HR: 1340h
AN: B33E-1666    [Abstracts]
TI: Comprehensive comparison of gap filling techniques for eddy covariance net carbon fluxes
AU: Moffat, A M
EM: amoffat@bgc-jena.mpg.de
AF: MPI for Biogeochemistry, Hans-Knoell-Str. 10, Jena, 07745, Germany
AU: * Papale, D
AF: DISAFRI, University of Tuscia, via C. de Lellis, Viterbo, 01100, Italy
AU: Reichstein, M
AF: MPI for Biogeochemistry, Hans-Knoell-Str. 10, Jena, 07745, Germany
AU: Hollinger, D Y
AF: USDA Forest Service, Northern Research Station, 271 Mast Rd., Durham, NH 03824, United States
AU: Richardson, A D
AF: Complex Systems Research Center, University of New Hampshire, Morse Hall, 39 College Road, Durham, NH 03824, United States
AU: Barr, A G
AF: Climate Research Branch, Meteorological Service of Canada, 11 Innovation Blvd., Saskatoon, SK S7N 3H5, Canada
AU: Beckstein, C
AF: Friedrich-Schiller-Universität Jena, Institut für Informatik, Ernst-Abbe-Platz 1-4, Jena, 07743, Germany
AU: Braswell, B H
AF: Institute for the Study of Earth, Ocean, and Space, University of New Hampshire, Durham, NH 03824, United States
AU: Churkina, G
AF: MPI for Biogeochemistry, Hans-Knoell-Str. 10, Jena, 07745, Germany
AU: Desai, A R
AF: Department of Atmospheric and Oceanic Sciences, University Wisconsin-Madison, 1225 W Dayton St., Madison, WI 53706, United States
AU: Falge, E
AF: Max-Planck-Institute for Chemistry, Biogeochemistry Department, J.J.v. Becherweg 27, Mainz, 55128, Germany
AU: Gove, J H
AF: USDA Forest Service, Northern Research Station, 271 Mast Rd., Durham, NH 03824, United States
AU: Heimann, M
AF: MPI for Biogeochemistry, Hans-Knoell-Str. 10, Jena, 07745, Germany
AU: Hui, D
AF: School of Forestry and Wildlife Sciences, Auburn University, Auburn, AL 36849-5418, United States
AU: Jarvis, A J
AF: Environmental Science Department, Lancaster University, Lancaster, LA1 4YQ, United Kingdom
AU: Kattge, J
AF: MPI for Biogeochemistry, Hans-Knoell-Str. 10, Jena, 07745, Germany
AU: Noormets, A
AF: North Carolina State University/USDA Forest Service, 920 Main Campus Drive, Raleigh, NC 27606, United States
AU: Stauch, V J
AF: Federal Office for Meteorology and Climatology, Meteoswiss, Zurich, 8044, Switzerland
AB: Review of fifteen techniques for estimating missing values of net ecosystem CO2 exchange (NEE) in eddy covariance time series and evaluation of their performance for different artificial gap scenarios based on a set of ten benchmark datasets from six forested sites in Europe. The goal of gap filling is the reproduction of the NEE time series and hence this present work focuses on estimating missing NEE values, not on editing or the removal of suspect values in these time series due to systematic errors in the measurements (e.g. nighttime flux, advection). The gap filling was examined by generating fifty secondary datasets with artificial gaps (ranging in length from single half-hours to twelve consecutive days) for each benchmark dataset and evaluating the performance with a variety of statistical metrics. The performance of the gap filling varied among sites and depended on the level of aggregation (native half- hourly time step versus daily), long gaps were more difficult to fill than short gaps, and differences among the techniques were more pronounced during the day than at night. The non-linear regression techniques (NLRs), the look-up table (LUT), marginal distribution sampling (MDS), and the semi-parametric model (SPM) generally showed good overall performance. The artificial neural network based techniques (ANNs) were generally, if only slightly, superior to the other techniques. The simple interpolation technique of mean diurnal variation (MDV) showed a moderate but consistent performance. Several sophisticated techniques, the dual unscented Kalman filter (UKF), the multiple imputation method (MIM), the terrestrial biosphere model (BETHY), but also one of the ANNs and one of the NLRs showed high biases which resulted in a low reliability of the annual sums, indicating that additional development might be needed. An uncertainty analysis comparing the estimated random error in the ten benchmark datasets with the artificial gap residuals suggested that the techniques are already at or very close to the noise limit of the measurements. Based on the techniques and site data examined here, the effect of gap filling on the annual sums of NEE is modest, with most techniques falling within a range of ±25 g C m-2 y-1.
DE: 0428 Carbon cycling (4806)
DE: 0430 Computational methods and data processing
DE: 0466 Modeling
SC: Biogeosciences [B]
MN: 2007 Fall Meeting