1. Severe Weather Forecasts
Ervin Zsoter

2. Outline
Extreme weather forecast products, EFI and other forecast indices, extreme weather risk maps
New EFI climate
Verification of extreme weather forecasts
Case studies

3. Extreme Weather Forecast Indices
Extreme Forecast Index (EFI): Scaled integral distance between the forecast and climate probability distributions
Ff(p) p
SPS (p)
Shift of Tails (SPS):
Proportional distance between the forecast and climate distributions in the meteorological variable space at the p-percentile
p (Fc(p))
Qc(p)- Qc(1)
SOT+(p)
Qf(p)- Qc(1)
Shift in Probability Space (SPS): Distance between the forecast and climate distributions in the probability space at the p-percentile
SPS (p)

4. 2m temperature EFI-s
12 UTC EFI
Daily max EFI
Daily min EFI

5. Examples with the Extreme Weather Indices
SOT an SPS may highlight areas relatively far from the EFI maximum
2m temperature
120-hour total precipitation

6. Multi-parameter Extreme Weather Risk map, based on the EFI

7. Extreme Weather Risk map

8. Distribution diagrams attached to the Extreme Weather Risk map
Evolution of EPS forecast distributions, relative to the climate
EFI is indicated as a measure of the level of extremety
Currently prepared for the location of maximum EFI in a 10*10 degrees gridbox
Different diagram for different verifying lead times (D+1 – D+5)
For 2m temperature, 10m wind speed and 24h total precipitation

9. Recent progress – Severe Weather Risk map for the Monthly Forecast System

10. New Medium range Model Climate
Running an additional EPS control re-forecast suite in dynamical adaptation mode (48h forecast)
Initial conditions from ERA40 ( )
Use latest resolution/ physics
12 UTC daily runs (for 30 years each day)
Same post-processing as for EPS (surface + a few pressure and PV levels)
Cost is only like adding six 10-days Control runs per day
Will allow an immediate adaptation of the EFI to any EPS model upgrade, and also an extension of the EFI (and other calibrated probabilistic products) to other parameters than rain, T2m and wind
In MARS: “Ensemble Forecast Atmospheric Hindcast” = efhc and “Ensemble Forecast Wave Hindcast” = ewhc.
Operational since 1 February 2006 (high resolution upgrade)

11. New EPS Control Climate for the EFI Example for Reading, diff
New EPS Control Climate for the EFI Example for Reading, diff. distribution sampling window from ±1 to ± 15 days

12. EFI with old and new model climatology
3 calendar month of archived EPS forecasts from previous years
EFI with old climate
EFI with new climate
EPS control model reruns for years ,
31 days from each year

13. EFI with old and new model climatology
Difference between the old and new EFI climate (measured by the EFI)
“Observed anomalies” July referenced to ERA-40 ( )

14. Verification of Extreme Weather Forecasts
Follow up of the study made by Francois Lalaurette & Federico Grazzini in 2005 (for 24h total precipitation EFI, 2003 Oct – 2005 May)
Verification of the EFI (based on the old pseudo-climate and the new EPS control re-forecast model climate) and also the EPS probability for extreme events
EFI is regarded directly as probability and truncated at 0 (no transformation is applied)
For parameters of 2m maximum temperature and 24-hour total precipitation
D+1, D+3, D+5, D+7 and D+9
For period of 2005 July – 2006 May
Observational climate is based on the Climate Atlas of Europe (Météo-France) and the new EPS control model climate

15. Definition of the extreme events
The atlas contains monthly means, upper and lower quintiles, daily extreme values and different frequency indices for temperature, precipitation, wind gust and sunshine duration for ~ 700 selected European stations. The climate period is
Monthly extreme events are defined as: at least as extreme as the percentile of the daily climate distribution based on sampling over the month
Average return period of 6-7 years. Apprx. the 5th most extreme case (99.5 percentile -> 1/200) in the monthly sample (size ~ 900, 30days*30years).
It is assumed that the model climate behaves similarly to the observed climate (similar shape characteristics of the distributions).

16. Definition of the extreme events
Monthly thresholds for extreme events (DayObs995) =
MonObsQ80 * (DayEpsQ995 / MonEpsQ80)
MonObsQ80 & MonEpsQ80 = Upper quintile of distribution of monthly means in the observation & EPS model climate (per station, per month)
MonEpsQ80 = Upper quintile of distribution of monthly means in the EPS control re-forecast climate (per station, per month)
Daily extreme thresholds are created by interpolating between adjacent months
Using GTS synop ~1700 (tp24) & ~2500 (tmax24) extreme events were found during the period July 2005 – May 2006

17. Examples of extreme thresholds
24-hour total precipitation
May 16th
2m daily maximum temperature
July 16th

18. EFI based on new versus old climate ROC, 24-hour total precipitation 2005 July – 2006 May
F/(R+F)
F/(H+F)

19. EFI based on new versus old climate ROC, 24-hour total precipitation 2005 July – 2006 May
F/(R+F)
F/(H+F)

20. EFI based on new versus old climate ROC, 24-hour total precipitation 2005 July – 2006 May
F/(R+F)
F/(H+F)

21. EFI based on new versus old climate ROC, 24-hour total precipitation 2005 July – 2006 May
F/(R+F)
F/(H+F)

22. EFI based on new versus old climate ROC, 24-hour total precipitation 2005 July – 2006 May
F/(R+F)
F/(H+F)

23. EFI new versus EPS probabilities ROC, 24-h total precipitation, 2005 July – 2006 May
F/(R+F)
F/(H+F)

24. EFI new versus EPS probabilities ROC, 24-h total precipitation, 2005 July – 2006 May
F/(R+F)
F/(H+F)

25. EFI new versus EPS probabilities ROC, 24-h total precipitation, 2005 July – 2006 May
F/(R+F)
F/(H+F)

26. EFI new versus EPS probabilities ROC, 24-h total precipitation, 2005 July – 2006 May
F/(R+F)
F/(H+F)

27. EFI new versus EPS probabilities ROC, 24-h total precipitation, 2005 July – 2006 May
F/(R+F)
F/(H+F)

28. EFI new versus EPS probabilities ROC, 2m maximum temperature 2005 July – 2006 May
F/(R+F)
F/(H+F)

29. EFI new versus EPS probabilities ROC, 2m maximum temperature 2005 July – 2006 May
F/(R+F)
F/(H+F)

30. EFI new versus EPS probabilities ROC, 2m maximum temperature 2005 July – 2006 May
F/(R+F)
F/(H+F)

31. EFI new versus EPS probabilities ROC, 2m maximum temperature 2005 July – 2006 May
F/(R+F)
F/(H+F)

32. EFI new versus EPS probabilities ROC, 2m maximum temperature 2005 July – 2006 May
F/(R+F)
F/(H+F)

33. EFI new versus EFI old & EPS prob Reliability diagram, 24-hour total precipitation 2005 July – 2006 May
F/(R+F)
F/(H+F)

34. EFI new versus EFI old & EPS prob Reliability diagram, 24-hour total precipitation 2005 July – 2006 May
F/(R+F)
F/(H+F)

35. EFI new versus EFI old & EPS prob Reliability diagram, 24-hour total precipitation 2005 July – 2006 May
F/(R+F)
F/(H+F)

36. EFI new versus EFI old & EPS prob Reliability diagram, 24-hour total precipitation 2005 July – 2006 May
F/(R+F)
F/(H+F)

37. EFI new versus EFI old & EPS prob Reliability diagram, 24-hour total precipitation 2005 July – 2006 May
F/(R+F)
F/(H+F)

38. Extreme event case study - I
“Swiss flood” - heavy precip in August 2005
Observed 24-hour total precipitation
22 August 2005
Extreme events

39. “Swiss flood” - heavy precip in August 2005

40. “Swiss flood” - heavy precip in August 2005

41. “Swiss flood” - heavy precip in August 2005

42. “Swiss flood” - heavy precip in August 2005

43. “Swiss flood” - heavy precip in August 2005

44. Extreme event case study - II
Heat wave in West Europe - in October 2005
Observed 24-hour maximum temperature, 30 October 2005
Extreme events

45. Heat wave in West Europe - in October 2005
D+9

46. Heat wave in West Europe - in October 2005
D+7

47. Heat wave in West Europe - in October 2005
D+5

48. Heat wave in West Europe - in October 2005
D+3

49. Heat wave in West Europe - in October 2005
D+1

50. Summary - I
After careful consideration and survey for demands, the range of extreme forecast products (forecast indices, maps) can be extended
New extreme indices (SOT, SPS) ?!
New parameters (Tmax, Tmin, Waves, etc) ?!
Extended forecast range (D+6 to monthly range – VAREPS) ?!
The new ERA40 based EPS control model re-forecasts provide more reliable base for any extreme forecast product at present or in the future
Further developments (possible use of EPS re-forecasts made for calibration purposes) ?!
The first set of verification results are encouraging
Need for detailed, quality controlled, representative observation climate

51. Summary - II The first set of verification results are encouraging
The better climate sampling with the 30-year model climate seems to be reflected in the verification result by slightly better ROC for the new EFI
In terms of resolution the EFI also seems to over perform little bit the raw EPS probabilities for extreme events
However statistical calibration is heavily needed in order to decrease the strong over forecasting tendency of the EFI (taken directly as probability)
Lot of more work is needed to further investigate the characteristics and value of these extreme forecast products