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Boundary Layer Verification
ECMWF training course
May 2010
Maike Ahlgrimm
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What does the BL parameterization do?
Attempts to integrate
effects of small scale
turbulent motion on
prognostic variables at
grid resolution.
Turbulence transports
temperature, moisture and
momentum (+tracers).
Ultimate goal: correct model output
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Which aspect of the BL can we evaluate?
1. 2m temperature/humidity2. Depth of BL
3. Diurnal variability of BL height
4. Structure of BL (temperature, moisture,velocity profiles)
5. Turbulent transport within BL
6. Boundaries: entrainment, surface fluxes,
clouds etc.
large scale
small scale
Chandra et al., sub. to J. Climate
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Part 1
Depth of the boundary layer
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BL depth from radiosondes
Problem: Define the top of the BL!
Concept: At he top of the BL, the air motion transitions from
turbulent to laminar flow.
For an equitable comparison, apply the same criteria for
identification of this transition to model profiles and radiosonde
profiles.
Alternative for convectively driven boundary layers: turbulent
mixing leads to T and q gradients at the BL top. Identify these
gradients in the profile.
DSE/cFigure: Martin Khler
norm
alizedBLheight
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Richardson number-based approach
Richardson number defined as:
flow is turbulent if Ri is negative
flow is laminar if Ri above critical value
calculate Ri for model/radiosonde profileand define BL height as level where Riexceeds critical number
buoyancy production/consumption
shear production (usually negative)Ri=
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Difficulties with this approach
discrete model layers -> bulk Ri number
where is the top and bottom of the bulk layer?
how much do surface fluxes increase buoyancy?
not most reliable model field
for sonde profiles, surface fluxes usuallyunavailable
noise in sonde profiles can introduce uncertainties
diagnostic BLH in IFS is currentlytuned to best agree with paramete-
rization based BL height
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How-to
Need T, u,v,q,z and some constants
Define conserved variable, e.g. virtual dry static energy:
Apply smoothing in the vertical if necessary
Starting at lowest model level, calculate Ri number, adding
an excess to the dse to make up for missing surface fluxes
Iterate, until Ri exceeds critical level (e.g. 0.25) Assign height of nearest layer as BL top height
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Example: dry convective boundary layer NW Africa
2K excess
1K excess
Theta [K] profiles shiftedFigures: Martin Khler
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Example: Inversion-topped BL
Inversion capped BLs dominate in the subtropical oceanic
regions Identify height of jump across inversion
EPIC, October 2001
southeast Pacific
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Limitations of sonde measurements
Sonde measurements are limited to populatedareas
Depend on someone to launch them (cost)
Model grid box averages are compared to point
measurements (representativity error)
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Took many years to compile this map
Neiburger et al.
1961
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Calipso tracks
Arabic peninsula - daytime
CALIPSO tracks
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BL from lidar how-to
Easiest: use level 2 product (GLAS)
Algorithm searches from the ground up for significant drop
in backscatter signal
Align model observations in time and space with satellite
track and compare directly, or compare statistics
surface return
backscatter from BL aerosol
molecular backscatter
Figure: GLAS ATBD
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Example: Lidar-derived BL depth from GLAS
Only 50 days of data yield a much more
comprehensive picture than Neiburgers map.
Ahlgrimm & Randall, 2006
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Limitations to this method
Definition of BL top is tied to aerosol
concentration - will pick residual layer
Does not work well for cloudy conditions
(excluding BL clouds), or when elevated aerosollayers are present
Overpasses only twice daily, same local time
Difficult to monitor given location
Th f i l
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The case of marine stratocumulus
Well mixed convective layer underneath strong
inversion Are clouds part of the BL?
As Sc transition to trade cumulus, where is the BL
top?
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Stratocumulus cloud top height
Model underestimates Sc
top height
hler & Ahlgrimm, sub. Hannay et al. 2009
EPIC
SEP
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Part 2
Diurnal cycle of boundary layer height
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Diurnal cycle of convective BL from radiosonde
Example: stratocumulus-topped marine BL in the south-east
Pacific: East Pacific Investigation of Climate (EPIC), 2001
Clear diurnal cycle of ~200m with minimum in early
afternoon, maximum during early morning.
Bretherton et al. 2004, BAMS
Di l l f CALIPSO
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Diurnal cycle from CALIPSO
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Part 3
Turbulent transport
Fl
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Flux towers
Example: Cabauw, 213m mast obtain measurements of roughness
length, drag coefficients etc.
KNMI webpage
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Bomex: trade cumulus regime
Stevens et al. 2001
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Bomex - DualM
Dual Mass Flux parameterization - example of statistical scheme mixing K-diffusion
and mass flux approach Updraft and environmental properties are described by PDFs, based on LES
Need to evaluate PDFs!
Neggers et al. 2009
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Turbulent characteristics: humidity
Raman lidar provides high resolution (in time and space)
water vapor observations
lot: Franz Ber er DWD
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Turbulent characteristics: vertical motion
Observations from mm-wavelength cloud radar at ARM SGP,
using insects as scatterers.
Chandra et al., sub. to J. Climate local time
reflectivity
reflectivity
doppler velocity
red dots: ceilometer cloud base
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Turbulent characteristics: vertical motion
Variance and skewness statistics in the convective BL (cloudfree) from four summer seasons at ARM SGP
Chandra et al. sub. to J. Climate
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Part 4
Boundaries
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Forcing
BL turbulence driven through surface fluxes, or radiative
cooling at cloud top.
Check: albedo, soil moisture, roughness length, clouds
BL top entrainment rate: important but elusive quantity
Entrainment rate DYCOMS II
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Entrainment rate - DYCOMS II
Example: DYCOMS II - estimate entrainment velocity
mixed layer concept:
Stevens et al. 2003
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Summary & Considerations
What parameter do you want to verify?
What observations are most suitable?
Define parameter in model and observations in as equitable
and objective a manner as possible.
Compare!
Are your results representative?
How do model errors relate to parameterization?
f (i i l d )
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References (in no particular order)
Neiburger et al.,1961: The Inversion Over the Eastern North Pacific Ocean
Bretherton et al., 2004: The EPIC Stratocumulus Study, BAMS Stevens et al., 2001: Simulations of trade wind cumuli under a strong
inversion, J. Atmos. Sci.
Stevens et al., 2003: Dynamics and Chemistry of Marine Stratocumulus -DYCOMS II, BAMS
Chandra, A., P. Kollias, S. Giangrande, and S. Klein: Long-term Observations
of the Convective Boundary Layer Using Insect Radar Returns at the SGPARM Climate Research Facility, submitted to J. Climate
Hannay et al., 2009: Evaluation of forecasted southeast Pacific stratocumulusin the NCAR, GFDL, and ECMWF models. J. Climate
Khler et al.: Stratocumulus in the ECMWF model. submitted to QJRMS
Ahlgrimm & Randall, 2006: Diagnosing monthly mean boundary layerproperties from reanalysis data using a bulk boundary layer model. JAS
Neggers, 2009: A dual mass flux framework for boundary layer convection.Part II: Clouds. JAS