Recent changes to UM microphysics and forthcoming new functionality Paul Field, Jonathan Wilkinson, Kalli Furtado, Ben Shipway, Adrian Hill, Florent Malavelle Convection in Met Office models at high resolution 13 June 2013 © Crown copyright Met Office UM Microphysics: • Based on Wilson and Ballard (1999) with modifications. • Single moment, bulk representation. Mass-mixing ratios for each category. • Particle size distribution, particle fall speeds and transfers between categories (e.g. melting, condensation) diagnosed each time step. Cloud Liquid qv (T+0) qcl (T+0) qcl (T+1) Cloud Ice / Snow qcf (T+0) qcf (T+1) qr (T+1) qg (T+1) Vapour Original Scheme New for high resolution Rain qr (T+0) New Jan 2013 Graupel qg (T+0) qv (T+1) Boundary Layer Clouds • Improved drizzle and fog package (Wilkinson et al 2013, QJRMS). • New particle size distribution (Abel and Boutle, 2012, QJRMS). Thompson Scheme Wilkinson et al (2013) • Moving towards an improved liquid to rain autoconversion (Boutle and Abel, 2012, ACP), Marshallbut not yet Palmer implemented. (Old UM) Abel and Boutle (2012) Introducing a new Generic Ice PSD • Microphysics changes • Change to a more realistic ice particle size distribution: • Data covers wider temperature and IWC range • Better quality data (Anti-shatter filtering) • Change to a fallspeed that is within the range of available data • Radiation changes • New ice optical properties which have • Same PSD as microphysics • Same mass-diameter relation as microphysics • Aims: • Improve high cloud • Tie parameterisations to better observations Houze et al 1979 Field et al. 2007 Comparison of PSDs • Insitu data from Constrain, 2010 • Black: • current global model PSD • Green: • Proposed change Fallspeed parameterisation • Black data from Mitchell 1996 • Purple: Global • Solid = snow • Dashed = ice • Green: UKV PS32 • Proposed change 10 year validation against ‘GA5’: Ice water content 215mb 600mb Control Experiment Differences Prognostic Graupel and Lightning Forecasting • Compare UM graupel scheme to others using Kinematic driver model (KiD; Shipway and Hill 2012, QJRMS) • Trial: Ottery St Mary hailstorm in a 1 km model. Old New • Use graupel mass to predict lightning (currently using McCaul et al 2009, Weather and Forecasting) Graupel water path A DYMECS lightning case: 1300-1900 UTC on 07/08/11 UKV Sferics 600kmx300 dx=1km Testing the parameterization of updraft velocity standard deviation ( W ) in NWP Run UM-UKV at x,y=1,5km horizontal resolution over the ASTEX domain [800*1000] Vertical velocity [m/s] < W>L using 3 NN [m/s] new < W>L [m/s] Apply contribution of sub-grid variability < W > = 0,038 m/s < < W > = 0,199 m/s W > increases by a factor ~ 5.2 Application to UKV: cold air outbreakcase Testing the parameterization of updraft velocity standard deviation ( W ) in NWP Run UM-UKV at x,y=1km horizontal resolution over the CONSTRAIN domain [750*1500] [email protected] Apply contribution of sub-grid variability < < < W > = 0,825 m/s W > increases by a factor ~ 2.7 W > = 0,202 m/s < W > = 0,550 m/s © Crown copyright Met Office DX=500M DX=200M DX=100M DX=1000M + SGS < w> = 0.257 < w> = < w> = 0.402 < w> = < w> = 0.600 < w> = 0.713 < w> = 0.712 < w> = 0.754 Questions??