Comparison of ICON- and COSMO-EU forecast quality
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1 Comparison of ICON- and COSMO-EU forecast quality Ulrich Damrath
2 Models - slide got from Felix Fundel ICON (no nest) Non-hydrostatic, icosahedral 13.2 km, 90 vertical levels (~75km) 3D Var analysis ICON-P1 (incl. EU Nest) Non-hydrostatic, icosahedral 13.2 km, 90 vertical levels 3D Var analysis Including the 2-way coupled nest ICON-EU Nest Non-hydrostatic, icosahedral 6.5 km, 60vertical levels (~22 km) Boundaries ICON-P1 Operational July 2015 COSMO-EU Non-hydrostatic, lat-lon 7 km, 40vertical levels (~22 km) Initial & boundaries from ICON Nudging analysis
3 Overview The influence of boundary conditions from ICON to the forecast quality of COSMO-EU Comparison of forecast quality for COSMO-EU with ICON global Comparison of forecast quality for COSMO-EU with ICON EU-nest
4 The effect of ICON-boundary conditions to the quality of forecasts for non surface parameters reduction of variance Quality of DWD-parallel suite compared to operational run since 2006
5 The effect of ICON-boundary conditions to the quality of forecasts for non surface parameters reduction of variance Quality of DWD-parallel suite compared to operational run last year
6 Quality of DWD-parallel suite compared to operational run, surface weather elements New dx2rad relation in LHN
7 Quality of DWD-parallel suite compared to operational run, surface weather elements ICON boundary conditions from ICON
8 Quality of DWD-parallel suite compared to operational run, precipitation - FSS ICON boundary conditions from ICON
9 Quality of DWD-parallel suite compared to operational run, precipitation - ETS ICON boundary conditions from ICON
10 Quality of COSMO-EU compared to ICON (global model), common region of COSMO-EU and ICON-EU, Period since start of ICON-EU
11 Quality of COSMO-EU compared to ICON (global model), common region of COSMO-EU and ICON-EU, Period since major revision of ICON
12 Quality of COSMO-EU compared to ICON (global model), region of Switzerland Period since start of ICON-EU
13 Quality of COSMO-EU compared to ICON (global model), region of Switzerland Period since major revision of ICON
14 Quality of COSMO-EU compared to ICON-EU, common region of COSMO-EU and ICON-EU, Period since start of ICON-EU
15 Quality of COSMO-EU compared to ICON-EU, common region of COSMO-EU and ICON-EU, Period since major revision of ICON
16 Quality of COSMO-EU compared to ICON-EU, region of Switzerland, Period since start of ICON-EU
17 Quality of COSMO-EU compared to ICON-EU, region of Switzerland, Period since major revision of ICON
18 BIAS of COSMO-EU forecasts compared to ICON-EU, region of Switzerland, Period since major revision of ICON
19 BIAS of COSMO-EU forecasts compared to ICON-EU, region of LM, Period since major revision of ICON
20 BIAS of COSMO-EU forecasts compared to ICON-EU, region of LM stations above 750 m, Period since major revision of ICON
21 Summary The influence of boundary conditions from ICON to the forecast quality of COSMO-EU o o It is clearly shown that the change of boundary conditons from GME to ICON lead to better forecast results for COSMO-EU concerning elements in the upper atmosphere. Forecast quality for surface weather elements is also influenced positively with a larger effect compared with other changes. Comparison of forecast quality for COSMO-EU with ICON global o Comparison of forecast quality for surface weather elements show that COSMO-EU is able to beat global version of ICON for most elements (Thank Goodness!). Comparison of forecast quality for COSMO-EU with ICON-EU o o ICON-EU is able to beat COSMO-EU with different degrees depending on the region of interest. A special advantage of ICON-EU against COSMO-EU is the more effective tuning for gusts forecasts.
22 Database of the new verification system Datbase NetCDF Feedback Files from Data Assimilation Observations (SYNOP/TEMP/SATOB/SCATT/ ) and modelequivalent from analysis and forecasts Additional information like time stamp, level, quality flags, observation error etc. which is useful for verification. Advantages No extensive data preparation (done by assimilation) Consistency of assignment of observation and forecast DA verification Wsmall disk space comared to full model Very rapid calculation of verification results (probably: online) Consistent treatment of different experiments Limitations Not useful for verifikation in horizontal spaces (analysis, object based) Relatively large effort when uising new data
23 Thank you for your attention!
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