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Projeto de investigação
Observation-based system for monitoring and verification of greenhouse gases
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Technical note
Publication . Walther, Sophia; Besnard, Simon; Nelson, Jacob Allen; El-Madany, Tarek Sebastian; Migliavacca, Mirco; Weber, Ulrich; Carvalhais, Nuno; Ermida, Sofia Lorena; Brümmer, Christian; Schrader, Frederik; Prokushkin, Anatoly Stanislavovich; Panov, Alexey Vasilevich; Jung, Martin; DCEA - Departamento de Ciências e Engenharia do Ambiente; Copernicus Publications
The eddy-covariance technique measures carbon, water, and energy fluxes between the land surface and the atmosphere at hundreds of sites globally. Collections of standardised and homogenised flux estimates such as the LaThuile, Fluxnet2015, National Ecological Observatory Network (NEON), Integrated Carbon Observation System (ICOS), AsiaFlux, AmeriFlux, and Terrestrial Ecosystem Research Network (TERN)/OzFlux data sets are invaluable to study land surface processes and vegetation functioning at the ecosystem scale. Space-borne measurements give complementary information on the state of the land surface in the surroundings of the towers. They aid the interpretation of the fluxes and support the benchmarking of terrestrial biosphere models. However, insufficient quality and frequent and/or long gaps are recurrent problems in applying the remotely sensed data and may considerably affect the scientific conclusions. Here, we describe a standardised procedure to extract, quality filter, and gap-fill Earth observation data from the MODIS instruments and the Landsat satellites. The methods consistently process surface reflectance in individual spectral bands, derived vegetation indices, and land surface temperature. A geometrical correction estimates the magnitude of land surface temperature as if seen from nadir or 40g off-nadir. Finally, we offer the community living data sets of pre-processed Earth observation data, where version 1.0 features the MCD43A4/A2 and MxD11A1 MODIS products and Landsat Collection 1 Tier 1 and Tier 2 products in a radius of 2 km around 338 flux sites. The data sets we provide can widely facilitate the integration of activities in the eddy-covariance, remote sensing, and modelling fields.
Global sensitivities of forest carbon changes to environmental conditions
Publication . Besnard, Simon; Santoro, Maurizio; Cartus, Oliver; Fan, Naixin; Linscheid, Nora; Nair, Richard; Weber, Ulrich; Koirala, Sujan; Carvalhais, Nuno; DCEA - Departamento de Ciências e Engenharia do Ambiente; Wiley-Blackwell
The responses of forest carbon dynamics to fluctuations in environmental conditions at a global scale remain elusive. Despite the understanding that favourable environmental conditions promote forest growth, these responses have been challenging to observe across different ecosystems and climate gradients. Based on a global annual time series of aboveground biomass (AGB) estimated from radar satellites between 1992 and 2018, we present forest carbon changes and provide insights on their sensitivities to environmental conditions across scales. Our findings indicate differences in forest carbon changes across AGB classes, with regions with carbon stocks of 50–125 MgC ha−1 depict the highest forest carbon gains and losses, while regions with 125–150 MgC ha−1 have the lowest forest carbon gains and losses in absolute terms. Net forest carbon change estimates show that the arc-of-deforestation and the Congo Basin were the main hotspots of forest carbon loss, while a substantial part of European forest gained carbon during the last three decades. Furthermore, we observe that changes in forest carbon stocks were systematically positively correlated with changes in forest cover fraction. At the same time, it was not necessarily the case with other environmental variables, such as air temperature and water availability at the bivariate level. We also used a model attribution method to demonstrate that atmospheric conditions were the dominant control of forest carbon changes (56% of the total study area) followed by water-related (29% of the total study area) and vegetation (15% of the total study area) conditions. Regionally, we find evidence that carbon gains from long-term forest growth covary with long-term carbon sinks inferred from atmospheric inversions. Our results describe the contributions from the atmosphere, water-related and vegetation conditions to forest carbon changes and provide new insights into the underlying mechanisms of the coupling between forest growth and the global carbon cycle.
Scaling carbon fluxes from eddy covariance sites to globe: Synthesis and evaluation of the FLUXCOM approach
Publication . Jung, Martin; Schwalm, Christopher; Migliavacca, Mirco; Walther, Sophia; Camps-Valls, Gustau; Koirala, Sujan; Anthoni, Peter; Besnard, Simon; Bodesheim, Paul; Carvalhais, Nuno; Chevallier, Frederic; Gans, Fabian; Goll, Daniel S.; Haverd, Vanessa; Köhler, Philipp; Ichii, Kazuhito; Jain, Atul K.; Liu, Junzhi; Lombardozzi, Danica; Nabel, Julia E. M. S.; Nelson, Jacob A.; O'Sullivan, Michael; Pallandt, Martijn; Papale, Dario; Peters, Wouter; Pongratz, Julia; Rödenbeck, Christian; Sitch, Stephen; Tramontana, Gianluca; Walker, Anthony; Weber, Ulrich; Reichstein, Markus; DCEA - Departamento de Ciências e Engenharia do Ambiente; Copernicus Publications
FLUXNET comprises globally distributed eddy-covariance-based estimates of carbon fluxes between the biosphere and the atmosphere. Since eddy covariance flux towers have a relatively small footprint and are distributed unevenly across the world, upscaling the observations is necessary to obtain global-scale estimates of biosphere-atmosphere exchange. Based on cross-consistency checks with atmospheric inversions, sun-induced fluorescence (SIF) and dynamic global vegetation models (DGVMs), here we provide a systematic assessment of the latest upscaling efforts for gross primary production (GPP) and net ecosystem exchange (NEE) of the FLUXCOM initiative, where different machine learning methods, forcing data sets and sets of predictor variables were employed. Spatial patterns of mean GPP are consistent across FLUXCOM and DGVM ensembles ( at 1 spatial resolution) while the majority of DGVMs show, for 70 of the land surface, values outside the FLUXCOM range. Global mean GPP magnitudes for 2008-2010 from FLUXCOM members vary within 106 and 130 PgC class with the largest uncertainty in the tropics. Seasonal variations in independent SIF estimates agree better with FLUXCOM GPP (mean global pixel-wise) than with GPP from DGVMs (mean global pixel-wise). Seasonal variations in FLUXCOM NEE show good consistency with atmospheric inversion-based net land carbon fluxes, particularly for temperate and boreal regions. Interannual variability of global NEE in FLUXCOM is underestimated compared to inversions and DGVMs. The FLUXCOM version which also uses meteorological inputs shows a strong co-variation in interannual patterns with inversions (for 2001-2010). Mean regional NEE from FLUXCOM shows larger uptake than inversion and DGVM-based estimates, particularly in the tropics with discrepancies of up to several hundred grammes of carbon per square metre per year. These discrepancies can only partly be reconciled by carbon loss pathways that are implicit in inversions but not captured by the flux tower measurements such as carbon emissions from fires and water bodies. We hypothesize that a combination of systematic biases in the underlying eddy covariance data, in particular in tall tropical forests, and a lack of site history effects on NEE in FLUXCOM are likely responsible for the too strong tropical carbon sink estimated by FLUXCOM. Furthermore, as FLUXCOM does not account for fertilization effects, carbon flux trends are not realistic. Overall, current FLUXCOM estimates of mean annual and seasonal cycles of GPP as well as seasonal NEE variations provide useful constraints of global carbon cycling, while interannual variability patterns from FLUXCOM are valuable but require cautious interpretation. Exploring the diversity of Earth observation data and of machine learning concepts along with improved quality and quantity of flux tower measurements will facilitate further improvements of the FLUXCOM approach overall.
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Entidade financiadora
European Commission
Programa de financiamento
H2020
Número da atribuição
776810