Abstract
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. To quantify the net
exchange of carbon dioxide between the terrestrial biosphere and the atmosphere for
regions or continents, flux tower measurements need to be extrapolated to these large
areas. Here we used remotely sensed data from the Moderate Resolution Imaging Spectrometer
(MODIS) instrument on board the National Aeronautics and Space Administration’s
(NASA) Terra satellite to scale up AmeriFlux NEE measurements to the continental scale.We
first combined MODIS and AmeriFlux data for representative U.S. ecosystems to develop a
predictive NEE model using a modified regression tree approach. The predictive model was
trained and validated using eddy flux NEE data over the periods 2000–2004 and 2005–2006,
respectively. We found that the model predicted NEE well (r = 0.73, p < 0.001). We then
applied the model to the continental scale and estimated NEE for each 1 km 1 km cell
across the conterminous U.S. for each 8-day interval in 2005 using spatially explicit MODIS
data. The model generally captured the expected spatial and seasonal patterns of NEE as
determined from measurements and the literature. Our study demonstrated that our
empirical approach is effective for scaling up eddy flux NEE measurements to the continental
scale and producing wall-to-wall NEE estimates across multiple biomes. Our
estimates may provide an independent dataset from simulations with biogeochemical
models and inverse modeling approaches for examining the spatiotemporal patterns of
NEE and constraining terrestrial carbon budgets over large areas.