wiki:GroupActivities/CodeAvalaibilityPublication/ORCHIDEE_gmd-2018-182

Version 1 (modified by mguimberteau, 6 years ago) (diff)

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ORCHIDEE_gmd-2018-182

This version of ORCHIDEE has been used in publication A generic pixel-to-point comparison for simulated large-scale ecosystem properties and ground-based observations: an example from the Amazon region by Anja Rammig, Jens Heinke, Florian Hofhansl, Hans Verbeeck, Timothy R. Baker, Bradley Christoffersen, Phillipe Ciais, Hannes De Deurwaerder, Katrin Fleischer, David Galbraith, Matthieu Guimberteau, Andreas Huth, Michelle Johnson, Bart Krujit, Fanny Langerwisch, Patrick Meir, Phillip Papastefanou, Gilvan Sampaio, Kirsten Thonicke, Celso von Randow, Christian Zang, and Edna Rödig in GMD as manuscript gmd-2018-182.

Abstract

Comparing model output and observed data is an important step for assessing model performance and quality of simulation results. However, such comparisons are often hampered by differences in spatial scales between local point observations and large-scale simulations of grid-cells or pixels. In this study, we propose a generic approach for a pixel-to-point comparison that accounts for the uncertainty resulting from landscape variability and measurement errors in ecosystem variables, and provide statistical measures. The basic concept of our approach is to determine the statistical properties of small-scale (within-pixel) variability and observational errors, and to use this information to correct for their effect when large-scale area averages (pixel) are compared to small-scale point estimates. We demonstrate our approach by comparing simulated values of aboveground biomass, woody productivity (woody net primary productivity, NPP) and residence time of woody biomass from four dynamic global vegetation models (DGVMs) with measured inventory data from permanent plots in the Amazon rainforest, a region with the typical problem of low data availability, a scale mismatch and high model uncertainty. We find that the DGVMs under- and overestimate aboveground biomass by 25% and up to 60%, respectively. Our comparison metrics provide a quantitative measure for model-data agreement and show moderate to good agreement with the region-wide spatial biomass pattern detected by plot observations. However, all four DGVMs overestimate woody productivity and underestimate residence time of woody biomass even when accounting for the large uncertainty range of the observational data. This is because DGVMs do not represent the relation between productivity and residence time of woody biomass correctly. Thus, the DGVMs may simulate the correct large-scale patterns of biomass but for the wrong reasons. We conclude that more information about the underlying processes driving biomass distribution are necessary to improve DGVMs. Our approach provides robust statistical measures for any pixel-to-point comparison, which is applicable for evaluation of models and remote sensing products.

Code access

Metadata

DOI TBD
Creator Matthieu GUIMBERTEAU
Affiliation LSCE, CEA
Title A generic pixel-to-point comparison for simulated large-scale ecosystem properties and ground-based observations: an example from the Amazon region
Publisher Institut Pierre Simon Laplace (IPSL)
PublicationYear 2018
ResourceType Software
Rights This software is distributed under the CeCILL license
rightsURI http://www.cecill.info/
Subject Land surface model, pixel-to-point comparison, biomass
DataManager Karim Ramage (IPSL)
DataCurator Josefine Ghattas (IPSL)
ContactPerson Matthieu Guimberteau (LSCE/CEA)
FundingReference EU-FP7 AMAZALERT project (grant agreement no. 282664) and the European Research Council Synergy grant ERC-2013-SyG-610028 IMBALANCE-P