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The Convective-scale UM Physics Developments. Richard Forbes (MET OFFICE, Joint Centre for Mesoscale Meteorology, Reading) October 2006. Talk Outline. Current status of convective-scale modelling at the Met Office. Recent developments in sub-grid parametrization schemes.
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The Convective-scale UM Physics Developments Richard Forbes (MET OFFICE, Joint Centre for Mesoscale Meteorology, Reading) October 2006
Talk Outline • Current status of convective-scale modelling at the Met Office. • Recent developments in sub-grid parametrization schemes. Convective-Scale Modelling (JCMM): Peter Clark, Rachel Capon, Richard Forbes, Carol Halliwell, Humphrey Lean, Andrew Macallan, Nigel Roberts Convective-Scale Data Assimilation (JCMM): Susan Ballard, Mark Dixon, Zhihong Li, Olaf Stiller, Sean Swarbrick
Developments in convective scale NWP • Development of version of model appropriate for convective scale since ~2000. • Now running routinely at ~1 km (and higher) in research mode. • Encouraging results so far, but many enhancements under development • Recent testing focussed on convective storm cases from the Convective Storms Initiation Project (CSIP) • Also assessing model for other extreme events (flooding/fog/wind….) • Emphasis increasingly on data assimilation (3DVAR+LHN, 4DVAR in future). • 4 km ‘intermediate’ UK model quasi-operational. • 1.5 km ‘on-demand’ small area model planned for early 2007 • 1.5 km UK model planned for 2009 (next supercomputer).
Standard Domains Previous Current
CSIP IOP 18 12km/4km/1.5km comparison Animation of surface rain rates for 12km, 4km, 1.5km and radar from 0800 UTC to 2000 UTC on 25/08/2005 UM 4km UM 12km UM 1.5km Radar
CSIP IOP 18 – 25/08/2006 11:30Z Modis Terra Visible Image 1.5 km Model 6hr Forecast Radar 1130 UTC
NWP Model Orography 12 km 4 km 1 km Height of model orography (m)
Fog Forecasting: Case Study Log(Visibility) 12 km RMS Error 4 km 1 km 12 km 1 km 24 h loop 18 UTC 09/12/2003 1km L76 Forecast
Convective-scale UM verification • Rainfall accumulation fraction skill score for different horizontal length scales
Convective-scale UM verification • Fraction skill score for hourly rainfall accumulations (for a 50km length scale and relative threshold of the 90th percentile) for convective case studies in 2004/2005 (12 cases, 48 f/c). • Dashed lines (spinup) • Solid lines (assimilation) • 4km spin-up significantly longer than 1km spin-up. • Assimilation better than spin-up at all forecast times. • After initial period, 1km better than 4km better than 12km.
Convective-scale UM Issues • Initiation of convection is of prime importance – if the model does not correctly initiate, the subsequent forecast will be in error. • Need to understand the inherent predictability of different mechanisms (e.g. surface forced sea-breeze convergence, orography, gravity waves, secondary initiation) -> CSIP • The subsequent evolution of the convective cells is particularly dependent on the sub-grid turbulent mixing and then the microphysics parametrization once condensation/precipitation begins. • Turbulence, microphysics and surface exchange parametrizations are all areas of active development.
Sub-grid parametrization developments • Sub-grid turbulence/boundary layer: • 3D Smagorinsky-Lilly first order turbulent mixing scheme (stochastic backscatter ?) • Blending with non-local 1D scheme for intermediate resolutions. • Microphysics: • Graupel, representation of ice/snow hydrometeors, numerics, warm rain processes. • Impact of latent heat terms on the dynamics (cold pools). • Surface Exchange: • Soil moisture, soil properties, LAI, urban areas, lakes, snow…. • Radiation: • Included slope aspect and angle into the incoming direct short-wave radiation scheme. • Parametrized Convection: • At 4km, CAPE dependent CAPE closure timescale to limit convective parametrization when high CAPE. • At ~1km, shallow convection mass-flux scheme being tested.
Parametrization of sub-grid mixing in the UM • Existing parametrizations in UM: • In the vertical • Deep/mid-level/shallow convection parametrization scheme • 1D non-local boundary layer scheme (Lock et al. 2000) • In the horizontal • Conservative operator with constant diffusion coefficient • For high resolution, require a 3D turbulence parametrization • First order scheme may be sufficient (do higher order schemes provide any benefit ?) • We have implemented a variant of Smagorinsky-Lilly subgrid model. • Eddy-viscosity and eddy-diffusivity computed from resolved strain-rate, scalar gradients and certain prescribed length scales.
Sub-grid turbulence scheme • Questions: • What are the resolution convergence properties ? • At what resolution does it become important to use a 3D local-mixing based approach ? • Can we improve on the intermediate resolutions ? • Do we need to treat the boundary layer differently to the free troposphere ? • Idealised simulations • Dry convective boundary layer • Shallow cumulus • Diurnal cycle of deep convection • Squall line • Real convective case studies
Sub-grid turbulence: Dry CBL • Dry convective boundary layer • Initial neutral 1km deep boundary layer • 300 Wm-2 surface heat flux • Boundary layer deepens with time and entrains air at top • Can look at properties as the horizontal grid resolution varies
Sub-grid turbulence: Diurnal Cycle UM with 1D BL scheme • Diurnal cycle of deep convection (GCSS Deep Convection WG Case 4). • UM simulations 100m to 4km resolution. Comparison with other CRMs. • Increasing onset delay and overshoot with decreasing resolution. • 3D Smagorinsky scheme reduces delay and overshoot. UM with 1D BL scheme + const. horiz diffusion UM with 3D Smagorinsky
Sub-grid turbulence: 16/06/05 Case study • Impact of 3D Smagorinsky turbulence scheme is to reduce intensity of over-active convective cells. 1km UM with 1D boundary layer scheme 1km UM with 3D Smagorinsky scheme Radar (5km res.)
Microphysics and cold pools • The microphysics parametrization has an impact on cold pool generation through evaporative cooling, which affects the evolution of the convection and secondary initiation. • Many uncertainties and approximations in microphysical schemes which can affect the location and intensity of latent heating/cooling. Primary Initiation Secondary Initiation (Coastal convergence /orography) Cold Pool
CSIP IOP 18 – 25/08/2006 11:30Z Modis Terra Visible Image 1.5 km Model 6hr Forecast Radar 1130 UTC
CSIP IOP 18 – 25th August 2005 – 12 UTC Screen Temperature 12 km 4 km
CSIP IOP 18 – 25th August 2005Chilbolton Timeseries: Near-surface temperature
Sensitivity to Microphysics: Case study Surface rainfall rate (mm/hr) at 13:00 UTC on 04/07/2005 from the 1km UM and radar. 300 km UM 1km UM 1km on 5km radar grid Radar 5km
Quantifying Microphysical Impacts • Some changes affect the mean precipitation, others have more of a dynamical impact (through influencing the cold pool generation) leading to shorter de-correlation times.
Surface exchange: • Soil moisture PDM (Probability Distribution Model) • What percentage of the rainfall remains in the soil and what percentage is runoff into the rivers ? • Urban representation • Street canyon/roof tops, anthropogenic heat source • Soil properties • Van Genuchten • Seasonally varying vegetation (Leaf Area Index) • JULES Joint UK Land Environment Simulator • Collaborative land surface model development (Met Office, UK Universities, Research Institutes) • Stand alone single-point / regional / global • Part of the UM system (used for NWP and Climate)
Urban Impact on 20 m Temperature Point 1: Upstream Point 2: Central London Point 3: Downstream Suburbs Point 4: Downstream Rural 1 2 Point 1 3 1.0 Point 2 Point 3 4 Point 4 1.5 0.5 T+12 00Z 11/05/2001
Summary • 4km UM operational for the UK (since May 2005). 1.5km on-demand UM operational 2007. 1.5km UK domain operational in 2009. • Current UM dynamics/physics giving broadly successful results. Verification methods show benefit of ~1km model over lower resolution models (with assimilation). (Need an appropriate method of verification for precipitation in high res. models). • However, there are still many improvements to be made and physics changes to investigate. For convection….. • Convective Initiation: Surface characteristics (can give predictability). • Early stages of convective development Turbulence scheme is a key factor. • Convective evolution and secondary initiation: Microphysics and cold pools. • Use of a hierarchy of idealised studies for understanding the implementation of sub-grid parametrizations can be very informative.