slide1
Download
Skip this Video
Download Presentation
What limits the utility of long-term eddy flux measurements?

Loading in 2 Seconds...

play fullscreen
1 / 34

What limits the utility of long-term eddy flux measurements? - PowerPoint PPT Presentation


  • 131 Views
  • Uploaded on

What limits the utility of long-term eddy flux measurements? Some suggestions based on observations made within and just above several forests. David Fitzjarrald Jungle Research Group Atmospheric Sciences Research Center University at Albany SUNY, US of A Otávio Acevedo Matt Czikowsky

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'What limits the utility of long-term eddy flux measurements?' - cullen


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
slide1
What limits the utility of long-term eddy flux measurements?

Some suggestions based on observations made within and just above several forests.

David Fitzjarrald

Jungle Research Group

Atmospheric Sciences Research Center

University at Albany SUNY, US of A

Otávio Acevedo

Matt Czikowsky

Jeff Freedman

Ralf Staebler

Ricardo Sakai

Kathleen E. Moore

Dwayne Spiess

slide2
What do we know about fluxes from

nearly flat surfaces?

Monin-Obukhov similarity hypothesis works.

What’s the problem with measuring fluxes over forests?

Despite major international efforts (EUROFLUX, AMERIFLUX)

to put eddy flux towers on every block, there are several disturbing facts:

• Observed energy budget doesn’t close.

Q* - Qg + H + LE + ADV + St = 0

for a box enclosing the forest.

• C uptake inferred is too large for many ecosystems.

Is the eddy flux methodology at fault, or is this just a practical problem?

• Typically instrument, other failures limit data recovery to

70-80% of total time.

• Most researchers discard calm night data. “insufficient mixing”

slide3
Eddy flux methodology. As old as O.Reynolds, 19th century.

C =   + c’

W =   + w’

WC = + & other terms drop out by definition.

Devil in the details is the <>.

• Why bother to make the Reynolds’ decomposition at all?

• Our gadgets do not work so well that we can believe tiny

Perturbations seen on long (greater than a few hours) time scales.

slide4
Energy budget

closure as published

by many researchers.

There is a common (low)

bias in the ratio:

[H + LE]/A

Is this bias in the elements

of the energy budget

alone, or does it apply

to all scalars measured

just above the forest?

Sakai et al. (2000)

slide5
z/h scaling

zc’ scaling

broadleaf

Std deviation of w

conifers, WT

Cumulative plant area

Density, from top down.

Wild hypothesis--can treat turbulent momentum absorption in

Plant canopies in the “Beer’s Law” manner.

Sakai et al. (2000)

slide6
z/h scaling

zc’ scaling

broadleaf

conifers, WT

Friction velocity u* inside forest canopies.

slide7
zc’(dc) =0.705 for the broad leaf forests

Drag coefficient over broadleaf forest doesn’t change much in fall.

( z0 goes up as d goes down) and the two almost compensate.

Sakai et al. (2000)

slide8
In winter, momentum penetrates further, but still is

largely dissipated before it gets to the ground.

Displacement height/h

Roughness length/h

Sakai et al. (2000)

slide9
Defining the thickness of the roughness sublayer RSL

• Inflection point in mean wind profile--instability!?

• Enhanced production of TKE

• Transport terms emphasized; MO hypothesis messed up.

• Is there any general pattern over many forest types?

• (z-d)/(h-d) ≈ 5 gets you to the “inertial layer”.

• Only works if you use the d found using the zc’ above.

Sakai et al. (2000)

slide11
Just let enough air go by--collect the information

on the large (CBL) eddies that advect past.

Running mean average period “wind run”

slide12
The first demonstration of cospectral similarity in

the RSL--seems to work for T, q, CO2, momentum.

slide15
Lots of things go on inside the rain forest canopy.

Vertical profiles at Ducke (Fitzjarrald et al., 1988)

slide16
Observing very local scale advective effects may not be possible

if there are no regular local flows to provide a periodic signal.

Test observations done by JRG at Harvard Forest (Staebler et al., 2000).

Which way is uphill?

slide17
Utility of SODAR observations.

It doesn’t measure quite what we want.

HF, DRAINO (Staebler, JRG).

Sodar at Harvard Forest

last week...

Effects of the local hill

extend well into the SBL.

(SODAR results and mysteries!)

slide20
It is always awkward to do field work at “remote” sites.

LBA-Ecology Pasture

Site (km 77)

Tower

Solar panels

slide21
“Humble” but continuous, long-term data should be highly prized.

(But remember that information goes both ways between modelers & observers.)

Automatic weather stations near Belterra (top) and at

Fazenda Caboco, km 117 (bottom). JRG, ASRC

slide24
Subtle topography and local site matter-examples from Albany.

Flux convergence during the

early evening transition can be

used to estimate fluxes. Acevedo & Fitzjarrald (2000)

slide25
Spatial s.d.

Nocturnal T variability observed at sfc stations.

Temporal s.d.

Midnight

Noon

Acevedo & Fitzjarrald (2000)

slide26
What can you do if you just have more, not better data?

Upper row: temporal evolution of temperature (upper panel) and wind gusts (lower panel)

at the 26 stations for 3 different nights.

Lower row: sT-spat for each of the nights shown in the upper row.

Acevedo & Fitzjarrald (2000)

slide27
Temperature evolution at indicated stations;

Thick solid line is average wind speed in the network.

Acevedo & Fitzjarrald (2000)

slide28
Left: relation of the temperature spread factor with altitude;

Right: temperature spread factor vs. the difference between station altitude (z)

and mean height of a 3 km x 3 km area (mz), centered on the station.

Squares indicate rural stations, and diamonds are urban ones.

Stations with no symbol are located in mixed environments.

Acevedo & Fitzjarrald (2000)

slide34
Some conclusions:

• long-term eddy flux estimates can stil be improved

• roughness sublayer has some “universal” characteristics

• a plausible correction scheme was developed.

• remaining to solve: horizontal advection; drainage flows.

• other uses of fluxes: using composites, case studies creatively.

ad