observations


Radiosonde Data Impact: 24-hr fcst, Aug. 04


Aircraft data Impact: 24-hr fcst, Aug. 04


AMSU-A data Impact: 24-hr fcst, Aug. 04


Next version of global system

• Hybrid vertical coordinate, 80L, lid 0.1hPa• Li & Barker Radiation scheme• Hines non-orographic GWD• New error statistics (Buehner)• Additional AMSU and AIRS channels, IASI ?• GPS-RO: CHAMP, GRACE, COSMIC, GRAS• ASCAT• SSM/IS• Bias Correction above 10 hPa ??• Target: Late spring 2008


Monitoring Web sites

• http://collaboration.cmc.eg.gc.ca/cmc/data_monitoring

• http://collaboration.cmc.eg.gc.ca/cmc/data_monitoring/CAMDAR

• http://collaboration.cmc.eg.gc.ca/cmc/data_monitoring/SAR

• User: monitoring PW: CMC


www.ec.gc.ca

meteorological service of canada status report josée morneau and nicolas wagneur data assimilation...

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