Click to add Text © Crown copyright Met Office Statistical Analysis of UK Convection and its representation in high resolution NWP Models Humphrey Lean, Kirsty Hanley, Carol Halliwell Reading, UK Robin Hogan, Thorwald Stein, Bob Plant, Peter Clark University of Reading, Reading, UK

© Crown copyright Met Office Introduction “Convection permitting models” (i.e. those with explicit convection) have provided a step change in our ability to forecast on smaller scales. Here describe work to improve our understanding of representation of convection in these models. Not a trivial question. Just running at higher resolution is not necessarily a panacea. Although there is no convection scheme we have to think about the representation of other subgrid processes.

© Crown copyright Met Office Model resolution Current highest resolution operational UK configuration 1.5km (UKV model) For research we are running higher resolution versions of the Unified Model down to 100m (55m for London) Helps understanding of convection permitting versions of model to look as function of gridlength. Also looking to future. Higher resolution very expensive but also interest in high res models of small areas (e.g. Weymouth 333m for Olympics, London 333m).

© Crown copyright Met Office Heathrow downscaler from UKV 300 x m resolution 70L 10 second timestep Run twice a day at 03Z and 09Z Run to T+36 Clive Wilson, Anke Finnenkoetter

© Crown copyright Met Office “UKV” 1.5km UK Model convection 1.5km modelRadar 15 UTC 12 th April 2012 Convective cells too large and too intense. Not enough light rain.

© Crown copyright Met Office Average cell diameter (km) (averaged over 22 convective cases) Threshold (mm/hr) Radar1.5km UKV UKV Under-resolved Currently investigating shallow scheme rather than trying to resolve smaller showers.

© Crown copyright Met Office Gridscale structure in 750 hPa w 13UTC 12/05/2010 – case of light scattered showers 4km 1.5km 500m Emilie Carter

© Crown copyright Met Office 100m UM versions Cold pooling in valleys COLPEX (Clark, Vosper, Carter) London (Lean) Convection (Carter, Halliwell, Hanley) Tornadoes (Hanley) StCu (Boutle) Fog inc nesting in ensemble (Porson) (Also 333m Weymouth model for Olympic sailing and 333m London model (fog)).

© Crown copyright Met Office Comparison with observations Temp RH Wind speed Wind dir Emilie Carter

COPE IOP 2 July sea breeze convergence Different scale! Vertical velocity at 500m amsl Below 500m starting to resolve BL turbulence K Hanley

© Crown copyright Met Office DYMECS project DYnamical and Microphysical Evolution of Convective Storms (DYMECS). Statistical analysis of convective cells with Chilbolton Radar over a number of cases. Compare to UM configurations between 1.5km and 100m R Hogan, Plant, Stein, Nicol, Clark University of Reading Lean, Halliwell, Hanley Also in summer 2013 had field phase of COPE (COnvective Precipitation Experiment) which will be used for similar analysis and model comparisons.

© Crown copyright Met Office The DYMECS approach: beyond case studies Met Office 1km rainfall composite Track storms in real time and automatically scan Chilbolton radar Derive properties of hundreds of storms on ~40 days: Vertical velocity 3D structure Rain & hail Ice water content TKE & dissipation rate Evaluate these properties in model varying: Resolution (down to 100m) Microphysics scheme Sub-grid turbulence parametrization 25m diameter S-band (3 GHz) Steerable (2 degrees per second) 0 dBZ out to 150 km

© Crown copyright Met Office Model Differences

© Crown copyright Met Office 2.2km1.5km 200m100m 1km RADAR 500m4km

© Crown copyright Met Office Convective cell life cycle Thorwald Stein

© Crown copyright Met Office 20 April Aug m model best 500m model best 1.5km model best 11 UTC - radar15 UTC - radar Surface rainrate statistics

© Crown copyright Met Office Cloud widths for different reflectivity thresholds. Radar Distance (km) 1.5km500m 200m100m Thorwald Stein Median width of deep storms 25 th Aug 2012

© Crown copyright Met Office 25 Aug 2012 Cutaway: reflectivity Surface: rainrate Shading: extent of cloud Robin Hogan 3D visualisation of data

© Crown copyright Met Office Reflectivity Actual model vertical velocity Estimated vertical velocity ObservationsUKV 1500m Updraft retrieval 10 km height 20 km width 40 dBZ +10 m/s -10 m/s Estimate vertical velocity from vertical profiles of radial velocity, assuming zero divergence across plane. Quantify errors due to 2D flow assumption John Nicol

© Crown copyright Met Office

Vertical distribution of vertical velocity and reflectivity Observations 1500m 500m 200m 100m John Nicol

© Crown copyright Met Office Vertical distribution of vertical velocity and reflectivity John Nicol Vertical velocity and reflectivity distributions as function of radius from centre of updrafts. Set to zero where: w<1m/s, Z<20dBZ UTC 25/08/12. Black traces - mean widths for 1m/s and 20dBZ. N.B. higher values of Z than before - rain

© Crown copyright Met Office Vertical distribution of vertical velocity and reflectivity John Nicol Vertical velocity and reflectivity distributions as function of radius from centre of updrafts. Set to zero where: w<1m/s, Z<20dBZ AND where values start increasing again. “primary profile” UTC 25/08/12. Black traces - mean widths for 1m/s and 20dBZ.

© Crown copyright Met Office Vertical velocity and reflectivity as a function of gridlength. John Nicol Observations 1500m 500m 200m 100m

© Crown copyright Met Office Vertical velocity and reflectivity as a function of gridlength. John Nicol Observations 1500m 500m 200m 100m Updrafts fit best at about 200m – definitely too narrow at 100m

© Crown copyright Met Office Vertical velocity and reflectivity as a function of gridlength. John Nicol Observations 1500m 500m 200m 100m Primary (monotonic) cloud widths proxy for updraft width

© Crown copyright Met Office Vertical velocity and reflectivity as a function of gridlength. John Nicol Observations 1500m 500m 200m 100m Non monotonic profiles of Z too narrow in 100m and 200m (tallies with cloud and rain data).

© Crown copyright Met Office Vertical velocity and reflectivity as a function of gridlength. John Nicol Observations 1500m 500m 200m 100m Obs show bigger increase from dropping the monotonic condition than any model. Fits with cloud not correctly filling in between updrafts.

© Crown copyright Met Office 25 Aug 2012 Cutaway: reflectivity Surface: rainrate Shading: extent of cloud Robin Hogan 3D visualisation of data

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Mixing length dependence John Nicol radar 200m l=300m 200m l=100m 200m l=40m Smaller mixing length lower vertical velocity (but more cells)

© Crown copyright Met Office Can we make the 200m model produce larger storms on 25 th Aug 2012 by changing the mixing length? Need to reduce the timestep to 3s to avoid hitting stability limit. Can produce larger storms but at the expense of the smaller storms. Increasing the mixing with height may be a solution i.e. make Smagorinsky scheme dependent on Δz. Varying the mixing length l=300m – 2491 storms l=100m – 3583 storms l=40m – 4359 storms 200m Kirsty Hanley

© Crown copyright Met Office Variation with microphysics John Nicol Observations aggregates graupel default Melting level at 2.6km. Hypothesise difference due to fall speed.

© Crown copyright Met Office Conclusions UKV clearly under-resolves many small showers in UK High res models (~100m) improve some aspects but also some problems. Models below 500m tend to produce too narrow showers (measured by surface rain or cloud) in cases where showers are large (for small showers 200m or 100m fits well). Cloud widths roughly the same in 200m and 100m. Updraft widths good in 200m model but too narrow at 100m. Above two together imply there may be an issue about how the model fills in cloud between updraft cores. Representation very sensitive to mixing. Also sensitivity to microphysics (fall speed).

© Crown copyright Met Office Future work What can be done to understand lack of convergence and too narrow updrafts/clouds in 100m/200m models? Suspect problem is turbulence “grey zone”. Would better resolution of turbulence solve these problems at higher resolution? Try higher vertical/horizontal resolution and see if updrafts/clouds get wider (or stop collapsing). Work with LES community. Can we improve models with more appropriate subgrid mixing schemes? Effect of microphysics?

© Crown copyright Met Office DYMECS References Hanley, K. E., Plant, R. S., Stein, T. H. M., Hogan, R. J., Nicol, J. C., Lean, H. W., Halliwell, C. and Clark, P. A. (2014), Mixing-length controls on high-resolution simulations of convective storms. Q.J.R. Meteorol. Soc.. doi: /qj.2356 Stein, Thorwald H. M., Hogan, Robin J., Hanley, Kirsty E., Nicol, John C., Lean, Humphrey W., Plant, Robert S., Clark, Peter A., Halliwell, Carol E. (2014), The three-dimensional morphology of simulated and observed convective storms over southern England. Mon. Wea. Rev.. doi: /MWR-D Stein, Thorwald H. M., Hogan, Robin J., Clark, Peter A., Halliwell, Carol E., Hanley, Kirsty E., Lean, Humphrey W., Nicol, John C., Plant, Robert S., (2014), The DYMECS project: A statistical approach for the evaluation of convective storms in high-resolution NWP models. (submitted to Bull. Amer. Meteorol. Soc.).

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