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Physics for ‘High Resolution’ UM Configurations. Peter Clark Met Office (Joint Centre for Mesoscale Meteorology, Reading). Talk Outline Current status Microphysics Turbulence Q&A Urban surface exchange Radiation. ‘High Resolution’ Aims & objectives.

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slide1

Physics

for

‘High Resolution’

UM Configurations

Peter Clark

Met Office (Joint Centre for Mesoscale Meteorology, Reading)

slide2

Talk Outline

    • Current status
    • Microphysics
    • Turbulence
    • Q&A
    • Urban surface exchange
    • Radiation
high resolution aims objectives
‘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+
current status 1 1 5 high resolution models
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.
high resolution microphysics
High Resolution Microphysics

Diagnostic

Operational Unified Model

Wilson and Ballard (1999)

“Cloud Resolving” Models

um physics status for convective scale

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

diurnal cycle case study
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).

slide9

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

csip iop 18 25 08 2006

Cloud streets from coast

Squall line

CSIP IOP 18 – 25/08/2006

3GHz Radar

1146-1148 UTC

Modis Terra 1125 UTC

Radar 1130 UTC

unified model 1 5km domain
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
microphysics sensitivity 11 utc
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

future plans microphysics
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.
turbulence at 1 km
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.
problems with initiation and shallow cumulus
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

subgrid turbulence scheme in um
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

dry cbl idealised model set up
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.
um lem comparison at 50 m resolution
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
um simulations
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.
sensitivity to grid resolution surface rainrate
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

sensitivity to grid resolution hydrometeor content
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

impact of vertical mixing
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

impact of vertical mixing1
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

impact of horizontal mixing
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

impact of horizontal mixing1
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.

implications for sub grid turbulence param
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).
impact of turbulence scheme on convective forecast csip iop18 25 th aug 2005
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

convective cell statistics csip iop18 sensitivity to turbulence scheme
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

convective cell statistics csip iop18 sensitivity to turbulence scheme1
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

convective cell statistics csip iop18 sensitivity to turbulence scheme2
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.
summary
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.
future plans turbulence

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?
urban surface exchange in the um
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

impact of anthropogenic heat flux
Impact of anthropogenic heat flux

London Weather Centre

Remote Rural

No AHF

With AHF

23 Cases

urban canyons

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

next steps
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.
radiation
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.
slide44

Scientific question. Spatial impact of model changes.

Single case

Change to vertical levels

Roberts, 2007, MWR (In press)

slide45

Scientific question. Spatial impact of model changes.

Single case

Modelling radiation on slopes