Abstract
High‐frequency measurements of water vapor (q) and carbon dioxide (c) concentrations were collected over the course of a transition from dry to wet surface conditions in an agricultural setting on the eastern shore of Virginia. Daytime correlation coefficients between q and c were close to −1 during the dry conditions but became degraded during the wet conditions. An application of wavelet analysis to the high‐frequency time series showed that the degraded q‐c correlations on the wet day were mainly caused by the influence of large‐scale eddies, which introduced positively correlated q‐c components to the half‐hour time series. Consistent differences in q‐c correlation were also observed for smaller eddy scales, which are more indicative of the surface‐atmosphere exchange. Correlations between q and c for this range of eddy scales were likewise closer to −1 for dry conditions, when transfer efficiencies of both scalars exhibited greater similarity. These correlations are influenced by the nonidentical source‐sink distributions of the water vapor and carbon dioxide fluxes and the relative magnitude of their constituent fluxes. A new method is introduced to estimate the components of the water vapor flux (transpiration and direct evaporation) and carbon dioxide flux (photosynthesis and respiration) by applying flux variance similarity assumptions separately to the stomatal and the nonstomatal exchange and by considering q‐c correlation. Water use efficiency for the vegetation, and how it varies with respect to vapor pressure deficit, is the only input needed for this approach that uses standard eddy covariance measurements. Reasonable estimates yielded by this technique when applied to the contrasting wet and dry days demonstrate its potential for flux partitioning.
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