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Aims and Requirements for Ensemble Forecasting By T.N.Palmer ECMWF.

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Presentation on theme: "Aims and Requirements for Ensemble Forecasting By T.N.Palmer ECMWF."— Presentation transcript:

1 Aims and Requirements for Ensemble Forecasting By T.N.Palmer ECMWF

2 A Brief History of Ensemble Prediction for Weather/Climate Monthly forecasting Medium Range Seasonal-to-Interannual Short rangeClimate Change 1980s 1990s 2000s Roots of ensemble forecasting J.M Lewis. Mon Wea Rev, 133, 1865 (2005)

3 First operational probabilistic ensemble forecast? Used in Met Office commercial operations.

4 Scientific Basis for Ensemble Prediction In a nonlinear dynamical system, the finite-time growth of initial uncertainties is flow dependent. Lorenz (1963): prototype model of chaos October 1987!

5 In a nonlinear system, finite-time predictability is a function of initial state


7 EPS spread/Error

8 ECMWF Ensemble Forecasts of Katrina 26 Aug 0z 26 Aug 12z 27 Aug 0z 27 Aug 12z

9 Who is coming? P threshold Queen 1% Mayor Mother-in-law Mates from the pub 10% 30% 70% Decision: Rent marquee if P>20%

10 Queen Mayor Mother -in-law Mates from pub From ECMWF web site.

11 Weather Roulette London-Heathrow, 2m temperature 2002: training data for dressing 2003: test data odds: set by dressed T511 forecast bets: placed by best member dressed EPS start capital: £1 (re-invest all money, unlimited stakes) odds(bin) = 1 / prob_hr(bin) bets(bin) = prob_eps(bin) * capital(t-1) Daily winnings: win(t) = odds(bin_v) * bets(bin_v) – capital(t-1) = (prob_eps(bin_v)/prob_hr(bin_v) – 1) * capital(t-1) Collaboration with L.Smith, LSE

12 Weather Roulette Days in Winnings [log_10 £] 168h lead time Collaboration with L.Smith, LSE

13 Weather Roulette Lead time [days] Winnings [log_10 £] Bootstrapping Results Collaboration with L.Smith, LSE

14 DEMETER-based PDFs of malaria incidence for Botswana (forecasts made 5 months in advance of epidemic; Thomson et al 2005) 5 years with lowest observed malaria incidence 5 years with highest observed malaria incidence

15 Why No Ensembles on the TV Weather Forecasts?



18 MLSP 66-hour forecasts, VT: 16-Oct-1987, 6 UTC TL399 EPS with TL95, moist SVs

19 Probability of Beaufort force 12 winds 6- 12am October 16 th 1987


21 Weather forecasts are inevitably uncertain, sometimes more so than others. We now run our forecast models many times with slightly different starting conditions to assess the uncertainty in the forecasts. Press the red button on your remote control to see an estimate of the expected accuracy of the forecast for some of the main cities in the UK.

22 Aims of Ensemble Forecasting To enhance (substantially) the value of numerical weather and climate forecasts by quantifying the flow-dependent uncertainty in the forecast To enhance the credibility of weather and climate forecasts, thereby allowing our profession to gain the respect of the public

23 Requirements for Ensemble Forecasting A better theoretical understanding of the role of error made in truncating/parametrizing the underlying PDEs of climate, on both initial uncertainty and forecast model uncertainty Much much much bigger computers (resolution, ensemble size and model complexity are all important) A recognition amongst media forecasters that uncertainty is an intrinsic part of the science of weather and climate prediction..and that the public will respect us more if we are more open about uncertainty A recognition amongst BBC TV producers that use of ensemble forecast information on weather forecasts can inform, educate and entertain the viewing public and is something worth giving more effort to.

24 He believed in the primacy of doubt; not as a blemish upon our ability to know, but as the essence of knowing Gleick (1992) on Richard Feynmans philosophy of science.

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