Bayesian integration of flux tower data into process-based simulator for quantifying uncertainty in simulated output

DOI

This research implemented a Bayesian statistical method to calibrate a widely used process-based simulator BIOME-BGC against estimates of gross primary production (GPP) data. Six parameters of BIOME-BGC were calibrated, which were also allowed to vary month-by-month to investigate the hypothesis that the phenology exhibited a seasonal cycle that was not accurately reproduced by the simulator. Time varying parameters substantially improved the simulated GPP as compared to GPP obtained with constant parameters.

A file list and description of data (i.e., metadata) in each file are provided in the uploaded pdf file "BayesianIntegration_BIOME-BGC_codebook_Version1.pdf". This pdf file also provides a brief description of the methods adopted in this research.

Identifier
DOI https://doi.org/10.17026/dans-zc7-7549
Metadata Access https://phys-techsciences.datastations.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.17026/dans-zc7-7549
Provenance
Creator R. Raj
Publisher DANS Data Station Phys-Tech Sciences
Contributor M Th Koelen; N.A.S. Hamm (Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede, The Netherlands); C.  van der Tol (Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede, The Netherlands); A. Stein (Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede, The Netherlands)
Publication Year 2016
Rights CC0 1.0; info:eu-repo/semantics/openAccess; http://creativecommons.org/publicdomain/zero/1.0
OpenAccess true
Contact M Th Koelen (Faculty of Geo-Information Science and Earth Observation)
Representation
Resource Type Dataset
Format text/plain; application/pdf; text/x-matlab; application/zip; application/octet-stream; text/csv
Size 16; 477587; 2715; 3250; 23646; 5818; 6545; 6599; 706; 6358; 1984; 1576985; 32351; 1099
Version 1.0
Discipline Agricultural Sciences; Agriculture, Forestry, Horticulture, Aquaculture; Agriculture, Forestry, Horticulture, Aquaculture and Veterinary Medicine; Life Sciences