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The convective-scale Unified Model: Results from UK case studies

The convective-scale Unified Model: Results from UK case studies. Richard Forbes (JCMM, Met Office) October 2005. Talk Outline. The high resolution UM in action An example UK case this summer from CSIP. How are we doing ? Verifying the high resolution UM convective rainfall.

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The convective-scale Unified Model: Results from UK case studies

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  1. The convective-scale Unified Model: Results from UK case studies Richard Forbes (JCMM, Met Office) October 2005

  2. Talk Outline • The high resolution UM in action • An example UK case this summer from CSIP. • How are we doing ? • Verifying the high resolution UM convective rainfall. • Improving the model • Examples of recent model developments

  3. The high resolution UM in action • An example UK case this summer from CSIP. • How are we doing ? • Verifying the high resolution UM convective rainfall. • Improving the model • Recent model developments. Peter Clark, Humphrey Lean

  4. HRTM Domains Note that operational UK 4km model uses larger (whole UK) domain

  5. CSIP Alan Blyth, Keith Browning, Lindsay Bennett, Karl Beswick, Karen Bozier, Barbara Brooks, Peter Clark, Fay Davies, Wendy Garland, Charles Kilburn, Darcy Ladd, John Marsham, Cyril Morcrette, Emily Norton, Doug Parker, Ed Pavelin, Nigel Roberts, Ann Webb.

  6. Aberystwyth Wind Profiler Leeds Sodar Salford Doppler Lidar Leeds AWS Reading JCMM, Forecast Centre Radiosondes Met Office Radiosonde Met Office Unified Model Forecasts Chilbolton Radars and Lidar UMIST Cessna Met Office Radiosonde Cyril Morcrette, University of Reading

  7. CSIP IOP 18 – 25th August 2005 0700 Water Vapour 1200 850 hPa w, 300 hPa height

  8. CSIP IOP 18 – 25th August 2005 09 UTC Network radar – 1/2/4 km Composite

  9. CSIP IOP 18 – 25th August 2005 10 UTC Network radar – 1/2/4 km Composite

  10. CSIP IOP 18 – 25th August 2005 11 UTC Network radar – 1/2/4 km Composite

  11. CSIP IOP 18 – 25th August 2005 12 UTC Network radar – 1/2/4 km Composite

  12. CSIP IOP 18 – 25th August 2005 13 UTC Network radar – 1/2/4 km Composite

  13. CSIP IOP 18 – 25th August 2005 14 UTC Network radar – 1/2/4 km Composite

  14. CSIP IOP 18 – 25th August 2005 MSG High Resolution Visible

  15. CSIP IOP 18 – 25th August 2005 Observations Chilbolton Rainfall Rate Timeseries Sferics 11Z to 13Z Peak 40 mm/hr Chilbolton 1.5m Temperature Timeseries 8 K drop

  16. A convective-scale NWP System Animation of surface rain rates for 12km, 4km, 1km and radar from 0800 UTC to 1500 UTC on 25/08/2005 300 km Radar UM 12km UM 4km UM 1km

  17. CSIP IOP 18 – 25th August 2005 – 12 UTC 4 km model 10 m wind and convergence Rainfall rate

  18. CSIP IOP 18 – 25th August 2005 – 12 UTC Screen Temperature 12 km 4 km

  19. CSIP IOP 18 – 25th August 2005 – 14 UTC Divergence Screen Temperature 4 km

  20. CSIP IOP 18 – 25th August 2005 – 14 UTC Surface Rainfall Rate 4 km 8hr f/c Radar

  21. CSIP IOP 18 – 25th August 2005 – 14 UTC 4 km 8hr f/c High/Med/Low Cloud Visible Sat Image

  22. Summary – CSIP case study • Showed high resolution UM results for one convective case study this summer (25th Aug 2005) • Secondary generation of convective storms by cold pools is an important process that needs to be captured by the model for a good forecast. • A 12km resolution model is poor at representing this aspect of the dynamics, but 4km and 1km models with explicit convection are able to do so.

  23. The high resolution UM in action • An example UK case this summer from CSIP. • How are we doing ? • Verifying the high resolution UM rainfall. • Improving the model • Recent model developments. Nigel Roberts, Humphrey Lean, Peter Clark

  24. Background - What do we want to know? 1km model – should improve precipitation forecasts In some circumstances (e.g. strong orographic forcing) small scales can be relatively predictable, but most of the time small scales are less predictable. Can a 1-km model provide more accurate and useful forecasts of rainfall events on the scales of river catchments? On what scales should the output be presented?

  25. Verification approach Verify against radar – good spatial coverage. Stable network over UK. Verify accumulations - smooth out temporal noise. Use accumulation exceedance thresholds e.g. > 4 mm, > 8 mm …. Verify over different spatial scales using a conceptually simple approach. Fractions/probabilities from nearest neighbouring points.

  26. Radar 12 km forecast 1 km forecast The problem we face Six hour accumulations 10 to 16 UTC 13th May 2003 0 100 km 0.125 0.5 1 2 4 8 16 32 mm

  27. Schematic example - different scales

  28. Six hour accumulations 10 to 16 UTC 13th May 2003 1-km forecast Radar 0.125 0.5 1 2 4 8 16 32 mm

  29. > 4 mm > 4 mm 4 mm threshold, Fractions at grid scale (1 or 0) Model Radar 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 Fraction

  30. > 4 mm > 4 mm 4 mm threshold, Fractions within 35x35 km squares Model Radar 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 Fraction

  31. 4 mm threshold, Fractions within 75x75 km squares Model Radar 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 Fraction

  32. 4 mm threshold, Fractions within 105x105 km squares Model Radar 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 Fraction

  33. Skill score for fractions/probabilities - Fractions Skill Score (FSS) A score for comparing fractions with fractions Brier score for comparing fractions

  34. Graphical behaviour of the Fractions Skill Score

  35. Summer 2004 Trial • Run seven cases from 2004 period (mostly convective) • For each case run 4 forecasts at 3 hour intervals • Run one suite with 4km, 1km assimilation and a • second initialising 4km, 1km from 12km analyses. • Forecasts out to T+7 for 1km model • Aggregate statistics over forecasts and cases.

  36. HRTM Domains Note that operational UK 4km model uses larger (whole UK) domain

  37. Assimilation Configuration • 12km 3d-Var, MOPS/LHN • 4km 3d-Var (scale selective), MOPS/LHN • 1km 4km increments, MOPS/LHN • 3 hour cycles all models

  38. Scores for 6 hour accums 1, 4 and 16mm thresholds Blue 12km Green 4km Red 1km Solid: Assim Dotted: Spinup 1mm / 6hr threshold 16mm / 6hr threshold 4mm / 6hr threshold

  39. Area average rain rates over 2004 summer trial Blue 12km Green 4km Red 1km Black Radar Solid: Assim Dotted: Spinup

  40. Scores for 1 hour accums 1 and 4mm threshold Blue 12km Green 4km Red 1km Solid: Assim Dotted: Spinup

  41. Summary - Verification • Verifying high resolution precipitation forecasts on the grid scale is not always very helpful given the chaotic nature of convection. • A skill score for an area is found to be a useful measure of rainfall forecast performance. • Verification from seven cases during the summer of 2004 shows there is increasing skill for higher rainrates as the resolution is increased. • Bias in the precipitation is still an issue (too much at high resolution) but this is being addressed.

  42. The high resolution UM in action • An example UK case this summer from CSIP. • How are we doing ? • Verifying the high resolution UM rainfall. • Improving the model • Recent model developments. Carol Halliwell, Richard Forbes, Peter Clark, Terry Davies, Yongming Tang

  43. Parametrization of sub-grid turbulent mixing Carol Halliwell, Peter Clark, Richard Forbes

  44. Parametrization of sub-grid mixing in the UM • Existing parametrizations in UM: • In the vertical • Convection scheme • 1D non-local boundary layer scheme • In the horizontal • First order conservative operator with constant diffusion coefficient • For high resolution, require a 3D turbulence parametrization • First order scheme may be sufficient • 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.

  45. Subgrid turbulence scheme in UM Smagorinsky-Lilly subgrid-turbulence scheme with Richardson number based stability factor (0 is basic mixing length)

  46. Impact of turbulence scheme on convective forecast (4th July 2005) Reference With Turbulence Param. 1km UM 6 hour forecast surface rainfall rate.

  47. Impact of turbulence scheme on convective forecast (4th July 2005) Number of cells Reference With Turbulence Time→ Average cell size Histogram of cell sizes Time→

  48. Summary – Turbulent Mixing • 3D sub-grid turbulent mixing parametrization introduced into the UM (based on Smagorinsky-Lilly). • Tested in idealised and real case studies and can have a very significant impact on convective initiation and evolution. • Reduces overprediction of small convective cells at 1km. Reduces excessive rain rates in larger storms. • Work is ongoing into most appropriate formulation for different resolutions, and enhancing the scheme (e.g. stochastic backscatter).

  49. Variable Resolution Grids Yongming Tang, Peter Clark, Terry Davies

  50. Variable Resolution • An alternative approach to 1-way nesting. • Grid varies from coarse resolution at the outer boundaries smoothly to a uniform fine resolution in the interior of the domain • Benefits close to hires domain boundary, e.g. reduces spin-up of convection at inflow boundaries Uniform High Res zone Uniform Coarse Res 1 Var-Res 1 Var-Res 2 Uniform Coarse Res 2 R1 R2 Typically, there are 3 regions, and inflation ratioR1 = R2 = 5~10%

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