B43D-0592
Flux tower in a mixed forest: spatial representativeness of seasonal footprints and the influence of land cover variability on the flux measurement
Abstract:
Flux tower measurements using eddy-covariance techniques are used as the primary data for calibration and validation of remote sensing estimates and ecosystem models. Therefore, understanding the characteristics of the land surface contributing to the flux, the so-called footprint, is critical to upscale tower flux to the regional landscape. This is especially true for the towers locating in heterogeneous ecosystems such as mixed forests. Here we (1) estimated the seasonal footprints of a flux tower, the EMS-tower (US-Ha1) in the Long Term Ecological Research (LTER) Harvard Forest, from 1992 to 2008 with a footprint climatology. The Harvard Forest is a temperate mixed-species ecosystem that is composed of deciduous stands (red oak and red maple) and evergreen coniferous stands (eastern hemlock and white pine). The heterogeneity of the landscape is primarily driven by the phenology of the deciduous stands which are not uniformly distributed over the forest and around the tower. The overall prevailing footprints are known to lie toward the southwest and northwest, but there were profound interannual variability in the extents and the orientations of the seasonal footprints. Furthermore we (2) examined whether vegetation density variation within the tower footprint in each season could adequately represent the vegetation density characteristics of moderate spatial resolution remote sensing estimates and ecosystem models (i.e. 1.0 km and 1.5 km). The footprints were found to cover enough area to be representative of the 1.0 km scale but not 1.5 km scale. Finally we (3) investigated the influence of the interannual variations in the land cover variability in the footprints on the seasonal flux measurements from 1999 to 2008, and found almost half of the interannual anomalies in the summertime GPP flux can be explained by the coniferous stand fraction within the footprint.