mesoscale data assimilation for the cosmo model: status and perspectives at the ims
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MESOSCALE DATA ASSIMILATION FOR THE
COSMO MODEL: STATUS AND PERSPECTIVES AT THE IMS
Massimo Bonavita, Lucio Torrisi, Antonio Vocino and Francesca Marcucci
CNMCA
Italian Meteorological Service
Pratica di Mare, Rome, Italy
29° EWGLAM, Dubrovnik, 8-11 October 2007
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Summary
Current DAS configuration at the IMS
Recent changes in the DAS
Observation usage
Initialization for the COSMO Model: 3D-VAR vs Nudging
The quest for a ”flow-dependent” analysis
29° EWGLAM, Dubrovnik, 8-11 October 2007
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NWP-DAS at the IMS
Domain size 769x513
Grid spacing 0.125° (14 Km)
Number of layers 40
Time step 150 sec
Forecast range 72 hrs
Initial time of model run 00/12 UTC
L.B.C. IFS
L.B.C. update frequency 3 hrs
Initial state CNMCA 3D-VAR
Initialization Digital Filter
External analysis None
Status Operational
Hardware IBM P690 (ECMWF)
N° of processors used 32 (Model), 90 (Analysis)
29° EWGLAM, Dubrovnik, 8-11 October 2007
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NWP-DAS at the IMS
• Data assimilation cycle:–3D-VAR FGAT analysis step;–3h refresh cycle;–Prognostic model: HRM
hydrostatic model at 14 Km grid (0.125°)
29° EWGLAM, Dubrovnik, 8-11 October 2007
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3h vs 6h DAS cycle
NWP-DAS at the IMS
6E-SAT/ST Meeting, Reading 14-15/05/2007
FGAT vs OPE DAS cycle
NWP-DAS at the IMS
7E-SAT/ST Meeting, Reading 14-15/05/2007
0.125° vs 0.25° DAS cycle
NWP-DAS at the IMS
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Daily observation usage stats. Synoptic Asynoptic• RAOB ~19000 - AIREP ~5500
• PILOT ~250 - AMDAR ~38000
• SYNOP ~5500 - ACAR ~8500
• SHIP,BUOY ~1200 - WIND PROF ~1200
- QSCAT/ERS2 ~1800
- ASCAT ~4000
- AMV (MET9/MET7/MODIS)~14000
- AMSU-A Rad. (NOAA1X) ~14000
Synoptic Obs ~26000 Asynoptic Obs ~87000
Total ~ 113000 obs/day
Observation usage
29° EWGLAM, Dubrovnik, 8-11 October 2007
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1. Use of METOP data: a) AMSU-A rad.: extension of current NOAA1x treatment, currently in passive monitoring configuration b) ASCAT winds: in place, impact and obs error characteristics under investigationc) GRAS Temperature/Spec. Hum. Profiles
2. Use of hyper-spectral sounders data:a) IASI L2 NRT products when available b) AIRS L2 products give positive NWP impact (Riishojgaard et al., 2007) but NRT availability is unclear
Observation usage
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Initialization of COSMO Model
• Initialization of COSMO Model at 7 Km resolution
29° EWGLAM, Dubrovnik, 8-11 October 2007
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Domain size 641 x 401
Grid spacing 0.0625 (7 km)
Number of layers 40
Time step 40 s
Forecast range 72 hrs
Initial time of model run 00 UTC
Lateral bound. condit. IFS
L.B.C. update freq. 3 hrs
Initial state Interpolated 3D-VAR
Initialization D.F.I.
External analysis T,u,v, q, SP
Special features Filtered topography
Status Operational
Hardware IBM P690 (ECMWF)
N° of processors 120
Initial Conditions: Interpolated 14 Km 3D-VAR analysis
Initialization of COSMO Model
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Initial Conditions: Nudging Data Assimilat. cycle
2 run per day starting at 00 and 12 UTC
Forecast length + 72 hours
Horizontal resolution about 7 km
40 vertical levels
3-hourly boundary conditions from IFS/ECMWF forecast
Initial Conditions through continuous assimilation cycle based on nudging
COSMO I7
• Initialization of COSMO Model
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COSMO-ME/COSMO-I7(LAMI)(7km)
COSMO-ME vs COSMO-I7 Temp T+12 00runMAM
COSMO-ME vs COSMO-I7 Temp T+24 00run
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Mean Error (dot) and Mean Absolute Error (cont.)
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COSMO-ME/COSMO-I7(LAMI)(7km)
COSMO-ME vs COSMO-I7 Temp T+36 00runMAM
COSMO-ME vs COSMO-I7 Temp T+48 00runMAM
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Mean Error (dot) and Mean Absolute Error (cont.)
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COSMO-ME/COSMO-I7(LAMI)(7km)
COSMO-ME vs COSMO-I7 Wmod T+12 00runMAM
COSMO-ME vs COSMO-I7 Wmod T+24 00runMAM
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Mean Error (dot) and Mean Absolute Error (cont.)
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COSMO-ME/COSMO-I7(LAMI)(7km)COSMO-ME vs COSMO-I7 Wmod T+36 00run
MAM COSMO-ME vs COSMO-I7 Wmod T+48 00run
MAM
-1,5 -1 -0,5 0 0,5 1 1,5 2 2,5 3 3,5 4 4,5 5
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Mean Error (dot) and Mean Absolute Error (cont.)
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• Interpolating a 3D-VAR analysis at 14 Km works well for the 7 Km COSMO Model
• Significant improvements from 28 to 14 Km analysis: will investigate further resolution increase in 3DVAR DAS (hydrostatic limit)
• Clear improvement over parallel COSMO implementation initialized with nudging. Not clear cut comparison, lack of explicit balance constraints in nudging could be an issue at 7 Km scale
29° EWGLAM, Dubrovnik, 8-11 October 2007
• Initialization of COSMO Model
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• Initialization of COSMO Model at 2.8 Km resolution
29° EWGLAM, Dubrovnik, 8-11 October 2007
• Initialization of COSMO Model
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•For the 2.8Km version (COSMO-IT) an experiment was run comparing two identical model configurations: one initialized from interpolated 14 Km 3D-VAR, the other with Nudging data assimil. cycle
• Initialization of COSMO Model
20Convegno FAI, Ischia 14/06/2007
• Initialization of COSMO Model
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• Initialization of COSMO Model
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• Initialization of COSMO Model
23Convegno FAI, Ischia 14/06/2007
• Initialization of COSMO Model
24Convegno FAI, Ischia 14/06/2007
• Initialization of COSMO Model
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• Interpolating a 3D-VAR analysis at 14 Km does not provide balanced I.C. for 2.8 Km LM
• Observation nudging is able to reduce/suppress precipitation spin-up present in the 3DVAR initialized version
• After the first 6-9h skill scores of 3DVAR vs Nudging COSMO-IT are very similar: at 2-3 Km scale, nudging intrinsic balance constraints seems effective and the method looks competitive with 3D-Var
• Currently, nudging initialization is employed in operational 2.8Km COSMO-IT
29° EWGLAM, Dubrovnik, 8-11 October 2007
• Initialization of COSMO Model
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• Extensive discussion inside COSMO community
• Lack of resources/expertise to develop 4DVAR
• EnKF approach is simpler and seems to be ripe for trial in operational environment (shown to outperform 3DVAR in perfect model simulations and, more recently in real world experiments)
The quest for a flow dependent analysis
29° EWGLAM, Dubrovnik, 8-11 October 2007
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The quest for a flow dependent analysis
• Possible EnKF advantages for high resolution DAS:
1. Complex observation operators (i.e. precipitation) coped with automatically
2. Covariances are evolved indefinitely
3. Can be extended to assimilate asynchronous observations (4DEnKF)
4. Gives “optimal” initial perturbations for ensemble forecasting
29° EWGLAM, Dubrovnik, 8-11 October 2007
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The quest for a flow dependent analysis
• Which EnKF version to use? Agreement on LETKF (Hunt et al. 2005) because:
1. Version of Ensemble Square Root Filter (EnSRF), avoids additional sampling error of perturbed observations
2. Avoids inefficient sequential analysis of observations of other EnSRF
3. Computationally efficient (computations performed in ensemble subspace)
4. Very efficient parallel implementation29° EWGLAM, Dubrovnik, 8-11 October
2007
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The quest for a flow dependent analysis
On the other hand:1. Rank deficiency of sampled B matrix
can be detrimental for affordable ensemble size. Observation localization can help, possible need of hybrid analysis step with 3DVAR
2. Effective treatment of model error still an issue
29° EWGLAM, Dubrovnik, 8-11 October 2007
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The quest for a flow dependent analysis
At which resolution should the filter be
used? Different ideas...1. DWD has proposed the KEnDA project
(COSMO project): Kilometer scale EnDA
2. Trying to tackle convection as an initial value problem too.
3. Running an ensemble DA and Forecast system at the Kilometer scale is very computationally expensive..
29° EWGLAM, Dubrovnik, 8-11 October 2007
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The quest for a flow dependent analysis
At which resolution should the filter be
used? Different ideas...1. At IMS we will not have the computing
power of DWD for the foreseeable future!
2. Our forecasting target is the very short to extended short range, i.e. +3h->+72h
3. For non organized convection +3h is very long range forecasting
4. Convective systems whose life cycle and predictability extends beyond 3h can usually be modelled at the mesoscale (7-10 Km)
29° EWGLAM, Dubrovnik, 8-11 October 2007
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The quest for a flow dependent analysis
MESO-DAPS project:
Data Assimilation and Prediction System at
the Mesoscale
Main advantage of unified approach:
“DA step samples initial uncertainties at
correct spatial scales for subsequent
ensemble forecast”
29th EWGLAM, Dubrovnik, 8-11 October 2007
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The quest for a flow dependent analysis
MESO-DAPS project:
1. Based on LETKF (or LETKF-3DVAR hybrid approach)
2. 10-14 Km resolution of ensemble members
3. Will provide lateral and initial conditions for nested Km scale COSMO model (+3-24h)
4. Currently national project. Will be proposed to COSMO community if proven
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Thank you!
29° EWGLAM, Dubrovnik, 8-11 October 2007
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3rd SRNWP Workshop on short-range EPS
www.meteoam.it
srepsws@meteoam.it
Rome, 10-12 December 2007Università Roma I “Sapienza”
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