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University of Reading: Robin Hogan, Bob Plant, Thorwald Stein, Kirsty Hanley, John Nicol Met Office: Humphrey Lean, Carol Halliwell. DYMECS: Dynamical and Microphysical Evolution of Convective Storms (NERC Standard Grant). The DYMECS approach: beyond case studies.
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University of Reading: Robin Hogan, Bob Plant, Thorwald Stein, Kirsty Hanley, John Nicol Met Office: Humphrey Lean, Carol Halliwell DYMECS: Dynamical and Microphysical Evolution of Convective Storms(NERC Standard Grant)
The DYMECS approach: beyond case studies 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 NIMROD radar network rainfall Evaluate these properties in model varying: • Resolution • Microphysics scheme • Sub-grid turbulence parametrization
Nimrod radar 1.5-km model 500-m model 200-m model Kirsty Hanley
Nimrod radar 1.5-km model Too few 500-m model 200-m model Too many Kirsty Hanley
Smagorinsky mixing length plays a key role in determining number of small storms Storm size distribution 1.5-km model 500-m model Kirsty Hanley
20 April 2012 25 Aug 2012 500-m model best 200-m model best 1.5-km model best 200-m model best Kirsty Hanley
First 60% of storms by cloud-top height Next 30% Top 10% Observations 1.5-km model 1.5-km + graupel Vertical profile Ice density too low? Higher reflectivity core Thorwald Stein
First 60% of storms by cloud-top height Next 30% Top 10% Observations 200-m model 500-m model Vertical profile Thorwald Stein
Estimation of vertical velocities from continuity • Vertical cross-sections (RHIs) are typically made at low elevations (e.g. < 10°) • Radial velocities provide accurate estimate of the horizontal winds • Assume vertical winds are zero at the surface • Working upwards, changes in horizontal winds at a given level increment the vertical wind up to that point • Must account for density change with height Key uncertainty in models is convective updraft intensity and spatial scale Can we estimate updrafts from Doppler wind sufficiently well to characterize the distribution of intensity and spatial scale? John Nicol
Estimating retrieval errors from the Unified Model Vertical wind (m/s) Reflectivity (dBZ) Retrieved vertical wind (m/s) Horizontal wind (m/s) Retrieval error (m/s) John Nicol
dBZ u (m/s) w (m/s) 12:45 07 August 2011 16:37 07 August 2011 John Nicol
Scientific and modelling questions • What is magnitude and scale of convective updrafts? How do two observational methods compare to model at various resolutions? • What model configurations lead to the best 3D storm structure and evolution, and why? • How good are predictions of hail occurrence and turbulence? • How is boundary-layer grey zone best treated at high resolution, and what is the role of the Smagorinsky length scale? • Does BL scheme “diffuse away” gust fronts necessary to capture triggering of daughter cells and if so how can this be corrected? • Can models distinguish single cells, multi-cell storms & squall lines, and the location of daughter cells formed by gust fronts? • What are the characteristics common to quasi-stationary storms in the UK from the large DYMECS database? • Can we diagnose parameters that should be used in convection schemes from observations?