The fundamentals of Seasonal Forecasting

1. RA VI Clips Workshop The fundamentals of Seasonal Forecasting J.P. Céron – Météo-France

2. Some Vocabulary • Long Range Forecasts and Climate Forecasts • Forecast Range, Forecast period and Lead time. Lead Time Forecast Period Forecast issue time Forecast Range

3. LT - 1 month Seasonal Forecast 1 May June July Aug Sept Octo Nov Forecast issue time Coupled Forecast : Range of 6 months

4. LT - 2 month Seasonal Forecast 2 May June July Aug Sept Octo Nov Forecast issue time Coupled Forecast : Range of 6 months

5. LT - 3 month Seasonal Forecast 3 May June July Aug Sept Octo Nov Forecast issue time Coupled Forecast : Range of 6 months

6. The Scientific bases • The evolution of the atmosphere is partly driven by the evolution of external forcing conditions (SST and continental surfaces). • The evolution of external forcings is often slow and predictable. It gives a slow memory to the atmosphere ; the evolution of the latter becoming partly predictable. • The successive instantaneous states of the atmosphere have a limited predictability while the mean states of the atmosphere have a greater predictability. • The mean circulation in tropical regions is strongly inflenced by the large scale organised convection.

7. Limitation of numerical forecast : Daily forecast Daily Scores over Northern Hemisphere

8. Limitation of numerical forecast : Daily forecast Daily Scores over Northern Hemisphere + Persistence Scores

9. Limitation of numerical forecast : Daily forecast Daily Scores over Northern Hemisphere + Perfect model Scores

10. Limitation of numerical forecast : Monthly forecast Daily Scores over Northern Hemisphere + Monthly running mean Scores

11. Limitation of numerical forecast : Seasonal forecast Daily Scores over Northern Hemisphere + seasonal running mean Scores

12. Limitation of numerical forecast : Seasonal forecast Daily Scores over Northern Hemisphere + Ensemble forecast, seasonal running mean and SST forecast

13. The Predictability « a Thunderstorm will be observed next Sunday over the Toulouse « Météopole » between 15h and 16h »  Irrealistic, the confidence that one can have in this forecast is very low « a rainy system will cross the Toulouse region Sunday afternoon  »  realistic, one can be quite confident in this forecast

14. The Predictability The predictability depends on : • The scale of the forecasted phenomenum (Thunderstorm, Easterly Wave, Blocking situation, ENSO, …) • The Range of the forecast (NowCasting, Short , Medium , Seasonnal , Climatic)

15. Predictability • Space Scales • Local  10-100 km • Regional  100-1000 km • Synoptic  1000-5000 km • Supra-synoptic > 5000- km seasonal Forecasting - supra-synoptic scales

16. Predictability • Actors and Associated Scales

17. Predictability • The different views of the Predictability • Through the observations • Through the models

18. The evolution of external forcing conditions • Evolution of Sea Surface temperature (SST) • Interannual variability (like ENSO) • Decadal variability (like PDO) • Evolution of continental surface conditions • Influence of continental surface conditions (snow, albedo, ..), • Intraseasonal variability (notably soil moisture), • Mutual influences • Decadal/ENSO • ENSO/Intraseasonal • Intraseasonal/Synoptic

19. The ENSO • The planetary influence of El Niño (left) and La Niña (right)

20. The ENSO • Through the observations in Winter

21. The ENSO • Through the observations in Summer

22. The ENSO • Through the observations in Winter

23. The ENSO • Through the observations in Summer

24. The fundamentals of seasonal Forecasting • The climatic variability • The forecasting models • Statistical models • SST forced Atmospheric General Circulation Models • Ocean/Atmosphere Coupled General Circulation Models • The verifications • Verification of the forecasts • Verification of the usefulness of the forecats • The chaos • Link with the climatic variability • Link with the ensemble forecast

25. The fundamentals of Seasonal Forecasting • The climatic variability : slow variation in the Atmosphere • NAO • PNA mode • PDO • QBO or TBO • http://www.cpc.ncep.noaa.gov/data/teledoc/telecontents.html and Barnston and Livezey 1987, Mon. Wea. Rev., 115, 1083-1126) East Atlantic (EA) , East Atlantic Jet (EA-Jet) , East Atlantic/Western Russia , Scandinavia (SCAND) , Polar/Eurasia Asian Summer , West Pacific (WP) , East Pacific (EP) , North Pacific (NP) , Tropical/Northern Hemisphere (TNH) , Pacific Transition (PT)

26. The « North Atlantic Oscillation»

27. The « North Atlantic Oscillation» Temperature in Winter Rainfall in Winter

28. The Pacific Decadal Oscillation 

29. The Pacific Decadal Oscillation 

30. The climatic variability

31. The climatic variability

32. The fundamentals of Seasonal Forecasting • The climate variability

33. The fundamentals of Seasonal Forecasting • The climatic variability

34. The fundamentals of seasonal Forecasting • The climatic variability

35. The fundamentals of seasonal Forecasting • The climatic variability Atlantic “El Nino” – Pirata buoy network

36. The fundamentals of seasonal Forecasting • The climatic variability JAS Observed Sahel Rainfall Vs JAS Observed THC index r = 0.45

37. The fundamentals of seasonal Forecasting Forecasting models • Statistical models • SST forced Atmospheric Global Circulation Models • Océan/Atmosphère Coupled General Circulation Models

38. The fundamentals of seasonal Forecasting The Statistical models East African Rainfall vs Nino3 Index Thank’s to Simon Mason

39. The fundamentals of seasonal Forecasting The Statistical models East African Rainfall vs Nino3 Index

40. The fundamentals of seasonal Forecasting The Statistical models East African Rainfall vs Nino3 Index

41. The fundamentals of seasonal Forecasting The Statistical models

42. The fundamentals of seasonal Forecasting The Statistical models

43. The fundamentals of seasonal Forecasting The Statistical models

44. The fundamentals of seasonal Forecasting The Statistical models

45. The fundamentals of seasonal Forecasting The Statistical models

46. The fundamentals of seasonal Forecasting • Numerical models

47. The fundamentals of seasonal Forecasting • The numerical models

48. The fundamentals of seasonal Forecasting • Coupled vs Forced models

49. Coupled vs Forced models

50. The fundamentals of seasonal Forecasting Forecast Verifications • Verification in « real time » (following up of the bias, pointing out and monitoring of the errors, …), • Verification in hindcast forecast mode , • Verification of the predictability of forecasting events, • Verification of the forecast value in a user’s point of view, • Verification of the use and impact of the forecast, • « Deterministic » vs « Probabilistic » Verifications • Comparison with climatology and persistence (often use as references by users), … • Problem of relevant and reliable dataset for verification purpose.