@Article{RammigHHVBCCDFGGHJKLMPOTVZR:2018:ExAmRe,
author = "Rammig, Anja and Heinke, Jens and Hofhansl, Florian and Verbeeck,
Hans and Baker, Timothy R. and Christoffersen, Bradley and Ciais,
Philippe and De Deurwaerder, Hannes and Fleischer, Katrin and
Galbraith, David and Guimberteau, Matthieu and Huth, Andreas and
Johnson, Michelle and Krujit, Bart and Langerwisch, Fanny and
Meir, Patrick Meir and Papastefanou, Phillip and Oliveira, Gilvan
Sampaio de and Thonicke, Kirsten and Von Randow, Celso and Zang,
Christian and R{\"o}dig, Edna",
affiliation = "{Technical University of Munich} and {Potsdam Institute for
Climate Impact Research} and {IIASA International Institute for
Applied Systems Analysis} and {CAVElab Computational \& Applied
Vegetation Ecology} and School of Geography, University of Leeds
and {The University of Texas Rio Grande Valley} and
{Universit{\'e} Paris-Saclay} and 4CAVElab Computational \&
Applied Vegetation Ecology, Department of Applied Ecology and
Environmental Biology, Faculty of Bioscience Engineering and
{Technical University of Munich} and {University of Leeds} and
{Universit{\'e} Paris-Saclay} and {Helmholtz Centre for
Environmental Research (UFZ)} and {University of Leeds} and
ALTERRA and {Potsdam Institute for Climate Impact Research} and
{University of Edinburgh} and {Technical University of Munich} and
{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Potsdam
Institute for Climate Impact Research} and {Instituto Nacional de
Pesquisas Espaciais (INPE)} and {Technical University of Munich}
and {Helmholtz Centre for Environmental Research (UFZ)}",
title = "A generic pixel-to-point comparison for simulated large-scale
ecosystem properties and ground-based observations: an example
from the Amazon region",
journal = "Geoscientific Model Development",
year = "2018",
volume = "11",
pages = "5203--5215",
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 and provide
statistical measures accounting for the uncertainty resulting from
landscape variability and measurement errors in ecosystem
variables. 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, potential scale mismatch
and thus 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 modeldata 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.",
doi = "10.5194/gmd-11-5203-2018",
url = "http://dx.doi.org/10.5194/gmd-11-5203-2018",
issn = "1991-959X",
language = "en",
targetfile = "rammig_generic.pdf",
urlaccessdate = "27 abr. 2024"
}