What limits the utility of long-term eddy flux measurements? Some suggestions based on observations made within and just above several forests.

David FitzjarraldJungle Research GroupAtmospheric Sciences Research CenterUniversity at Albany SUNY, US of A

Otávio AcevedoMatt CzikowskyJeff FreedmanRalf StaeblerRicardo Sakai

Kathleen E. MooreDwayne Spiess

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 = 0for 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”

Eddy flux methodology. As old as O.Reynolds, 19th century.C =  <C> + c’W =  <W> + w’WC = <W><C> + <w’c’> & 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.

Table 1: Energy budget closure for several experiments.

Study Energybudgetclosure =(H+LE)/A

Instrumentation Methods for Reynold’s averaging

Pattey et al. (1997) 0.91 KD, IRGA Block average _ hour

Baldocchi et al.(1997)

0.94 ATI, Open pathIR analyzer

400 s recursive filter & _ hour fluxcalculation

Goulden et al. (1997) 0.81 ATI, IRGA Linear fit detrend _ hour flux

Blanken et al. (1998) 0.87 KD, IRGA Block average _ hour

Jarvis et al. (1997) 0.97 SG, IRGA 200 s recursive filter _ hour period

Lafleur et al. (1997) 0.75 to 0.81 CA27, KH20 Block average _ hour (daily averaged)

McCaughey et al.(1997)

0.85 to 0.95 CA27, KH20 Block average _ hour (daily averaged)

Blanken et al. (1997) 0.98 KD, IRGA Block average _ hour (daily averaged)

Lee and Black(1993b)

0.82 CA27, KH20 Block average _ hour (daily averaged)

Fitzjarrald and Moore(1994)

0.90 ATI, KH20. 240 s running mean average, _ hour period.

Barr et al. (1994) 0.91 KD, LH Block average _ hour average

Sakai et al. (2000)

Energy budgetclosure as publishedby many researchers.There is a common (low)bias in the ratio:[H + LE]/A

Is this bias in the elementsof the energy budgetalone, or does it applyto all scalars measuredjust above the forest?

zc

' ( dc

) = 1 −

u*

2

dzc

'

0

1

∫

u*

2

h( )

Sakai et al. (2000)

Wild hypothesis--can treat turbulent momentum absorption inPlant canopies in the “Beer’s Law” manner.

Cumulative plant areaDensity, from top down.

Std deviation of w

z/h scaling zc’ scaling

broadleaf

conifers, WT

z/h scaling zc’ scaling

Friction velocity u* inside forest canopies.

conifers, WT

broadleaf

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

Sakai et al. (2000)

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)

Roughness length/h

Dis

plac

emen

t hei

ght/

hIn winter, momentum penetrates further, but still islargely dissipated before it gets to the ground.

Sakai et al. (2000)

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.

Wait longer, get more flux.

Just let enough air go by--collect the informationon the large (CBL) eddies that advect past.

Running mean average period “wind run”

The first demonstration of cospectral similarity in the RSL--seems to work for T, q, CO2, momentum.

Demonstrating the RSL cospectral similarity forms.

Kansas

BOREAS

Harvard Forest

Finding a correction factor to fix up the fluxes.

Lots of things go on inside the rain forest canopy.Vertical profiles at Ducke (Fitzjarrald et al., 1988)

Observing very local scale advective effects may not be possibleif 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?

Effects of the local hillextend well into the SBL.(SODAR results and mysteries!)

HF, DRAINO (Staebler, JRG).

Utility of SODAR observations.It doesn’t measure quite what we want.

Sodar at Harvard Forestlast week...

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

LBA-Ecology PastureSite (km 77)

Solar panels

Tower

Automatic weather station at Belterra. Tapajós River in background.

Automatic weather station at Fazenda Caboco, km 117.

“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

Subtle topography and local site matter-examples from Albany.

Flux convergence during theearly evening transition can beused to estimate fluxes. Acevedo & Fitzjarrald (2000)

Spatial s.d.

Temporal s.d.

Nocturnal T variability observed at sfc stations.

Noon Midnight

Acevedo & Fitzjarrald (2000)

Upper row: temporal evolution of temperature (upper panel) and wind gusts (lower panel) at the 26 stations for 3 different nights. Lower row: T-spat for each of the nights shown in the upper row.

Acevedo & Fitzjarrald (2000)

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

Temperature evolution at indicated stations;

Thick solid line is average wind speed in the network.Acevedo & Fitzjarrald

(2000)

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)

Fitzjarrald et al. (2000)

Freedman & Fitzjarrald (2000)

Freedman & Fitzjarrald (2000)

Freedman & Fitzjarrald (2000)

Freedman & Fitzjarrald (2000)

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.