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

1. 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

2. 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”

3. 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.

4. 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)

5. 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)

6. z/h scaling zc’ scaling broadleaf conifers, WT Friction velocity u* inside forest canopies.

7. 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)

8. 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)

9. 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)

10. Wait longer, get more flux.

11. Just let enough air go by--collect the information on the large (CBL) eddies that advect past. Running mean average period “wind run”

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

13. Demonstrating the RSL cospectral similarity forms. Harvard Forest Kansas BOREAS

14. Finding a correction factor to fix up the fluxes.

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

16. 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?

17. 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!)

20. It is always awkward to do field work at “remote” sites. LBA-Ecology Pasture Site (km 77) Tower Solar panels

21. “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

24. 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)

25. Spatial s.d. Nocturnal T variability observed at sfc stations. Temporal s.d. Midnight Noon Acevedo & Fitzjarrald (2000)

26. 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)

27. Temperature evolution at indicated stations; Thick solid line is average wind speed in the network. Acevedo & Fitzjarrald (2000)

28. 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)

29. Fitzjarrald et al. (2000)

30. Freedman & Fitzjarrald (2000)

31. Freedman & Fitzjarrald (2000)

32. Freedman & Fitzjarrald (2000)

33. Freedman & Fitzjarrald (2000)

34. 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.