Upscaling of Eddy Flux Measurements in the Upper Great Lakes Region Using MODIS Data and Modeling Approaches

Quantification of regional-scale ecosystem-atmosphere carbon fluxes remains a challenge. Eddy covariance flux towers provide continuous measurements of net ecosystem carbon exchange (NEE) for a wide range of climate and biome types. However, these measurements only represent the carbon fluxes at the scale of the tower footprint. Remote sensing can be used to estimate fluxes across space, but the information content available from satellite is limited. Further, in heterogeneous regions like the forests of the upper Midwest, considerable sub-pixel variability can lead to errors in flux estimates. We used satellite observations from the Moderate Resolution Imaging Spectroradiometer (MODIS), high-resolution land-cover maps and simple modeling approaches to upscale eddy flux measurements from the unusually densely instrumented Chequamegon Ecosystem-Atmosphere Study (ChEAS) to the regional scale. We first developed light use efficiency and regression models to estimate gross primary productivity (GPP) and NEE at the site level. Unlike previous approaches, our models are driven by MODIS data and are not dependent on gridded ground-based climatology data that typically have low spatial and temporal resolution. Eddy flux measurements were used to calibrate and validate the models, and provide estimates of heterotrophic respiration. We then applied the models to the regional scale using a hybrid of MODIS data and higher resolution land cover data and produced spatially explicit estimates across the ChEAS region. Our approaches could be applied to other geographical regions over the globe to upscale eddy flux measurements to regional scales and to thereby quantify the net exchange of carbon dioxide between the terrestrial ecosystems and the atmosphere.