1. Finnish Meteorological Institute
EPS based probabilistic forecasts and verification at Finnish Meteorological Institute (FMI)
Janne Kauhanen
Juha Kilpinen
Matias Brockman
Finnish Meteorological Institute

2. Outline Introduction About RAVAKE-project Some verification results
ECAM 2011 Kauhanen-Kilpinen-Brockman

3. Introduction
EPS forecasts been used widely at FMI since mid 1990’ies. However, the data has been mostly used as guidance information. Now FMI is moving towards more direct and operational use of probabilistic information also for customer products and warnings.
Computations of the probabilities of accumulated precipitation forecasts (and also many other parameters) of ECMWF EPS system are performed at FMI to allow the determination of user specific thresholds.
The example of spesific treshold of wind (11m/s) in local SmartMet workstation at FMI.
ECAM 2011 Kauhanen-Kilpinen-Brockman

4. Introduction (continues)
A probabilistic rainfall warning system is under development at FMI (with an interactive user-interface).
The aim is to produce a solid probabilistic rainfall forecast from +15 min to +5 days combining all available data sources (radar observations and extrapolations, deterministic NWP output with post-processing (PEPS, etc.) and ECWMF EPS)
The main focus is to offer the end-users an interface where they can modify the products for their own needs.
Verification of this data has also started and at first ECMWF EPS data is considered. Some results are shown here.
24h and 12 hours probability forecasts for rain over 10 mm in 6 hours and observed precipitation measured by radar network.
ECAM 2011 Kauhanen-Kilpinen-Brockman

5. Convective rain in Pori
Introduction (continues)
Convective rain in Pori
August 2007:
~120 mm in 3 hours
damage M€
RAVAKE – project plan
ECMWF deterministic /EPS/GFS?
PEPS/NEIGHBOURHOOD METHOD
GLAMEPS
HIRLAM/RCR/MBE
AROME
RADAR EXTRAPOLATION
Lead time
Juha Kilpinen RAVAKE-projekti

6. Introduction (continues)
An example of heavy precipitation causing flooding in Helsinki Area was some weeks ago. Two convective cells hit Helsinki Metropolitan area causing a flash flood with substantial harm to property and traffic. The measured maximum precipitation was mm in about 90 minutes.
The NWP models did not capture the cells well. Only high resolution Harmonie (2.5 km) was able forecast the phenomenon reasonably well. The case was also difficult to observe by the radar due to the strong attenuation.
Helsinki
ECAM 2011 Kauhanen-Kilpinen-Brockman

7. Verification of ECMWF EPS precipitation forecasts
Two data sets:
Years : 12h and 24h accumulative precipitation forecasts for about 130 stations.
Year 2010: 6 hourly accumulative precipitation up to +66h
4 stations (02981, 02974, 02935, 02836)
ECAM 2011 Kauhanen-Kilpinen-Brockman

8. Examples of the present verification products
ECAM 2011 Kauhanen-Kilpinen-Brockman

9. ROC and Brier Score
Annual results for daily (24h) probability of precipitation (>= 10 mm) and group rain gage precipitation stations with 00 UTC analysis hours and using arrival time as lead time basis
ECAM 2011 Kauhanen-Kilpinen-Brockman

10. Results: 6 hourly accumulative precipitation
ROC AREA
Results: 6 hourly accumulative precipitation
ECAM 2011 Kauhanen-Kilpinen-Brockman

11. ROC curves RR>1.0mm RR>0.1mm RR>5.0mm RR>0.5mm
ECAM 2011 Kauhanen-Kilpinen-Brockman

12. Results: 6 hourly accumulative precipitation
Brier Score
Results: 6 hourly accumulative precipitation
ECAM 2011 Kauhanen-Kilpinen-Brockman

13. Conclusions
Due to small data sample and the coarse resolution of ECMWF EPS (compared to the scale of a typical convective system) the verification of heavy precipitation did not give very promising results. But for early warning use in longer time ranges ECMWF EPS provides a good data to start.
For time ranges between extrapolated radar data and ECMWF EPS the up-scaled AROME and PEPS products offers an interesting challenge for near future.
Originally calibration of EPS was on the work list but it had to be postponed to some later project.
The combination/merging of different data sources on daily and hourly basis is enough challenging.
ECAM 2011 Kauhanen-Kilpinen-Brockman

14. Thank You for your attention !
ECAM 2011 Kauhanen-Kilpinen-Brockman