WG 4 activities

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# WG 4 activities - PowerPoint PPT Presentation

WG 4 activities. 1. COSMO LEPS. Feasibility study of COSMOLEPS at 7 km (cleps_7).

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### Feasibility study of COSMOLEPS at 7 km (cleps_7)

• “Keep the pace” with deterministic model (x~ 2-3 km): if the gap in resolutions between deterministic and probabilistic systems is too large, the two systems go for different solutions (that is, they forecast different weather!).

Motivations:

Provide a more detailed description of mesoscale processes by incresing the horizontal resolution.

Do not lose a “reasonable advantage” against ECMWF EPS, which will go to x=25 km during 2009.

from 10 to 7 km (plus small domain extensions) does not seem a lot

New system

x = 7 km

z = 40 ML

t = 72 s

ngp = 510x405x40 = 8.262.000

fcst range = 132h

cost = 1925 BU x run

elapsed time = 138 min

Present system

x = 10 km

z = 40 ML

t = 90 s

ngp = 306x258x40 = 3.157.920

fcst range = 132h

cost = 640 BU x run

elapsed time = 45 min

… cleps_7 is about 3 times more expensive than the present configuration

new computer at ECMWF being installed

Computer resources for each ECMWF member state will increase by a factor of 5 (five)  and ….

The dream is possible

COSMO-LEPS 10 km

COSMO-LEPS 7 km

• the grid of cleps_7 would be almost identical to that of COSMO-EU, this making easier and cleaner the use of initial fields provided by DWD (e.g. soil moisture analysis).
Future plans (2008 and 2009)
• test the use of the Soil Moisture Analysis fields provided by DWD;
• run cleps_7 for ~ 40 days in autumn 2008 and assess the impact;
• within TIGGE-LAM, develop coding of COSMO-LEPS output files in GRIB2 format;
• migration to the new machine at ECMWF;
• use a better snow analysis (possibly provided by DWD or Meteoswiss);
• extend the cluster analysis so as to consider not only ECMWF EPS, but also UKMO MOGREPS as global ensemble providing ic’s and bc’s (first tests);
• implement cosmoleps_7;
• gaining from COSMO-SREPS experience, introduce more model perturbations;
• test COSMO-LEPS nested on the under-development ECMWF EDA over MAP D‑PHASE period;
• optimise use of reforecasts + calibration of wind gust;
• support CONSENS + verification
2. Postprocessing
• Provide standard interface for internal postprocessing
• WG6

WG4: Provide standard internal postprocessing methods (i.e. formula catalog)

• Instability indices
• Front parameter
• Synthetic satellite images
• Exchange external postprocessing methods
• KF, MOS on wind, wind gusts

mm/24h

COSMO-2

3. Use and interpretation of models

Forecasters: we all started to use WRF for precipitation!

3. Use and interpretation of NWP models
• Serious problems with “non-equilibrium convection cases ». Neither the 7km (parametrised convection) nor the 2km (explicit deep convection) predict precipitation correctly (even yes or no).
• Who to blame?
• The forecasters overconfident in model(s)?
The problem

Quality of models

Expectations from models

1960

1970

1980

2000

2010

1990

Expectations / promises
• Small grid spacing  high resolution forecast
• Good (perfect) timing
• Desire for sophisticated parameters:
• Surface temperature
• Rainfall
• Cloudiness
• Fog
• Wind gusts
• …..
• Expectations: from forecasters
• Promises: from modellers
Discussion points
• What is really the quality of a model?
• Which model is better?
• In which situation?
• For which parameter?
• In a convective situation, do we look a the model rainfall pattern or a TS index? Or synoptics?
• How does it compare with a statistical postprocessing on a global model?
• Conditional verification can (must) be used
• How can forecasters specify the conditions (weather classification, stability, season,…)
• How can these informations be communicated?
WG4: Interpretation and applications

Discussion on these topic also started (recently) within SRNWP

• Catalog and exchange of posprocessing methods
• Listing and exchange of end-user applications (agriculture, aviation,…)
• Use and interpretation of models?

I am open to any collaborative suggestions for activities in this WG.