Erica McGrath-Spangler Dept. of Atmospheric Science Colorado State University ChEAS May 14, 2007

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

System

Erica McGrath-Spangler

Dept. of Atmospheric Science

Colorado State University

ChEAS 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

€

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

€

dθv

dt


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

€

w'θv' | zi = −α w'θv' | s


€

∂θ∂t

=α w'θv' | s

Δz

€

∂rv∂t

=qvM

ρ 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

€

M =ρα w'θv' | s

Δθv

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 0.3

alpha

Temperature (K)


PBL height vs alpha

1840

1860

1880

1900

1920

1940

1960

1980

2000

2020

2040

0 0.05 0.1 0.15 0.2 0.25 0.3

alpha

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

4.5

4.7

4.9

5.1

5.3

5.5

5.7

5.9

6.1

6.3

0 0.05 0.1 0.15 0.2 0.25 0.3

alpha

Mixing ratio (g/kg)

Documents

Erica McGrath-Spangler Dept. of Atmospheric Science Colorado State University ChEAS May 14, 2007