420 likes | 603 Views
Fuzzy and standard verification for COSMO-EU and COSMO-DE. Ulrich Damrath (with contributions by Ulrich Pflüger ) COSMO GM Rome 2011. General outlook. Upper air verification for COSMO-EU and COSMO-DE Fuzzy verification COSI @ DWD. C-EU verification against radiosondes.
E N D
Fuzzy and standard verification for COSMO-EU and COSMO-DE Ulrich Damrath (with contributions by Ulrich Pflüger) COSMO GM Rome 2011
General outlook • Upper air verification for COSMO-EU and COSMO-DE • Fuzzy verification • COSI @ DWD
C-EU verification against radiosondes Temperature BIAS, 00 UTC RK, new vertical coord., new reference atm. since July 2010: analysis in lower troposphere warmer V=00 error structure in upper tropo-sphere and above smoother, reduced error amplitude V=24 summer:troposphere always too warm V=48
C-EU verification against radiosondes RK, new vertical coord., ,new reference atm. • Geopotential BIAS, 00 UTC (and 12 UTC) V=00 since July 2010: reduced bias at height of tropopause and above V=24 V=48
C-EU verification against radiosondes RK, new vertical coord., ,new reference atm. • Geopotential RMSE, 00 UTC (and 12 UTC) V=00 since July 2010: reduced rmse at height of tropopause and above V=24 V=48
C-EU verification against radiosondes Wind speed, RMSE 00 UTC RK, new vertical coord., new reference atm. V=48 wind speed, RMSE Dec 2010/2009 Since July 2010: reduced RMSE of wind speed in upper troposhere solid: 2010 dashed: 2009 00 h 24 h 48 h
C-DE verification against radiosondes Temperature BIAS 00 UTC modifications to mixing length and subgrid scale cloud scheme V=00 no change compared to years before V=18 lower troposphere in summer clearly too warm
C-DE verification against radiosondes modifications to mixing length and subgrid scale cloud scheme • Temperature BIAS 12 UTC V=00 boandary layer and lower troposphere too warm especially in summer V=12
00 UTC C-DE verification against radiosondes modifications to mixing length and subgrid scale cloud scheme • Rel. humidity BIAS pos. bias in rel. humidity slight increase in spr/sum 2011 V=12 • 12 UTC pos. bias in rel. humidity decreases in 2011 boandary layer and lower troposhere too dry, above too wet V=12
Results of verification against radiosondes 2010/2011 • COSMO-EU: • amplitude of temperature bias between troposphere and above has been reduced • reduced bias and rmse of gepotential at tropopause and above • slightly reduced error in wind speed at upper troposphere • COSMO-DE: • already since 2009 boundary layer too warm (except analysis 00 UTC) • slighty increased humidity bias at 00 UTC but reduced bias at 12 UTC • Modification of radiosonde measurements lead also to the change of RH bias (better results for noon, worse for midnight)
Outlook for fuzzy verification • Motivation for fuzzy verification • State at DWD (until May 2011) • Are the properties of COSMO 2 compared to COSMO 7 other than the properties of CDE compared to CEU? • Quality of CEU- and CDE-forecasts for different regions • Current application of Fuzzy-methods • Operational implementiation
182.0 92.4 47.6 25.2 14.0 8.4 2.8 mm/12 h Weusthoff, Tanja, Felix Ament, Marco Arpagaus, Mathias W. Rotach, 2010: Assessing the Benefits of Convection-Permitting Models by Neighborhood Verification: Examples from MAP D-PHASE. Mon. Wea. Rev., 138, 3418–3433. ahhdfkfflflflflflfkfkfkjdjdddnbdnnnd
Configuration of precipitation verification with FUZZY-methods • Up to May 2011: • Observation data: Radar data prepared by assimilation scheme • Model data: GME-, CEU- and CDE-GRIBS interpolated to CDE-grid (nearest gridpoint) • Run: 00 UTC • Forecast times: GME, CEU: 06-18, 06-30, CDE: 06-18 hours • Verification area: part of CDE that is covered by radar data • Since May 2011: • Observation data as before, modell data: CEU- and CDE-GRIBS interpolated to CDE-grid (nearest gridpoint) • Run: 00, 03, 06, 09, 12, 15, 18, 21 • Forecast times: 01-04, 03-06, 06-12, 12-15, 15-18, 18-21 hours • Verification aread : CDE, Northern part of Germany, Southern part of Germany, North-Western part of Germany, North-Eastern part of Germany , South-Western part of Germany, South-Eastern part of Germany
Application of Fuzzy-methods • Calculation of all Fuzzy-scores with the IDL-Program by Beth Ebert. • Monthly evaluation of data for Fractions Skill Score and Upscaling ETS • Generation of results for • 8 (forecast runs) • * 7 (forecast intervals) • * 3 (2 models and one difference) • * 7 (regions) • * 2 (scores) ---------------------------------------------2352 Plots per time interval • Necessity to have a fast access to the data
Some examples:ETS upscaling July 2011, Run: 00 UTC, forecast time 01-04 hours
Some examples :FSS July 2011, Run: 00 UTC, forecast time 01-04 hours
Some examples :ETS upscaling July 2011, Run: 00 UTC, forecast time 12-15 hours
Some examples :FSS July 2011, Run: 00 UTC, forecast time 12-15 hours
Some examples :ETS upscaling July 2011, Run: 00 UTC, forecast time 18-21 hours
Some examples :FSS July 2011, Run: 00 UTC, forecast time 18-21 hours
Some aggregated results:ETS Upscaling July 2011 for different runs and forecast intervals (Germany)
Some aggregated results:FSS July 2011 for different runs and forecast intervals (Germany)
Some aggregated results:ETS Upscaling July 2011 for different runs and forecast intervals (NW-Germany)
Some aggregated results:ETS Upscaling July 2011 for different runs and forecast intervals (NE-Germany)
Some aggregated results:ETS Upscaling July 2011 for different runs and forecast intervals (SW-Germany)
Some aggregated results:ETS Upscaling July 2011 for different runs and forecast intervals (SE-Germany)
Some aggregated results:ETS Upscaling May 2011 for different runs and forecast intervals (Germany)
Some aggregated results:ETS Upscaling June 2011 for different runs and forecast intervals (Germany)
Some aggregated results:ETS Upscaling July 2011 for different runs and forecast intervals (Germany)
Some aggregated results:ETS Upscaling July 2011 for different runs and forecast intervals (Germany)
U, V, T, p‘, QV, QC, QI, QR, QS, T_SNOW, W_SNOW LHN (RH=const) Principle of boundary conditions for COSMO-DEand latent heat nudging
Some aggregated results:ETS Upscaling July 2011 for different runs and forecast intervals (Germany)
Summary concerning Fuzzy-Verification • The application of Fuzzy-verification for 3h-intervals allows a more detailed insight on the differences between the quality of precipitation forecast of CDE and CEU. • The results got by MeteoSwiss could be reproduces at least in a qualitative way. • Fractions Skill Score and ETS upscaling give for special cases notable different results. But the aggregated results are relatively good correlated. • The effect of LHN is especially for the whole region of Germany and for runs between sun rise and sun set relatively clear pronounced. • Also for parts of Germany this can be stated – but not with the same degree as for the whole region. • For some forecast intervals the effect of threee hour old boundar values of the CEU can be seen.