1. WG4: interpretation and applications overview and plans Pierre Eckert MeteoSwiss, Geneva

2. Topics FIELDEXTRA  presentation by JM Bettems
CORSO  presentation by G. Rivin
COSMO-1
Italy
Switzerland
Some applications at MeteoSwiss
Which posprocessing for the COSMO Consortium?

6. Status and recent developments
COSMO-1
Status and recent developments
Oliver Fuhrer
With results from the whole COSMO-NExT Team
COSMO-GM 13, Sibiu

7. Project COSMO-NExT ensemble data assimilation: LETKF
Boundary conditions: IFS 10km 4x daily
Boundary conditions: VarEPS 20km 2x daily
ensemble data assimilation: LETKF
COSMO-1: 8x daily O(24 hour) forecasts 1.1km grid size (convection permitting)
COSMO-E: 2x daily 5 day forecasts 2.2km grid size (convection permitting) O(21) ensemble members
Um lokale Vorhersagen zu machen, verwendet man ein 3-stufiges Verfahren:
Zuerst ein globales Modell, das das Verhalten der Atmosphäre auf dem ganzen Globus vorhersagt. Dazu wird die Kugel mit einem Gitternetz überzogen, dessen Maschenweite ca. 16km beträgt.
Auf einem Ausschnitt über Europa wird die Prognose auf einem Gitter mit 6.6km Maschen verfeinert (COSMO-7).
Über dem Alpenbogen wird ein Netz mit 2.2km Machenweite aufgespannt (COSMO-2). Damit erhält man viel mehr Details, wie z.B. die Alpentäler.
Das jeweils eingebettete Modell braucht die Vorhersagen des übergeordneten an den Rändern (Ein- und Ausströmen der Luft).
Faustregel: eine 24h Vorhersage muss in 30‘ erstellt werden können, damit sie nützlich ist. Je enger die Maschen, desto grösser der Rechenaufwand, deshalb die immer kleineren Gebiete.

8. Settings for dynamics and physics
New fast waves solver (consistent 2nd-order accuracy, strong conservation form of divergence operator, increased divergence damping)
Horizontal non-linear Smagorinsky diffusion
No artificial horizontal diffusion
Rayleigh damping of all variables at upper boundary (test running with condition on w only looks very similar)
6 category microphysics including graupel (as COSMO-2)
Standard turbulence and multilayer soil module
Explicit deep convection but Tiedtke shallow convection (C-2)
Ritter-Geleyn radiation every 6’
Roughness length only from land use (Z0 ≤ 1m)
No sub grid scale orography

9. Stability of dynamical core @1km
Not a lot of experience with new fast waves solver and fundamental changes
Consistent accuracy in numerics (2nd-order)
Strong conservation form of divergence operator
Investigation of 10 crashing cases and idealized setups
Increase of divergence damping could significantly increase stability
No artificial horizontal diffusion required!
The stability is sensitive to several parameters (e.g. upper/lower BC, divergence damping, etc.)
Vertical level distribution can have an impact on the stability of the model
A truly horizontal pressure gradients following Mahrer (1984) shows better results

10. External parameters
Current resolution of external parameters is not sufficient for COSMO-1:
Soil type database km)
Topography m)
No sub-grid scale roughness information! …
The model is not getting a fair chance to be better!
Work on the software for the generation of external parameters (EXTPAR) has finished
Better topographic dataset
Better soil dataset

11. Summary (so far) We have a 1km setup which runs stably!
Fall and winter verification shows good results
Better humidity specially in the standard deviation
Too strong 10m winds
Good precipitation scores
Similar upper air scores as COSMO-2
Improvements available or ongoing
Configuration
External parameters
Turbulence

12. Some applications @ MeteoSwiss
From the presentation of Jacques Ambühl

15. We have to join model performances with user needs

16. Postprocessing in COSMO
No reference to postprocessing in the presently active science plan
As shown before, many applications use more or less directly model outputs
Most of them are of national interest or are subject to intellectual property restrictions
WG4 however strongly recommends that national methods are exchanged and is ready to organise the exchange.
What postprocessing on consortium level?
(What terms of reference for WG4?)

17. COSMO-1

18. COSMO-1

19. Model interpretation “1 day convection = 10 day synoptics”
High-resolution + ENS = Information flood
The challenge is to prepeare the relevant information in a clear way.
A scale adapted modell interpretation is necessary
Derived quantities (SDI)
Bulk quantities (temporal and spatial neighbourhood)
Intuitive quantities (dBZ)
Probabilistic quantities (lagged ensemble, COSMO-E)
Situation dependent

20. My personal view
Model
Processing
Users
Meteorologist
Verification

21. Principles of consortium postprocessing
Help to understanding the characteristics of model output by analysing (space, time, parameter, ensemble member) combinations of the output fields
Provide the users of models (including meteorological forecasters) with recommendations of use of model output
The consortium management may define specific strategic areas of consortium postprocessing, for example aviation, energy,…

22. Thanks for attention

23. My personal view