1. Page 1© Crown copyright Some Strengths and Weaknesses of ECMWF Forecasts for the UK Tim Hewson 15 th June 2006 Contributors include: Eleanor Crompton, Tim Legg, Helen Watkin

2. Page 2© Crown copyright Contents Synoptic Scale performance around the UK Subjectively-verified EC OP and ensemble forecasts Focus on adverse/severe weather 1. Snow 2. Strong Winds 3. New products – Cyclonic feature tracking Summary of recommendations

3. Page 3© Crown copyright Synoptic Scale performance around the UK GOOD FORECASTS EC OP EC ENS MEAN 19/20- 4/5- 3/5- 1/4 1/10 POOR FORECASTS EC OP EC ENS MEAN 1/300- 1/40- 1/10- 1/41/5 1/2 DAY 3 DAY 4 DAY 5 DAY 6/7 DAY 8-10 12Z Forecasts subjectively verified during 2005

4. Page 4© Crown copyright Comparison with previous years Some signs of year on year improvement at all leads, though always a noisy signal

5. Page 5© Crown copyright Multi-model comparison Within the basket of international operational models, NCEP appear to have suddenly become very competitive. Especially true in winter. Similar results seen for other lead times.

6. Page 6© Crown copyright Snow in the UK ECMWF forecasts provide key input to early warning issue Primarily this is through the Met Offices calibrated, automated First Guess Early Warning System (FGEW) derived from ensemble output. One parameter - snow ppn total. The utility of FGEW has been revisited for the 2005/6 winter, using a number of high profile UK snow events (hits and misses only)

7. Page 7© Crown copyright UK Snow Cases - 2005/6 winter Nov 25 th SW England- 7% * Nov 28 th W/SW Midlands- 4% Dec 27 th E England- 4% * Dec 30 th E England- 30% Mar 3 rd + NE Scotland- 1% Mar 3 rd N England- 4% Mar 12 th NW of UK- 70% * Apr 10 th SE England- 1% Values show FGEW probabilities at 3/4 day lead times. Greater than 10cm snow believed to have occurred at populated altitudes in each of the above cases. All were highlighted by the media. For the convective cases highlighted in red there was little or no increase in probabilities as the event approached.

8. Page 8© Crown copyright Mar 12 th 2006 – NW of UK

9. Page 9© Crown copyright Mar 12 th 2006 – NW of UK

10. Page 10© Crown copyright Snow Events in the UK Handling of frontal snow cases by the EPS and FGEW looks good, and has proved very useful to forecasters, in this and previous winters These constitute approximately 50% (?) of all winter snow cases Unfortunately the handling of convective cases is much worse, with EPS and FGEW generally misleading (though broadscale often useful)

11. Page 11© Crown copyright Dec 27 th 2005 – E England

12. Page 12© Crown copyright Dec 27 th 2005 – E England

13. Page 13© Crown copyright Nov 25 th 2005 – SW England

14. Page 14© Crown copyright Nov 25 th 2005 – SW England EPS member gridbox

15. Page 15© Crown copyright Precipitation Drift MODELS Up to ~100km

16. Page 16© Crown copyright Precipitation totals for Cornwall / Bodmin Snow Event – Nov 2005 Key weakness of current operational (12km) model formulation well illustrated – snow focussed over seas. Same is true of EC model – due to parametrisation used Little or no propogation inland. Reality (radar) very different, partly due to slow fall speed of snow. contours show orography

17. Page 17© Crown copyright Options: Met Office Parametrisation could incorporate snow-drift effect. More appropriate for higher resolution. The first Met Office Mesoscale model did this (lost during unification). This aspect is very high priority for forecasting in the Met Office. Special field modification tools being built in the short term. Inputs – convective cloud depth, wind profile, freezing level. Higher resolution models will be used longer term

18. Page 18© Crown copyright Verification of Chief Forecasters Output Forecasters greatest contribution in short term forecasts is in reducing errors associated with cold air convection In winter snow is often involved

19. Page 19© Crown copyright Options: ECMWF For ECMWF data, scope for a post processing stage, to smear out convective ppn totals inland, according to wind strength and freezing level Worth considering, though boundary layer temperature variations add complexity In some cases, such as the Cornwall event, this would not work – complexity of mesoscale flow patterns is also too great Incorporation into parametrisation may be the best strategy? Important consideration: affects other parts of Europe with coasts information content of model runs is being wasted

20. Page 20© Crown copyright H L Cornwall Snow event 12Z 25/11/05 Mesoscale structure 0C +5C

21. Page 21© Crown copyright Strong Winds A strong wind representivity problem exists for fast moving systems This arises because of diagnostic types used around the world It is more acute because faster moving systems have a greater potential to facilitate strong winds developing inland (trajectory curvature on S flank is reduced) Affects Met Office models, EC model, EFI (?)

22. Page 22© Crown copyright This winters one storm! -12Z 10/1/06

23. Page 23© Crown copyright 18Z =Strong Wind Zone

24. Page 24© Crown copyright 00Z

25. Page 25© Crown copyright 06Z

26. Page 26© Crown copyright 12Z X No strong winds expected here??!

27. Page 27© Crown copyright Solution New but simple lower tropospheric wind diagnostics are required Interrogation of every model timestep should be used Analogous to rainfall accumulations Name of resulting plan view field would be (eg) Max 10m wind in 6 hours up to VT This would emphasise damage swathes Similar ideas should be used for interrogating temperatures, etc – why not correlate (MOS) with model max temperature, rather than model 12Z temperature (as in talk yesterday!) ?

28. Page 28© Crown copyright Cyclonic windstorms Even with improved diagnostic selection, models still fail to fully represent details and strength of damaging windstorms Resolution and boundary layer issues.. 4+kts rms 10m wind speed error in EC over Europe. For the more extreme events recalibration is unreliable and ill-specified Windstorms are however related to synoptic features - commonly a cyclone, which often evolves from a frontal wave – and which models can represent A feature-based approach is used widely within operational forecasting Therefore use feature-tracking within model forecasts as a conduit for understanding and forecasting windstorms

29. Page 29© Crown copyright Objective Cyclonic Features - Snapshot Frontal Wave Barotropic Low Diminutive Wave Frontal Wave (weak) Diminutive Wave (weak)

30. Page 30© Crown copyright Conceptual Cyclone Life-Cycle 0 3 4 5 6 2-d Front Frontal wave cyclone Frontal fracture T-bone Mature cyclone 1 Diminutive frontal wave 2 Frontal wave After Shapiro and Keyser (1990) – stages 3-6

31. Page 31© Crown copyright Example: Windstorm Damage,19 Nov 04, Slovakia

32. Page 32© Crown copyright Storm track, 12h interval 00Z, 18 th Nov 04 to 12Z, 22 nd 1 2 1 2 3 3 4 4 5 6 5 6

33. Page 33© Crown copyright Application to ECMWF ensemble data As part of THORPEX / TIGGE Code used out to 15 days Different post-processing strategies required for different lead times Under development - 2 examples presented Thanks to Helen Watkin Processing code will soon be running at ECMWF Also being used in Met Office MOGREPS ensemble

34. Page 34© Crown copyright Example Storm in EC Ensemble forecasts Click on feature To follow evolution

35. Page 35© Crown copyright Feature-Specific plumes MSLP Vorticity Max 1km Wind Within 300km Radius of feature Feature tracks

36. Page 36© Crown copyright Longer Ranges - use feature track density T+120

37. Page 37© Crown copyright T+216

38. Page 38© Crown copyright Summary of Requests/Recommendations New diagnostics required that utilise multi time-step interrogation – especially for near surface winds Improved re-derivation of EFI, SOT, SPS based on the above? Strategy for addressing snow-drift? – views of other member states? Archive of forecasts of severe events, or hindcasts of these from more recent models, valuable for testing new approaches, such as cyclonic feature tracking More web-based diagnostics – eg from Operational runs - would help Met Office forecasting effort at all lead times - see last years wish list – this still applies!

39. Page 39© Crown copyright Supplementary slides follow

40. Page 40© Crown copyright Nov 28 th 2005 – W/SW Midlands

41. Page 41© Crown copyright Nov 28 th 2005 – W/SW Midlands

42. Page 42© Crown copyright Dec 30 th 2005 – E England

43. Page 43© Crown copyright Dec 30 th 2005 – E England

44. Page 44© Crown copyright Mar 3 rd 2006 – NE Scotland / N England

45. Page 45© Crown copyright Mar 3 rd 2006 – NE Scotland / N England

46. Page 46© Crown copyright Apr 10 th 2006 – SE England

47. Page 47© Crown copyright Apr 10 th 2006 – SE England

48. Page 48© Crown copyright Scope for Improvement Forecasters are usually able to improve upon raw (Met Office) model output, using different models, knowledge of systematic errors, comparison with current trends Degree of improvement could potentially be increased by making more use of the high quality ECMWF operational run, which at present is under-utilised WISH LIST! – 3 hourly data, T+0 to T+48 Instantaneous total ppn rates, plus cloud cover and mslp (same format?!) Separate plots showing dynamic /convective rain and snow components 10m mean wind and likely gust strength Sub areas – parts of Europe ? Timely appearance on ECMWF web site is crucial (probably the most expedient route for making this data available)

49. Page 49© Crown copyright Extras for Wish List Meteograms to include overlapping 24-hour rainfall totals (but still in 6 hour blocks) Total cloud cover – is this altitude weighted, or is 8 oktas cirrus considered cloudy? Weighting would be preferable Postage stamps showing estimated surface gusts, with colour-shading for high values Cluster ensemble means for mslp, thickness, annotated with percentages of members

50. Page 50© Crown copyright Accreditation WAFC World Area Forecast Centre