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1 12/09/2002 © Crown copyright
Modelling the high resolution structure of frontal rainbands
Talk Outline Resolution dependence of extra-tropical cyclone
modelling The impact of ice evaporation on frontal dynamics
Peter Clark, Richard Forbes, Humphrey Lean
Met Office (JCMM)
Research at the Joint Centre for Mesoscale Meteorology “Stormscale” NWP: the Unified Model at ~1km resolution Convection / Microphysics / Validation using radar / Data assimilation
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FASTEX IOP 16 Cyclone12Z 17/02/1997
Cloud Head
Convection
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IOP 16 Radar and Dropsonde dataC130 Run 5C130 Run 1
Figures show C130 w, IWC, windP3 Radar reflectivity
Roberts and Forbes (2002, Atmos. Sci. Lett.)
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FASTEX IOP 16 Cyclone Emerging multiple cloud heads
06Z 09Z09Z 12Z
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Non-Hydrostatic Simulations
60km global
Horizontal Resolutions:
24km, 12km, 4km, 2km LAMs, ~300x250 grid
points
Vertical Resolutions:
2km with 45, 90 and 135 levels
i.e. 400m, 200m and 130m mid-trop. layer
spacing approx.
12km ‘AC’ scheme analysis valid at 0Z, 9 hour forecast
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FASTEX IOP 16 Cyclone Simulation
12 km
4 km
2 km
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800 hPa Vertical Velocity as a function of resolution ; FASTEX IOP
16 Cyclone60 km
24 km12 km
4 km 2 km
-0.15 -0.75m/s
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Power Spectrum of vertical velocity
Possible aliasing from fronts(not present in 2 km run)
Same Region at 60, 24, 12, 4, 2 km grid
Excluding frontal region
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Frontal Collapse to gridscale
12 km
4 km
2 km
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Ratio of Vertical Velocity Power Spectrum to Spectrum at 2 km
Normalized By Grid Scale
dx/2dx/5
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800 hPa Vertical Velocity as a function of resolution ; FASTEX IOP
16 Cyclone60 km
24 km12 km
4 km 2 km
-0.15 -0.75m/s
Cross Section 1
09Z (T+9) 12/02/1997
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Cross Frontal Velocity as a function of resolution ; FASTEX IOP 16
Cyclone
60 km
24 km
12 km
4 km
2 km
-15 0.0m/s 5-10
450 km
1000 hPa
0 hPa
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Slantwise instability of front: 2km Simulations
400 hPa
45 Levels~ 400 m
90 Levels~ 200 m
135 Levels ~ 130 m
200 km
~75 hPa
Slope: 1/20-1/30
950 hPa
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Slantwise instability of front: 2km 90 level simulations
No sublimation cooling
Reference
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800 hPa Vertical Velocity as a function of resolution ; FASTEX IOP
16 Cyclone60 km
24 km12 km
4 km 2 km
-0.1 0.3m/s
Averaged to 60 km grid
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Vertical Velocity at 800 hPa24 km L45 12 km L45 4 km L45
2 km L45 2 km L90 2 km L135
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Vertical Velocity at 800 hPaaveraged to 60 km
24 km L45 12 km L45 4 km L45
2 km L45 2 km L90 2 km L135
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Vertical VelocityCross section
24 km L45 12 km L45 4 km L45
2 km L45 2 km L90 2 km L135
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Vertical Velocity Averaged to 60 km
24 km L45 12 km L45 4 km L45
2 km L45 2 km L90 2 km L135
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Dry PV at 800 hPa24 km L45 12 km L45 4 km L45
2 km L45 2 km L90 2 km L135
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PV Cross Section
3x10-6-3x10-6
24 km L45 12 km L45 4 km L45
2 km L45 2 km L90 2 km L135
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PV Cross Section (120 km blowup)
24 km L45 12 km L45 4 km L45
2 km L45 2 km L90 2 km L135
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PV Cross SectionAveraged to 60 km
3x10-60
24 km L45 12 km L45 4 km L45
2 km L45 2 km L90 2 km L135
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PV Generation
Ice Fallout
Saturated Ascent
Saturated Descent
-
+
-• On the larger scale, symmetric dipole/tripole anomalies cancel each other out.
•Monopole dominates far-field response.
• Dipole/tripole component of a PV anomaly has only a weak influence on the far field.
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Conclusions Model properly represents scales greater than about 5 gridlengths
Probably some frontal aliasing at resolutions of 4km+
Over a short forecast, high resolution simulation has only a small impact on larger scales - greater near surface fronts than in slantwise ascent
High resolution has little net impact on overall diabatic heating and on PV generation, i.e. slantwise overturning is not a strong net generator (saturated descent)
This may be why climate models work (at all!)
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Impact of evaporative cooling on frontal dynamics
Cooling due to rain/snow evaporation significantly enhances frontal downdraughts– A number of papers have shown the importance of downdraughts in convective systems
– Observations of strong narrow frontal downdraughts: Thorpe and Clough (1991), Browning et al. (1997)
– 2D semi-geostrophic models of frontogenesis: Huang and Emanuel (1991) , Parker and Thorpe (1995)
– 3D idealised front in the Met Office Unified Model (UM)
– FASTEX frontal cyclone case studies using the UM: Forbes and Clark (2003, submitted to QJRMS)
For high resolution forecasting, NWP models require the correct distribution of diabatic heating and evaporative cooling.
Main surface “weather” impacts: Distribution of precipitation, wind gusts
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Hypotheses Ice evaporation is rapid in the subsaturated zone beneath a frontal surface
leading to intense cooling in a shallow layer with a significant local dynamical impact.
The Unified Model does not represent the profile of evaporative cooling accurately, resulting in an incorrect dynamical response.
The UM can be improved by varying microphysical parameters within their bounds of uncertainty.
Method Evaluate the model against observations. Understand the uncertainty in the formulation of microphysics
parametrizations. Determine the sensitivity of the moisture/dynamical fields to these
uncertainties. Predict parameter changes to give a closer fit to the observations.
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Idealised Front
Refe
rence
fore
cast
Downdraught is significantly weaker when there is no ice evaporative cooling
Diabatic Heating Rate (K/hr)
Cloud Ice (g/kg) Vertical Wind (m/s)
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FASTEX IOP16:Dynamical impact of evaporative cooling
Plan view of vertical velocity at 800hPa with and without ice
evaporative cooling
Evaporative cooling leads to enhanced descent beneath the frontal cloud band and enhanced ascent in the frontal updraught
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Does the model have the correct characteristics in the evaporation cooling zone beneath frontal updraughts ?
Few observations of downdraughts, so use proxy data. The important parameters are the vertical ice flux and the depth scale of the cooling. Can derive ice water content and evaporation depths from radar observations.
Perform statistical comparison between model and observations (1 year of data).– Timeseries from operational Unified Model forecasts Includes mixed-
phase microphysics parametrization (Wilson and Ballard, 1999)
– Timeseries of radar reflectivity data from the vertically pointing 94GHz cloud radar based at Chilbolton. Convert to ice water content and average to model resolution.
Algorithm extracts vertical profiles which contain ice evaporation beneath stratiform cloud.
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Observations of Evaporation
02 Apr 2000 11 Dec 1999
94GHz Radar Derived Ice Water Content (below 0degC)
Radar data provided by Robin Hogan (Reading Univ.) and RCRU (RAL)
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Model/Obs Comparison
Operational model 12km resolution
Radar averaged to
12km
Evaporation depth scale cumulative probability from the operational Unified Model and the radar data averaged to 12km
Probability of ice evaporative depth scale from 1 year of data
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Model/Obs Comparison
Average ice evaporative depth scale from the Chilbolton 94 GHz cloud radar and the operational UM for 20 separate days in Oct, Nov, Dec 1999.
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Model/Obs Comparison
Probability of ice water content for the model and radar
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What are the reasons for the difference between the model and the observed depth scales ?
Hypotheses:
– Inadequate vertical resolution (model layers are 500-750m)
– Too much ice
– Relative humidity forcing in the model subsaturated zone is too moist
– Parametrized ice particle evaporation rate is too low
– Parametrized ice particle terminal fall speed is too high
Reasons for Model/Obs Differences
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Microphysics Parametrization
Uncertainty in microphysical parameters– Various sources of uncertainty in microphysics parametrization schemes due to:
» insufficient knowledge of the real world
» simplification of the processes in the parametrization.
– The ice evaporation rate and ice terminal fall speed parametrizations in the model could have a bias of a factor of 2.
Sensitivity of forecasts to parameter uncertainty – Determined the sensitivity of the model to ice evaporation rate and fall speed variations within the bounds of uncertainty (analytical, 1D evaporation model, 3D frontal cyclone
forecasts)
– Increasing ice evaporation rate -> stronger narrower downdraughts
– Decreasing ice fall speed -> stronger narrower downdraughts, higher ice content
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FASTEX IOP 16: Sensitivity
Increasing the ice evaporation rate increases frontal development Increasing ice terminal fall speed decreases frontal development
Sensitivity of the model to changes that affect ice sublimation
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IOP 16 Sensitivity Forecasts:Surface precipitation
Increasing ice fall speed
Increasing dep/sublim
rate
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Summary of the Model Evaluation
Model Errors
– Ice evaporation depths are too deep (by a factor of 2-3)
– Ice water contents are too low (by up to a factor of 2) (?)
Suggested changes:
– decrease ice fall speed (consistent with observed ice fallspeeds)
– increase ice evaporation rate (consistent with ventilation assumption)
– increase vertical resolution to at least 250m in mid-troposphere
Predicted Impacts
– Higher ice water content and shallower, stronger frontal downdraughts.
40 12/09/2002 © Crown copyright
FASTEX IOP 16: Validation
Comparison of the model ice evaporative depth scales with 94GHz radar observation
statistics
Average depth scale
Reference:1260 m
Modified: 780 m
Obs: 640 m (160m)
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Conclusions Ice evaporation is rapid in the subsaturated zone beneath a frontal surface leading
to intense cooling in a shallow layer. – Evaporation depth scale < 1km beneath stratiform frontal cloud
– Average cooling rate of 1 K/hr.
The Unified Model does not represent the profile of evaporative cooling accurately, resulting in an incorrect dynamical response.
– UM underestimates the amount of ice and overestimates the evaporative depth scales
– This leads to a significant underestimate in the cooling and strength of frontal circulations.
– Due to poor vertical resolution, weak ice evaporation rate, high fall speed and moist bias.
The UM can be improved by varying microphysical parameters within their bounds of uncertainty.
– Many uncertainties in the microphysics of complex irregular ice particles and in microphysics parametrization formulation.
– Estimate an uncertainty of up to a factor of two in the fall speed and evaporation rate.
– Modifiying these two parameters improves the model fit with observations.