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“Spatial ensemble characterisation for summer convective cases” S. Dey Supervisors: R. Plant, N. Roberts and S. Migliorini Mesoscale group 03/06/2014.

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Presentation on theme: "“Spatial ensemble characterisation for summer convective cases” S. Dey Supervisors: R. Plant, N. Roberts and S. Migliorini Mesoscale group 03/06/2014."— Presentation transcript:

1 “Spatial ensemble characterisation for summer convective cases” S. Dey Supervisors: R. Plant, N. Roberts and S. Migliorini Mesoscale group 03/06/2014

2 Can we develop scale appropriate, multivariate and physically meaningful methods for obtaining information from convection permitting ensembles? Outline Background Technique for calculating believable spatial scales Multivariate correlations

3 Motivation Scale dependence – Faster error growth at smaller scales (Hohenegger and Schär 2007, BAMS) – Need ensembles at convective scale Forecast verification Review papers: Ebert (2008), Gilleland et al. (2009), and Johnson and Wang (2013) Ensembles Clark et al. 2011; Johnson et al. 2014; Surcel et al. 2014

4 Background: MOGREPS-UK – 2.2km resolution – Convection permitting – 12 members – Downscaled from MOGREPS-G – Methods not specific to MOGREPS

5 v Background: cases 17 th July 17Z2nd August 10Z27 th July 23Z 3 rd August 14Z2 nd August 18Z Nimrod rain rates 0.1 0.5 1.0 2.0 4.0 8.0 [mm/hr]

6 Background: mean example 1 Ensemble membersEnsemble mean Spatially aligned cells Radar derived rain rates Scattered showers Need ways of evaluating ensemble physically Methods should be multivariate

7 Background: mean example 2 27 th July 23Z 3 rd August 14Z

8 Ensemble mean not physically representative Need new methods of ensemble evaluation – On appropriate scales – Physically representative – Robust – Varying in meaningful manner New method 1 2 3 cv Individual forecasts Ensemble meanPhysical meaning

9 Spatial analysis: method Over what spatial scales are the forecasts acceptably similar? Compare two ensemble members A and B at a grid point (i,j) Is the criterion met ? 1.Yes- this is the scale to use 2.No- try a larger Neighbourhood Squared error Max Squared error Spatial separation

10 ?=?= L A B Spatial analysis: method Two ensemble members All ensemble members 12 members - 66 comparisons 12 4 3

11 v Results: Spatial scales 17 th July 17Z2nd August 10Z27 th July 23Z 3 rd August 14Z2 nd August 16Z Spatial scales 20 55 90 125 [ km] 9 25 41 57 [ points]

12 v Radar rain rates (again!) 17 th July 17Z2nd August 10Z27 th July 23Z 3 rd August 14Z2 nd August 18Z Nimrod rain rates 0.1 0.5 1.0 2.0 4.0 8.0 [mm/hr] c

13 Method: Correlations 12 Mean over all members in Neighbourhood “Av” Standard deviation over all members in Neighbourhood “Std” 12 Level 1 Level 2 12

14 Different variables- 27/07/2013 Temperature, specific humidity, cloud fraction, horizontal wind speed

15 Different variables- 27/07/2013 – Inter variable relationships – Physical processes in model – Correlation structure useful for data assimilation Colder, dryer, more cloud, faster wind speed Warmer, wetter, more cloud, slower wind speed Warmer, wetter, less cloud, slower wind speed Colder, dryer, less cloud, faster wind speed Tropopause Stronger convection Weaker convection 4km 2km Colder Warmer Colder

16 Temporal correlations with rain rates Time for 3D variable Behind Ahead Future Past Examples 1. Cloud fraction-rain rates 2.Horizontal divergence-rain rates

17 Cloud fraction-rain rates 17 th July 17Z [41X41]2nd August 10Z [61X61]27 th July 23Z [21X21] 3 rd August 14Z [21x21]2 nd August 18Z [21x21] Correlations cloud-rain

18 Horizontal divergence-rain rates 17 th July 17Z [41X41]2nd August 10Z [61X61]27 th July 23Z [21X21] 3 rd August 14Z [21x21]2 nd August 18Z [21X21] Correlations Divergence - rain Divergence Convergence

19 Conclusions Ensemble mean not physically representative of ensemble Technique for calculating believable spatial scales – Summary of information from ensemble – Overview of spatial predictability across the domain Multivariate correlations – Give information about the model convection – Physical processes – Inter variable relationships

20 Future cases 0.1 0.25 0.5 1 2 4 8 16 32 >32 Scattered convection 29/07/2013 Bands of thunderstorms 23/07/2013 1 17 th JulyOrganized thunderstorms (NOT COPE CASE) 23 rd JulyBands of thunderstorms (IOP 5) 27 th JulyMCS (IOP 7) 29 th JulyConvective showers (IOP 9) 2 nd AugustConvection along SW peninsula (IOP 10) 3 rd AugustConvection along SW peninsula (IOP 11)


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