1. Verification of COSMO-LEPS and coupling with a hydrologic model
André Walser1) and Simon Jaun2)
1)MeteoSwiss
2)Institute for Atmospheric and Climate Science, ETH

2. Overview
Part 1: Status report of Task 4.2 of PP Interpretation: Use of COSMO-LEPS in hydrologic models
Part 2: COSMO-LEPS verification against SYNOP messages

3. Model chain ECMWF EPS  COSMO-LEPS  PREVAH Global ensembles ECMWF EPS
Downscaling with COSMO-LEPS
PREVAH as hydrologic model
Fig. M. Verbunt
ECMWF EPS  COSMO-LEPS  PREVAH
Uncertainties in the hydrologic model/processes not considered

4. Data flow for MAP D-PHASE
Main partner WSL: Swiss Federal Institute for Forest, Snow and Landscape Research

5. “MAP D-PHASE Catchments”

6. Product delivered for D-PHASE VP

7. Comparison different models
August 2007 event Linth at Mollis, initial time

8. Comparison different models
August 2007 event Linth at Mollis, initial time

9. Comparison different models
August 2007 event Linth at Mollis, initial time

10. Verification August 2005 Event
Probability to exceed 10y event
> 10 y event
Jaun et al.: A probabilistic view on the August 2005 floods in the upper Rhine catchment, to be submitted

11. Conclusions & Outlook
Operational ensemble runoff forecast are established for MAP D-PHASE
Seems to provide reliable information about the forecast uncertainty and early indication for flood events
 Verification over an extended period needed

12. Part II Most recent COSMO-LEPS Verification Results:
12-h sum of precipitation from SYNOP messages, COSMO-LEPS domain
Brier Skill Score for 1, 5, 10, 25 mm
Climatological event frequency estimated from data from

13. BSS for precipitation > 1 mm/12h
night-time precipitation
daytime precipitation
No skill
lead-time

14. BSS for precipitation > 5 mm/12h
lead-time

15. BSS for precipitation > 10 mm/12h
lead-time

16. BSS for precipitation > 25 mm/12h
lead-time

17. Large spatial variability of the skill
BSS for precipitation > 1 mm/12h MAM 2006 (+42h)

18. Station Sion: BSS for precipitation > 1 mm/12h
lead-time

19. “No skill station”: Sion
12-h precipitation sum > 1mm MAM 2006:

20. Station Sion: BSS for postprocessed precipitation > 1 mm/12h
Very simple post-processing:
p’=0.5p
lead-time

21. Conclusions
For low precipitation thresholds skill up to forecast day 5 for all seasons
No skill for high threshold 25mm/12h for all seasons
In spring and summer higher skill for night-time precipitation than for daytime
High spatial variability
There is potential to improve precip. forecast in Alpine region with post-processing  sophisticated method Talk/Poster of F. Fundel