The CO 2 record at the Amazon Tall Tower Observatory: A new opportunity to study processes on seasonal and inter-annual scales.

Autor: Botía S; Biogeochemical Signals Department, Max Planck Institute for Biogeochemistry, Jena, Germany., Komiya S; Biogeochemical Processes Department, Max Planck Institute for Biogeochemistry, Jena, Germany., Marshall J; Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany., Koch T; Biogeochemical Signals Department, Max Planck Institute for Biogeochemistry, Jena, Germany., Gałkowski M; Biogeochemical Signals Department, Max Planck Institute for Biogeochemistry, Jena, Germany.; Faculty of Physics and Applied Computer Science, AGH University of Science and Technology, Kraków, Poland., Lavric J; Biogeochemical Processes Department, Max Planck Institute for Biogeochemistry, Jena, Germany., Gomes-Alves E; Biogeochemical Processes Department, Max Planck Institute for Biogeochemistry, Jena, Germany., Walter D; Multiphase Chemistry Department, Max Planck Institute for Chemistry, Mainz, Germany., Fisch G; Departamento de Ciência e Tecnologia Aeroespacial (DCTA), Instituto de Aeronautica e Espaço (IAE), São José dos Campos, Brazil., Pinho DM; Environmental Dynamics Department, Brazil's National Institute for Amazon Research - INPA, Manaus, Brazil., Nelson BW; Environmental Dynamics Department, Brazil's National Institute for Amazon Research - INPA, Manaus, Brazil., Martins G; Environmental Dynamics Department, Brazil's National Institute for Amazon Research - INPA, Manaus, Brazil., Luijkx IT; Meteorology and Air Quality Department, Wageningen University and Research Center, Wageningen, The Netherlands., Koren G; Meteorology and Air Quality Department, Wageningen University and Research Center, Wageningen, The Netherlands., Florentie L; Meteorology and Air Quality Department, Wageningen University and Research Center, Wageningen, The Netherlands., Carioca de Araújo A; Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA), Belém, Brazil., Sá M; Instituto Nacional de Pesquisas da Amazônia (INPA), Manaus, Brazil., Andreae MO; Biogeochemistry Department, Max Planck Institute for Chemistry, Mainz, Germany.; Scripps Institution of Oceanography, University of California San Diego, La Jolla, California, USA., Heimann M; Biogeochemical Signals Department, Max Planck Institute for Biogeochemistry, Jena, Germany.; Institute for Atmospheric and Earth System Research (INAR) / Physics, University of Helsinki, Helsinki, Finland., Peters W; Meteorology and Air Quality Department, Wageningen University and Research Center, Wageningen, The Netherlands.; Groningen University, Energy and Sustainability Research Institute Groningen, Groningen, The Netherlands., Gerbig C; Biogeochemical Signals Department, Max Planck Institute for Biogeochemistry, Jena, Germany.
Jazyk: angličtina
Zdroj: Global change biology [Glob Chang Biol] 2022 Jan; Vol. 28 (2), pp. 588-611. Date of Electronic Publication: 2021 Oct 26.
DOI: 10.1111/gcb.15905
Abstrakt: High-quality atmospheric CO 2  measurements are sparse in Amazonia, but can provide critical insights into the spatial and temporal variability of sources and sinks of CO 2 . In this study, we present the first 6 years (2014-2019) of continuous, high-precision measurements of atmospheric CO 2 at the Amazon Tall Tower Observatory (ATTO, 2.1°S, 58.9°W). After subtracting the simulated background concentrations from our observational record, we define a CO 2 regional signal ( Δ CO 2 obs ) that has a marked seasonal cycle with an amplitude of about 4 ppm. At both seasonal and inter-annual scales, we find differences in phase between Δ CO 2 obs and the local eddy covariance net ecosystem exchange (EC-NEE), which is interpreted as an indicator of a decoupling between local and non-local drivers of Δ CO 2 obs . In addition, we present how the 2015-2016 El Niño-induced drought was captured by our atmospheric record as a positive 2σ anomaly in both the wet and dry season of 2016. Furthermore, we analyzed the observed seasonal cycle and inter-annual variability of Δ CO 2 obs together with net ecosystem exchange (NEE) using a suite of modeled flux products representing biospheric and aquatic CO 2 exchange. We use both non-optimized and optimized (i.e., resulting from atmospheric inverse modeling) NEE fluxes as input in an atmospheric transport model (STILT). The observed shape and amplitude of the seasonal cycle was captured neither by the simulations using the optimized fluxes nor by those using the diagnostic Vegetation and Photosynthesis Respiration Model (VPRM). We show that including the contribution of CO 2 from river evasion improves the simulated shape (not the magnitude) of the seasonal cycle when using a data-driven non-optimized NEE product (FLUXCOM). The simulated contribution from river evasion was found to be 25% of the seasonal cycle amplitude. Our study demonstrates the importance of the ATTO record to better understand the Amazon carbon cycle at various spatial and temporal scales.
(© 2021 The Authors. Global Change Biology published by John Wiley & Sons Ltd.)
Databáze: MEDLINE
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