Pertti Nurmi Juha Kilpinen Sigbritt Näsman Annakaisa Sarkanen ( Finnish Meteorological Institute )

1. Pertti Nurmi Juha Kilpinen Sigbritt Näsman Annakaisa Sarkanen ( Finnish Meteorological Institute ) Probabilistic Forecasts and Their Verification as Decision-Making Tools for Warnings against Near-Gale Force Winds WSN05: WWRP Symposium on Nowcasting and Very Short Range Forecasting Toulouse, 5-9 September 2005 WWRP_WSN05, Toulouse, 5-9 September 2005

2. Introduction: • Develop warning criteria / Guidance methods to forecast probability of near-gale force winds in the Baltic  Joint Scandinavian research undertaking • e.g. Finland and Sweden issue near-gale & storm force wind warnings for same areas using different criteria  Homogenize ! • 6 Finnish coastal stations  c. 15-20 stations from Sweden, Denmark, Norway • Probabilistic vs. deterministic approach • HIRLAM  ECMWF model input • Different calibration methods, e.g. Kalman filtering • Goal: Common Scandinavian operational warning practice WWRP_WSN05, Toulouse, 5-9 September 2005

3. HIRLAM (limited area model) RCR ~ 22 km version MBE ~ 9 km version Data coverage: 9.11.2004 – 31.3.2005  ~ 140 cases ECMWF Applied as reference, only Data interpolated to 0.5o *0.5o  Nearest grid point Data coverage: 1.10.2004 – 30.4.2005  ~ 210 cases Forecast lead time: +6 hrs (and beyond  ECAM paper) Forecasts: wind speed at 10m Observations: 10 minute mean wind speed Data: WWRP_WSN05, Toulouse, 5-9 September 2005

4. with height of instrumentation ? with observing site surroundings and obstacles ? with the coast ? with nearby islands ? with barriers ? with installations ? with low-level stability ? NE Potential problems: “Statistical correction” scheme available at FMI WWRP_WSN05, Toulouse, 5-9 September 2005

5. Height of the instrumentation - Large filled dots: 6 Finnish stations being used- Yellow dot: Station_981; Results presented here (m) 55 50 45 40 35 30 25 20 15 10 5 WWRP_WSN05, Toulouse, 5-9 September 2005

6. 979 - Bogskär Unstable 32 m Neutral Stable 10 m Wind speed dependence: Logarithmic wind profile 14 m/s 15 15,5 m/s threshold WWRP_WSN05, Toulouse, 5-9 September 2005

7. Methods for producing probabilistic forecasts 1: • ECMWF EPS (51 members)  P (wind speed) > 14 m/s • Kalman filtering • Various approaches  No details given here • Deterministic forecast, “dressed” with “a posteriori” description of theobserved error distribution of the past, dependent sample P (wind speed) > 14 m/s • “Simplistic reference” ! Deterministic forecasts: • Error distribution of original sample (~140 cases) • Approximation of the error distribution with a Gaussian fit (m, s): • ”Dressing” method WWRP_WSN05, Toulouse, 5-9 September 2005

8. Methods for producing probabilistic forecasts 2: • Deterministic forecast, adjusted with a Gaussian fit to model forecasted stability ( Temperature forecasts from 2 adjacent model levels)  P (wind speed) > 14 m/s “Stability” method • Scheme used at SMHI (H. Hultberg) • “Uncertainty area” method (aka ”Neighborhood method”) (aka ”Probabilistic upscaling”) • Spatial (Fig.) and/or temporal neighboring grid points • Size of uncertainty area ? • Size of time window ? • c. 50-500 “members” • RCR: ± 3 points ~ 150*150 km2 • MBE: ± 6 points ~ 120*120 km2 WWRP_WSN05, Toulouse, 5-9 September 2005

9. Relative Operating Characteristic Probabilistic FCs: ROC • To determine the ability of a forecasting system to discriminate between situations when a signal is present (here, occurrence of near-gale) from no-signal cases (“noise”) • To test model performance ( H vs. F ) relative to a given probability threshold • Applicable for probability forecasts and also for categorical deterministic forecasts • Allows for their comparison • “R” statistical package used for ROC computation/presentation WWRP_WSN05, Toulouse, 5-9 September 2005

10. ROC curve/area; Station_981; +6 hrs; No. of events ~25/130 ”Simple reference” (dep. sample): HIR_MBE_”Dressing” HIR_MBE_”Uncertainty area” ~ 120 * 120 km ROCA = 0.93 ROCA fit = 0.91 ROCA = 0.82 ROCA fit = 0.91 WWRP_WSN05, Toulouse, 5-9 September 2005

11. ROC curve/area; Station_981; +6 hrs; No. of events ~25/130 ”Simple reference” (dep. sample): HIR_MBE_”Dressing” HIR_MBE_”Stability” ROCA = 0.93 ROCA fit = 0.91 ROCA = 0.84 ROCA fit = 0.82 WWRP_WSN05, Toulouse, 5-9 September 2005

12. Comparison of methods; Station_981; +6 hrs WWRP_WSN05, Toulouse, 5-9 September 2005

13. Conclusions  Future: • We’ve only scratched the (sea) surface • Need (much) more experimentation with various methods • Different methods for different time/space scales ? • Apply to data of other Scandinavian counterparts (here, only single station) • Scores depend on station properties (e.g. observation height; Not dealt with here) • (Statistical) adjustment of original observations required ! • Finland has an operational scheme for this ! • “Dressing” of dependent sample: quality level hard to reach • “Uncertainty area” size: a tricky issue • Higher resolution HIRLAM version produces higher scores • Not necessarily a trivial result ! • Reach the goal, i.e. common operational practice !!! WWRP_WSN05, Toulouse, 5-9 September 2005