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Assessing tower flux footprint climatology and scaling between remotely sensed and eddy covariance measurements

Assessing tower flux footprint climatology and scaling between remotely sensed and eddy covariance measurements
Assessing tower flux footprint climatology and scaling between remotely sensed and eddy covariance measurements
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.
carbon balance, eddy-covariance measurements, flux footprint, footprint climatology, gross primary productivity, remote sensing, upscaling
0006-8314
137-167
Chen, Baozhang
1106bc47-8770-4aa5-9edb-f2b2723d69b6
Black, T. Andrew
f6187e30-d043-4094-b5ef-372c60de403b
Coops, Nicholas C.
5511e778-fec2-4f54-8708-de65ba5a0992
Hilker, Thomas
c7fb75b8-320d-49df-84ba-96c9ee523d40
Trofymow, J.A. (Tony)
374e4acd-e8a0-4f6c-a296-3dbb4996aea6
Morgenstern, Kai
df11b322-f710-4dbd-b689-790c77dc5d12
Chen, Baozhang
1106bc47-8770-4aa5-9edb-f2b2723d69b6
Black, T. Andrew
f6187e30-d043-4094-b5ef-372c60de403b
Coops, Nicholas C.
5511e778-fec2-4f54-8708-de65ba5a0992
Hilker, Thomas
c7fb75b8-320d-49df-84ba-96c9ee523d40
Trofymow, J.A. (Tony)
374e4acd-e8a0-4f6c-a296-3dbb4996aea6
Morgenstern, Kai
df11b322-f710-4dbd-b689-790c77dc5d12

Chen, Baozhang, Black, T. Andrew, Coops, Nicholas C., Hilker, Thomas, Trofymow, J.A. (Tony) and Morgenstern, Kai (2009) Assessing tower flux footprint climatology and scaling between remotely sensed and eddy covariance measurements. Boundary-Layer Meteorology, 130 (2), 137-167. (doi:10.1007/s10546-008-9339-1).

Record type: Article

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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More information

Accepted/In Press date: 20 November 2008
e-pub ahead of print date: 24 December 2008
Published date: February 2009
Keywords: carbon balance, eddy-covariance measurements, flux footprint, footprint climatology, gross primary productivity, remote sensing, upscaling
Organisations: Global Env Change & Earth Observation, Geography & Environment

Identifiers

Local EPrints ID: 384705
URI: https://eprints.soton.ac.uk/id/eprint/384705
ISSN: 0006-8314
PURE UUID: db19ace6-1b3b-4205-9805-5d6c657db55e

Catalogue record

Date deposited: 27 Jan 2016 14:15
Last modified: 17 Jul 2017 20:02

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