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Bayesian Updating• Philosophy is to emulate forecaster behaviourby using latest forecast to update an existingprediction• Start from PoP climatology• Could use a naive algorithm• Proposed method uses finite-counting statistics• Currently using binomial distribution• Compare performance of these two options© Crown copyright Met Office MOSAC Paper 13.9, 14 Nov 2008
Bayesian Updatingnaïve vs finite counting methods• Applied to FY 07-08 POP for KPT sites• Inputs are• ECMWF(RECAL) at 5, 4, 3, and 2 days ahead• MOGREPS-R (old-KFMOS) at 2 days ahead• Brier Skill Scores:• Equal weighting 0.529• Bayesian updating 0.531• MOGREPS-R (KFMOS) 0.477• ECMWF (RECAL) 0.509© Crown copyright Met Office MOSAC Paper 13.9, 14 Nov 2008
Page 1 and 2: Research to Improve Forecasting ofP
Page 3 and 4: Summary of Conclusions -PoP Score
Page 5 and 6: Summary of Conclusions -Post-proces
Page 7 and 8: The Stornoway EffectPoor October sc
Page 9 and 10: Stornoway -Maritime convection not
Page 11 and 12: Stornoway EffectWeaknesses of PoP S
Page 13 and 14: Possibilities of Hedging StornowayS
Page 15 and 16: IGPSIntelligent GridPoint Selection
Page 17 and 18: The “new CDP”Additionally - adv
Page 19 and 20: How good is the CDP?Last summer ind
Page 21 and 22: Bayesian Updating© Crown copyright
Page 23 and 24: Bayesian Updatingnaïve algorithmCl
Page 29 and 30: Bayesian Updatingnaïve vs finite c
Page 35: Bayesian Updatingnaïve vs finite c
Page 41 and 42: Bayesian Updatingfinite counting -
Page 43 and 44: Bayesian Updating• Philosophy is
Page 45 and 46: Bayesian Updatingwhy not be naïve?
Page 47 and 48: Combining improvementsFallbackClima
Page 49 and 50: Ensemble Index• Development of a
Page 51 and 52: Ensemble Upgrades• Some key ensem
Page 53: Questions?© Crown copyright Met Of

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