Transcript Paul Field (Met Office, microphysics)
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.
Original Scheme New for high resolution New Jan 2013 Vapour Cloud Liquid Cloud Ice / Snow Rain Graupel q v (T+0) q cl (T+0) q cf (T+0) q r (T+0) q g (T+0) q q q v (T+1) q cl (T+1) q cf (T+1) r (T+1) g (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 • Moving towards an improved liquid to rain autoconversion (Boutle and Abel, 2012, ACP), but not yet implemented. Marshall Palmer (Old UM) Wilkinson et al (2013) 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
215mb
10 year validation against ‘GA5’: Ice water content
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.
• Use graupel mass to predict lightning (currently using McCaul et al 2009, Weather and Forecasting) Old New Graupel water path
UKV
A DYMECS lightning case: 1300-1900 UTC on 07/08/11
Sferics
600kmx300 dx=1km
Vertical velocity [m/s] 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] < 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] LES@250m
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=1000M DX=500M DX=200M DX=100M < w> = 0.257
< w> = 0.402
< w> = 0.600
< w> = 0.712
< w> = 0.627
< w> = 0.704
< w> = 0.713
< w> = 0.754