Conditional Sampling, Event-Based Composites, and Observational Reynolds Ensemble Methods: Thirty Years of Parsing Data to Determine Vegetation–Atmosphere Feedbacks

There is not simply a one-way interaction between a vegetated surface and the lower atmosphere, as the common term ‘atmospheric forcing’ would suggest. If one focuses on events, rather than always examining averages in the established hourly, monthly, annual averages, the real-world sensitivity to particular inputs can be estimated. This presentation discusses the advantages of re-examining data using conditional sampling, Reynolds ensemble averaging, case studies, and composite approaches. We examine time scales beginning with looking again at the ‘raw’ turbulence data, then developing a practical method to complete ensembles to examine particular phenomena . Each of the several efforts discussed examined a different time scale. Special emphasis was given not only to inferring the sensitivity of the vegetation-atmosphere interaction to particular environmental ‘forcings’ but also on the cooperative feedbacks that real vegetation has with the atmosphere.

There is a distinction among the techniques involved; composite analyses are not quite similar as the Reynolds ensemble approach. For example, in the study of the response of vegetation to step changes in illumination, we used the formal Reynolds ensemble to get w’ and T’ separately, and then averaged over many events to find the flux. (We considered a similar approach with the rainfall interception paper, but found the 5-minute time averages worked well enough to make our point.)

Topic	Time scale	“Trigger” for t = 0
1. contribution of ‘large eddies’ to forest-atmosphere fluxes (Lu & Fitzjarrald, 1992)	1-3 minutes	T’, w’ excursions
2. carbon uptake, WUE response to step light changes (Kivalov & Fitzjarrald, 2018, 2019	1-10 minutes	cloud shadow-to-sunlight transition
3. estimating rainfall interception from eddy water vapor fluxes, forest (Czikowsky & Fitzjarrald, 2009)	≈ ½ day	rainfall event; ensemble assembly
4. diurnal wind rotation--river breeze (Oliveira & Fitzjarrald, 1990)	daily	diurnal composite, fair days
5. forced cumulus development (Freedman & Fitzjarrald, 2000)	≈ weekly	cold frontal passage
6. vegetation effecting sfc. climate, Cu clouds; (Fitzjarrald et al., 2001; Freedman et al. 2001)	≈ 3 weeks/seasonal	deciduous tree leaf emergence (phenology)
7. streamflow response to leaf emergence (Czikowsky & Fitzjarrald, 2004)	Seasonal or multidecadal	rainfall & changes in recession time constant; spring transition; reforestation