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Forecast quality and predictability of severe European cyclones

Forecast quality and predictability of severe European cyclones. Jenny Owen Peter Knippertz , Tomasz Trzeciak . University of Leeds, School of Earth and Environment, Leeds, UK. Motivation. Xynthia. Damaging weather Important for Europe Cause fatalities and economic losses. Daria.

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Forecast quality and predictability of severe European cyclones

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  1. Forecast quality and predictability of severe European cyclones Jenny Owen Peter Knippertz, Tomasz Trzeciak. University of Leeds, School of Earth and Environment, Leeds, UK

  2. Motivation Xynthia • Damaging weather • Important for Europe • Cause fatalities and economic losses Daria Lothar Friedhelm

  3. Method I How well are severe European windstorms forecast? What factors affect forecast quality? • Select historic storms • Storm Severity Index: • Measures ‘unusualness’ of wind speed • Cubed ~ power of the wind ~ damage • Track storms automatically • Minima in mean sea level pressure (MSLP) • Connect together at consecutive timesteps Daria

  4. Selected Storms • Daria • Nana • Vivian • Wiebke • Udine • Verena • Agnes • Urania • Silke • Lara • Anatol • Franz • Lothar • Martin • Kerstin • Rebekka • Elke • Lukas • Pawel • Jennifer • Frieda • Jeanette • Gero • Cyrus • Hanno • Kyrill • Emma • Klaus • Quinten • Xynthia

  5. Method II • Categorise storms: • Jet stream shape, relative to the track of the storm • Processes that govern deepening, by pressure tendency equation

  6. Categorising Storms: Jet Cross Early Cross Late Kyrill Klaus Edge Split Jet Xynthia Jeanette • Based on jet stream (wind speed at 300hPa). • Meridional sections that move with the storm track. • Similar plots for θe showed no clear groupings.

  7. Categorising Storms: Jet • Klaus • Vivian • Wiebke • Kyrill • Lothar • Martin • Emma • Jeanette • Daria • Agnes • Anatol • Udine • Rebekka • Lara • Xynthia • Jennifer • Gero • Hanno • Silke • Elke • Urania • Nana • Quinten • Verena • Kerstin • Pawel • Cyrus • Lukas • Franz • Frieda Cross Early Edge Cross Late Split

  8. Pressure Tendency Equation • Fink et al. (2012, GRL) applied the Pressure Tendency Equation to mid-latitude cyclones • 3o x 3o column • From surface to 100hPa • Box moves along storm track and compares properties from one time step to the next • Identify processes that add or remove mass from column and affect core pressure

  9. Pressure Tendency Equation Density tendency Stratosphere horizvertdiab Precip

  10. Categorising Storms: PTE PTE terms’ contribution to deepening for ten of the storms BaroclinicityDiabatic Processes

  11. Categorising Storms: PTE • Klaus • Vivian • Wiebke • Kyrill • Lothar • Martin • Emma • Jeanette • Daria • Agnes • Anatol • Udine • Rebekka • Lara • Xynthia • Jennifer • Gero • Hanno • Silke • Elke • Urania • Nana • Quinten • Verena • Kerstin • Pawel • Cyrus • Lukas • Franz • Frieda Horiz Diab

  12. Linking Categories • Storms that spend longer on the north side of the jet tend to be more baroclinic – stronger temperature gradients. • Diabatic storms tend to spend more time on the south side of the jet – warmer and wetter, more potential for latent heat release.

  13. Method III • Run automatic tracker on ECMWF Ensemble Control Forecast • Spatial and temporal resolution • Initialisation time • Match forecast tracks to analysis tracks • Quantify best match based on proximity of analysis and forecast tracks at similar time • Quality control: reject if tracks > 20 degrees apart at any matched point

  14. Matched Tracks: Location Cross Early Cross Late Kyrill Klaus Edge Split Jet Jeanette Xynthia • Some storms are better forecast than others • Some tracks are not a good match

  15. Matched Tracks: Pressure Kyrill Klaus Jeanette Xynthia • Storms not always weaker in forecast – but difficult to see big picture

  16. Method IV • Assess how forecast quality varies with lead time • Correlations • Correlation coefficient, R • Test for significance of correlation, T • Future Work: Perform more rigorous statistical tests

  17. Results: Latitude & Longitude • Storms move more slowly W-E in forecasts, than in analysis • Storms slightly further south in forecasts

  18. Results: Core Pressure • Storms have higher core pressure in forecast => storm less intense in forecast • Agrees with previous work e.g. Froude et al.

  19. Jet Stream Type: Pressure • Core pressure underprediction stronger in some jet stream types than others

  20. PTE Type: Core Pressure • Indication that core pressure underprediction stronger in storms where baroclinic processes dominate deepening, than in those where diabatic processes dominate. • Needs further statistical testing

  21. Resolution: Core Pressure • Operational forecast, so forecast system upgraded regularly (dynamics and resolution). • Some evidence of relationship between forecast quality and system evolution.

  22. Summary I • Selected 30 European windstorms. • Categorised by: • Jet stream • Processes that dominate deepening (PTE) • Assessed forecast quality: • Longitude & latitude • Core pressure (intensity)

  23. Summary II • Storms in forecast too slow. • Core pressure generally underforecast: • Strength of relationship with lead time depends on jet stream type. • Baroclinic storms may be more underforecast than diabatic ones. • Tendency for improvements of forecast system to affect forecast quality.

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