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Page 1© Crown copyright 2006 The Convective-scale UM Physics Developments Richard Forbes (MET OFFICE, Joint Centre for Mesoscale Meteorology, Reading) October 2006
Page 2© Crown copyright 2006 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
Page 3© Crown copyright 2006 Current status of convective-scale UM
Page 4© Crown copyright 2006 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).
Page 5© Crown copyright 2006 Standard Domains Previous Current
Page 6© Crown copyright 2006 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 1.5kmRadar
Page 7© Crown copyright 2006 CSIP IOP 18 – 25/08/ :30Z Radar 1130 UTC Modis Terra Visible Image1.5 km Model 6hr Forecast
Page 8© Crown copyright 2006 NWP Model Orography 12 km4 km 1 km Height of model orography (m)
Page 9© Crown copyright 2006 Fog Forecasting: Case Study 24 h loop 18 UTC 09/12/2003 1km L76 Forecast Log(Visibility) RMS Error 12 km 4 km 1 km 12 km
Page 10© Crown copyright 2006 Convective-scale UM verification Rainfall accumulation fraction skill score for different horizontal length scales
Page 11© Crown copyright 2006 Convective-scale UM verification Fraction skill score for hourly rainfall accumulations (for a 50km length scale and relative threshold of the 90 th 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.
Page 12© Crown copyright 2006 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.
Page 13© Crown copyright 2006 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.
Page 14© Crown copyright 2006 Sub-grid Turbulent Mixing
Page 15© Crown copyright 2006 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.
Page 16© Crown copyright 2006 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
Page 17© Crown copyright 2006 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
Page 18© Crown copyright 2006 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
Page 19© Crown copyright 2006 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.)
Page 20© Crown copyright 2006 Microphysics
Page 21© Crown copyright 2006 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) Cold Pool Secondary Initiation
Page 22© Crown copyright 2006 CSIP IOP 18 – 25/08/ :30Z Radar 1130 UTC Modis Terra Visible Image1.5 km Model 6hr Forecast
Page 23© Crown copyright 2006 CSIP IOP 18 – 25 th August 2005 – 12 UTC 4 km 12 km Screen Temperature
Page 24© Crown copyright 2006 CSIP IOP 18 – 25 th August 2005 Chilbolton Timeseries: Near-surface temperature
Page 25© Crown copyright 2006 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 1kmUM 1km on 5km radar grid Radar 5km 300 km
Page 26© Crown copyright 2006 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.
Page 27© Crown copyright 2006 Surface Exchange
Page 28© Crown copyright 2006 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)
Page 29© Crown copyright 2006 Urban Impact on 20 m Temperature T+12 00Z 11/05/2001 Point 2 Point 3 Point 1 Point 4 Point 1: Upstream Point 2: Central London Point 3: Downstream Suburbs Point 4: Downstream Rural
Page 30© Crown copyright 2006 Summary
Page 31© Crown copyright 2006 Summary 4km UM operational for the UK (since May 2005). 1.5km on-demand UM operational km UK domain operational in 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.
Page 32© Crown copyright 2006 The End
© Crown copyright Met Office Met Office Experiences with Convection Permitting Models Humphrey Lean Reading, UK Nowcasting Workshop,
Dynamical and Microphysical Evolution of Convective Storms (DYMECS) University: Robin Hogan, Bob Plant, Thorwald Stein, Kirsty Hanley, John Nicol Met Office:
Cloud Resolving Models: Their development and their use in parametrization development Richard Forbes, Adrian Tompkins.
Page 1© Crown copyright 2005 Use of EPS at the Met Office Ken Mylne and Tim Legg.
DYMECS: Dynamical and Microphysical Evolution of Convective Storms (NERC Standard Grant) University of Reading: Robin Hogan, Bob Plant, Thorwald Stein,
Parametrizations in Data Assimilation ECMWF Training Course May 2012 Philippe Lopez Physical Aspects Section, Research Department, ECMWF (Room 113)
1 00/XXXX © Crown copyright Carol Roadnight, Peter Clark Met Office, JCMM Halliwell Representing convection in convective scale NWP models : An idealised.
Parameterizations in Data Assimilation Philippe Lopez Physical Aspects Section, Research Department, ECMWF (Room 113) ECMWF Training Course May 2010.
© Crown copyright Met Office Regional climate model formulation PRECIS Workshop, Reading University, 23 rd – 27 th April 2012.
Regional Models Lake Victoria Model Prepared by C. Tubbs, P. Davies, Met Office UK Revised, delivered by P. Chen, WMO Secretariat SWFDP-Eastern Africa.
Predictable Chaotic Exhibits memory Equilibrium Towards non-equilibrium Acknowledgements LD is supported by NERC CASE award NER/S/A/2004/ Conclusions.
Clouds and their turbulent environment Robin Hogan, Andrew Barrett, Natalie Harvey Helen Dacre, Richard Forbes (ECMWF) Department of Meteorology, University.
Urban Modelling 1 03/2003 © Crown copyright Urban Scale NWP with the Met Office's Unified Model Peter Clark Mesoscale Modelling Group Met Office Joint.
© Crown copyright Met Office Scientific background and content of new gridded products Bob Lunnon, Aviation Outcomes Manager, Met Office WAFS Workshop.
© Crown copyright Met Office Convection plans Alison Stirling.
4. First look Initial analysis of contrasting timeseries (Figure 2) shows: Shorter timescales have a smaller range of mass fluxes with lower maxima and.
Laura Davies, University of Reading, UK. Supervisors: Bob Plant, Steve Derbyshire (Met Office)
Reading, UK Parametrizations and data assimilation © ECMWF 2012 Marta JANISKOVÁ ECMWF Parametrizations and data assimilation.
An Overview of Numerical Weather Prediction Models.
Reading, UK Parametrizations and data assimilation © ECMWF 2010 Marta JANISKOVÁ ECMWF Parametrizations and data assimilation.
Some questions on convection that could be addressed through another UK field program centered at Chilbolton Dan Kirshbaum 1.
Robin Hogan Julien Delanoe, Ewan OConnor, Anthony Illingworth, Jonathan Wilkinson University of Reading, UK Quantifying the skill of cloud forecasts from.
Robin Hogan Ewan OConnor, Anthony Illingworth University of Reading, UK Chris Ferro, Ian Jolliffe, David Stephenson University of Exeter, UK Verifying.
Gettelman: November 2006 An Introduction to Climate Modeling Andrew Gettelman National Center for Atmospheric Research Boulder, Colorado USA Assistance.
1 PV Generation in the Boundary Layer Robert Plant 18th February 2003 (With thanks to S. Belcher)
Arctic observing system for regional NWP Harald Schyberg (met.no), Frank Thomas Tveter (met.no) Roger Randriamampianina (met.no), Trygve Aspelien (met.no)
Robin Hogan Department of Meteorology University of Reading Cloud and Climate Studies using the Chilbolton Observatory.
Robin Hogan Ewan OConnor, Anthony Illingworth University of Reading, UK Clouds radar collaboration meeting 17 Nov 09 Ground based evaluation of cloud forecasts.
Cliquez pour modifier le style du titre Cliquez pour modifier le style des sous-titres du masque 1 Nowcasting strategies : Rapid analysis refresh and high.
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