130 likes | 235 Views
WG 4 activities. 1. COSMO LEPS. Feasibility study of COSMOLEPS at 7 km (cleps_7).
E N D
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
COSMO-LEPS at 7 km (cleps_7): the answer to forecasters’ dream? 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 RADAR 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 bad model(s)? • 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.