Joint Research Centre (JRC)

Transcription

1 Toulouse on 15/06/2009-HEPEX 1 Joint Research Centre (JRC) Comparison of the different inputs and outputs of hydrologic prediction system - the full sets of Ensemble Prediction System (EPS), the reforecast and the calibration of this system by the verification tools of ensemble forecasts. N.B. Trinh(*) F. Pappenberger(**) K. Bogner(*) (*): European Commission, DG Joint Research Centre, Institute for Environment and sustainability, Ispra, Italy (**): European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, RG29AX, Uk

2 Outlines Toulouse on 15/06/2009 HEPEX 2 Introduction. Overviews of EPS and EFAS. Case study Danube Skill Calibration methods Conclusion.

3 Use Ensemble Prediction System as inputs in Hydrological model Toulouse on 15/06/2009 HEPEX 3 Advantages of the use EPS as inputs into hydrological model : Long lead time : Medium-rang 1-10 days forecast for EPS and 16 days forecast for NCEP and Canadian Meteorology Centre. In future, 15 (32) days forecast (VAREPS). EPS is a best measure of objective uncertainties (model, initial conditions and imperfect boundary condition: snow cover, vegetation properties, soil moisture,..). Inconveniences of the use EPS as inputs into hydrological model : Different scale. Hydrological model is a non-linear filter and therefore the resulting probabilistic quantitative forecasts for each member of EPS may not be equally distributed. EPS are often under-dispersive or over-dispersive.

4 Calibration of EPS as input and output Toulouse on 15/06/2009 HEPEX 4 Calibration of EPS as the post-processing before using them like inputs in hydrologic model? Using the reforecast to calibrate EPS before using them like inputs in hydrologic model? Calibration of the outputs of hydrologic model?

5 Approach s description Toulouse on 15/06/2009 HEPEX 5 Uncalibrated EPS Uncalibrated hydrological forecasts Calibration of Temperature and precipitation Calibration by Reforecast Observational data: Meteorological stations Hydrological distributed Model Lisflood Hydrological forecasts with calibrated inputs Hydrological forecasts with calibrated inputs Observational data (proxies): Hydrological simulations Observational Hydrological data Verification tools only for precipitation and temperature Verification tools

6 Verification tools of ensemble forecasts : Spread + Skill Toulouse on 15/06/2009 HEPEX 6 Spread: Talagrand diagram : Talagrand diagram (Talagrand and al.(1997)) likes rank diagram in which the rank is the ensemble number + 1. Spread-skill relationship: Houtekamer (1998) proposes to compare the standard deviation of the mean ensemble error absolute and the mean of standard deviation of ensemble (σ). Skill : Continuous Ranked probability score (CRPS) (Hersbach,2000): we can have also the decomposition of CRPS in reliability and in resolution. Relative Operating Characteristic (ROC): Plot hit rate (POD) vs false alarm rate (POFD), using a set of increasing probability thresholds (for example, 0.05, 0.15, 0.25, etc.) to make the yes/no decision.

7 Calibration of EPS as the post-processing Toulouse on 15/06/2009 HEPEX 7 Calibration of temperature : hierarchical modeling in order to obtain a total uncertainty ensemble forecast. Calibration of precipitation : Contingency table for the occurrence of the precipitation 0.2 [mm] to eliminate the concentration of the mass of the precipitation s distribution at zero. Quantification of the probability distribution function (pdf) of the precipitation forecasts and the observational precipitation. Calibration of precipitation forecasts is simulated by the Probabilistic Quantitative Precipitation Forecasts (PQPF), which is quantified by Bayesian theory and the dependence relationship after Copulas.

8 Case Study Danube Toulouse on 15/06/2009 HEPEX 8 In order to limit the calculation, we studied only Danube catchment The period studied is 01/03/ /10/2008. The lead time is between 3 to 14 days We concentrate on four hydrological observational stations: Oberndorf (Germany), Kienstock (Austria), Korneuburg (Austria) and Bezdan (Serbia).

9 Danube River Basin LISFLOOD modeled catchments Toulouse on 15/06/2009 HEPEX 9 Oberndorf Kienstock Carpathians ALPS Korneuburg Bezdan

10 Pdf of precipitation Toulouse on 15/06/2009 HEPEX 10 A case of contingency table observational precipitation >= 0.2 mm and forecasts precipitation >= 0.2 mm : Pdf of Birbaum-Saunders. Copulas AMH family is the best a prior.

11 Images of cdf adjustment + Copulas a priori Toulouse on 15/06/2009 HEPEX 11 1 Empirical CDF 0.9 Copulas a priori F(x) toto 4 real cells c3569 real c2124 real c88 real c1573 real BBS s imul toto HA s imul toto Poids pondérés x frk 1,fg m 2,g auss 3,cb1 4,cb3 5,amh 6,amhb 7,frkb 8,sar 9,plcb 10,sym1 11,sym2 12,sym3 13,asym1 14,asym2 15,asym3 16

12 Approach s description Toulouse on 15/06/2009 HEPEX 12 Uncalibrated EPS Uncalibrated hydrological forecasts Hydrologic model Lisflood Observational data: Meteorological stations Observational data (proxies): Hydrological simulations Observational Hydrological data Verification tools

13 Very preliminary results skill Kienstock 50 Toulouse on 15/06/2009 HEPEX 13 Score CRPS CRPS reliability Lead time 4.5 CRP S res olution Lead time Lead time

14 Preliminary results spread Kienstock Toulouse on 15/06/2009 HEPEX S pread Mean of S tandard deviation S tandard deviation of the mean error abs olute lead time

15 Summary and way forward Toulouse on 15/06/2009 HEPEX 15 Study of applying different methodologies for calibrating temperature and precipitation as input into LISFLOOD are ongoing. Results need yet to be explored in detail. More observational data need to be incorporated into the study The impact of using calibrated inputs on the hydrological response will be quantified