the convective-scale um physics developments
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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. - PowerPoint PPT PresentationTRANSCRIPT
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The Convective-scale UMPhysics Developments
Richard Forbes
(MET OFFICE, Joint Centre for Mesoscale Meteorology, Reading)
October 2006
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Talk Outline
1. Current status of convective-scale modelling at the Met Office.
2. 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
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Current status of convective-scale UM
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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).
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Standard Domains
Previous Current
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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 12km UM 4km UM 1.5km Radar
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CSIP IOP 18 – 25/08/2006 11:30Z
Radar 1130 UTC
Modis Terra Visible Image 1.5 km Model 6hr Forecast
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NWP Model Orography
12 km 4 km 1 km
Height of model orography (m)
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Fog Forecasting: Case Study
24 h loop18 UTC 09/12/2003 1km L76 Forecast
Log(Visibility)
RM
S E
rro
r
12 km
4 km
1 km
1 km12 km
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Convective-scale UM verification
• Rainfall accumulation fraction skill score for different horizontal length scales
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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.
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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.
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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.
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Sub-grid Turbulent Mixing
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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.
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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
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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
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Sub-grid turbulence: Diurnal Cycle
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
UM with 1D BL scheme + const. horiz
diffusion
UM with 3D Smagorinsky
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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.)
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Microphysics
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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
(Coastal convergence/orography)
ColdPool
Secondary Initiation
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CSIP IOP 18 – 25/08/2006 11:30Z
Radar 1130 UTC
Modis Terra Visible Image 1.5 km Model 6hr Forecast
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CSIP IOP 18 – 25th August 2005 – 12 UTC
4 km 12 km
Screen Temperature
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CSIP IOP 18 – 25th August 2005Chilbolton Timeseries: Near-surface temperature
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Sensitivity to Microphysics: Case study
Surface rainfall rate (mm/hr) at 13:00 UTC on 04/07/2005 from the 1km UM and radar.
UM 1km UM 1km on 5km radar grid
Radar 5km
300 km
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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.
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Surface Exchange
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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)
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Urban Impact on 20 m Temperature
1
23
4
0.5
1.0
1.5
T+12 00Z 11/05/2001
Point 2Point 3
Point 1
Point 4
Point 1: Upstream
Point 2: Central London
Point 3: Downstream Suburbs
Point 4: Downstream Rural
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Summary
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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.
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The End