The three-dimensional structure of convective storms Robin Hogan John Nicol Robert Plant Peter Clark Kirsty Hanley Carol Halliwell Humphrey Lean Thorwald Stein Department of Meteorology

Convection-permitting models (e.g. UKV) struggle with timing and characteristics of convective storms MetOffice rainfall radar network MetOffice 1.5km model Original slide from Kirsty Hanley Model storms too regular (circular and smooth) Not enough small storms (smaller than 40 km 2 ) Model storms have typical evolution (not enough variability)

Track rainfall features in rainfall radar data and model surface precipitation. Analyse storm bulk statistics (area, mean rainfall rate). Use tracking information for real-time tracking with Chilbolton. Study storm morphological evolution. Derive vertical velocities from RHI scans through convective cores (see John Nicol’s talk). How to evaluate thunderstorms

Tracking storm “1504” Storm tracked in rainfall-radar network over 3-hour period shows growth of surface rainfall area as well as intensification in mean rainfall. Area Mean rainfall

Tracking storm “1504” Analysis of Chilbolton volume scans shows increase in height as area remains constant ( ). Occurrence of 40dBZ above 4km (approx. 1300) coincides with higher mean rainfall in rainfall- radar network. Area Mean rainfall Height

Tracking storm “1504” Height Analysis of Chilbolton volume scans shows increase in height as area remains constant ( ). Occurrence of 40dBZ above 4km (approx. 1300) coincides with higher mean rainfall in rainfall- radar network. 20 dBZ 40 dBZ 0 dBZ

Tracking storm “1504” Height Analysis of Chilbolton volume scans shows increase in height as area remains constant ( ). Occurrence of 40dBZ above 4km (approx. 1300) coincides with higher mean rainfall in rainfall- radar network. 20 dBZ 40 dBZ 0 dBZ

At z=2km Reshape into circles Store profile of “area-equivalent diameter” D D z Storm morphology: single storm 20 dBZ 40 dBZ 0 dBZ

“Shallow” “Deep” ObservationsUKV 1500m200m Storm morphology: multiple storms 500m Distance from centre [km] ObservationsUKV 1500m200m500m Drizzle from nowhere? Intense small storms? Cumulonimbus too narrow? dBZ

Vertical profiles of reflectivity from volumes 1.5-km 1.5-km + graupel 1.5-km no crystals Observations Conditioned on average reflectivity at m below 0 o C. Reflectivity distributions for profiles with this mean Z dBZ are shown. Model: High rainfall rate from relatively shallow storms. 200-m

Model: For ice dBZ < 20 Top 50% of rain dBZ are 5-10 dB too high Condition rain dBZ distribution on ice dBZ No crystals? Aggregates-only rain dBZ 5-10 dB too low.

Drizzle from cloud-ice below 0 dBZ? Change ice microphysics… Observations UKV 1500m UKV 1500m, no crystals NB! Does not affect storm width above freezing level. Not yet been tested with new microphysics. Mixing length controls on high resolution simulations of convective storms, Hanley et al. (2014), QJRMS, in press. The three-dimensional morphology of simulated and observed convective storms over southern England, Stein et al. (2014), MWR, in review.

Track storm rainfall features in rainfall-radar network and compare with X-band radar scans. Reconstruct storm volumes: see full hemisphere every 5-10min (instead of approx. 60deg every 15min with Chilbolton). Perform DYMECS statistical analyses, but full radar hemisphere  observe volumes more frequently  study storm evolution statistically. Identify life cycle stage of individual storms (growth, mature, dissipating) and compare temporal evolution with models. Use life cycle identification to place IOP observations of microphysical and dynamical processes into context of storm life cycle. Storm morphology and COPE

Observations (rainfall radar network) Normalised time Normalised area … and mean rainfall Model (UKV 3Z) Obtain mean evolution of area mature growth dissipating