Physics for ‘High Resolution’ UM Configurations

1. Physics for ‘High Resolution’ UM Configurations Peter Clark Met Office (Joint Centre for Mesoscale Meteorology, Reading)

2. Talk Outline • Current status • Microphysics • Turbulence • Q&A • Urban surface exchange • Radiation

3. ‘High Resolution’ Aims & objectives • Prediction of individual major storms over 1-3 h timescale. • Fine scale DA – nowcasting. • Useful (statistical) prediction of storm characteristics over 24 h timescales. • Organisation and triggering better than parametrization can achieve. • Improvement of forecast characteristics particularly affected by surface forcing: • rainfall, visibility and fog, extreme wind, applicability to the urban environment • Intermediate scale model (4 km) operational since early 2006. • UK coverage. • 3h cycle 3DVAR+Latent Heat Nudging/Moisture Observation Processing System. • Development of a new convective scale NWP model and data assimilation configuration with a grid length of about 1km. • 1.5 km ‘on-demand’ 450x450 km Dec 2006. • 1.5 km UK 2009. • Ensembles 2011+

4. Current status – 1 & 1.5 high resolution models • Substantial experience running at 1 km. Now implemented 1.5 km. 76 levels (2x38), 50 s timestep. (Will be implementing 70 level set soon). • Enhanced microphysics (see later). • Standard BL scheme+del-4 horizontal diffusion, no convection scheme. (See later) • Standard MOSES II 9-tile surface exchange (ITE 25 m land-use over GB) + anthropogenic heat source. • New ‘two-tile’ urban scheme under test. • Radiation called every 5 min (6 timesteps) + radiation on slopes. • Variable resolution working and likely to be adopted for 2009 implementation.

5. Microphysics

6. High Resolution Microphysics Diagnostic Operational Unified Model Wilson and Ballard (1999) “Cloud Resolving” Models

7. Cloud liquidwater Water vapour Ice crystals Snow aggregates Rain Graupel UM Physics Status for Convective Scale • Enhanced microphysics available from UM 6.0 • Bulk, single moment formulation • Switches enable choices: • Single ice prognostic with diagnostic split between snow/ice. • Prognostic/diagnostic rain. • Graupel/no graupel • Most evaluation done with intermediate scheme • Tested in idealised model, especially GCSS LBA diurnal cycle (Grabowski et al. 2006). • Major benefits of prog. rain for ‘seeder/feeder’ orographic enhancement. Cloud liquidwater Water vapour Ice crystals + Snow aggregates Rain

8. Diurnal Cycle Case Study Average rainrates through the diurnal cycle from TRMM-LBA radar. • Data from TRMM LBA observational campaign (Rondonia, Brazil) • Initialisation from representative single profile at sunrise (07:30 am local time). Diurnally varying surface fluxes. Bicyclic model domain. • Intercomparison of CRMs (GCSS Deep Convection WG Case 4, Grabowski et al. 2006). • Focus on development of convection in first 6 hours. Observed onset of precipitation is ~10:30 (3 hours after sunrise). Plan view of model surface rain rate 6 hours after sunrise (1.30pm local time).

9. GCSS TRMM-LBA Diurnal Cycle Timeseries of vertical profiles of hydrometeor water contents UM with enhanced microphysics UM Reference Comparison with CRM – possibly excessive glaciation

10. Cloud streets from coast Squall line CSIP IOP 18 – 25/08/2006 3GHz Radar 1146-1148 UTC Modis Terra 1125 UTC Radar 1130 UTC

11. Unified Model 1.5km Domain • 360x288 gridpoints • 76 Vertical Levels • Nested in UK 4km model • Initial and LBC operational 06 UTC 12 km ‘UK Mesoscale’ • No additional DA

12. 1.5 km L76 UM Forecast 13 UTC Cross Section

13. Microphysics sensitivity 11 UTC Wind speed Potential Temp Control Dashed line= Freezing level Heterogeneous Nucleation only at T<-40C White contours= Cloud fraction With graupel No rain evaporation

14. Future plans - microphysics • Improvements to vertical transport (especially graupel). • Improved timestep dependence – especially Bergeron-Findeisen. • Two moment single ice to replace single moment ice and snow. • Minor updates to process rates.

15. Turbulence

16. Turbulence at 1 km • Current forecasting capability of UM at 1 km horizontal resolution uses ‘standard’ non-local 1D BL plus fixed (del-4) horizontal diffusion. • Works well but not perfectly. • Anticipate need for 3D scheme, but highly asymmetric grid. • Starting point is Smagorinsky-Lilly approach: horizontal and vertical diffusion function of Richardson no., shear and a mixing length that scales with grid length. • Tested robustness of the UM dynamics and implementation of scheme by comparing genuine large-eddy simulation with the Met office Large-eddy model (which has been thoroughly tested at this limit). • Dry CBL • Cu-capped BL (BOMEX equilibrium trade cumulus case) • Tested appropriate choice of scheme at ~1 km using idealised diurnal cycle and real cases.

17. Problems with initiation and shallow cumulus 1 km Cloud-top temperature Radar (5km) MSG High Res Visible Cirrus Cloud streets CSIP IOP 12 28/07/2005 We have a consistent problem of precipitation from explicit ‘shallow’ cumulus. 1 km precipitation rate

18. Subgrid turbulence scheme in UM Smagorinsky-Lilly subgrid-turbulence scheme with Richardson number (Ri) based stability factor where Mixing length scale Wind shear where Stability function (unstable) and

19. Dry CBL idealised model set up • Met Office Unified model in idealised mode: • bi-periodic domain • prescribed forcings e.g. surface fluxes and geostrophic winds • Dry convective boundary layer case: • prescribed surface heat flux of 300Wm-2 • initial mixed layer up to 1km with overlying stratification • Domain 5kmx5kmx5km • resolution 50 m in horizontal for both. Refined vertical grid near the surface for UM. • Comparison with Met Office Large-eddy model in the same configuration. • Smagorinsky model: • Mixing length = CsD where D is the horizontal grid length- significant control of sub-grid dissipation. • Lilly ’69 derives a value of Cs=0.17 for a homogeneous inertial sub-range. In practical large-eddy simulation Cs is adjusted in the region of this value. • A value of Cs=0.23 is used in the control UM and LEM simulations.

20. UM/LEM comparison at 50 m resolution W at 1 km snapshot UM Cs=0.46 UM Cs=0.23 LEM UM Cs=0.115 • UM works at 50 m resolution • Requires Cs smaller than LEM • Cu-capped BL acceptable • More variability • Within range of other models

21. UM Simulations • Reference: • 1D vertical non-local boundary layer scheme. • Constant horizontal diffusion. • 3DSL • “3D” Smagorinsky-Lilly local turbulent mixing scheme with Cs=0.23. • Series of sensitivity simulations with variations to mixing length (Cs) and combinations of the above.

22. Sensitivity to grid resolution (Surface rainrate) • Increasing delay of first rain and overshoot with decreasing resolution • “3D” Smagorinsky scheme reduces overshoot significantly and reduces variation of delay with res. • 200m “3D” Smagorinsky scheme is close to 200m CRM (within uncertainty) • 1km reference run has the first rain at the same time as the 200m UM and CRM REFERENCE 3DSL Cs=0.23

23. Sensitivity to grid resolution(Hydrometeor Content) • Increasing delay of first rain and overshoot with decreasing resolution • “3D” Smagorinsky scheme reduces overshoot significantly and reduces variation of delay with res. • 200m “3D” Smagorinsky scheme is close to 200m CRM (within uncertainty) • 1km reference run has the first rain at the same time as the 200m UM and CRM REFERENCE 3DSL Cs=0.23

24. Impact of vertical mixing • Increased vertical mixing in the boundary layer leads to earlier convective initiation All UM runs have constant horizontal diffusion K=1430

25. Impact of vertical mixing • Increased vertical mixing in the boundary layer leads to earlier convective initiation All UM runs have constant horizontal diffusion K=1430

26. Impact of horizontal mixing • Increased horizontal mixing in the boundary layer leads to later convective initiation All UM runs have the non-local boundary layer scheme in the vertical

27. Impact of horizontal mixing • Increased horizontal mixing in the boundary layer leads to later convective initiation All UM runs have the non-local boundary layer scheme in the vertical. ConstDiff Coefficient: K=1430. Max Diff for Cs runs: K=2086.

28. Implications for sub-grid turbulence param. • Results are a subtle balance of horizontal mixing (delays initiation) and vertical mixing (promotes initiation). • For 1km grid resolution, the results suggest: • The non-local scheme is appropriate for vertical mixing in the boundary layer. • There is a need for increased mixing of convective updraughts in the free-troposphere to reduce the overshoot. A shear/stability dependent approach is more physical than constant coefficient diffusion. • For 200m grid resolution, the results suggest: • The shear/stability dependent approach of the Smagorinsky-Lilly scheme is more appropriate than the non-local scheme. • The model is close to convergence (from earlier comparison with 100m resolution simulations).

29. Impact of turbulence scheme on convective forecast (CSIP IOP18 - 25th Aug 2005) Reference Satellite IR and Radar Satellite (Visible) MODIS Horiz Cs=0.075 Horiz Cs=0.10 Horiz Cs=0.15

30. Convective cell statistics (CSIP IOP18)Sensitivity to turbulence scheme Reference Cell Area (>2 mm/h) Radar Radar Reference Cell Number (>2 mm/h) Model data is area-averaged to 5km radar grid

31. Convective cell statistics (CSIP IOP18)Sensitivity to turbulence scheme Average convective cell size as a function of rainrate threshold Average number of convective cells as a function of rainrate threshold Radar Reference Reference Radar Model data is area-averaged to 5km radar grid

32. Convective cell statistics (CSIP IOP18)Sensitivity to turbulence scheme • Reference run has too many, too small convective cells compared to the observations, particularly at low rain rates. • Simulations with horizontal turbulence scheme have cell sizes closer to observed, particularly as the horizontal mixing is increased (higher Cs). • Simulations with the horizontal turbulence scheme have cell numbers closer to observed, particularly at lower rain rates (<4 mm/hr) but still have too many cells with higher rain rates (> 4mm/hr). • (Note, the 8mm/hr threshold is dominated by the main organised squall line in the radar and is not representative.) • The model still does not have enough stratiform rain around convective cores.

33. Summary • 3D sub-grid turbulent mixing parametrization introduced into the UM (based on Smagorinsky-Lilly). UM works as LES (50 m). • At ~ 1 km use hybrid approach combining the 1D non-local boundary layer scheme with aspects of the 3D scheme. • Tested in idealised and real case studies and can have a very significant impact on convective initiation and evolution. • Reduces over-prediction of small convective cells at 1.5km. Reduces excessive rain rates in larger storms.

34. Turbulence scale Mixing length ∆x Future plans - turbulence • ‘Blended’ BL and (moist) 3D turbulence. • Mixed turbulence/large eddy behaviour in BL • Smagorinsky outside (?) • Stochastic backscatter. • Initially based on Weinbrecht/Mason • Extensions for shallow Cu?

35. Questions & Answers

36. Urban Surface Exchange

37. Urban surface exchange in the UM • The UM uses a ‘tile’ surface exchange scheme, including an ‘urban’ tile. • The urban tile is quite crude: • Enhanced roughness. • Enhanced drainage. • Modified albedo. • Urban ‘canopy’ to represent thermal inertia of buildings. • Anthropogenic heat source Nocturnal heat island in 1.5 km forecast– 05/07/2006 00 UTC

38. Impact of anthropogenic heat flux London Weather Centre Remote Rural No AHF With AHF 23 Cases

39. Troof Twall1 Twall2 Tfloor Urban Canyons • Negligible roof<>canyon coupling. • Single canyon temperature. • Implies two-tile simplification. • Resistance measurements (Barlow/Harman) • Resistance model (Harman) • Radiation model and two surface simplification (Harman) • Two-tile surface only (Best) UM • Two-tile with radiation model single column UM (Harman) • Further work, full UM (Porson) Troof Tcanyon Tcanyon Tcanyon

40. Surface-only tests Martin Best

41. Next Steps • Fully integrated two-tile model in UM. • Parameter provision – different approaches. • Validate in surface only model • Model intercomparison. • Impact on mesoscale flow. • Boundary layer development through urban/rural/urban transition. • Revisit momentum transport (and scalar) – move away from effective roughness treatment.

42. Radiation

43. Radiation • Edwards-Slingo radiation scheme has been modified to include slope aspect and angle in direct solar radiation part. (Dominant terms, based on Oliphant et al 2003). • Significant impacts on screen temperature but very difficult o demonstrate impact on forecast.

44. Scientific question. Spatial impact of model changes. Single case Change to vertical levels Roberts, 2007, MWR (In press)

45. Scientific question. Spatial impact of model changes. Single case Modelling radiation on slopes

46. Questions & Answers