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Sun W, Luo X, Fang Y, Shiga YP, Zhang Y, Fisher JB, Keenan TF, Michalak AM. Biome-scale temperature sensitivity of ecosystem respiration revealed by atmospheric CO 2 observations. Nat Ecol Evol 2023; 7:1199-1210. [PMID: 37322104 PMCID: PMC10406605 DOI: 10.1038/s41559-023-02093-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2022] [Accepted: 05/10/2023] [Indexed: 06/17/2023]
Abstract
The temperature sensitivity of ecosystem respiration regulates how the terrestrial carbon sink responds to a warming climate but has been difficult to constrain observationally beyond the plot scale. Here we use observations of atmospheric CO2 concentrations from a network of towers together with carbon flux estimates from state-of-the-art terrestrial biosphere models to characterize the temperature sensitivity of ecosystem respiration, as represented by the Arrhenius activation energy, over various North American biomes. We infer activation energies of 0.43 eV for North America and 0.38 eV to 0.53 eV for major biomes therein, which are substantially below those reported for plot-scale studies (approximately 0.65 eV). This discrepancy suggests that sparse plot-scale observations do not capture the spatial-scale dependence and biome specificity of the temperature sensitivity. We further show that adjusting the apparent temperature sensitivity in model estimates markedly improves their ability to represent observed atmospheric CO2 variability. This study provides observationally constrained estimates of the temperature sensitivity of ecosystem respiration directly at the biome scale and reveals that temperature sensitivities at this scale are lower than those based on earlier plot-scale studies. These findings call for additional work to assess the resilience of large-scale carbon sinks to warming.
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Affiliation(s)
- Wu Sun
- Department of Global Ecology, Carnegie Institution for Science, Stanford, CA, USA.
| | - Xiangzhong Luo
- Department of Environmental Science, Policy and Management, University of California, Berkeley, CA, USA
- Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
- Department of Geography, National University of Singapore, Singapore, Singapore
| | - Yuanyuan Fang
- Bay Area Air Quality Management District, San Francisco, CA, USA
| | - Yoichi P Shiga
- Universities Space Research Association, Mountain View, CA, USA
- , San Francisco, CA, USA
| | - Yao Zhang
- Department of Environmental Science, Policy and Management, University of California, Berkeley, CA, USA
- Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Joshua B Fisher
- Schmid College of Science and Technology, Chapman University, Orange, CA, USA
| | - Trevor F Keenan
- Department of Environmental Science, Policy and Management, University of California, Berkeley, CA, USA
- Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Anna M Michalak
- Department of Global Ecology, Carnegie Institution for Science, Stanford, CA, USA.
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2
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Tracking 21 st century anthropogenic and natural carbon fluxes through model-data integration. Nat Commun 2022; 13:5516. [PMID: 36163167 PMCID: PMC9512848 DOI: 10.1038/s41467-022-32456-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Accepted: 08/01/2022] [Indexed: 12/01/2022] Open
Abstract
Monitoring the implementation of emission commitments under the Paris agreement relies on accurate estimates of terrestrial carbon fluxes. Here, we assimilate a 21st century observation-based time series of woody vegetation carbon densities into a bookkeeping model (BKM). This approach allows us to disentangle the observation-based carbon fluxes by terrestrial woody vegetation into anthropogenic and environmental contributions. Estimated emissions (from land-use and land cover changes) between 2000 and 2019 amount to 1.4 PgC yr−1, reducing the difference to other carbon cycle model estimates by up to 88% compared to previous estimates with the BKM (without the data assimilation). Our estimates suggest that the global woody vegetation carbon sink due to environmental processes (1.5 PgC yr−1) is weaker and more susceptible to interannual variations and extreme events than estimated by state-of-the-art process-based carbon cycle models. These findings highlight the need to advance model-data integration to improve estimates of the terrestrial carbon cycle under the Global Stocktake. Accurate estimates of carbon fluxes are important to our understanding of the carbon cycle. Here, via model-data integration, the authors disentangle anthropogenic and environmental carbon flux contributions of terrestrial woody vegetation, and find that environmental processes are weaker and more susceptible to interannual variations and extreme events in the 21st century than previously estimated.
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3
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Botía S, Komiya S, Marshall J, Koch T, Gałkowski M, Lavric J, Gomes-Alves E, Walter D, Fisch G, Pinho DM, Nelson BW, Martins G, Luijkx IT, Koren G, Florentie L, Carioca de Araújo A, Sá M, Andreae MO, Heimann M, Peters W, Gerbig C. The CO 2 record at the Amazon Tall Tower Observatory: A new opportunity to study processes on seasonal and inter-annual scales. GLOBAL CHANGE BIOLOGY 2022; 28:588-611. [PMID: 34562049 DOI: 10.1111/gcb.15905] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/07/2021] [Accepted: 09/16/2021] [Indexed: 06/13/2023]
Abstract
High-quality atmospheric CO2 measurements are sparse in Amazonia, but can provide critical insights into the spatial and temporal variability of sources and sinks of CO2 . In this study, we present the first 6 years (2014-2019) of continuous, high-precision measurements of atmospheric CO2 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 CO2 regional signal ( ΔCO2obs ) 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 ΔCO2obs 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 ΔCO2obs . 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 ΔCO2obs together with net ecosystem exchange (NEE) using a suite of modeled flux products representing biospheric and aquatic CO2 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 CO2 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.
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Affiliation(s)
- Santiago Botía
- Biogeochemical Signals Department, Max Planck Institute for Biogeochemistry, Jena, Germany
| | - Shujiro Komiya
- Biogeochemical Processes Department, Max Planck Institute for Biogeochemistry, Jena, Germany
| | - Julia Marshall
- Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
| | - Thomas Koch
- Biogeochemical Signals Department, Max Planck Institute for Biogeochemistry, Jena, Germany
| | - Michał Gałkowski
- 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
| | - Jost Lavric
- Biogeochemical Processes Department, Max Planck Institute for Biogeochemistry, Jena, Germany
| | - Eliane Gomes-Alves
- Biogeochemical Processes Department, Max Planck Institute for Biogeochemistry, Jena, Germany
| | - David Walter
- Multiphase Chemistry Department, Max Planck Institute for Chemistry, Mainz, Germany
| | - Gilberto Fisch
- Departamento de Ciência e Tecnologia Aeroespacial (DCTA), Instituto de Aeronautica e Espaço (IAE), São José dos Campos, Brazil
| | - Davieliton M Pinho
- Environmental Dynamics Department, Brazil's National Institute for Amazon Research - INPA, Manaus, Brazil
| | - Bruce W Nelson
- Environmental Dynamics Department, Brazil's National Institute for Amazon Research - INPA, Manaus, Brazil
| | - Giordane Martins
- Environmental Dynamics Department, Brazil's National Institute for Amazon Research - INPA, Manaus, Brazil
| | - Ingrid T Luijkx
- Meteorology and Air Quality Department, Wageningen University and Research Center, Wageningen, The Netherlands
| | - Gerbrand Koren
- Meteorology and Air Quality Department, Wageningen University and Research Center, Wageningen, The Netherlands
| | - Liesbeth Florentie
- Meteorology and Air Quality Department, Wageningen University and Research Center, Wageningen, The Netherlands
| | | | - Marta Sá
- Instituto Nacional de Pesquisas da Amazônia (INPA), Manaus, Brazil
| | - Meinrat O Andreae
- Biogeochemistry Department, Max Planck Institute for Chemistry, Mainz, Germany
- Scripps Institution of Oceanography, University of California San Diego, La Jolla, California, USA
| | - Martin Heimann
- Biogeochemical Signals Department, Max Planck Institute for Biogeochemistry, Jena, Germany
- Institute for Atmospheric and Earth System Research (INAR) / Physics, University of Helsinki, Helsinki, Finland
| | - Wouter Peters
- Meteorology and Air Quality Department, Wageningen University and Research Center, Wageningen, The Netherlands
- Groningen University, Energy and Sustainability Research Institute Groningen, Groningen, The Netherlands
| | - Christoph Gerbig
- Biogeochemical Signals Department, Max Planck Institute for Biogeochemistry, Jena, Germany
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Wieder WR, Butterfield Z, Lindsay K, Lombardozzi DL, Keppel‐Aleks G. Interannual and Seasonal Drivers of Carbon Cycle Variability Represented by the Community Earth System Model (CESM2). GLOBAL BIOGEOCHEMICAL CYCLES 2021; 35:e2021GB007034. [PMID: 35860341 PMCID: PMC9285408 DOI: 10.1029/2021gb007034] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Revised: 06/18/2021] [Accepted: 06/25/2021] [Indexed: 06/15/2023]
Abstract
Earth system models are intended to make long-term projections, but they can be evaluated at interannual and seasonal time scales. Although the Community Earth System Model (CESM2) showed improvements in a number of terrestrial carbon cycle benchmarks, relative to its predecessor, our analysis suggests that the interannual variability (IAV) in net terrestrial carbon fluxes did not show similar improvements. The model simulated low IAV of net ecosystem production (NEP), resulting in a weaker than observed sensitivity of the carbon cycle to climate variability. Low IAV in net fluxes likely resulted from low variability in gross primary productivity (GPP)-especially in the tropics-and a high covariation between GPP and ecosystem respiration. Although lower than observed, the IAV of NEP had significant climate sensitivities, with positive NEP anomalies associated with warmer and drier conditions in high latitudes, and with wetter and cooler conditions in mid and low latitudes. We identified two dominant modes of seasonal variability in carbon cycle flux anomalies in our fully coupled CESM2 simulations that are characterized by seasonal amplification and redistribution of ecosystem fluxes. Seasonal amplification of net and gross carbon fluxes showed climate sensitivities mirroring those of annual fluxes. Seasonal redistribution of carbon fluxes is initiated by springtime temperature anomalies, but subsequently negative feedbacks in soil moisture during the summer and fall result in net annual carbon losses from land. These modes of variability are also seen in satellite proxies of GPP, suggesting that CESM2 appropriately represents regional sensitivities of photosynthesis to climate variability on seasonal time scales.
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Affiliation(s)
- William R. Wieder
- National Center for Atmospheric ResearchClimate and Global Dynamics LaboratoryBoulderCOUSA
- Institute of Arctic and Alpine ResearchUniversity of ColoradoBoulderCOUSA
| | - Zachary Butterfield
- Department of Climate and Space Sciences and EngineeringUniversity of MichiganAnn ArborMIUSA
| | - Keith Lindsay
- National Center for Atmospheric ResearchClimate and Global Dynamics LaboratoryBoulderCOUSA
| | - Danica L. Lombardozzi
- National Center for Atmospheric ResearchClimate and Global Dynamics LaboratoryBoulderCOUSA
| | - Gretchen Keppel‐Aleks
- Department of Climate and Space Sciences and EngineeringUniversity of MichiganAnn ArborMIUSA
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5
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COS-derived GPP relationships with temperature and light help explain high-latitude atmospheric CO 2 seasonal cycle amplification. Proc Natl Acad Sci U S A 2021; 118:2103423118. [PMID: 34380737 DOI: 10.1073/pnas.2103423118] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
In the Arctic and Boreal region (ABR) where warming is especially pronounced, the increase of gross primary production (GPP) has been suggested as an important driver for the increase of the atmospheric CO2 seasonal cycle amplitude (SCA). However, the role of GPP relative to changes in ecosystem respiration (ER) remains unclear, largely due to our inability to quantify these gross fluxes on regional scales. Here, we use atmospheric carbonyl sulfide (COS) measurements to provide observation-based estimates of GPP over the North American ABR. Our annual GPP estimate is 3.6 (2.4 to 5.5) PgC · y-1 between 2009 and 2013, the uncertainty of which is smaller than the range of GPP estimated from terrestrial ecosystem models (1.5 to 9.8 PgC · y-1). Our COS-derived monthly GPP shows significant correlations in space and time with satellite-based GPP proxies, solar-induced chlorophyll fluorescence, and near-infrared reflectance of vegetation. Furthermore, the derived monthly GPP displays two different linear relationships with soil temperature in spring versus autumn, whereas the relationship between monthly ER and soil temperature is best described by a single quadratic relationship throughout the year. In spring to midsummer, when GPP is most strongly correlated with soil temperature, our results suggest the warming-induced increases of GPP likely exceeded the increases of ER over the past four decades. In autumn, however, increases of ER were likely greater than GPP due to light limitations on GPP, thereby enhancing autumn net carbon emissions. Both effects have likely contributed to the atmospheric CO2 SCA amplification observed in the ABR.
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6
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Wang K, Wang X, Piao S, Chevallier F, Mao J, Shi X, Huntingford C, Bastos A, Ciais P, Xu H, Keeling RF, Pacala SW, Chen A. Unusual characteristics of the carbon cycle during the 2015-2016 El Niño. GLOBAL CHANGE BIOLOGY 2021; 27:3798-3809. [PMID: 33934460 DOI: 10.1111/gcb.15669] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/07/2021] [Accepted: 03/27/2021] [Indexed: 06/12/2023]
Abstract
The 2015-2016 El Niño was one of the strongest on record, but its influence on the carbon balance is less clear. Using Northern Hemisphere atmospheric CO2 observations, we found both detrended atmospheric CO2 growth rate (CGR) and CO2 seasonal-cycle amplitude (SCA) of 2015-2016 were much higher than that of other El Niño events. The simultaneous high CGR and SCA were unusual, because our analysis of long-term CO2 observations at Mauna Loa revealed a significantly negative correlation between CGR and SCA. Atmospheric inversions and terrestrial ecosystem models indicate strong northern land carbon uptake during spring but substantially reduced carbon uptake (or high emissions) during early autumn, which amplified SCA but also resulted in a small anomaly in annual carbon uptake of northern ecosystems in 2015-2016. This negative ecosystem carbon uptake anomaly in early autumn was primarily due to soil water deficits and more litter decomposition caused by enhanced spring productivity. Our study demonstrates a decoupling between seasonality and annual carbon cycle balance in northern ecosystems over 2015-2016, which is unprecedented in the past five decades of El Niño events.
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Affiliation(s)
- Kai Wang
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Xuhui Wang
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Shilong Piao
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China
- Key Laboratory of Alpine Ecology and Biodiversity, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China
- Center for Excellence in Tibetan Earth Science, Chinese Academy of Sciences, Beijing, China
| | - Frédéric Chevallier
- Laboratoire des Sciences du Climat et de l'Environnement, CEA CNRS UVSQ, Gif-sur-Yvette, France
| | - Jiafu Mao
- Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Xiaoying Shi
- Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | | | - Ana Bastos
- Department Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, CEA CNRS UVSQ, Gif-sur-Yvette, France
| | - Hao Xu
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Ralph F Keeling
- Scripps Institution of Oceanography, University of California, San Diego, La Jolla, CA, USA
| | - Stephen W Pacala
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
| | - Anping Chen
- Department of Biology and Graduate Degree Program in Ecology, Colorado State University, Fort Collins, CO, USA
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7
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Wei Y, Shrestha R, Pal S, Gerken T, Feng S, McNelis J, Singh D, Thornton MM, Boyer AG, Shook MA, Chen G, Baier BC, Barkley ZR, Barrick JD, Bennett JR, Browell EV, Campbell JF, Campbell LJ, Choi Y, Collins J, Dobler J, Eckl M, Fiehn A, Fried A, Digangi JP, Barton‐Grimley R, Halliday H, Klausner T, Kooi S, Kostinek J, Lauvaux T, Lin B, McGill MJ, Meadows B, Miles NL, Nehrir AR, Nowak JB, Obland M, O’Dell C, Fao RMP, Richardson SJ, Richter D, Roiger A, Sweeney C, Walega J, Weibring P, Williams CA, Yang MM, Zhou Y, Davis KJ. Atmospheric Carbon and Transport - America (ACT-America) Data Sets: Description, Management, and Delivery. EARTH AND SPACE SCIENCE (HOBOKEN, N.J.) 2021; 8:e2020EA001634. [PMID: 34435081 PMCID: PMC8365738 DOI: 10.1029/2020ea001634] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Revised: 04/19/2021] [Accepted: 05/09/2021] [Indexed: 06/13/2023]
Abstract
The ACT-America project is a NASA Earth Venture Suborbital-2 mission designed to study the transport and fluxes of greenhouse gases. The open and freely available ACT-America data sets provide airborne in situ measurements of atmospheric carbon dioxide, methane, trace gases, aerosols, clouds, and meteorological properties, airborne remote sensing measurements of aerosol backscatter, atmospheric boundary layer height and columnar content of atmospheric carbon dioxide, tower-based measurements, and modeled atmospheric mole fractions and regional carbon fluxes of greenhouse gases over the Central and Eastern United States. We conducted 121 research flights during five campaigns in four seasons during 2016-2019 over three regions of the US (Mid-Atlantic, Midwest and South) using two NASA research aircraft (B-200 and C-130). We performed three flight patterns (fair weather, frontal crossings, and OCO-2 underflights) and collected more than 1,140 h of airborne measurements via level-leg flights in the atmospheric boundary layer, lower, and upper free troposphere and vertical profiles spanning these altitudes. We also merged various airborne in situ measurements onto a common standard sampling interval, which brings coherence to the data, creates geolocated data products, and makes it much easier for the users to perform holistic analysis of the ACT-America data products. Here, we report on detailed information of data sets collected, the workflow for data sets including storage and processing of the quality controlled and quality assured harmonized observations, and their archival and formatting for users. Finally, we provide some important information on the dissemination of data products including metadata and highlights of applications of ACT-America data sets.
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Byrne B, Liu J, Bloom AA, Bowman KW, Butterfield Z, Joiner J, Keenan TF, Keppel‐Aleks G, Parazoo NC, Yin Y. Contrasting Regional Carbon Cycle Responses to Seasonal Climate Anomalies Across the East-West Divide of Temperate North America. GLOBAL BIOGEOCHEMICAL CYCLES 2020; 34:e2020GB006598. [PMID: 33281280 PMCID: PMC7685151 DOI: 10.1029/2020gb006598] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Revised: 08/20/2020] [Accepted: 10/11/2020] [Indexed: 05/19/2023]
Abstract
Across temperate North America, interannual variability (IAV) in gross primary production (GPP) and net ecosystem exchange (NEE) and their relationship with environmental drivers are poorly understood. Here, we examine IAV in GPP and NEE and their relationship to environmental drivers using two state-of-the-science flux products: NEE constrained by surface and space-based atmospheric CO2 measurements over 2010-2015 and satellite up-scaled GPP from FluxSat over 2001-2017. We show that the arid western half of temperate North America provides a larger contribution to IAV in GPP (104% of east) and NEE (127% of east) than the eastern half, in spite of smaller magnitude of annual mean GPP and NEE. This occurs because anomalies in western ecosystems are temporally coherent across the growing season leading to an amplification of GPP and NEE. In contrast, IAV in GPP and NEE in eastern ecosystems is dominated by seasonal compensation effects, associated with opposite responses to temperature anomalies in spring and summer. Terrestrial biosphere models in the MsTMIP ensemble generally capture these differences between eastern and western temperate North America, although there is considerable spread between models.
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Affiliation(s)
- B. Byrne
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | - J. Liu
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
- Division of Geological and Planetary SciencesCalifornia Institute of TechnologyPasadenaCAUSA
| | - A. A. Bloom
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | - K. W. Bowman
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
- Joint Institute for Regional Earth System Science and EngineeringUniversity of CaliforniaLos AngelesUSA
| | - Z. Butterfield
- Department of Climate and Space Sciences and EngineeringUniversity of MichiganAnn ArborMIUSA
| | - J. Joiner
- Laboratory of Atmospheric Chemistry and DynamicsNASA Goddard Space Flight CenterGreenbeltMDUSA
| | - T. F. Keenan
- Earth and Environmental Sciences AreaLawrence Berkeley National LaboratoryBerkeleyCAUSA
- Department of Environmental Science, Policy and ManagementUniversity of CaliforniaBerkeleyCAUSA
| | - G. Keppel‐Aleks
- Department of Climate and Space Sciences and EngineeringUniversity of MichiganAnn ArborMIUSA
| | - N. C. Parazoo
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | - Y. Yin
- Division of Geological and Planetary SciencesCalifornia Institute of TechnologyPasadenaCAUSA
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Determination of Region of Influence Obtained by Aircraft Vertical Profiles Using the Density of Trajectories from the HYSPLIT Model. ATMOSPHERE 2020. [DOI: 10.3390/atmos11101073] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Aircraft atmospheric profiling is a valuable technique for determining greenhouse gas fluxes at regional scales (104–106 km2). Here, we describe a new, simple method for estimating the surface influence of air samples that uses backward trajectories based on the Lagrangian model Hybrid Single-Particle Lagrangian Integrated Trajectory Model (HYSPLIT). We determined “regions of influence” on a quarterly basis between 2010 and 2018 for four aircraft vertical profile sites: SAN and ALF in the eastern Amazon, and RBA and TAB or TEF in the western Amazon. We evaluated regions of influence in terms of their relative sensitivity to areas inside and outside the Amazon and their total area inside the Amazon. Regions of influence varied by quarter and less so by year. In the first and fourth quarters, the contribution of the region of influence inside the Amazon was 83–93% for all sites, while in the second and third quarters, it was 57–75%. The interquarter differences are more evident in the eastern than in the western Amazon. Our analysis indicates that atmospheric profiles from the western sites are sensitive to 42–52.2% of the Amazon. In contrast, eastern Amazon sites are sensitive to only 10.9–25.3%. These results may help to spatially resolve the response of greenhouse gas emissions to climate variability over Amazon.
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Comparison of Regional Simulation of Biospheric CO2 Flux from the Updated Version of CarbonTracker Asia with FLUXCOM and Other Inversions over Asia. REMOTE SENSING 2020. [DOI: 10.3390/rs12010145] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
There are still large uncertainties in the estimates of net ecosystem exchange of CO2 (NEE) with atmosphere in Asia, particularly in the boreal and eastern part of temperate Asia. To understand these uncertainties, we assessed the CarbonTracker Asia (CTA2017) estimates of the spatial and temporal distributions of NEE through a comparison with FLUXCOM and the global inversion models from the Copernicus Atmospheric Monitoring Service (CAMS), Monitoring Atmospheric Composition and Climate (MACC), and Jena CarboScope in Asia, as well as examining the impact of the nesting approach on the optimized NEE flux during the 2001–2013 period. The long-term mean carbon uptake is reduced in Asia, which is −0.32 ± 0.22 PgC yr−1, whereas −0.58 ± 0.26 PgC yr−1 is shown from CT2017 (CarbonTracker global). The domain aggregated mean carbon uptake from CTA2017 is found to be lower by 23.8%, 44.8%, and 60.5% than CAMS, MACC, and Jena CarboScope, respectively. For example, both CTA2017 and CT2017 models captured the interannual variability (IAV) of the NEE flux with a different magnitude and this leads to divergent annual aggregated results. Differences in the estimated interannual variability of NEE in response to El Niño–Southern Oscillation (ENSO) may result from differences in the transport model resolutions. These inverse models’ results have a substantial difference compared to FLUXCOM, which was found to be −5.54 PgC yr−1. On the one hand, we showed that the large NEE discrepancies between both inversion models and FLUXCOM stem mostly from the tropical forests. On the other hand, CTA2017 exhibits a slightly better correlation with FLUXCOM over grass/shrub, fields/woods/savanna, and mixed forest than CT2017. The land cover inconsistency between CTA2017 and FLUXCOM is therefore one driver of the discrepancy in the NEE estimates. The diurnal averaged NEE flux between CTA2017 and FLUXCOM exhibits better agreement during the carbon uptake period than the carbon release period. Both CTA2017 and CT2017 revealed that the overall spatial patterns of the carbon sink and source are similar, but the magnitude varied with seasons and ecosystem types, which is mainly attributed to differences in the transport model resolutions. Our findings indicate that substantial inconsistencies in the inversions and FLUXCOM mainly emerge during the carbon uptake period and over tropical forests. The main problems are underrepresentation of FLUXCOM NEE estimates by limited eddy covariance flux measurements, the role of CO2 emissions from land use change not accounted for by FLUXCOM, sparseness of surface observations of CO2 concentrations used by the assimilation systems, and land cover inconsistency. This suggested that further scrutiny on the FLUXCOM and inverse estimates is most likely required. Such efforts will reduce inconsistencies across various NEE estimates over Asia, thus mitigating ecosystem-driven errors that propagate the global carbon budget. Moreover, this work also recommends further investigation on how the changes/updates made in CarbonTracker affect the interannual variability of the aggregate and spatial pattern of NEE flux in response to the ENSO effect over the region of interest.
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