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Experiences concerning fuzzy-verification and pattern recognition methods

Experiences concerning fuzzy-verification and pattern recognition methods. Ulrich Damrath. Outlook. Results on operational verifcation for winter and summer month An approach concerning significance test of „fuzzy“-verification results

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Experiences concerning fuzzy-verification and pattern recognition methods

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  1. Experiences concerning fuzzy-verification and pattern recognition methods Ulrich Damrath

  2. U. Damrath: Experiences concerning fuzzy-verification ... -COSMO GM, Offenbach 2009 Outlook • Results on operational verifcation for winter and summer month • An approach concerning significance test of „fuzzy“-verification results • Estimation of consistency of forecasts using a pattern recognition method (CRA method by Beth Ebert)

  3. U. Damrath: Experiences concerning fuzzy-verification ... -COSMO GM, Offenbach 2009 GME COSMO-EU COSMO-DE Fractions skill score for forecasts of GME, COSMO-EU and COSMO-DE for December 2008, forecast time 06-18 hours

  4. U. Damrath: Experiences concerning fuzzy-verification ... -COSMO GM, Offenbach 2009 GME COSMO-EU COSMO-DE ETS upscaling for forecasts of GME, COSMO-EU and COSMO-DE for December 2008, forecast time 06-18 hours

  5. U. Damrath: Experiences concerning fuzzy-verification ... -COSMO GM, Offenbach 2009 Global Europe Germany Fractions skill score for forecasts of GME, COSMO-EU and COSMO-DE for August 2009, forecast time 06-18 hours

  6. U. Damrath: Experiences concerning fuzzy-verification ... -COSMO GM, Offenbach 2009 Global Europe Germany ETS upscaling for forecasts of GME, COSMO-EU and COSMO-DE for August 2009, forecast time 06-18 hours

  7. U. Damrath: Experiences concerning fuzzy-verification ... -COSMO GM, Offenbach 2009 Examination of statistical significance of „fuzzy“-verification results using bootstrapping • Basic idea of bootstrapping: • Repeat a resampling all elements of a given in a sample of forecasts and observations as often as necessary (N times) and calculate the relevant score(s) • Calculate from N scores statistical properties of the sample such as mean value standard deviation, confidence intervals and quantiles • Application to „fuzzy“-verification • Resampling is done using „blocks“. • Blocks are defined as single days. • Number of resampling cases: N=Days*100 • Calculation scores from N samples for NT thesholds and NW windows • Calculation of quantiles for each window and threshold

  8. U. Damrath: Experiences concerning fuzzy-verification ... -COSMO GM, Offenbach 2009 Values and quantiles 0.1 and 0.9 for Upscaling ETS GME, period June - August 2009 Germany

  9. U. Damrath: Experiences concerning fuzzy-verification ... -COSMO GM, Offenbach 2009 Values and quantiles 0.1 and 0.9 for Upscaling ETS COSMO-EU, period June - August 2009 Germany

  10. U. Damrath: Experiences concerning fuzzy-verification ... -COSMO GM, Offenbach 2009 Values and quantiles 0.1 and 0.9 for Upscaling ETS COSMO-DE, period June -August 2009 Germany

  11. U. Damrath: Experiences concerning fuzzy-verification ... -COSMO GM, Offenbach 2009 Next step: Evaluation of significance • First impression: Is the result of Model 1 better than the result of Model 2? • Significance hypothesis checked using a Wilcoxon-test (IDL-code RS_TEST)

  12. U. Damrath: Experiences concerning fuzzy-verification ... -COSMO GM, Offenbach 2009 Differences between GME and COSMO-EU Germany ETS(COSMO-EU) - ETS(GME) Significance test COSMO-EU better than GME COSMO-EU worse than GME

  13. U. Damrath: Experiences concerning fuzzy-verification ... -COSMO GM, Offenbach 2009 Differences between GME and COSMO-DE Germany ETS(COSMO-DE) - ETS(GME) Significance test COSMO-DE better than GME COSMO-DE worse than GME

  14. U. Damrath: Experiences concerning fuzzy-verification ... -COSMO GM, Offenbach 2009 Differences between COSMO-DE and COSMO-EU Germany Significance test ETS(COSMO-DE) - ETS(COSMO-EU) COSMO-DE better than COSMO-EU COSMO-DE worse than COSMO-EU

  15. U. Damrath: Experiences concerning fuzzy-verification ... -COSMO GM, Offenbach 2009 Differences between COSMO-DE and COSMO-EU Significance test ETS(COSMO-DE) - ETS(COSMO-EU) COSMO-DE better than COSMO-EU COSMO-DE worse than COSMO-EU

  16. U. Damrath: Experiences concerning fuzzy-verification ... -COSMO GM, Offenbach 2009 Example of good precipitation forecast of COSMO-DE Zeigten die numerischen Modelle und die statistischen Prognose- --------------------------------------------------------------- verfahren Signale für das Ereignis? ----------------------------------- Die Numerik zeigte im Vorfeld vermehrt Signale für kräftige Konvektion. Während diese bei GME und COSMO-EU recht breit gestreut und pauschal auftraten, signalisierten mehrere COSMO- DE-Läufe eine linienartige Struktur mit unwetterartigen Zellen (auf Basis der 1- bzw. 3-stündigen RR-Prognosen) im Grenzbereich von Hessen zu NRW und Niedersachsen. Diese Linie trat dann in den Mittags- und frühen Nachmittagsstunden tatsächlich auf, wenn auch nicht 100%ig kongruent, aber doch in der Nähe, so dass in diesem Fall von einer guten Prognose gesprochen werden kann (mehr dazu siehe "Zentraler UW- Sofortbericht" der VBZ).

  17. U. Damrath: Experiences concerning fuzzy-verification ... -COSMO GM, Offenbach 2009 Example of good precipitation forecast of COSMO-DE 3h-precipitation observation 10.08.2009 09-12 UTC 3h-precipitation forecast of COSMO-DE valid 10.08.2009 12 UTC, left 03 UTC +9h, right 06 UTC +6h.

  18. U. Damrath: Experiences concerning fuzzy-verification ... -COSMO GM, Offenbach 2009 Example of good precipitation forecast of COSMO-DE compared to other models

  19. U. Damrath: Experiences concerning fuzzy-verification ... -COSMO GM, Offenbach 2009 Example of good precipitation forecast of COSMO-DE compared to other models

  20. U. Damrath: Experiences concerning fuzzy-verification ... -COSMO GM, Offenbach 2009 About consistency and inconsistency • Forecasters are interested in consistent model forecasts. • But due to growing of errors during forecast time forecasts consistency cannot be expected concerning all properties of the forecasted fields! • Inconsistency: Differences between forecasts that are valid for the same time concerning different properties of the forecasted fields (properties of the pattern, values at special points of interest, extreme values, ...) • Differences between the forecasted fields concerning • phase, • amplitude • and the remaining part

  21. Observed Forecast • Entity-based QPF verification (rain “blobs”) • by E. Ebert (BOM Melbourne) • Verify the properties of the forecast rain system against the properties of the observed rain system: • location • rain area • rain intensity (mean, maximum) CRA error decomposition The total mean squared error (MSE) can be written as: MSEtotal = MSEdisplacement + MSEvolume+ MSEpattern Configuration for the current study: - “Observations”: forecasts: 06-30 hours - Forecasts : forecasts: 30-54 hours and forecasts: 54-78 hours

  22. U. Damrath: Experiences concerning fuzzy-verification ... -COSMO GM, Offenbach 2009 Dark :forecasts 30-54 h Light:forecasts 54-78 h

  23. U. Damrath: Experiences concerning fuzzy-verification ... -COSMO GM, Offenbach 2009 Dark :forecasts 30-54 h Light:forecasts 54-78 h

  24. U. Damrath: Experiences concerning fuzzy-verification ... -COSMO GM, Offenbach 2009 Dark :forecasts 30-54 h Light:forecasts 54-78 h

  25. U. Damrath: Experiences concerning fuzzy-verification ... -COSMO GM, Offenbach 2009 Dark :forecasts 30-54 h Light:forecasts 54-78 h

  26. U. Damrath: Experiences concerning fuzzy-verification ... -COSMO GM, Offenbach 2009 Summary • Scores like Fractions skill score and ETS from upscaling show in general advantages of COSMO models compared to GME. • This is true especially for summer months. • For winter months all models have nearly the same quality for low precipitation amounts and large window sizes for averaging. • Significance test lead to the results, that: • The advantages of COSMO models compared to GME are statistically significant for most window sizes and precipitation amounts. • The differences between COSMO-EU and COSMO-DE are not significant altough there are systematical differences for different precipitation amounts and window sizes. • There are some cases with very useful precipitation forecasts of COSMO-DE compared to COSMO-EU from the view of forecasters. • A study about the consistency of precipitation forecasts showed - it could be expected , but now it is proved - that: • Forecasts of high precipitation amounts are less consistent than those for low precipitation amounts. • Pattern errors contribute most to forecast errors. • During winter months volume errors are higher than displacement errors. • During summer months displacement errors are higher than volume errors.

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