1. “High resolution ensemble analysis: linking correlations and spread to physical processes ” S. Dey Supervisors: R. Plant, N. Roberts and S. Migliorini Quo Vadis 12/03/2014

2. Research Question Can we develop scale appropriate, multivariate and physically meaningful methods for obtaining information from convection permitting ensembles? – Ensemble – Forecasting – Data assimilation BackgroundRecent results Future plans

3. Background : spatial predictability Predictability limits “certain turbulent systems, possibly including the earth’s atmosphere, possess for practical purposes a finite range of predictability” (Lorenz, 1969) Scale dependence – Faster error growth at smaller scales (Hohenegger and Schär 2007, BAMS) – Need ensembles at convective scale Limited samples Need to “fill in gaps”

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

5. Method Spatial scales L ?=?= 12 AB Pilot case6 COPE cases

6. Results : meteorology and spatial scales 17/07/2013 17Z03/08/2013 14Z 02/08/2013 18Z 9 25 41 57 [ grid points] [mm/hr] 0.1 0.5 1.0 2.0 4.0 8.0 16.0 [mm/hr] Radar rain rates Spatial scales

7. Results : neighbourhood correlations 17/07/2013 17Z03/08/2013 14Z 02/08/2013 18Z Divergence Height [km] 5km 10km Height [km] 5km 10km -2hrs 0 +2hrs Convergence Divergence -ve correlation +ve correlation

8. And at a single grid point … 17/07/2013 17Z03/08/2013 14Z 02/08/2013 18Z Divergence Height [km] 5km 10km -3hrs 0 +3hrs

9. Summary: COPE cases Conclusions so far – Correlations can expose physical relationships providing they are calculated over a suitable area – Scales from spatial comparison are giving this suitable area – Ensemble derived scales close to real scales Further work for COPE cases 0.1 0.25 0.5 1 2 4 8 16 32 >32 Mesoscale Convective System 27/07/2013 Scattered convection 29/07/2013 Bands of thunderstorms 23/07/2013 1

10. Questions for future work Different ensemble membership: – Increased membership by time lagging? – Including the UKV forecast in the ensemble? – Global ensemble – Spatially increasing membership versus adding more “real” members Other questions: a more statistical approach – How do convective and non convective cases compare? – Do any patterns emerge? – Do we have an informative tool for forecasting ? 3Z 9Z 2 2 22 2 2 22 2 12

11. Future work to investigate these further using different ensemble membership and a more statistical approach Summary Can we develop scale appropriate, multivariate and physically meaningful methods for obtaining information from convection permitting ensembles? Yes, using vertical correlations over an appropriate neighbourhood

12. References Hohenegger, C. and C. Schär, 2007: Atmospheric predictability at synoptic versus cloud- resolving scales. Bull. Amer. Meteor. Soc., 88 (7), 1783–1793. Lorenz, E. N., 1969: The predictability of a flow which possesses many scales of motion. Tellus, 21 (3), 289–307. Roberts, N. M. and H. W. Lean, 2008: Scale-selective verification of rainfall accumulations from high-resolution forecasts of convective events. Mon. Wea. Rev., 136 (1), 78– 97. Questions?