Towards the spatial rectification of tower-based eddy-covariance flux observations

Abstract:

Eddy-covariance (EC) observations of ecologically relevant trace gas and energy fluxes are too sparse spatially for direct assimilation into gridded earth system models (ESMs). The spatial coverage of a tower EC measurement may represent less than 1% of a grid cell resolved by ESMs. For advancing ecological inference it is hence desirable to improve the spatial representativeness of EC measurements. The objectives of this study are (i) to map the spatio-temporally variable flux field around tower EC measurements, and (ii) to quantify spatial representativeness when surrogating the flux over an ESM grid cell with EC observations that source a spatio-temporally variable patch of surface close to the tower.

The present study employs environmental response functions (ERFs) for this purpose. The underlying principle is to extract the relationship between biophysical drivers and ecological responses from measurements in the time-domain under varying environmental conditions. The resulting ERF can then be used for projecting the fluxes into target areas. Based on the probability density functions of resulting flux grids, the representativeness of tower measurements is quantified.

We apply ERF to EC measurements from July and August 2011 at the AmeriFlux Park Falls tall tower, Wisconsin, U.S.A. With the ERF procedure, the spatial coverage can be increased to >70% for target areas around the tower of 400 km². From this we determine that 85% and 24% of the tower flux observations can capture the mean turbulent flux and its variability over a 900 km² target area, respectively, at 5% significance and 80% representativeness level. Lastly, we determine an uncertainty budget for this methodology. Our companion presentation “Assessing and correcting spatial representativeness of tower eddy-covariance flux measurements” shows the applicability of the ERF procedure to provide consistent flux time series for target regions under different climatic and ecological environments.