Hydrological Ensemble Prediction Chains at WSL Three years of real-time experience

1. Hydrological Ensemble Prediction Chains at WSL Three years of real-time experience Kaethi Liechti & Massimiliano Zappa Swiss Federal Research Institute WSL

2. SYNOPSIS • Operational hydrological ensemble prediction systems (HEPS) have a very short history • The "European Flood Alert System" EFAS has been operational since 2003 (Thielen et al., HESS, 2009) • Applications for mesoscale areas are more recent (Jaun et al., HESS, 2009) • Several semi-operational ensemble forecasting chains were developed for the demonstration period of the MAP D-PHASE project in summer and fall 2007 (Rotach et al., BAMS, 2009) • Some of these chains continued to work after the end of MAP D-PHASE and are generating to-date operational ensemble forecasts for different areas (Zappa et al., ASL, 2008) ( http://hydro.slf.ch/sihl/ticino/ )

3. MAP D-PHASE (2007-2008) Meteo- Swiss AEMet ARPA Piemonte DLR ARPA- SIMC Uni Wien ZAMG APAT CNMCA ETHZ Uni Brescia WWA Kempten ARPA Liguria LUBW IMK-IFU Uni Hohenheim ARPA Veneto POLIMI Uni Paul Sabatier WSL Env Canada ARPA Lombardia DWD Met Office MétéoFrance ISAC- CNR FOEN SRNWP Steering Committee & WG chairmen Operational Service University Res. Inst. Data Provider Rotach, M.W. et al., 2009. MAP D-PHASE: Real-time Demonstration of Weather Forecast Quality in the Alpine Region. Bulletin of the American Meteorological Society, doi: 10.1175/2009BAMS2776.1

4. MAP D-PHASE (2007-2008) Meteo- Swiss ETHZ IMK-IFU WSL FOEN Steering Committee & WG chairmen Operational Service University Res. Inst. Data Provider Rotach, M.W. et al., 2009. MAP D-PHASE: Real-time Demonstration of Weather Forecast Quality in the Alpine Region. Bulletin of the American Meteorological Society, doi: 10.1175/2009BAMS2776.1

5. MAP D-PHASE: Implementing an operational hydrological ensemble prediction system for research and practitioners UCA Ticino Plot: Simon Jaun

6. EPS/NWP - Hydrological Model Chain Monday April 21st 2008, Day -1 -> Do NWP Models agree? Updated DAILY since April 2007 Plot: Simon Jaun, WSL/IACETH

7. EPS/NWP - Hydrological Model Chain Tuesday April 22nd 2008, Day 0 -> YES, they do! ….. Too Late? Updated DAILY since April 2007 Plot: Simon Jaun, WSL/IACETH

8. MAP D-PHASEVerification of our HEPS chain June 2007 to November 2008 Thur Andelfingen PREVAH_COSMO_LEPS_WSL_ETHZ Rank Histograms – Ticino Bellinzona PREVAH_COSMO_LEPS_WSL_ETHZ Is a time series of 18 months long enough sound verification? Low flows periods strongly influences the statistics (Talagrand) Plots: Diezig, Vogt, Jaun and Fundel, 2010

9. Seamless information for flood mitigation measures with up to five days lead time: an operational implementation for the city of Zurich (Switzerland) 9

10. 181 Seamless information for flood mitigation measures An operational implementation for the city of Zurich (Switzerland) • Area: 336 km2 • Reservoir lake: • Devides catchment in two parts. • Used for hydropower production for the railway company. • Retention basin for ~ 46% of the catchment. • Leadtimes: • Floodwave: 2 to 6 h from Blattwag to Zurich 10

11. 181 Seamless information for flood mitigation measures An operational implementation for the city of Zurich (Switzerland) 11

12. Forecasting System Timetable (S. Vogt, FOEN) 12

13. COSMO-LEPS Forecast

14. COSMO-7 Forecast (time lagged plots)

15. COSMO-2 Forecast (time lagged plots)

16. Translating the Infomation - Discharge Warning Persistence

17. Explaining HEPS or the spaghetti plot surveys in 2008 The task How big will the peak discharge from this forecast be? At which time will the peak discharge occur?

18. Explaining HEPS or the spaghetti plot surveys in 2008 The answers

19. Conclusions and comments • The development of operational hydrological ensemble prediction systems is progressed thank to international collaborations in the framework of MAP D-PHASE, COST-731, HEPEX and IMPRINTS (FP7) • Obtaining a climatology of HEPS is prohibitive (Cloke and Pappenberger, JHYDROL, 2009). Systems evolve too quickly and non-events are a dominant but needed component of this statistic • Experience on uncertainty propagation and superposition is needed • A methodological framework for verification of operational HEPS is needed (Schaake et al., BAMS, 2007; Brown et al., ENSO, 2010) • Dealing daily with problems and challenges of an end-to-end operational HEPS is FUN, but be aware if you want to afford this FUN, because your job turns suddenly in a 365 days per year challenge with data providers, stakeholders and endusers (if you are lucky to have one!)

20. COST 731: “PROPAGATION OF UNCERTAINTY IN ADVANCED HYDRO-METEOROLOGICAL FORECAST SYSTEMS” (2005-2010) SPECIAL ISSUE, due in May 2010: Joint HEPEX/COST731 workshop on downscaling NWP products and propagation of uncertainty in hydrological modelling Toulouse, 2009 Rossa A, Haase G, Keil C, Pfeifer, M., Bech, J., Ballard, S. 2010a. Propagation of uncertainty from observing systems into NWP: COST-731 Working Group 1. Atmospheric Science Letters . doi:10.1002/asl.nnn Zappa M, Beven KJ, Bruen M, Cofino A, Kok K, Martin E, Nurmi P, Orfila B, Roulin E, Schröter K,Seed A,  Stzurc J, Vehviläinen B, Germann U, Rossa A. 2010. Propagation of uncertainty from observing systems and NWP into hydrological models: COST-731 Working Group 2. Atmospheric Science Letters. doi:10.1002/asl.248 Bruen M, Krahe P, Zappa M, Olsson J, Vehvilainen B, Kok K, Daamen K. Visualising flood forecasting uncertainty: some current European EPS platforms – COST731 Working Group 3. 2010. Atmospheric Science Letters . doi:10.1002/asl.258