national center for atmospheric research * asp summer colloquium * boulder colorado * june 1, 2009...

National Center for Atmospheric Research * ASP Summer Colloquium * Boulder Colorado * June 1, 2009

University of Colorado at Boulder

Boundary Layer Lecture

Surface-based: Flux Measurements

Andrey A. Grachev 1, 2

(also Christopher W. Fairall 2and Jeffrey E. Hare 1, 2)

1 Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, Colorado, USA 2 NOAA Earth System Research Laboratory, Boulder, Colorado, USA

Exploring the Atmosphere: Observational Instruments and TechniquesAdvanced Study Program (ASP) Summer Colloquium



Atmospheric Surface Layer (ASL)(constant-flux layer)

The atmospheric surface layer (or “constant-flux layer”) occupies the lower 10% of the atmospheric boundary layer, or 50-150 m elevation. This is the region we live in, and some of its characteristics are important for a variety of applications. Strong gradients in wind speed, temperature & other scalars in surface boundary layer exist in ASL. Monin-Obukhov similarity scaling is applied in ASL. This theory links mean fields and turbulent fluxes in the surface layer. Eddy flux measurements made in surface layer.



Turbulent Fluxes(definition)

Momentum flux (or surface stress): wuu 2

Sensible heat flux: TwcH pS

222 ))( wvwuu

Latent heat flux (moisture flux): wqLH eL

Transfer of trace gases (CO2, O3 etc.): cac rwF

where cp is the heat capacity of air at constant pressure, Le is the latent heat of evaporation of

water, and rc mixing ratio relative to dry air component.



Monin–Obukhov similarity theory(Obukhov, 1946; Monin and Obukhov, 1954)

Lz /

v

v

Twg

TuL

3

Monin – Obukhov stability parameter (Monin & Obukhov, 1954):

Obukhov length (Obukhov, 1946):

Neutral case: 1 hm

Non-dimensional velocity and temperature gradients :

Businger–Dyer (Kansas-type) profiles: 4/1)1()( mm

mm 1)( hh 1)(

2/1)1()( hh0

0

for

for

)(,)( hm dz

d

T

z

dz

dU

u

z

Free convection: 3/1 hm Very stable stratification: hm

(Flux-gradient relationships)



Limitations of the Monin–Obukhov similarity theoryUpward Momentum Transfer in the Marine Boundary Layer

Weak wind at sea is frequently accompanied by the presence of fast travelingocean swell, which dramatically affects momentum transfer. It is found that the mean momentum flux (uw-covariance) decreases monotonically with decreasing wind speed, and reaches zero around a wind speed U 1.5–2 m/s Further decrease of the wind speed (i.e., increase of the wave age) leads to a sign reversal of the momentum flux, implying negative drag coefficient. Upward momentum transfer is associated with fast-traveling swell running in the same direction as the wind, and this regime can be treated as swell regime. The common practice of using the friction velocity as a scaling parameter evidently is invalid for swell conditions since x reaches zero and changes sign. Thus, the standard Monin–Obukhov similarity theory presumably is not applicable to describe the momentum transfer in swell conditions.



Limitations of the Monin–Obukhov similarity theoryEkman Surface Layer

-1 -0.5 0 0.5 1-0.5

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

West component, m s-1

So

uth

co

mp

on

en

t, m

s-1

4 am5 am6 am7 am8 am

Evolving Ekman-type spirals during the polar day observed during JD 507 (22 May, 1998) for five hours from 12.00 to 16.00 UTC (4:00–8:00 a.m. local time, see the legend) observed during SHEBA program. Markers indicate ends of wind vectors at levels 1 to 5 (1.9, 2.7, 4.7, 8.6, and 17.7 m).

-1

-0.5

0

0.50

1

2

3

4

0

5

10

15

20

South component, m s

-1West component, m s -1

He

igh

t, m

3D view of the Ekman spiral for 14:00 UTC JD 507 (local time 6 a.m.), 22 May 1998 (SHEBA data).



Turbulent Flux MeasurementsSonic anemometer/thermometer

t1 = L / (c + v) ; t2 = L / (c - v); v = 0.5 L (1/t1 – 1/t2); c = 0.5 L (1/t1 + 1/t2);Ts = c2 / 403; T = Ts / (1 + 0.32 e / p)

L = path length, t = time of flightc = speed of sound, v = wind velocityT = temperature, Ts = “virtual” tempp = pressure, e = water vapor pressure

)51.0( wqTwTcwTcH sppS



Turbulent Flux MeasurementsGas Analyser (H2O and CO2 fluxes)

Absorptance of a particular gas α = 1 – A / Ao

A = power received at absorbing wavelength

Ao = power received at non-absorbing wavelength

ρ = Pe f(α / Pe) [mol m-3] number density

ρ = Pe f([1 – z A / Ao ] S / Pe) , where Pe is equivalent pressure, S is ‘span’

Channels available for water vapor and carbon dioxide



Turbulent Flux MeasurementsEddy Correlation (or Covariance) Method

Eddy fluxes calculated as covariances in the time domain, <w’u’>, <w’T’>, <w’c’> etc. Spectra and cospectra in the frequency domain. Frequency sampling rate ~ 10-20 Hz. Averaging period must be long enough to capture low-frequency contributions to eddy fluxes. Averaging periods of 30 min or 1 hr are commonly used.

10-3

10-2

10-1

100

101

-8

-6

-4

-2

0

x 10-3

Frequency, f (Hz)

f*C

ow

u (

m2 s

-2)

a

Level 1Level 2Level 4Level 5

10-3

10-2

10-1

100

101

-5

-4

-3

-2

-1

0

1x 10

-4

Frequency, f (Hz)

f*C

ow

T (

m s

-1 d

eg

) b

Level 1Level 2Level 3Level 4Level 5

Typical (a) stress cospectra (1998 JD 45.4167), and cospectra of the sonic temperature flux (1997 JD 324.5833) for weakly and moderate stable conditions measured during SHEBA.

10-4

10-3

10-2

10-1

100

101

102

-0.5

0

0.5

1

1.5

f*S

wq(f)

, (m

/s) (

g/g)

H2O & CO

2 Flux cospectra, Year = 2007, YD = 243, hr = 22 (UTC)

10-4

10-3

10-2

10-1

100

101

102

-8

-6

-4

-2

0

2x 10

-3

Frequency, f (Hz)

f*S

wc(f)

, (m

/s) (

ppm

)

Typical raw cospectra of the H2O (upper panel) and CO2 (bottom panel) fluxes measured August 31, 2007 at Eureka site, Canada.



10-4

10-3

10-2

10-1

100

101

10-5

10-4

10-3

10-2

10-1

100

f (Hz)

f*S

x(f)

Variance spectra: u-blue v-green w-red T-cyan 08/30/2007 10:00

Turbulent Flux MeasurementsInertial-Dissipation Method

Frequency spectra in the inertial subrange (Kolmogorov, 1941):

wvufuKf ,,,)2/()(S 3/53/23/2 3/53/23/1 )2/()(S fuNKf ttt

10-3

10-2

10-1

100

101

10-4

10-3

10-2

10-1

Frequency, f (Hz)

f*S

u (m

2 s-2

)

aLevel 1

Level 2Level 4

Level 5

10-3

10-2

10-1

100

101

10-4

10-3

10-2

Frequency, f (Hz)f*

St (

de

g2 )

bLevel 1

Level 2Level 4

Level 5



Turbulent Flux MeasurementsBulk Relationships

Momentum flux (or surface stress): 2UCD

Sensible heat flux: )( 0 apHS TTUcCH

Latent heat flux (moisture flux): )( 0 aeEL qqULCH

Traditionally, the transfer coefficients are adjusted to neutral conditions using Monin-Obukhov similarity theory. The neutral counterparts of the drag coefficient, Stanton number, and Dalton number are derived from the following relationships:

m

DnD CC

2/12/1

h

H

D

nH

nD

C

C

C

C

2/12/1

h

E

D

nE

nD

C

C

C

C

2/12/1

The neutral transfer coefficients uniquely define the aerodynamic roughness length and scalar roughness lengths for temperature and humidity:

nDCzz

exp0

nH

nD

t C

Czz

exp0

nE

nD

q C

Czz

exp0



Bulk RelationshipsCOARE Flux Algorithm

COARE Model History: 1996 - Bulk Meteorological fluxes (Fairall et al., 1996); 2000 – Carbon Dioxide (Fairall et al., 2000); 2003 – Update, version 3.0, 8000 1-hr eddy covariance observations (Fairall et al., 2003); 2004 – DMS and 2006 - Ozone.

Air-Sea transfer coefficients as a function of wind speed: latent heat flux (upper panel) and momentum flux (lower panel). The red line is the COARE algorithm version 3.0; the circles are the average of direct flux measurements from 12 ETL cruises (1990-1999); the dashed line the original NCEP model.



Air-Sea Flux MeasurementsNOAA R/V Ronald H. Brown

Using advanced techniques for direct measurement of air-sea fluxes, we have obtained data from oceans around the world. This data has been used to develop parameterizations to estimate air-sea fluxes from mean state variables (wind speed, air temperature, sea temperature, humidity, etc). Air-sea fluxes of heat (latent/sensible) are also fundamental to cloud development (hence, surface energy budget, precipitation, etc).



NOAA R/V Ronald H. BrownFlow distortion study



NOAA R/V Ronald H. BrownNOAA/ESRL Turbulent Flux System



Texas Air Quality Study (TexAQS)R/V Ronald H. Brown cruise track

NOAA R/V Ronald H. Brown cruise track during TexAQS-06. The ship departed Charleston, South Carolina on 27 July 2006, arriving initially in Galveston, Texas on 2 August 2006. The cruise track included passages into Port Arthur/Beaumont, Matagorda Bay, Freeport Harbor, Galveston Bay to Barbour’s cut (15 transits), and the Houston Ship Channel (4 transits). The cruise ended in Galveston, Texas on 11 September 2006.



230 231 232 233 234 235 236 237 238 239 240 241 242

123456789

Lo

catio

n C

od

e a

230 231 232 233 234 235 236 237 238 239 240 241 24224262830323436

Te

mp

, d

eg

C

b

T a

T w

230 231 232 233 234 235 236 237 238 239 240 241 2420

2

4

6

8

10

U ,

m/s

c

0

90

180

270

360

Dir , d

eg

wind speed

direction

230 231 232 233 234 235 236 237 238 239 240 241 2420

200

400

600

800

1000

R S

, W

/ m

2

2006 Year Day (UTC)

d

400

420

440

460

R L , W

/ m2

230 231 232 233 234 235 236 237 238 239 240 241 24210

-4

10-3

10-2

10-1

CD

n

a

230 231 232 233 234 235 236 237 238 239 240 241 24210

-4

10-3

10-2

10-1

CH

n

bEddy correlation method

Inertial dissipation method

230 231 232 233 234 235 236 237 238 239 240 241 24210

-4

10-3

10-2

10-1

CE

n

cEddy correlation method

Inertial dissipation method

230 231 232 233 234 235 236 237 238 239 240 241 242-2

-1.5

-1

-0.5

0

0.5

2006 Year Day (UTC)z

/ L

d

Time series of (a) the location code, (b) the air and water temperature, (c) the wind speed and the true wind direction, and (d) the shortwave (circles) and long-wave (triangles) radiation for year days 230–242 (August 18–30, 2006). The data are based on 1 hour averaging.

Time series of (a) the neutral drag coefficient, (b) the neutral Stanton number, (c) the neutral Dalton number, and (d) the Monin-Obukhov stability parameter for year days 230–242 (August 18–30, 2006). The data are based on 1 hour averaging. The neutral transfer coefficients are based on the both covariance (circles) and the ID (triangles) estimates.

Location codes: 1. Gulf of Mexico, 2. Galveston Bay, 3. Port of Galveston, 4. Sabine River and Lake, 5. Beaumont, 6. Barbour’s Cut, 7. Houston Ship Channel, 8. Freeport, 9. Matagorda Bay, 10. Jacintoport.

Texas Air Quality Study (TexAQS)R/V Ronald H. Brown, Time Series – Leg 2



Turbulent fluxes and transfer of CO2 in ArcticSEARCH station Eureka, Canada



Time Series of the Turbulent FluxesSEARCH station Eureka, Canada

241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264-8-6-4-202468

101214

H 2

O fl

ux ,

(m

/ s)

*(kg

/ kg

)

241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264-12-10-8-6-4-202468

10

CO

2 fl

ux *

102 ,

(m/s

)*pp

m

241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264-10-8-6-4-202468

10

2007 Year Day (UTC)

Air

Tem

p, d

eg C

An example of the time series of the hourly averaged fluxes of H2O and CO2, and air temperature for the Eureka site obtained during August-September 2007 (YD 241-264). Measurements were made by the sonic anemometer and Licor-7500. Negative signs mean downward fluxes. and vise versa. Hourly averages of the fluxes and air temperature show large diurnal variations during end of August and beginning of September.



Questions ?

national center for atmospheric research * asp summer colloquium * boulder colorado * june 1, 2009...

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