Natural Resources, School of

 

Authors

Eva Falge, SPM, University of California, Berkeley, Berkeley, CA
Dennis D. Baldocchi, University of California, BerkeleyFollow
Richard Olson, Environmental Science Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
Peter Anthoni, Richardson Hall, Oregon State University, Corvallis, OR
Marc Aubinet, Unité de Physique, Faculté des Sciences Agronomiques de Gembloux, B-50 30 Gembloux, Belgium
Christian Bernhofer, Technische Universität Dresden, IHM Meteorologie, Pienner Str. 9, 01737 Tharandt, Germany
George Burba, University of Nebraska-LincolnFollow
Reinhart Ceulemans, University of Antwerpen, Universiteitsplein 1, B-2610, Wilrijk, Antwerp, Belgium
Robert Clement, University of Edinburgh, Edinburgh EH9 3JU, UK
Han Dolman, Alterra, Postbus 47, 6700 AA Wageningen, The Netherlands
Andre Grainer, INRA, Unité d’Ecophysiologie Forestière, F-54280 Champenoux, France
Thomas Grunwald, Technische Universität Dresden, IHM Meteorologie, Pienner Str. 9, 01737 Tharandt, Germany
David Hollinger, USDA Forest Service, 271 Mast Rd, Durham, NH 03824, USA
Niels-Otto Jensen, Plant Biology and Biogeochemistry Department, Risoe National Laboratory, P.O. Box 49, DK-4000 Roskilde, Denmark
Gabriel Katul, Duke University, Durham, NC 27708-0328, USA
Petri Keronen, University of Helsinki, P.O. Box 9, FIN-00014 Helsinki, Finland
Andrew Kowalski, University of Antwerpen, Universiteitsplein 1, B-2610, Wilrijk, Antwerp, Belgium
Chun Ta Lai, Duke University, Durham, NC 27708-0328, USA
Beverly E. Law, Oregon State UniversityFollow
Tilden Meyers, NOAA/ATDD
Jon Moncrieff, Institute of Ecology and Resource Management, University of Edinburgh, Edinburgh EH9 3JU, UK
Eddy Moors, Alterra, Postbus 47, 6700 AA Wageningen, The Netherlands
J. William Munger, Harvard University
Kim Pilegaard, SPM, University of California, Berkeley
Ullar Rannik, University of Helsinki, P.O. Box 9, FIN-00014 Helsinki, Finland
Corinna Rebmann, Max-Planck-Institut für Biogeochemie, Tatzendpromenade 1a, 07701 Jena, Germany
Andrew E. Suyker, University of Nebraska - LincolnFollow
John Tenhunen, Pflanzenökologie, Universität Bayreuth, 95440 Bayreuth, Germany
Kevin Tu, University of New Hampshire, Durham, NH 03824, USA
Shashi Verma, University of Nebraska - LincolnFollow
Timo Vesala, University of Helsinki, P.O. Box 9, FIN-00014 Helsinki, Finland
Kell Wilson, NOAA/ATDD, 456 S. Illinois Avenue, Oak Ridge, TN 37831-2456, USA
Steve Wofsy, Harvard University

Date of this Version

2-8-2001

Comments

Published in Agricultural and Forest Meteorology 107 (2001) 43–69.

Abstract

Heightened awareness of global change issues within both science and political communities has increased interest in using the global network of eddy covariance flux towers to more fully understand the impacts of natural and anthropogenic phenomena on the global carbon balance. Comparisons of net ecosystem exchange (FNEE) responses are being made among biome types, phenology patterns, and stress conditions. The comparisons are usually performed on annual sums of FNEE; however, the average data coverage during a year is only 65%. Therefore, robust and consistent gap filling methods are required.

We review several methods of gap filling and apply them to data sets available from the EUROFLUX and AmeriFlux databases. The methods are based on mean diurnal variation (MDV), look-up tables (LookUp), and nonlinear regressions (Regr.), and the impact of different gap filling methods on the annual sum of FNEE is investigated. The difference between annual FNEE filled by MDV compared to FNEE filled by Regr. ranged from −45 to +200gCm−2 per year (MDV−Regr.). Comparing LookUp and Regr. methods resulted in a difference (LookUp−Regr.) ranging from −30 to +150gCm−2 per year.

We also investigated the impact of replacing measurements at night, when turbulent mixing is insufficient. The nighttime correction for low friction velocities (u*) shifted annual FNEE on average by +77gCm−2 per year, but in certain cases as much as +185gCm−2 per year.

Our results emphasize the need to standardize gap filling-methods for improving the comparability of flux data products from regional and global flux networks.

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