How to address scaling, storage flux and non-closed energy balance problems for eddy-covariance observations? Mapping surface-atmosphere exchange using environmental response function

Eddy-covariance and profile measurements are widely used to develop and test parameterizations of land-atmosphere interactions in earth system models. However, a fundamental challenge for these comparisons lies in the scale mismatch: Observations represent temporally varying and small source areas (10⁰–10¹ km²), while simulations produce temporally regular, regional-scale grids (10³–10⁴ km²). The environmental response function (ERF) method provides a promising link through unveiling the regional flux field underlying the observed surface-atmosphere exchange. This is achieved by relating sub-hourly turbulent fluxes to meteorological forcings and surface properties, and utilizing the resulting relationships for spatio-temporal mapping.

However, a new challenge arises: At sub-hourly time scales, surface-atmosphere exchange is rarely resolved completely by the turbulent flux alone. Specifically in the case of taller towers, storage beneath the turbulent flux measurement height can comprise a substantial amount of the actual surface-atmosphere exchange. The companion paper by Metzger presents the methodological considerations for, and implications of, combining turbulent and storage flux into an ERF virtual control volume.

Here, we show the first practical application of this concept, and produce temporally resolved maps of heat, water and carbon net ecosystem exchange. For this purpose, eddy-covariance and profile observations in 2011 Aug from the 447 m tall AmeriFlux Park Falls WLEF tower in Wisconsin, USA are used. To construct the coupled ERF, eddy-covariance and profile observations are related to surface properties and meteorological forcings separately. In this study, turbulent flux, storage flux and surface-atmosphere exchange of sensible heat integrated over a 20×20 km² target domain differ substantially from the tower observations in their monthly averaged value (+4.7 W/m², +2.7 W/m² and +7.3 W/m²) and diurnal cycle. Through superimposing storage and turbulent flux, we demonstrate an improved performance in mapping net ecosystem exchange. This bears the potential to diagnose advective contributions and surface-heterogeneity-related components of a frequently observed non-closed energy balance. These advances promise significant improvements for model-data comparison, assimilation and model building.