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Bayesian Updatingwhy not be naïve?• Simple weighting performs well• We could try to optimise the weights© Crown copyright Met Office MOSAC Paper 13.9, 14 Nov 2008
Bayesian Updatingwhy not be naïve?• Simple weighting performs well• We could try to optimise the weights• The Bayesian approach could be refined• Test sensitivity to assumed sample sizes• Move away from using the binomial distribution• Select distribution parameters using verification data• Update parameters in real-time• Possibility of generalising;• Generate parameters without reference to longhistory of forecasts© 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 41 and 42: Bayesian Updatingfinite counting -
Page 43: Bayesian Updating• Philosophy is
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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