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Verification of COSMO-LEPS Model Against Observations for Weather Forecasting

Explore the validation process of COSMO-LEPS model in comparison to observational data, using techniques such as bi-linear interpolation and Brier Skill Score. Analyze the ROC area, contingency tables, and forecast usefulness metrics for different probability classes.

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Verification of COSMO-LEPS Model Against Observations for Weather Forecasting

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  1. COSMO-LEPS Verification Chiara Marsigli ARPA-SMR

  2. Available italian stations

  3. X X X X X X X X X Verification on station points Bi-linear interpolation (4 nearest points)

  4. X X X X X X X X X Verification on super-boxes Average value – maximum value – frequency PRED. OBS.

  5. X X X X OVERLAPPING BOXES

  6. COSMO-LEPS vs observations station points weighted Need for LM verification at these fc ranges ROC area Nov 02 – Dec 02 – Jan 03

  7. COSMO-LEPS vs observations station points not weighted ROC area

  8. w +48 h nw

  9. w +120 h nw

  10. COSMO-LEPS vs observations station points weighted Brier Skill Score

  11. COSMO-LEPS vs observations station points not weighted Brier Skill Score

  12. Brier Skill Score

  13. Weighting procedure It is possible to decide (in real-time) if it is better to weight or not to weight? Dependence from ensemble spread? Flow dependence?

  14. Brier Skill Score station points average values on super-boxes

  15. Brier Skill Score station points average values on super-boxes

  16. Brier Skill Score Nov 02 only

  17. Brier Skill Score

  18. contingency table Observed Yes No Forecast Yes a b No c d ROC area A contingency table can be built for each probability class (a probability class can be defined as the % of ensemble elements which actually forecast a given event). For the k-th probability class: The area under the ROC curve is used as a statistic measure of forecast usefulness

  19. Brier Skill Score Brier Score • oi= 1 if the event occurs • = 0 if the event does not occur  • fi is the probability of occurrence according to the forecast system (e.g. the fraction of ensemble members forecasting the event) • BS can take on values in the range [0,1], a perfect forecast having BS = 0 • The forecast system has predictive skill if BSS is positive, a perfect system having BSS = 1. Brier Skill Score = total frequency of the event (sample climatology)

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