Recent and future progress in meteorological forecasting

1. Recent and future progress in meteorological forecasting Emmanuel Legrand Deputy-head of Forecasting, Meteo-France WRMA-2006 Toulouse October 3-5, 2006

2. A continuous progress

3. A continuous progress

4. A continuous progress • The main factors • progress in (super)-computers • a factor 1000 in 15 years • progress in Earth observation • mainly by satellite • reducing the NorthHem / SouthHem difference • progress in science • The main tool: numerical weather prediction • No reason to stop

5. A continuous progress • Towards longer range • seasonal forecasting • aiming at forecasting very general features like warmer/colder, dryer/wetter than average over the next months • because fine details are unpredictable so long in advance • good quality over tropical areas, poorer skill in mid-latitude regions (esp. Western Europe) • for users able to take advantage of information with marginal added value • a relatively new activity • progressing like the other aspects of forecasting

6. A continuous progress • Towards longer range • seasonal forecasting Ex: OND-2006, temperature

7. A continuous progress • Towards longer range • "monthly" forecasting • trying to fill the gap between "classical" and seasonal forecasting • aiming at general features at week scale • technique close to seasonal forecasting • same importance of ocean/atmosphere coupling • a pre-operational system running at ECMWF • current status over Europe: some signal in temperature • in general up to week 2 • sometimes on longer range • already some pre-operational usage • ex: EDF • again progress to be expected in future

8. A continuous progress • Towards longer range • "monthly" forecasting

9. A continuous progress • Towards longer range • not forgetting the climate change issues • next IPCC report next year

10. A continuous progress • Towards shorter range at finer scale • Questions like: • will it be raining in 1 hour ? • what about fog next night ? • where may I face thunderstorms this afternoon ? • A new generation of models in development • a sudden increase in resolution • plus more complex equations • at Meteo-France: AROME (operational end 2008) • co-operation with most of the European NMSs • more or less similar developments in the other major NWP centres

11. A continuous progress • Towards shorter range at finer scale at current resolution

12. A continuous progress • Towards shorter range at finer scale at AROME resolution

13. A continuous progress • Towards shorter range at finer scale

14. A continuous progress • Towards shorter range at finer scale "Autan" wind effect of the city of Toulouse

15. From forecasting to decision making • Good forecast / useful forecast • Each customer has specific questions • with his/her own sensitivity to weather (cost/loss function) • with his/her own knowledge in meteorology • The meteorological information is not always simple… • need for a good link meteorologist/customer • The challenge for met services

16. From forecasting to decision making • Our customers have to cope with our forecast errors • we have to provide them with information characterizing the errors • Especially those involved in Weather Risk Management ! • The need for a more probabilistic approach • probability that something happens • and if not, what else ? • confidence in the forecast • which varies from day to day • "error bars" • which are not always as simple as just error bars • And again the need for "translating" the info in customer's words • again technical issues plus communication issues

17. From forecasting to decision making • Most of our information comes from ensemble prediction systems • richer information than just statistics on past errors • aiming at describing the day-to-day variations of confidence • have been available for some time for medium range forecasting • typically Day 3-10 • ongoing developments for short range forecasting • common practice in seasonal forecasting • but not on day-to-day of course

18. From forecasting to decision making • Most of our information comes from ensemble prediction systems

19. From forecasting to decision making • Most of our information comes from ensemble prediction systems

20. From forecasting to decision making • Most of our information comes from ensemble prediction systems

21. From forecasting to decision making • Two ways of building these ensemble prediction systems • developing a specific system • work on initial perturbations, model perturbations • heavy cost (computer resources) • exchanging numerical forecasts with other centres • "poor man's ensemble forecast" • cheaper • also because specific systems often lack of variability • A trend to more and more combine both approaches • WMO/Thorpex for 1-14 day forecast • Thorpex Interactive Grand Global Ensemble (TIGGE)

22. From forecasting to decision making • Not forgetting that probabilistic elements provided by ensemble techniques are… a forecast • having their own errors

23. From forecasting to decision making • Not forgetting that probabilistic elements provided by ensemble techniques are… a forecast • and continuously progressing

24. From forecasting to decision making • More downstream issues are customer-specific • ex: military tactical decision aid system • here a 3-component mission

25. From forecasting to decision making • More downstream issues are customer-specific • the complexity of the link meteo info / customer activity • the level of integration into meteo / customer information system • the need of additional communication • ex: Ferrari for weather-critical Grand Prix • The met services pay more and more attention to that

26. Summary • The technical part of weather forecasting is continuously progressing • There is more and more information on forecast uncertainties/errors • Met Services are now paying more attention to forecast usefulness / decision making issues

27. Image: ESA - AOES Medialab