the convective-scale unified model: results from uk case studies
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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. - PowerPoint PPT PresentationTRANSCRIPT
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The convective-scale Unified Model:Results from UK case studies
Richard Forbes (JCMM, Met Office)
October 2005
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Talk Outline
1. The high resolution UM in action An example UK case this summer from CSIP.
2. How are we doing ? Verifying the high resolution UM convective rainfall.
3. Improving the model Examples of recent model developments
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1. The high resolution UM in action An example UK case this summer from CSIP.
2. How are we doing ? Verifying the high resolution UM convective rainfall.
3. Improving the model Recent model developments.
Peter Clark, Humphrey Lean
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HRTM Domains
Note that operational UK 4km model uses larger (whole UK) domain
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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.
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Salford Doppler Lidar
Aberystwyth Wind Profiler
Leeds AWS
Leeds Sodar
Reading JCMM, Forecast Centre
Met Office Radiosonde
Met Office Radiosonde
Radiosondes
UMIST CessnaChilbolton Radars and Lidar
Met Office Unified Model Forecasts
Cyril Morcrette, University of Reading
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CSIP IOP 18 – 25th August 2005
0700 Water Vapour
850 hPa w, 300 hPa height
1200
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CSIP IOP 18 – 25th August 2005
Network radar – 1/2/4 km Composite
09 UTC
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CSIP IOP 18 – 25th August 2005
Network radar – 1/2/4 km Composite
10 UTC
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CSIP IOP 18 – 25th August 2005
Network radar – 1/2/4 km Composite
11 UTC
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CSIP IOP 18 – 25th August 2005
Network radar – 1/2/4 km Composite
12 UTC
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CSIP IOP 18 – 25th August 2005
Network radar – 1/2/4 km Composite
13 UTC
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CSIP IOP 18 – 25th August 2005
Network radar – 1/2/4 km Composite
14 UTC
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CSIP IOP 18 – 25th August 2005
MSG High Resolution Visible
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CSIP IOP 18 – 25th August 2005 Observations
Chilbolton Rainfall Rate Timeseries
Chilbolton 1.5m Temperature Timeseries
8 K drop
Peak 40 mm/hr Sferics 11Z to 13Z
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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
UM 12km UM 4km UM 1km Radar
300 km
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CSIP IOP 18 – 25th August 2005 – 12 UTC
4 km model
10 m wind and convergence Rainfall rate
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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 2005 – 14 UTC
4 km
DivergenceScreen Temperature
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CSIP IOP 18 – 25th August 2005 – 14 UTC
4 km 8hr f/c Radar
Surface Rainfall Rate
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CSIP IOP 18 – 25th August 2005 – 14 UTC
Visible Sat Image
4 km 8hr f/cHigh/Med/Low Cloud
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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.
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1. The high resolution UM in action An example UK case this summer from CSIP.
2. How are we doing ? Verifying the high resolution UM rainfall.
3. Improving the model Recent model developments.
Nigel Roberts, Humphrey Lean, Peter Clark
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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?
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Verification approach
Verify over different spatial scales using a conceptually simple approach. Fractions/probabilities from nearest neighbouring points.
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 ….
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Radar 12 km forecast 1 km forecast
0.125 0.5 1 2 4 8 16 32 mm
The problem we face
0 100 km
Six hour accumulations 10 to 16 UTC 13th May 2003
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Schematic example - different scales
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1-km forecast Radar
0.125 0.5 1 2 4 8 16 32 mm
Six hour accumulations 10 to 16 UTC 13th May 2003
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4 mm threshold, Fractions at grid scale (1 or 0)
Model Radar> 4 mm > 4 mm
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
Fraction
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Model Radar> 4 mm > 4 mm
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
Fraction
4 mm threshold, Fractions within 35x35 km squares
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Model Radar
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
Fraction
4 mm threshold, Fractions within 75x75 km squares
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Model Radar
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
Fraction
4 mm threshold, Fractions within 105x105 km squares
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Brier score for comparing fractions
Skill score for fractions/probabilities - Fractions Skill Score (FSS)
A score for comparing fractions with fractions
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Graphical behaviour of the Fractions Skill Score
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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.
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HRTM Domains
Note that operational UK 4km model uses larger (whole UK) domain
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Assimilation Configuration
• 12km 3d-Var, MOPS/LHN
• 4km 3d-Var (scale selective), MOPS/LHN
• 1km 4km increments, MOPS/LHN
• 3 hour cycles all models
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Scores for 6 hour accums 1, 4 and 16mm thresholds
Solid: AssimDotted: Spinup
Blue 12kmGreen 4kmRed 1km
1mm / 6hr threshold
4mm / 6hr threshold 16mm / 6hr threshold
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Area average rain rates over 2004 summer trial
Solid: AssimDotted: Spinup
Blue 12kmGreen 4kmRed 1kmBlack Radar
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Scores for 1 hour accums 1 and 4mm threshold
Solid: AssimDotted: Spinup
Blue 12kmGreen 4kmRed 1km
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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.
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1. The high resolution UM in action An example UK case this summer from CSIP.
2. How are we doing ? Verifying the high resolution UM rainfall.
3. Improving the model Recent model developments.
Carol Halliwell, Richard Forbes, Peter Clark, Terry Davies, Yongming Tang
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Parametrization of sub-grid turbulent mixing
Carol Halliwell, Peter Clark, Richard Forbes
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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.
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Subgrid turbulence scheme in UM
2mSf Ri 2
h hSf Ri
jiij
j i
uuS
x x
1/ 2
2
, ,1,3
1/ 2
2ij iji j
S S S
22 20 0
1 1 1
k z z
(0 is basic mixing length)
Smagorinsky-Lilly subgrid-turbulence scheme with Richardson number based stability factor
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Impact of turbulence scheme on convective forecast (4th July 2005)
Reference With Turbulence Param.
1km UM 6 hour forecast surface rainfall rate.
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Impact of turbulence scheme on convective forecast (4th July 2005)
Number of cellsReference With Turbulence
Histogram of cell sizes
Average cell size
Time →
Time →
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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).
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Variable Resolution Grids
Yongming Tang, Peter Clark, Terry Davies
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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
UniformHigh Res
zoneVar-Res 2Var-Res 1
UniformCoarse Res 1
UniformCoarse Res 2
Typically, there are 3 regions, and inflation ratio R1 = R2 = 5~10%
R2R1
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May 3 2002 Case - Variable Resolution Model
Rainfall at 14 UTC. The three regions of the variable resolution domain are shown
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Summary – Variable Resolution
Variable resolution grid capability implemented in the UM.
Tested in idealised and real case studies with a nesting ratio of 1 : 4 and results look promising.
Currently working on the model parametrizations to make them depend appropriately on the local grid-length in different parts of the domain (e.g. grid-length dependent convection scheme).
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Summary – Variable Resolution
Variable resolution grid capability implemented in the UM.
Tested in idealised and real case studies with a nesting ratio of 1 : 4 and results look promising.
Currently working on the model parametrizations to make them depend appropriately on the local grid-length in different parts of the domain (e.g. grid-length dependent convection scheme).
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Summary
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Summary
1. 4km UM now operational for the UK (since May 2005)
2. Performed many case studies with 1km/4km models over UK as well as idealised studies (diurnal cycle of convection) and other regions of the world (Alps, Africa, NewZealand)
3. Convective rainfall is of particular interest (for flooding) and 4km/1km models show skill in forecasting higher rain rates (better than 12 km model)
4. But …there are still improvements to be made !!!
Including missing processes in the model (e.g. turbulence, radiation on slopes, microphysics, improved representation of urban areas, other surface characteristics, lakes, snow)
Different approaches to modelling (e.g. variable resolution)
Understanding high resolution processes (convective initiation – CSIP)
Data assimilation (3D/4DVAR ?)
New applications (air quality)
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The End
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A convective-scale NWP System
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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Scores for 1 hour accums 10% and 1% threshold
Solid: AssimDotted: Spinup
Blue 12kmGreen 4kmRed 1km
Threshold is rainrate for which 10% of rainy grid points are higher
Threshold is rainrate for which 1% of rainy grid points are higher
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CSIP IOP 18 – 25th August 2005
Radar
4 km
12 km
1 km
Rainfall Accumulations over 300x300 km box
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CSIP IOP 18 – 25th August 2005 – 12 UTC
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CSIP IOP 18 – 25th August 2005
Reflectivity
Doppler Radial Velocity
1227 UTC120 RHI
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CSIP IOP 18 – 25th August 2005 – 12 UTC
10 m wind and convergence Rainfall rate
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CSIP IOP 18 – 25th August 2005 – 12 UTC
2 gridlengths
Cross section through 4 km model gust front Wind speed along section
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Incoming solar radiation on orographic slopes
James Manners
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Surface radiation interactions
Real situation is complex:
• Sloped surfaces, shadowed regions, reflection in valleys...
• Non-isotropic diffuse radiation... …and this is just the SW.
Current 2-stream parametrization:
• SW and LW up and down.
• Direct SW incoming at angle of Sun
• Assumes flat surface.
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Orographic features important to radiation
• Oliphant et. al. 2003, ‘Spatial variability of surface radiation fluxes in mountainous terrain’
• Characteristics in order of importance: slope aspect, slope angle, elevation, albedo, shading, sky view factor, leaf area index
• The most important factor is the area presented by each grid-box to the incoming direct SW radiation
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Grid-box mean slope aspect and angle
Slope aspect: Slope angle:
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4km Mesoscale Unified Model: 8 hr forecast
Extra direct SW surface flux: Temperature difference at 1.5 metres:
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4km Mesoscale Unified Model: 16 hr forecast
Extra direct SW surface flux: Temperature difference at 1.5 metres:
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Summary – Orography and Radiation
Included slope aspect and angle into the incoming direct short-wave radiation scheme.
Tested in UM with grid resolutions ranging from 60km (global) to 1km (over the southern UK).
At high resolution, small (0.5K) surface temperature changes resulting from the scheme can lead to differences in convective initiation and evolution.
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Scales of Motion & Predictability
Hail shaft
Thunderstorm
Front
Extratropical
CycloneSpace Scale
Lifetime
Predictability?
10mins 1 hr 12hrs 3 days
30mins 3 hrs 36hrs 9 days
1000km
100km
10km
1km
MCS
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Boscastle accumulations