implementation of a boundary layer heat flux parameterization into the regional atmospheric...

Implementation of a boundary layer heat flux parameterization into the Regional Atmospheric Modeling

System

Erica McGrath-SpanglerDept. of Atmospheric Science

Colorado State UniversityChEAS May 14, 2007

Acknowledgements: Scott Denning, Kathy Corbin, Ian Baker

ChEAS meeting: May 14, 2007

Overview

• Motivation• Parameterization• Experiment Setup• Results• Conclusions• Future Work


Motivation

• A 20% error in Zi produces a 20% error in CO2 tendency

• Zi is very difficult to determine accurately in mesoscale models because of the coarse resolution

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dCO2

dt∝ NEE

ZiZi is the depth of the PBL


SAM model Courtesy Tak Yamaguchi

QuickTime™ and aYUV420 codec decompressor

are needed to see this picture.

White = pos buoyantRed = neg buoyant

Large-Eddy Simulation: Morning Mixed-Layer Development


Mesoscale Models

• Mesoscale models can’t resolve overshooting thermals because of grid spacing

• Process is not currently parameterized in RAMS


Mixing at the top of the PBL

• At the top of the boundary layer, the Richardson number is very large ( )

• Since the mixing coefficient is inversely proportional to the Richardson number, the mixing is ~ 0 within the capping inversion

• Very difficult to initiate growth of the boundary layer

• RAMS does not include any process to initiate mixing

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dθvdt


Closure Assumption

• Heat flux at the boundary layer top is negatively proportional to the surface heat flux

• Mixes warm, dry free tropospheric air into the PBL and cool, moist boundary layer air into the capping inversion

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w'θv' | zi = −α w'θv' | s


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∂θ∂t

= α w'θv' | sΔz

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∂rv∂t

= qvMρ dryΔz

• Also mix the three wind components, TKE, and CO2 concentration

• The tendencies from entrainment mixing are the quantities themselves times the mass flux divided by density and the layer thickness

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M = ρα w'θv' | sΔθv

Units of kg m-2 s-1


RAMS setup

• RAMS version 5.04 modified to BRAMS version 2.0

• 42 vertical levels starting at 15m and vertically stretched by ~1.1 up to 6600m

• Includes a shallow convection parameterization• Use Mellor and Yamada (1982) closure option for

vertical diffusion• Smagorinsky (1963) used for horizontal diffusion• Coupled to SiB version 3


Idealized simulation• Cyclic lateral boundary conditions

– No weather systems can be horizontally advected into the system

• Initialized horizontally homogeneously from a dry sounding

• Homogeneous surface– Flat topography at sea level– Vegetation is C3 broadleaf and needleleaf trees– Loam soil type– FPAR = 0.8– LAI = 4.0


Pot Temp_ML vs alpha

299

299.5

300

300.5

301

301.5

0 0.05 0.1 0.15 0.2 0.25 0.3alpha

Temperature (K)


PBL height vs alpha

18401860188019001920194019601980200020202040

0 0.05 0.1 0.15 0.2 0.25 0.3alpha

Height (m)


Conclusions

• In nature, overshooting thermals warm, dry, and deepen the PBL

• Mesoscale models don’t include overshooting thermals

• I’ve introduced a parameterization into RAMS that accounts for this process

• Hope to be able to better simulate Zi and CO2 concentrations


Future Work

• Compare mesoscale simulations to an LES run of RAMS and to observations– Both with and without the parameterization

included• Parameterization also affects surface

temperature and dew point that are observed• Assimilate those variables in order to better

determine a value for the tunable parameter


Thanks


Mixing ratio_ML vs alpha

4.54.74.95.15.35.55.75.96.16.3

0 0.05 0.1 0.15 0.2 0.25 0.3alpha

Mixing ratio (g/kg)

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