Assessing Tower Flux Footprint Climatology and Scaling Between Remotely Sensed and Eddy Covariance Measurements |
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Authors: | Baozhang?Chen T?Andrew?Black Nicholas?C?Coops Thomas?Hilker J?A? Trofymow Kai?Morgenstern |
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Institution: | (1) Faculty of Land and Food Systems, University of British Columbia, 2357 Main Mall, Vancouver, Canada, V6T 1Z4;(2) Department of Forest Resource Management, University of British Columbia, 2424 Main Mall, Vancouver, Canada, V6T 1Z4;(3) Canadian Forest Service (Pacific Forestry Centre), Natural Resources Canada, Victoria, BC, Canada, V8Z 1M5 |
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Abstract: | We describe pragmatic and reliable methods to examine the influence of patch-scale heterogeneities on the uncertainty in long-term
eddy-covariance (EC) carbon flux data and to scale between the carbon flux estimates derived from land surface optical remote
sensing and directly derived from EC flux measurements on the basis of the assessment of footprint climatology. Three different
aged Douglas-fir stands with EC flux towers located on Vancouver Island and part of the Fluxnet Canada Research Network were
selected. Monthly, annual and interannual footprint climatologies, unweighted or weighted by carbon fluxes, were produced
by a simple model based on an analytical solution of the Eulerian advection-diffusion equation. The dimensions and orientation
of the flux footprint depended on the height of the measurement, surface roughness length, wind speed and direction, and atmospheric
stability. The weighted footprint climatology varied with the different carbon flux components and was asymmetrically distributed
around the tower, and its size and spatial structure significantly varied monthly, seasonally and inter-annually. Gross primary
productivity (GPP) maps at 10-m resolution were produced using a tower-mounted multi-angular spectroradiometer, combined with
the canopy structural information derived from airborne laser scanning (Lidar) data. The horizontal arrays of footprint climatology
were superimposed on the 10-m-resolution GPP maps. Monthly and annual uncertainties in EC flux caused by variations in footprint
climatology of the 59-year-old Douglas-fir stand were estimated to be approximately 15–20% based on a comparison of GPP estimates
derived from EC and remote sensing measurements, and on sensor location bias analysis. The footprint-variation-induced uncertainty
in long-term EC flux measurements was mainly dependent on the site spatial heterogeneity. The bias in carbon flux estimates
using spatially-explicit ecological models or tower-based remote sensing at finer scales can be estimated by comparing the
footprint-weighted and EC-derived flux estimates. This bias is useful for model parameter optimizing. The optimization of
parameters in remote-sensing algorithms or ecosystem models using satellite data will, in turn, increase the accuracy in the
upscaled regional carbon flux estimation. |
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Keywords: | Carbon balance Eddy-covariance measurements Flux footprint Footprint climatology Gross primary productivity Remote sensing Upscaling |
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