Gross primary productivity (GPP) is the largest
and most variable component of the global terrestrial carbon
cycle. Repeatable and accurate monitoring of terrestrial
GPP is therefore critical for quantifying dynamics in
regional-to-global carbon budgets. Remote sensing provides high frequency observations of terrestrial ecosystems and is
widely used to monitor and...
Full Text:
. Roupsard, E. J. Moors, P. Toscano, F. P. Vaccari, D. Gianelle, G. Bohrer, A. Varlagin,
N. Buchmann, E
Gross primary productivity (GPP) is the largest
and most variable component of the global terrestrial carbon
cycle. Repeatable and accurate monitoring of terrestrial
GPP is therefore critical for quantifying dynamics in
regional-to-global carbon budgets. Remote sensing provides high frequency observations of terrestrial ecosystems and is
widely used to monitor and...
Full Text:
., Roupsard, O., Moors, E. J., Toscano, P., Vaccari, P.,
Gianelle, D., Bohrer, G., Varlagin, A., Buchmann, N
Gross primary productivity (GPP) is the largest
and most variable component of the global terrestrial carbon
cycle. Repeatable and accurate monitoring of terrestrial
GPP is therefore critical for quantifying dynamics in
regional-to-global carbon budgets. Remote sensing provides high frequency observations of terrestrial ecosystems and is
widely used to monitor and...
The eddy-covariance method often underestimates fluxes under stable, low-wind conditions at night when turbulence is not well developed. The most common approach to resolve the problem of nighttime flux underestimation is to identify and remove the deficit periods using friction-velocity (u*) threshold filters (u*[superscript Th]). This study modifies an accepted...