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Joshi AP, Ghoshal PK, Chakraborty K, Sarma VVSS. Sea-surface pCO 2 maps for the Bay of Bengal based on advanced machine learning algorithms. Sci Data 2024; 11:384. [PMID: 38615101 PMCID: PMC11016078 DOI: 10.1038/s41597-024-03236-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Accepted: 04/08/2024] [Indexed: 04/15/2024] Open
Abstract
Lack of sufficient observations has been an impediment for understanding the spatial and temporal variability of sea-surface pCO2 for the Bay of Bengal (BoB). The limited number of observations into existing machine learning (ML) products from BoB often results in high prediction errors. This study develops climatological sea-surface pCO2 maps using a significant number of open and coastal ocean observations of pCO2 and associated variables regulating pCO2 variability in BoB. We employ four advanced ML algorithms to predict pCO2. We use the best ML model to produce a high-resolution climatological product (INCOIS-ReML). The comparison of INCOIS-ReML pCO2 with RAMA buoy-based sea-surface pCO2 observations indicates INCOIS-ReML's satisfactory performance. Further, the comparison of INCOIS-ReML pCO2 with existing ML products establishes the superiority of INCOIS-ReML. The high-resolution INCOIS-ReML greatly captures the spatial variability of pCO2 and associated air-sea CO2 flux compared to other ML products in the coastal BoB and the northern BoB.
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Affiliation(s)
- A P Joshi
- Indian National Centre for Ocean Information Services, Ministry of Earth Sciences, Hyderabad, India
| | - Prasanna Kanti Ghoshal
- Indian National Centre for Ocean Information Services, Ministry of Earth Sciences, Hyderabad, India
- Faculty of Ocean Science and Technology, Kerala University of Fisheries and Ocean Studies, Kochi, India
| | - Kunal Chakraborty
- Indian National Centre for Ocean Information Services, Ministry of Earth Sciences, Hyderabad, India.
| | - V V S S Sarma
- CSIR-National Institute of Oceanography, Visakhapatnam, India
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2
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Liu W, Niu Z, Feng X, Zhou W, Liang D, Lyu M, Wang G, Lu X, Liu L, Turnbull JC. Atmospheric CO 2 and 14CO 2 observations at the northern foot of the Qinling Mountains in China: Temporal characteristics and source quantification. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 920:170682. [PMID: 38325447 DOI: 10.1016/j.scitotenv.2024.170682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Revised: 01/26/2024] [Accepted: 02/02/2024] [Indexed: 02/09/2024]
Abstract
A two-year (March 2021 to February 2023) continuous atmospheric CO2 and a one-year regular atmospheric 14CO2 measurement records were measured at the northern foot of the Qinling Mountains in Xi'an, China, aiming to study the temporal characteristics of atmospheric CO2 and the contributions from the sources of fossil fuel CO2 (CO2ff) and biological CO2 (CO2bio) fluxes. The two-year mean CO2 mole fraction was 442.2 ± 16.3 ppm, with a yearly increase of 4.7 ppm (i.e., 1.1 %) during the two-year observations. Seasonal CO2 mole fractions were the highest in winter (452.1 ± 17.7 ppm) and the lowest in summer (433.5 ± 13.3 ppm), with the monthly CO2 levels peaking in January and troughing in June. Diurnal CO2 levels peaked at dawn (05:00-07:00) in spring, summer and autumn, and at 10:00 in winter. 14C analysis revealed that the excess CO2 (CO2ex, atmospheric CO2 minus background CO2) at this site was mainly from CO2ff emissions (67.0 ± 26.8 %), and CO2ff mole fractions were the highest in winter (20.6 ± 17.7 ppm). Local CO enhancement above the background mole fraction (ΔCO) was significantly (r = 0.74, p < 0.05) positively correlated with CO2ff in a one-year measurement, and ΔCO:CO2ff showed a ratio of 23 ± 6 ppb/ppm during summer and winter sampling days, much lower than previous measurements and suggesting an improvement in combustion efficiency over the last decade. CO2bio mole fractions also peaked in winter (14.2 ± 9.6 ppm), apparently due to biomass combustion and the lower and more stable wintertime atmospheric boundary layer. The negative CO2bio values in summer indicated that terrestrial vegetation of the Qinling Mountains had the potential to uptake atmospheric CO2 during the corresponding sampling days. This site is most sensitive to local emissions from Xi'an and to short distance transportation from the southern Qinling Mountains through the valleys.
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Affiliation(s)
- Wanyu Liu
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, China; Interdisciplinary Research Center of Earth Science Frontier, Beijing Normal University, Beijing 100875, China
| | - Zhenchuan Niu
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, China; Institute of Global Environmental Change, Xi'an Jiaotong University, Xi'an 710049, China; Open Studio for Oceanic-Continental Climate and Environment Changes, Pilot National Laboratory for Marine Science and Technology (Qingdao), Qingdao 266061, China; National Observation and Research Station of Regional Ecological Environment Change and Comprehensive Management in the Guanzhong Plain, China.
| | - Xue Feng
- Xi'an Institute for Innovative Earth Environment Research, Xi'an 710061, China
| | - Weijian Zhou
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, China; Open Studio for Oceanic-Continental Climate and Environment Changes, Pilot National Laboratory for Marine Science and Technology (Qingdao), Qingdao 266061, China; Shaanxi Provincial Key Laboratory of Accelerator Mass Spectrometry Technology and Application, Joint Xi'an AMS Center Between IEECAS and Xi'an Jiaotong University, Xi'an 710061, China
| | - Dan Liang
- Xi'an Institute for Innovative Earth Environment Research, Xi'an 710061, China
| | - Mengni Lyu
- Xi'an Institute for Innovative Earth Environment Research, Xi'an 710061, China
| | - Guowei Wang
- Xi'an Institute for Innovative Earth Environment Research, Xi'an 710061, China
| | - Xuefeng Lu
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, China; Shaanxi Provincial Key Laboratory of Accelerator Mass Spectrometry Technology and Application, Joint Xi'an AMS Center Between IEECAS and Xi'an Jiaotong University, Xi'an 710061, China
| | - Lin Liu
- Interdisciplinary Research Center of Earth Science Frontier, Beijing Normal University, Beijing 100875, China
| | - Jocelyn C Turnbull
- National Isotope Center, GNS Science, Lower Hutt 5040, New Zealand; CIRES, University of Colorado, Boulder, Colorado 80305, USA
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3
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Jiao K, Liu Z, Wang W, Yu K, Mcgrath MJ, Xu W. Carbon cycle responses to climate change across China's terrestrial ecosystem: Sensitivity and driving process. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 915:170053. [PMID: 38224891 DOI: 10.1016/j.scitotenv.2024.170053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Revised: 12/19/2023] [Accepted: 01/08/2024] [Indexed: 01/17/2024]
Abstract
Investigations into the carbon cycle and how it responds to climate change at the national scale are important for a comprehensive understanding of terrestrial carbon cycle and global change issues. Contributions of carbon fluxes to the terrestrial sink and the effects on climate change are still not fully understood. In this study, we aimed to explore the relationship between ecosystem production (GPP/SIF/NDVI) and net ecosystem carbon exchange (NEE) and to investigate the sensitivity of carbon fluxes to climate change at different spatio-temporal scales. Furthermore, we sought to delve into the carbon cycle processes driven by climate stress in China since the beginning of the 21st century. To achieve these objectives, we employed correlation and sensitivity analysis techniques, utilizing a wide range of data sources including ground-based observations, remote sensing observations, atmospheric inversions, machine learning, and model simulations. Our findings indicate that NEE in most arid regions of China is primarily driven by ecosystem production. Climate variations have a greater influence on ecosystem production than respiration. Warming has negatively impacted ecosystem production in Northeast China, as well as in subtropical and tropical regions. Conversely, increased precipitation has strengthened the terrestrial carbon sink, particularly in the northern cool and dry areas. We also found that ecosystem respiration exhibits heightened sensitivity to warming in southern China. Moreover, our analysis revealed that the control of terrestrial carbon cycle by ecosystem production gradually weakens from cold/arid areas to warm/humid areas. We identified distinct temperature thresholds (ranging from 10.5 to 13.7 °C) and precipitation thresholds (approximately 1400 mm yr-1) for the transition from production-dominated to respiration-dominated processes. Our study provides valuable insights into the complex relationship between climate change and carbon cycle in China.
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Affiliation(s)
- Kewei Jiao
- CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Science, Shenyang 110016, China; Key Laboratory of Terrestrial Ecosystem Carbon Neutrality, Liaoning Province, Shenyang 110016, China
| | - Zhihua Liu
- CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Science, Shenyang 110016, China; Key Laboratory of Terrestrial Ecosystem Carbon Neutrality, Liaoning Province, Shenyang 110016, China.
| | - Wenjuan Wang
- Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China.
| | - Kailiang Yu
- High Meadows Environmental Institute, Princeton University, Princeton, NJ 08544, USA
| | - Matthew Joseph Mcgrath
- Laboratoire des Sciences du Climat et de l'Environnement, UMR 8212 CEA-CNRS-UVSQ, Gif-sur-Yvette, France
| | - Wenru Xu
- CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Science, Shenyang 110016, China; Key Laboratory of Terrestrial Ecosystem Carbon Neutrality, Liaoning Province, Shenyang 110016, China
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4
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Jin Y, Keeling RF, Stephens BB, Long MC, Patra PK, Rödenbeck C, Morgan EJ, Kort EA, Sweeney C. Improved atmospheric constraints on Southern Ocean CO 2 exchange. Proc Natl Acad Sci U S A 2024; 121:e2309333121. [PMID: 38289951 PMCID: PMC10861854 DOI: 10.1073/pnas.2309333121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 12/19/2023] [Indexed: 02/01/2024] Open
Abstract
We present improved estimates of air-sea CO2 exchange over three latitude bands of the Southern Ocean using atmospheric CO2 measurements from global airborne campaigns and an atmospheric 4-box inverse model based on a mass-indexed isentropic coordinate (Mθe). These flux estimates show two features not clearly resolved in previous estimates based on inverting surface CO2 measurements: a weak winter-time outgassing in the polar region and a sharp phase transition of the seasonal flux cycles between polar/subpolar and subtropical regions. The estimates suggest much stronger summer-time uptake in the polar/subpolar regions than estimates derived through neural-network interpolation of pCO2 data obtained with profiling floats but somewhat weaker uptake than a recent study by Long et al. [Science 374, 1275-1280 (2021)], who used the same airborne data and multiple atmospheric transport models (ATMs) to constrain surface fluxes. Our study also uses moist static energy (MSE) budgets from reanalyses to show that most ATMs tend to have excessive diabatic mixing (transport across moist isentrope, θe, or Mθe surfaces) at high southern latitudes in the austral summer, which leads to biases in estimates of air-sea CO2 exchange. Furthermore, we show that the MSE-based constraint is consistent with an independent constraint on atmospheric mixing based on combining airborne and surface CO2 observations.
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Affiliation(s)
- Yuming Jin
- Geosciences Research Division, Scripps Institution of Oceanography, University of California, San Diego, La Jolla, CA92093
| | - Ralph F. Keeling
- Geosciences Research Division, Scripps Institution of Oceanography, University of California, San Diego, La Jolla, CA92093
| | - Britton B. Stephens
- Earth Observing Laboratory, National Center for Atmospheric Research, Boulder, CO80307
| | - Matthew C. Long
- Climate and Global Dynamics Laboratory, National Center for Atmospheric Research, Boulder, CO80307
| | - Prabir K. Patra
- Research Institute for Global Change, Japan Agency for Marine-Earth Science and Technology, Yokohama236-0001, Japan
| | | | - Eric J. Morgan
- Geosciences Research Division, Scripps Institution of Oceanography, University of California, San Diego, La Jolla, CA92093
| | - Eric A. Kort
- Department of Atmospheric, Oceanic and Space Sciences, University of Michigan, Ann Arbor, MI48109
| | - Colm Sweeney
- Global Monitoring Laboratory, National Oceanic and Atmospheric Administration, Boulder, CO80309
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5
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Fernández-Martínez M, Peñuelas J, Chevallier F, Ciais P, Obersteiner M, Rödenbeck C, Sardans J, Vicca S, Yang H, Sitch S, Friedlingstein P, Arora VK, Goll DS, Jain AK, Lombardozzi DL, McGuire PC, Janssens IA. Diagnosing destabilization risk in global land carbon sinks. Nature 2023; 615:848-853. [PMID: 36813960 DOI: 10.1038/s41586-023-05725-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Accepted: 01/11/2023] [Indexed: 02/24/2023]
Abstract
Global net land carbon uptake or net biome production (NBP) has increased during recent decades1. Whether its temporal variability and autocorrelation have changed during this period, however, remains elusive, even though an increase in both could indicate an increased potential for a destabilized carbon sink2,3. Here, we investigate the trends and controls of net terrestrial carbon uptake and its temporal variability and autocorrelation from 1981 to 2018 using two atmospheric-inversion models, the amplitude of the seasonal cycle of atmospheric CO2 concentration derived from nine monitoring stations distributed across the Pacific Ocean and dynamic global vegetation models. We find that annual NBP and its interdecadal variability increased globally whereas temporal autocorrelation decreased. We observe a separation of regions characterized by increasingly variable NBP, associated with warm regions and increasingly variable temperatures, lower and weaker positive trends in NBP and regions where NBP became stronger and less variable. Plant species richness presented a concave-down parabolic spatial relationship with NBP and its variability at the global scale whereas nitrogen deposition generally increased NBP. Increasing temperature and its increasing variability appear as the most important drivers of declining and increasingly variable NBP. Our results show increasing variability of NBP regionally that can be mostly attributed to climate change and that may point to destabilization of the coupled carbon-climate system.
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Affiliation(s)
- Marcos Fernández-Martínez
- PLECO (Plants and Ecosystems), Department of Biology, University of Antwerp, Wilrijk, Belgium.
- CREAF, Campus de Bellaterra (UAB), Cerdanyola del Vallès, Spain.
- BEECA-UB, Department of Evolutionary Biology, Ecology and Environmental Sciences, University of Barcelona, Barcelona, Spain.
| | - Josep Peñuelas
- CREAF, Campus de Bellaterra (UAB), Cerdanyola del Vallès, Spain
- CSIC, Global Ecology Unit, CREAF-CSIC-UAB, Bellaterra, Barcelona, Spain
| | - Frederic Chevallier
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Michael Obersteiner
- International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria
- School of Geography and the Environment, University of Oxford, Oxford, UK
| | - Christian Rödenbeck
- Department of Biogeochmical Systems, Max Planck Institute for Biogeochemistry, Jena, Germany
| | - Jordi Sardans
- CREAF, Campus de Bellaterra (UAB), Cerdanyola del Vallès, Spain
- CSIC, Global Ecology Unit, CREAF-CSIC-UAB, Bellaterra, Barcelona, Spain
| | - Sara Vicca
- PLECO (Plants and Ecosystems), Department of Biology, University of Antwerp, Wilrijk, Belgium
| | - Hui Yang
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Stephen Sitch
- College of Life and Environmental Sciences, University of Exeter, Exeter, UK
| | - Pierre Friedlingstein
- College of Engineering, Mathematics, and Physical Sciences, University of Exeter, Exeter, UK
| | - Vivek K Arora
- Canadian Centre for Climate Modelling and Analysis, Climate Research Division, Environment and Climate Change Canada, Victoria, BC, Canada
| | - Daniel S Goll
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Atul K Jain
- Department of Atmospheric Sciences, University of Illinois, Urbana, IL, USA
| | - Danica L Lombardozzi
- Climate and Global Dynamics Laboratory, National Center for Atmospheric Research, Boulder, CO, USA
| | - Patrick C McGuire
- Department of Meteorology, Department of Geography & Environmental Science, National Centre for Atmospheric Science, University of Reading, Reading, UK
| | - Ivan A Janssens
- PLECO (Plants and Ecosystems), Department of Biology, University of Antwerp, Wilrijk, Belgium
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6
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Liu Z, Kimball JS, Ballantyne AP, Parazoo NC, Wang WJ, Bastos A, Madani N, Natali SM, Watts JD, Rogers BM, Ciais P, Yu K, Virkkala AM, Chevallier F, Peters W, Patra PK, Chandra N. Respiratory loss during late-growing season determines the net carbon dioxide sink in northern permafrost regions. Nat Commun 2022; 13:5626. [PMID: 36163194 PMCID: PMC9512808 DOI: 10.1038/s41467-022-33293-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Accepted: 09/12/2022] [Indexed: 11/20/2022] Open
Abstract
Warming of northern high latitude regions (NHL, > 50 °N) has increased both photosynthesis and respiration which results in considerable uncertainty regarding the net carbon dioxide (CO2) balance of NHL ecosystems. Using estimates constrained from atmospheric observations from 1980 to 2017, we find that the increasing trends of net CO2 uptake in the early-growing season are of similar magnitude across the tree cover gradient in the NHL. However, the trend of respiratory CO2 loss during late-growing season increases significantly with increasing tree cover, offsetting a larger fraction of photosynthetic CO2 uptake, and thus resulting in a slower rate of increasing annual net CO2 uptake in areas with higher tree cover, especially in central and southern boreal forest regions. The magnitude of this seasonal compensation effect explains the difference in net CO2 uptake trends along the NHL vegetation- permafrost gradient. Such seasonal compensation dynamics are not captured by dynamic global vegetation models, which simulate weaker respiration control on carbon exchange during the late-growing season, and thus calls into question projections of increasing net CO2 uptake as high latitude ecosystems respond to warming climate conditions. The northern high latitude permafrost region has been an important contributor to the carbon sink since the 1980s. A new study finds that as tree cover increases, respiratory CO2 loss during late-growing season offsets photosynthetic CO2 uptake and leads to a slower rate of increasing annual net CO2 uptake.
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Affiliation(s)
- Zhihua Liu
- Numerical Terradynamic Simulation Group, WA Franke College of Forestry and Conservation, University of Montana, Missoula, MT, USA. .,CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, Liaoning, China.
| | - John S Kimball
- Numerical Terradynamic Simulation Group, WA Franke College of Forestry and Conservation, University of Montana, Missoula, MT, USA. .,Department of Ecosystem and Conservation Sciences, University of Montana, Missoula, MT, USA.
| | - Ashley P Ballantyne
- Department of Ecosystem and Conservation Sciences, University of Montana, Missoula, MT, USA. .,Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France.
| | - Nicholas C Parazoo
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| | - Wen J Wang
- Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, Changchun, Jilin, China.
| | - Ana Bastos
- Max Planck Institute for Biogeochemistry, Department of Biogeochemical Integration, Jena, Germany
| | - Nima Madani
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| | | | | | | | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Kailiang Yu
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
| | | | - Frederic Chevallier
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Wouter Peters
- Meteorology and Air Quality Group, Wageningen University and Research, Wageningen, the Netherlands.,University, Centre for Isotope Research, Groningen, the Netherlands
| | - Prabir K Patra
- Research Institute for Global Change, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokohama, Japan
| | - Naveen Chandra
- Research Institute for Global Change, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokohama, Japan
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7
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Walley S, Pal S, Campbell JF, Dobler J, Bell E, Weir B, Feng S, Lauvaux T, Baker D, Blume N, Erxleben W, Fan T, Lin B, McGregor D, Obland MD, O'Dell C, Davis KJ. Airborne Lidar Measurements of XCO 2 in Synoptically Active Environment and Associated Comparisons With Numerical Simulations. JOURNAL OF GEOPHYSICAL RESEARCH. ATMOSPHERES : JGR 2022; 127:e2021JD035664. [PMID: 36582815 PMCID: PMC9786724 DOI: 10.1029/2021jd035664] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Revised: 06/29/2022] [Accepted: 08/07/2022] [Indexed: 06/17/2023]
Abstract
Frontal boundaries have been shown to cause large changes in CO2 mole-fractions, but clouds and the complex vertical structure of fronts make these gradients difficult to observe. It remains unclear how the column average CO2 dry air mole-fraction (XCO2) changes spatially across fronts, and how well airborne lidar observations, data assimilation systems, and numerical models without assimilation capture XCO2 frontal contrasts (ΔXCO2, i.e., warm minus cold sector average of XCO2). We demonstrated the potential of airborne Multifunctional Fiber Laser Lidar (MFLL) measurements in heterogeneous weather conditions (i.e., frontal environment) to investigate the ΔXCO2 during four seasonal field campaigns of the Atmospheric Carbon and Transport-America (ACT-America) mission. Most frontal cases in summer (winter) reveal higher (lower) XCO2 in the warm (cold) sector than in the cold (warm) sector. During the transitional seasons (spring and fall), no clear signal in ΔXCO2 was observed. Intercomparison among the MFLL, assimilated fields from NASA's Global Modeling and Assimilation Office (GMAO), and simulations from the Weather Research and Forecasting--Chemistry (WRF-Chem) showed that (a) all products had a similar sign of ΔXCO2 though with different levels of agreement in ΔXCO2 magnitudes among seasons; (b) ΔXCO2 in summer decreases with altitude; and (c) significant challenges remain in observing and simulating XCO2 frontal contrasts. A linear regression analyses between ΔXCO2 for MFLL versus GMAO, and MFLL versus WRF-Chem for summer-2016 cases yielded a correlation coefficient of 0.95 and 0.88, respectively. The reported ΔXCO2 variability among four seasons provide guidance to the spatial structures of XCO2 transport errors in models and satellite measurements of XCO2 in synoptically-active weather systems.
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Affiliation(s)
- Samantha Walley
- Department of GeosciencesAtmospheric Science DivisionTexas Tech UniversityLubbockTXUSA
| | - Sandip Pal
- Department of GeosciencesAtmospheric Science DivisionTexas Tech UniversityLubbockTXUSA
| | | | | | - Emily Bell
- Colorado State UniversityFort CollinsCOUSA
| | - Brad Weir
- Universities Space Research AssociationColumbiaMDUSA
- NASA Goddard Space Flight CenterGreenbeltMDUSA
| | - Sha Feng
- Atmospheric Sciences and Global Change DivisionPacific Northwest National LaboratoryRichlandWAUSA
- Department of Meteorology and Atmospheric ScienceThe Pennsylvania State UniversityUniversity ParkPAUSA
| | - Thomas Lauvaux
- Department of Meteorology and Atmospheric ScienceThe Pennsylvania State UniversityUniversity ParkPAUSA
- LSCE ‐ IPSLCEA SaclaySaclayFrance
| | | | | | | | | | - Bing Lin
- NASA Langley Research Center (LaRC)HamptonVAUSA
| | | | | | | | - Kenneth J. Davis
- Atmospheric Sciences and Global Change DivisionPacific Northwest National LaboratoryRichlandWAUSA
- Earth and Environmental Systems InstituteThe Pennsylvania State UniversityUniversity ParkPAUSA
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8
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Che K, Liu Y, Cai Z, Yang D, Wang H, Ji D, Yang Y, Wang P. Characterization of Regional Combustion Efficiency using ΔXCO: ΔXCO 2 Observed by a Portable Fourier-Transform Spectrometer at an Urban Site in Beijing. ADVANCES IN ATMOSPHERIC SCIENCES 2022; 39:1299-1315. [PMID: 35578720 PMCID: PMC9093556 DOI: 10.1007/s00376-022-1247-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 12/17/2021] [Accepted: 01/05/2022] [Indexed: 06/15/2023]
Abstract
Measurements of column-averaged dry-air mole fractions of carbon dioxide and carbon monoxide, CO2 (XCO2) and CO (XCO), were performed throughout 2019 at an urban site in Beijing using a compact Fourier Transform Spectrometer (FTS) EM27/SUN. This data set is used to assess the characteristics of combustion-related CO2 emissions of urban Beijing by analyzing the correlated daily anomalies of XCO and XCO2 (e.g., ΔXCO and ΔXCO2). The EM27/SUN measurements were calibrated to a 125HR-FTS at the Xianghe station by an extra EM27/SUN instrument transferred between two sites. The ratio of ΔXCO over ΔXCO2 (ΔXCO:ΔXCO2) is used to estimate the combustion efficiency in the Beijing region. A high correlation coefficient (0.86) between ΔXCO and ΔXCO2 is observed. The CO:CO2 emission ratio estimated from inventories is higher than the observed ΔXCO:ΔXCO2 (10.46 ± 0.11 ppb ppm-1) by 42.54%-101.15%, indicating an underestimation in combustion efficiency in the inventories. Daily ΔXCO:ΔXCO2 are influenced by transportation governed by weather conditions, except for days in summer when the correlation is low due to the terrestrial biotic activity. By convolving the column footprint [ppm (µmol m-2 s-1)-1] generated by the Weather Research and Forecasting-X-Stochastic Time-Inverted Lagrangian Transport models (WRF-X-STILT) with two fossil-fuel emission inventories (the Multi-resolution Emission Inventory for China (MEIC) and the Peking University (PKU) inventory), the observed enhancements of CO2 and CO were used to evaluate the regional emissions. The CO2 emissions appear to be underestimated by 11% and 49% for the MEIC and PKU inventories, respectively, while CO emissions were overestimated by MEIC (30%) and PKU (35%) in the Beijing area.
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Affiliation(s)
- Ke Che
- Key Laboratory of Middle Atmosphere and Global Environment Observation, Institute of Atmospheric Physics, Chinese Academy of Science, Beijing, 100029 China
- Carbon Neutrality Research Center, Institute of Atmospheric Physics, Chinese Academy of Science, Beijing, 100029 China
- University of Chinese Academy of Science, Beijing, 100049 China
| | - Yi Liu
- Carbon Neutrality Research Center, Institute of Atmospheric Physics, Chinese Academy of Science, Beijing, 100029 China
- University of Chinese Academy of Science, Beijing, 100049 China
| | - Zhaonan Cai
- Carbon Neutrality Research Center, Institute of Atmospheric Physics, Chinese Academy of Science, Beijing, 100029 China
| | - Dongxu Yang
- Carbon Neutrality Research Center, Institute of Atmospheric Physics, Chinese Academy of Science, Beijing, 100029 China
| | - Haibo Wang
- Key Laboratory of Middle Atmosphere and Global Environment Observation, Institute of Atmospheric Physics, Chinese Academy of Science, Beijing, 100029 China
- University of Chinese Academy of Science, Beijing, 100049 China
| | - Denghui Ji
- Key Laboratory of Middle Atmosphere and Global Environment Observation, Institute of Atmospheric Physics, Chinese Academy of Science, Beijing, 100029 China
- University of Chinese Academy of Science, Beijing, 100049 China
| | - Yang Yang
- Key Laboratory of Middle Atmosphere and Global Environment Observation, Institute of Atmospheric Physics, Chinese Academy of Science, Beijing, 100029 China
- University of Chinese Academy of Science, Beijing, 100049 China
| | - Pucai Wang
- Carbon Neutrality Research Center, Institute of Atmospheric Physics, Chinese Academy of Science, Beijing, 100029 China
- University of Chinese Academy of Science, Beijing, 100049 China
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9
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Agustí-Panareda A, McNorton J, Balsamo G, Baier BC, Bousserez N, Boussetta S, Brunner D, Chevallier F, Choulga M, Diamantakis M, Engelen R, Flemming J, Granier C, Guevara M, Denier van der Gon H, Elguindi N, Haussaire JM, Jung M, Janssens-Maenhout G, Kivi R, Massart S, Papale D, Parrington M, Razinger M, Sweeney C, Vermeulen A, Walther S. Global nature run data with realistic high-resolution carbon weather for the year of the Paris Agreement. Sci Data 2022; 9:160. [PMID: 35410420 PMCID: PMC9001646 DOI: 10.1038/s41597-022-01228-2] [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: 03/26/2021] [Accepted: 02/21/2022] [Indexed: 11/13/2022] Open
Abstract
The CO2 Human Emissions project has generated realistic high-resolution 9 km global simulations for atmospheric carbon tracers referred to as nature runs to foster carbon-cycle research applications with current and planned satellite missions, as well as the surge of in situ observations. Realistic atmospheric CO2, CH4 and CO fields can provide a reference for assessing the impact of proposed designs of new satellites and in situ networks and to study atmospheric variability of the tracers modulated by the weather. The simulations spanning 2015 are based on the Copernicus Atmosphere Monitoring Service forecasts at the European Centre for Medium Range Weather Forecasts, with improvements in various model components and input data such as anthropogenic emissions, in preparation of a CO2 Monitoring and Verification Support system. The relative contribution of different emissions and natural fluxes towards observed atmospheric variability is diagnosed by additional tagged tracers in the simulations. The evaluation of such high-resolution model simulations can be used to identify model deficiencies and guide further model improvements. Measurement(s) | atmospheric carbon dioxide, methane and carbon monoxide | Technology Type(s) | numerical simulation | Factor Type(s) | None | Sample Characteristic - Organism | long-lived greenhouse gases | Sample Characteristic - Environment | atmosphere | Sample Characteristic - Location | global atmosphere |
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10
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Halder S, Tiwari YK, Valsala V, Sijikumar S, Janardanan R, Maksyutov S. Benefits of satellite XCO 2 and newly proposed atmospheric CO 2 observation network over India in constraining regional CO 2 fluxes. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 812:151508. [PMID: 34762957 DOI: 10.1016/j.scitotenv.2021.151508] [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: 07/14/2021] [Revised: 10/13/2021] [Accepted: 11/03/2021] [Indexed: 06/13/2023]
Abstract
Top-down modeling estimates are among the most reliable information available on the CO2 fluxes of the earth system. The inadequate coverage of CO2 observing stations over the tropical regions adds a limitation to this estimate, especially when the satellite XCO2 is strictly screened for cloud contamination, aerosol, dust, etc. In this study, we investigated the potential benefit of a global ground-based observing station network, 17 newly proposed stations over India, and global satellite XCO2 in reducing the uncertainty of terrestrial biospheric fluxes of Tropical Asia-Eurasia in TransCom cyclo-stationary inversion. The data from selected 80 global ground-based CO2 observation stations, together with two additional stations from India (i.e., Cape Rama and Sinhagad) and satellite XCO2, helps to reduce the temperate Eurasian terrestrial flux uncertainty by 23.8%, 26.4%, and 36.2%, respectively. This further improved to 54.7% by adding the newly proposed stations over India into the inversion. By separating the Indian sub-continent from temperate Eurasia (as inspired by the heterogeneity in the terrestrial ecosystems, prevailing meteorological conditions, and the orography of this vast region), the inversion evinces the capacity of existing CO2 observations to reduce the Indian terrestrial flux uncertainty by 20.5%. The largest benefit (70% reduction of annual mean uncertainty) for estimating Indian terrestrial fluxes could be achieved by combining these global observations with data from the newly proposed stations over India. The existing two stations from India suggest Temperate Eurasia as a mild source of CO2 (0.33 ± 0.57 Pg C yr-1), albeit with prominent anthropogenic influences visible in these two stations during the dry seasons. This implies that the proposed new stations should be cautiously placed to avoid such effects. The study also finds that the newly proposed stations over India also have an impact in constraining nearby oceanic CO2 fluxes.
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Affiliation(s)
- Santanu Halder
- Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Pune, India; Department of Atmospheric and Space Sciences, Savitribai Phule Pune University, Pune, India
| | - Yogesh K Tiwari
- Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Pune, India; Department of Atmospheric and Space Sciences, Savitribai Phule Pune University, Pune, India.
| | - Vinu Valsala
- Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Pune, India; Department of Atmospheric and Space Sciences, Savitribai Phule Pune University, Pune, India
| | - S Sijikumar
- Space Physics Laboratory, Vikram Sarabhai Space Centre, Thiruvananthapuram, India
| | - Rajesh Janardanan
- Satellite Observation Center, Earth System Division, National Institute for Environmental Studies, Tsukuba, Japan
| | - Shamil Maksyutov
- Satellite Observation Center, Earth System Division, National Institute for Environmental Studies, Tsukuba, Japan
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11
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Long MC, Stephens BB, McKain K, Sweeney C, Keeling RF, Kort EA, Morgan EJ, Bent JD, Chandra N, Chevallier F, Commane R, Daube BC, Krummel PB, Loh Z, Luijkx IT, Munro D, Patra P, Peters W, Ramonet M, Rödenbeck C, Stavert A, Tans P, Wofsy SC. Strong Southern Ocean carbon uptake evident in airborne observations. Science 2021; 374:1275-1280. [PMID: 34855495 DOI: 10.1126/science.abi4355] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
[Figure: see text].
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Affiliation(s)
- Matthew C Long
- National Center for Atmospheric Research, Boulder, CO, USA
| | | | - Kathryn McKain
- Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO, USA.,Global Monitoring Laboratory, National Oceanic and Atmospheric Administration, Boulder, CO, USA
| | - Colm Sweeney
- Global Monitoring Laboratory, National Oceanic and Atmospheric Administration, Boulder, CO, USA
| | - Ralph F Keeling
- Scripps Institution of Oceanography, University of California, San Diego, La Jolla, CA, USA
| | - Eric A Kort
- Department of Climate and Space Sciences and Engineering, University of Michigan, Ann Arbor, MI, USA
| | - Eric J Morgan
- Scripps Institution of Oceanography, University of California, San Diego, La Jolla, CA, USA
| | - Jonathan D Bent
- National Center for Atmospheric Research, Boulder, CO, USA.,Scripps Institution of Oceanography, University of California, San Diego, La Jolla, CA, USA
| | - Naveen Chandra
- National Institute of Environmental Studies, Tsukuba, Japan
| | - Frederic Chevallier
- Laboratoire des Sciences du Climat et de l'Environnement, IPSL-LSCE, CEA-CNRS-UVSQ, UMR8212 91191, France
| | - Róisín Commane
- Department of Earth and Environmental Sciences, Lamont-Doherty Earth Observatory of Columbia University, Palisades, NY, USA
| | - Bruce C Daube
- Department of Earth and Planetary Sciences, Harvard University, Cambridge, MA, USA
| | - Paul B Krummel
- Climate Science Centre, CSIRO Oceans and Atmosphere, Aspendale, Victoria, Australia
| | - Zoë Loh
- Climate Science Centre, CSIRO Oceans and Atmosphere, Aspendale, Victoria, Australia
| | - Ingrid T Luijkx
- Department of Meteorology and Air Quality, Environmental Sciences Group, Wageningen University, Netherlands
| | - David Munro
- Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO, USA.,Global Monitoring Laboratory, National Oceanic and Atmospheric Administration, Boulder, CO, USA
| | - Prabir Patra
- Research Institute for Global Change, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokohama, Japan
| | - Wouter Peters
- Department of Meteorology and Air Quality, Environmental Sciences Group, Wageningen University, Netherlands.,Centre for Isotope Research, University of Groningen, Groningen, Netherlands
| | - Michel Ramonet
- Laboratoire des Sciences du Climat et de l'Environnement, IPSL-LSCE, CEA-CNRS-UVSQ, UMR8212 91191, France
| | | | - Ann Stavert
- Climate Science Centre, CSIRO Oceans and Atmosphere, Aspendale, Victoria, Australia
| | - Pieter Tans
- Global Monitoring Laboratory, National Oceanic and Atmospheric Administration, Boulder, CO, USA
| | - Steven C Wofsy
- Department of Earth and Planetary Sciences, Harvard University, Cambridge, MA, USA.,Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
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12
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Zhu L, Ciais P, Bastos A, Ballantyne AP, Chevallier F, Gasser T, Kondo M, Pongratz J, Rödenbeck C, Li W. Decadal variability in land carbon sink efficiency. CARBON BALANCE AND MANAGEMENT 2021; 16:15. [PMID: 33973052 PMCID: PMC8112069 DOI: 10.1186/s13021-021-00178-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Accepted: 04/30/2021] [Indexed: 06/12/2023]
Abstract
BACKGROUND The climate mitigation target of limiting the temperature increase below 2 °C above the pre-industrial levels requires the efforts from all countries. Tracking the trajectory of the land carbon sink efficiency is thus crucial to evaluate the nationally determined contributions (NDCs). Here, we define the instantaneous land sink efficiency as the ratio of natural land carbon sinks to emissions from fossil fuel and land-use and land-cover change with a value of 1 indicating carbon neutrality to track its temporal dynamics in the past decades. RESULTS Land sink efficiency has been decreasing during 1957-1990 because of the increased emissions from fossil fuel. After the effect of the Mt. Pinatubo eruption diminished (after 1994), the land sink efficiency firstly increased before 2009 and then began to decrease again after 2009. This reversal around 2009 is mostly attributed to changes in land sinks in tropical regions in response to climate variations. CONCLUSIONS The decreasing trend of land sink efficiency in recent years reveals greater challenges in climate change mitigation, and that climate impacts on land carbon sinks must be accurately quantified to assess the effectiveness of regional scale climate mitigation policies.
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Affiliation(s)
- Lei Zhu
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, China
- Joint Center for Global Change Studies, Beijing, China
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Ana Bastos
- Department of Geography, Ludwig-Maximilians Universität, München, Germany
- Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany
| | - Ashley P Ballantyne
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
- Department of Ecosystem and Conservation Sciences, WA Franke College of Forestry and Conservation, University of Montana, Missoula, MT, USA
| | - Frederic Chevallier
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Thomas Gasser
- International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria
| | - Masayuki Kondo
- Institute for Space-Earth Environmental Research, Nagoya University, Nagoya, Japan
- Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba, Japan
| | - Julia Pongratz
- Department of Geography, Ludwig-Maximilians Universität, München, Germany
- Max Planck Institute for Meteorology, Hamburg, Germany
| | - Christian Rödenbeck
- Department of Biogeochmical Systems, Max Planck Institute for Biogeochemistry, Jena, Germany
| | - Wei Li
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, China.
- Joint Center for Global Change Studies, Beijing, China.
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13
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Jones MW, Andrew RM, Peters GP, Janssens-Maenhout G, De-Gol AJ, Ciais P, Patra PK, Chevallier F, Le Quéré C. Gridded fossil CO 2 emissions and related O 2 combustion consistent with national inventories 1959-2018. Sci Data 2021; 8:2. [PMID: 33414478 PMCID: PMC7791114 DOI: 10.1038/s41597-020-00779-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Accepted: 11/24/2020] [Indexed: 01/29/2023] Open
Abstract
Quantification of CO2 fluxes at the Earth's surface is required to evaluate the causes and drivers of observed increases in atmospheric CO2 concentrations. Atmospheric inversion models disaggregate observed variations in atmospheric CO2 concentration to variability in CO2 emissions and sinks. They require prior constraints fossil CO2 emissions. Here we describe GCP-GridFED (version 2019.1), a gridded fossil emissions dataset that is consistent with the national CO2 emissions reported by the Global Carbon Project (GCP). GCP-GridFEDv2019.1 provides monthly fossil CO2 emissions estimates for the period 1959-2018 at a spatial resolution of 0.1°. Estimates are provided separately for oil, coal and natural gas, for mixed international bunker fuels, and for the calcination of limestone during cement production. GCP-GridFED also includes gridded estimates of O2 uptake based on oxidative ratios for oil, coal and natural gas. It will be updated annually and made available for atmospheric inversions contributing to GCP global carbon budget assessments, thus aligning the prior constraints on top-down fossil CO2 emissions with the bottom-up estimates compiled by the GCP.
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Affiliation(s)
- Matthew W Jones
- Tyndall Centre for Climate Change Research, School of Environmental Sciences, University of East Anglia, Norwich, NR4 7TJ, UK.
| | - Robbie M Andrew
- CICERO Center for International Climate Research, Oslo, 0349, Norway
| | - Glen P Peters
- CICERO Center for International Climate Research, Oslo, 0349, Norway
| | - Greet Janssens-Maenhout
- European Commission, Joint Research Centre (JRC), Via E. Fermi 2749 (T.P. 123), 21027, Ispra, Varese, Italy
| | - Anthony J De-Gol
- Tyndall Centre for Climate Change Research, School of Environmental Sciences, University of East Anglia, Norwich, NR4 7TJ, UK
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, Institut Pierre-Simon Laplace, CEA-CNRS-UVSQ, CE Orme des Merisiers, 91191, Gif sur Yvette, France
| | - Prabir K Patra
- Research Institute for Global Change, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokohama, 236 0001, Japan
| | - Frederic Chevallier
- Laboratoire des Sciences du Climat et de l'Environnement, Institut Pierre-Simon Laplace, CEA-CNRS-UVSQ, CE Orme des Merisiers, 91191, Gif sur Yvette, France
| | - Corinne Le Quéré
- Tyndall Centre for Climate Change Research, School of Environmental Sciences, University of East Anglia, Norwich, NR4 7TJ, UK
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14
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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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15
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Gelati E, Zajac Z, Ceglar A, Bassu S, Bisselink B, Adamovic M, Bernhard J, Malagó A, Pastori M, Bouraoui F, de Roo A. Assessing groundwater irrigation sustainability in the Euro-Mediterranean region with an integrated agro-hydrologic model. ADVANCES IN SCIENCE AND RESEARCH 2020. [DOI: 10.5194/asr-17-227-2020] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022] Open
Abstract
Abstract. We assess the sustainability of groundwater irrigation in the Euro-Mediterranean region. After analysing the available data on groundwater irrigation, we identify areas where irrigation causes groundwater depletion. To prevent the latter, we experiment with guidelines to restrict groundwater irrigation to sustainable levels, simulating beneficial and detrimental impacts in terms of improved environmental flow conditions and crop yield losses. To carry out these analyses, we apply the integrated model of water resources, irrigation and crop production
LISFLOOD-EPIC. Crop growth is simulated accounting for atmospheric conditions and abiotic stress factors, including transpiration deficit.
Four irrigation methods are modelled: drip, sprinkler, and intermittent and permanent flooding. Hydrologic and agricultural modules are dynamically coupled at the daily time scale through soil moisture, plant water uptake, and irrigation water abstraction and application. Water abstractions of other sectors are simulated based on requirement data. Water may be withdrawn from groundwater, rivers, lakes and reservoirs. As groundwater is abstracted to buffer the effects of drought, we use groundwater depletion to detect unsustainable water exploitation. We characterise reported data of annual groundwater abstractions for irrigation available at
country and sub-national levels. Country data are the most complete, but their spatial resolution is often coarse. While the resolution of sub-national data is finer, their coverage is heterogeneous. Simulated and reported irrigation groundwater abstractions compare well in several areas,
particularly in France, while some structural discrepancies emerge:
simulated values tend to be larger than those reported, especially in southern Spain; and simulated inter-annual variability is significantly smaller than reported in some areas, most remarkably in Turkey. Potential causes of these discrepancies are simplified model assumptions influencing irrigation frequency and amounts; lack of high temporal and spatial resolution data on irrigated areas, and irrigation technologies and distribution; and possible unreported abstractions in areas
where groundwater irrigation is significant. We identify areas undergoing groundwater depletion from model simulations. In the southern Iberian Peninsula, Greece, Middle East and northern Africa, most simulated depletion is caused by irrigation. In other Mediterranean areas, depletion is caused by all sectors combined. From well measurements of groundwater table depth in Spain, we find statistically significant decline rates affecting large areas of the south, thus in agreement with the model, but also areas in the north-eastern and central parts where model estimates detect no depletion. The comparison of model- and well-based depletion rates is limited by spatial scale differences and groundwater model assumptions, for which we suggest potential research directions.
We design rules restricting irrigation groundwater abstraction to prevent groundwater depletion and minimise severe irrigation shortages.
We optimise them and simulate their effects in the southern Iberian Peninsula. Irrigation restrictions cause crop yield reductions in groundwater-dependent irrigated areas, particularly in the Algarve and Segura river basin districts. At the same time, they positively impact environmental flows. This study shows the potential of integrated agro-hydrologic modelling for detecting water resources over-exploitation and exploring trade-offs between crop production, sustainable irrigation and ecosystem support.
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16
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Thompson RL, Broquet G, Gerbig C, Koch T, Lang M, Monteil G, Munassar S, Nickless A, Scholze M, Ramonet M, Karstens U, van Schaik E, Wu Z, Rödenbeck C. Changes in net ecosystem exchange over Europe during the 2018 drought based on atmospheric observations. Philos Trans R Soc Lond B Biol Sci 2020; 375:20190512. [PMID: 32892731 PMCID: PMC7485096 DOI: 10.1098/rstb.2019.0512] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
The 2018 drought was one of the worst European droughts of the twenty-first century in terms of its severity, extent and duration. The effects of the drought could be seen in a reduction in harvest yields in parts of Europe, as well as an unprecedented browning of vegetation in summer. Here, we quantify the effect of the drought on net ecosystem exchange (NEE) using five independent regional atmospheric inversion frameworks. Using a network of atmospheric CO2 mole fraction observations, we estimate NEE with at least monthly and 0.5° × 0.5° resolution for 2009–2018. We find that the annual NEE in 2018 was likely more positive (less CO2 uptake) in the temperate region of Europe by 0.09 ± 0.06 Pg C yr−1 (mean ± s.d.) compared to the mean of the last 10 years of −0.08 ± 0.17 Pg C yr−1, making the region close to carbon neutral in 2018. Similarly, we find a positive annual NEE anomaly for the northern region of Europe of 0.02 ± 0.02 Pg C yr−1 compared the 10-year mean of −0.04 ± 0.05 Pg C yr−1. In both regions, this was largely owing to a reduction in the summer CO2 uptake. The positive NEE anomalies coincided spatially and temporally with negative anomalies in soil water. These anomalies were exceptional for the 10-year period of our study. This article is part of the theme issue ‘Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale’.
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Affiliation(s)
- R L Thompson
- ATMOS, NILU - Norsk Institutt for Luftforskning, Kjeller, Norway
| | - G Broquet
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif sur Yvette, France
| | - C Gerbig
- Biogeochemical Signals, Max Planck Institute for Biogeochemistry, Jena, Germany
| | - T Koch
- Biogeochemical Signals, Max Planck Institute for Biogeochemistry, Jena, Germany.,Meteorologisches Observatorium Hohenpeissenberg, Deutscher Wetterdienst, Germany
| | - M Lang
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif sur Yvette, France
| | - G Monteil
- Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden
| | - S Munassar
- Biogeochemical Signals, Max Planck Institute for Biogeochemistry, Jena, Germany
| | - A Nickless
- School of Chemistry, University of Bristol, Bristol, UK
| | - M Scholze
- Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden
| | - M Ramonet
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif sur Yvette, France
| | - U Karstens
- ICOS Carbon Portal, Lund University, Sweden
| | - E van Schaik
- Meteorology and Air Quality, Wageningen University and Research, Wageningen, The Netherlands
| | - Z Wu
- Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden
| | - C Rödenbeck
- Biogeochemical Signals, Max Planck Institute for Biogeochemistry, Jena, Germany
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17
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Performance of the Remotely-Derived Products in Monitoring Gross Primary Production across Arid and Semi-Arid Ecosystems in Northwest China. LAND 2020. [DOI: 10.3390/land9090288] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
As an important component to quantify the carbon budget, accurate evaluation of terrestrial gross primary production (GPP) is crucial for large-scale applications, especially in dryland ecosystems. Based on the in situ data from six flux sites in northwestern China from 2014 to 2016, this study compares seasonal and interannual dynamics of carbon fluxes between these arid and semi-arid ecosystems and the atmosphere. Meanwhile, the reliability of multiple remotely-derived GPP products in representative drylands was examined, including the Breathing Earth System Simulator (BESS), the Moderate Resolution Imaging Spectroradiometer (MODIS) and data derived from the OCO-2 solar-induced chlorophyll fluorescence (GOSIF). The results indicated that the carbon fluxes had clear seasonal patterns, with all ecosystems functioning as carbon sinks. The maize cropland had the highest GPP with 1183 g C m−2 y−1. Although the net ecosystem carbon exchange (NEE) in the Tamarix spp. ecosystem was the smallest among these flux sites, it reached 208 g C m−2 y−1. Furthermore, distinct advantages of GOSIF GPP (with R2 = 0.85–0.98, and RMSE = 0.87–2.66 g C m−2 d−1) were found with good performance. However, large underestimations in three GPP products existed during the growing seasons, except in grassland ecosystems. The main reasons can be ascribed to the uncertainties in the key model parameters, including the underestimated light use efficiency of the MODIS GPP, the same coarse land cover product for the BESS and MODIS GPP, the coarse gridded meteorological data, and distribution of C3 and C4 plants. Therefore, it still requires more work to accurately quantify the GPP across these dryland ecosystems.
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18
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Sorooshian A, Corral AF, Braun RA, Cairns B, Crosbie E, Ferrare R, Hair J, Kleb MM, Mardi AH, Maring H, McComiskey A, Moore R, Painemal D, Jo Scarino A, Schlosser J, Shingler T, Shook M, Wang H, Zeng X, Ziemba L, Zuidema P. Atmospheric Research Over the Western North Atlantic Ocean Region and North American East Coast: A Review of Past Work and Challenges Ahead. JOURNAL OF GEOPHYSICAL RESEARCH. ATMOSPHERES : JGR 2020; 125:10.1029/2019jd031626. [PMID: 32699733 PMCID: PMC7375207 DOI: 10.1029/2019jd031626] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2019] [Accepted: 01/21/2020] [Indexed: 05/26/2023]
Abstract
Decades of atmospheric research have focused on the Western North Atlantic Ocean (WNAO) region because of its unique location that offers accessibility for airborne and ship measurements, gradients in important atmospheric parameters, and a range of meteorological regimes leading to diverse conditions that are poorly understood. This work reviews these scientific investigations for the WNAO region, including the East Coast of North America and the island of Bermuda. Over 50 field campaigns and long-term monitoring programs, in addition to 715 peer-reviewed publications between 1946 and 2019 have provided a firm foundation of knowledge for these areas. Of particular importance in this region has been extensive work at the island of Bermuda that is host to important time series records of oceanic and atmospheric variables. Our review categorizes WNAO atmospheric research into eight major categories, with some studies fitting into multiple categories (relative %): Aerosols (25%), Gases (24%), Development/Validation of Techniques, Models, and Retrievals (18%), Meteorology and Transport (9%), Air-Sea Interactions (8%), Clouds/Storms (8%), Atmospheric Deposition (7%), and Aerosol-Cloud Interactions (2%). Recommendations for future research are provided in the categories highlighted above.
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Affiliation(s)
- Armin Sorooshian
- Department of Chemical and Environmental Engineering, University of Arizona, Tucson, AZ
- Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, AZ
| | - Andrea F. Corral
- Department of Chemical and Environmental Engineering, University of Arizona, Tucson, AZ
| | - Rachel A. Braun
- Department of Chemical and Environmental Engineering, University of Arizona, Tucson, AZ
| | - Brian Cairns
- NASA Goddard Institute for Space Studies, New York, NY
| | - Ewan Crosbie
- NASA Langley Research Center, Hampton, VA
- Science Systems and Applications, Inc., Hampton, VA
| | | | | | | | - Ali Hossein Mardi
- Department of Chemical and Environmental Engineering, University of Arizona, Tucson, AZ
| | | | | | | | - David Painemal
- NASA Langley Research Center, Hampton, VA
- Science Systems and Applications, Inc., Hampton, VA
| | - Amy Jo Scarino
- NASA Langley Research Center, Hampton, VA
- Science Systems and Applications, Inc., Hampton, VA
| | - Joseph Schlosser
- Department of Chemical and Environmental Engineering, University of Arizona, Tucson, AZ
| | | | | | - Hailong Wang
- Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, WA
| | - Xubin Zeng
- Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, AZ
| | | | - Paquita Zuidema
- Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, FL
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19
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Kondo M, Patra PK, Sitch S, Friedlingstein P, Poulter B, Chevallier F, Ciais P, Canadell JG, Bastos A, Lauerwald R, Calle L, Ichii K, Anthoni P, Arneth A, Haverd V, Jain AK, Kato E, Kautz M, Law RM, Lienert S, Lombardozzi D, Maki T, Nakamura T, Peylin P, Rödenbeck C, Zhuravlev R, Saeki T, Tian H, Zhu D, Ziehn T. State of the science in reconciling top-down and bottom-up approaches for terrestrial CO 2 budget. GLOBAL CHANGE BIOLOGY 2020; 26:1068-1084. [PMID: 31828914 DOI: 10.1111/gcb.14917] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/03/2019] [Revised: 11/07/2019] [Accepted: 11/07/2019] [Indexed: 06/10/2023]
Abstract
Robust estimates of CO2 budget, CO2 exchanged between the atmosphere and terrestrial biosphere, are necessary to better understand the role of the terrestrial biosphere in mitigating anthropogenic CO2 emissions. Over the past decade, this field of research has advanced through understanding of the differences and similarities of two fundamentally different approaches: "top-down" atmospheric inversions and "bottom-up" biosphere models. Since the first studies were undertaken, these approaches have shown an increasing level of agreement, but disagreements in some regions still persist, in part because they do not estimate the same quantity of atmosphere-biosphere CO2 exchange. Here, we conducted a thorough comparison of CO2 budgets at multiple scales and from multiple methods to assess the current state of the science in estimating CO2 budgets. Our set of atmospheric inversions and biosphere models, which were adjusted for a consistent flux definition, showed a high level of agreement for global and hemispheric CO2 budgets in the 2000s. Regionally, improved agreement in CO2 budgets was notable for North America and Southeast Asia. However, large gaps between the two methods remained in East Asia and South America. In other regions, Europe, boreal Asia, Africa, South Asia, and Oceania, it was difficult to determine whether those regions act as a net sink or source because of the large spread in estimates from atmospheric inversions. These results highlight two research directions to improve the robustness of CO2 budgets: (a) to increase representation of processes in biosphere models that could contribute to fill the budget gaps, such as forest regrowth and forest degradation; and (b) to reduce sink-source compensation between regions (dipoles) in atmospheric inversion so that their estimates become more comparable. Advancements on both research areas will increase the level of agreement between the top-down and bottom-up approaches and yield more robust knowledge of regional CO2 budgets.
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Affiliation(s)
- Masayuki Kondo
- Center for Environmental Remote Sensing, Chiba University, Chiba, Japan
| | - Prabir K Patra
- Center for Environmental Remote Sensing, Chiba University, Chiba, Japan
- Department of Environmental Geochemical Cycle Research, Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan
| | - Stephen Sitch
- College of Life and Environmental Sciences, University of Exeter, Exeter, UK
| | - Pierre Friedlingstein
- College of Engineering, Mathematics, and Physical Sciences, University of Exeter, Exeter, UK
| | - Benjamin Poulter
- Biospheric Science Laboratory, National Aeronautics and Space Administration Goddard Space Flight Center, Greenbelt, MD, USA
| | - Frederic Chevallier
- Laboratoire des Sciences du Climat et de l'Environnement, Institut Pierre Simon Laplace, Gif-sur-Yvette, France
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, Institut Pierre Simon Laplace, Gif-sur-Yvette, France
| | - Josep G Canadell
- Global Carbon Project, Commonwealth Scientific and Industrial Research Organisation-Oceans and Atmosphere, Canberra, ACT, Australia
| | - Ana Bastos
- Department of Geography, Ludwig-Maximilian University of Munich, Munich, Germany
| | | | - Leonardo Calle
- W.A. Franke College of Forestry & Conservation, University of Montana, Missoula, MT, USA
| | - Kazuhito Ichii
- Center for Environmental Remote Sensing, Chiba University, Chiba, Japan
- Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba, Japan
| | - Peter Anthoni
- Institute of Meteorology and Climate Research/Atmospheric Environmental Research, Karlsruhe Institute of Technology, Garmisch-Partenkirchen, Germany
| | - Almut Arneth
- Institute of Meteorology and Climate Research/Atmospheric Environmental Research, Karlsruhe Institute of Technology, Garmisch-Partenkirchen, Germany
| | - Vanessa Haverd
- Commonwealth Scientific and Industrial Research Organisation-Oceans and Atmosphere, Canberra, ACT, Australia
| | - Atul K Jain
- Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | | | - Markus Kautz
- Institute of Meteorology and Climate Research/Atmospheric Environmental Research, Karlsruhe Institute of Technology, Garmisch-Partenkirchen, Germany
- Department of Forest Health, Forest Research Institute Baden-Württemberg, Freiburg, Germany
| | - Rachel M Law
- Commonwealth Scientific and Industrial Research Organisation-Oceans and Atmosphere, Aspendale, Vic., Australia
| | - Sebastian Lienert
- Climate and Environmental Physics, Physics Institute and Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
| | - Danica Lombardozzi
- Climate and Global Dynamics, National Center for Atmospheric Research, Boulder, CO, USA
| | - Takashi Maki
- Meteorological Research Institute, Tsukuba, Japan
| | | | - Philippe Peylin
- Laboratoire des Sciences du Climat et de l'Environnement, Institut Pierre Simon Laplace, Gif-sur-Yvette, France
| | | | - Ruslan Zhuravlev
- Central Aerological Observatory of Russian Hydromet Service, Moscow, Russia
| | - Tazu Saeki
- Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba, Japan
| | - Hanqin Tian
- International Center for Climate and Global Change Research, School of Forestry and Wildlife Sciences, Auburn University, Auburn, AL, USA
| | - Dan Zhu
- Laboratoire des Sciences du Climat et de l'Environnement, Institut Pierre Simon Laplace, Gif-sur-Yvette, France
| | - Tilo Ziehn
- Commonwealth Scientific and Industrial Research Organisation-Oceans and Atmosphere, Aspendale, Vic., Australia
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20
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Evidence of Carbon Uptake Associated with Vegetation Greening Trends in Eastern China. REMOTE SENSING 2020. [DOI: 10.3390/rs12040718] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Persistent and widespread increase of vegetation cover, identified as greening, has been observed in areas of the planet over late 20th century and early 21st century by satellite-derived vegetation indices. It is difficult to verify whether these regions are net carbon sinks or sources by studying vegetation indices alone. In this study, we investigate greening trends in Eastern China (EC) and corresponding trends in atmospheric CO2 concentrations. We used multiple vegetation indices including NDVI and EVI to characterize changes in vegetation activity over EC from 2003 to 2016. Gap-filled time series of column-averaged CO2 dry air mole fraction (XCO2) from January 2003 to May 2016, based on observations from SCIAMACHY, GOSAT, and OCO-2 satellites, were used to calculate XCO2 changes during growing season for 13 years. We derived a relationship between XCO2 and surface net CO2 fluxes from two inversion model simulations, CarbonTracker and Monitoring Atmospheric Composition and Climate (MACC), and used those relationships to estimate the biospheric CO2 flux enhancement based on satellite observed XCO2 changes. We observed significant growing period (GP) greening trends in NDVI and EVI related to cropland intensification and forest growth in the region. After removing the influence of large urban center CO2 emissions, we estimated an enhanced XCO2 drawdown during the GP of −0.070 to −0.084 ppm yr−1. Increased carbon uptake during the GP was estimated to be 28.41 to 46.04 Tg C, mainly from land management, which could offset about 2–3% of EC’s annual fossil fuel emissions. These results show the potential of using multi-satellite observed XCO2 to estimate carbon fluxes from the regional biosphere, which could be used to verify natural sinks included as national contributions of greenhouse gas emissions reduction in international climate change agreements like the UNFCC Paris Accord.
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21
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Wigneron JP, Fan L, Ciais P, Bastos A, Brandt M, Chave J, Saatchi S, Baccini A, Fensholt R. Tropical forests did not recover from the strong 2015-2016 El Niño event. SCIENCE ADVANCES 2020; 6:eaay4603. [PMID: 32076648 PMCID: PMC7002128 DOI: 10.1126/sciadv.aay4603] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/21/2019] [Accepted: 11/22/2019] [Indexed: 05/29/2023]
Abstract
Severe drought and extreme heat associated with the 2015-2016 El Niño event have led to large carbon emissions from the tropical vegetation to the atmosphere. With the return to normal climatic conditions in 2017, tropical forest aboveground carbon (AGC) stocks are expected to partly recover due to increased productivity, but the intensity and spatial distribution of this recovery are unknown. We used low-frequency microwave satellite data (L-VOD) to feature precise monitoring of AGC changes and show that the AGC recovery of tropical ecosystems was slow and that by the end of 2017, AGC had not reached predrought levels of 2014. From 2014 to 2017, tropical AGC stocks decreased by1.3 1.2 1.5 Pg C due to persistent AGC losses in Africa (- 0.9 - 1.1 - 0.8 Pg C) and America (- 0.5 - 0.6 - 0.4 Pg C). Pantropically, drylands recovered their carbon stocks to pre-El Niño levels, but African and American humid forests did not, suggesting carryover effects from enhanced forest mortality.
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Affiliation(s)
- Jean-Pierre Wigneron
- ISPA, UMR 1391, Inrae Nouvelle-Aquitaine, Université de Bordeaux, Grande Ferrade, Villenave d’Ornon, France
| | - Lei Fan
- ISPA, UMR 1391, Inrae Nouvelle-Aquitaine, Université de Bordeaux, Grande Ferrade, Villenave d’Ornon, France
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster, School of Geographical Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, 91191 Gif-sur-Yvette, France
| | - Ana Bastos
- Department of Geography, Ludwig-Maximilians Universität, Luisenstr. 37, 80333 Munich, Germany
| | - Martin Brandt
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
| | - Jérome Chave
- Laboratoire Evolution and Diversité Biologique, Bâtiment 4R3 Université Paul Sabatier, Toulouse, France
| | - Sassan Saatchi
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
- Institute of the Environment and Sustainability, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Alessandro Baccini
- Woods Hole Research Center, 149 Woods Hole Road, Falmouth, MA 02540-1644, USA
- Department of Earth and Environment, Boston University, Boston, MA 02215, USA
| | - Rasmus Fensholt
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
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22
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Piao S, Wang X, Wang K, Li X, Bastos A, Canadell JG, Ciais P, Friedlingstein P, Sitch S. Interannual variation of terrestrial carbon cycle: Issues and perspectives. GLOBAL CHANGE BIOLOGY 2020; 26:300-318. [PMID: 31670435 DOI: 10.1111/gcb.14884] [Citation(s) in RCA: 58] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2019] [Accepted: 10/11/2019] [Indexed: 06/10/2023]
Abstract
With accumulation of carbon cycle observations and model developments over the past decades, exploring interannual variation (IAV) of terrestrial carbon cycle offers the opportunity to better understand climate-carbon cycle relationships. However, despite growing research interest, uncertainties remain on some fundamental issues, such as the contributions of different regions, constituent fluxes and climatic factors to carbon cycle IAV. Here we overviewed the literature on carbon cycle IAV about current understanding of these issues. Observations and models of the carbon cycle unanimously show the dominance of tropical land ecosystems to the signal of global carbon cycle IAV, where tropical semiarid ecosystems contribute as much as the combination of all other tropical ecosystems. Vegetation photosynthesis contributes more than ecosystem respiration to IAV of the global net land carbon flux, but large uncertainties remain on the contribution of fires and other disturbance fluxes. Climatic variations are the major drivers to the IAV of net land carbon flux. Although debate remains on whether the dominant driver is temperature or moisture variability, their interaction,that is, the dependence of carbon cycle sensitivity to temperature on moisture conditions, is emerging as key regulators of the carbon cycle IAV. On timescales from the interannual to the centennial, global carbon cycle variability will be increasingly contributed by northern land ecosystems and oceans. Therefore, both improving Earth system models (ESMs) with the progressive understanding on the fast processes manifested at interannual timescale and expanding carbon cycle observations at broader spatial and longer temporal scales are critical to better prediction on evolution of the carbon-climate system.
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Affiliation(s)
- 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
| | - Xuhui Wang
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Kai Wang
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Xiangyi Li
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Ana Bastos
- Department of Geography, Ludwig-Maximilians Universität, Munchen, Germany
| | - Josep G Canadell
- Global Carbon Project, CSIRO Oceans and Atmosphere, Canberra, ACT, Australia
| | - Philippe Ciais
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China
- Laboratoire des Sciences du Climat et de l'Environnement, CEA CNRS UVSQ, Gif-sur-Yvette, France
| | - Pierre Friedlingstein
- College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UK
| | - Stephen Sitch
- College of Life and Environmental Sciences, University of Exeter, Exeter, UK
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23
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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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24
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Park T, Chen C, Macias-Fauria M, Tømmervik H, Choi S, Winkler A, Bhatt US, Walker DA, Piao S, Brovkin V, Nemani RR, Myneni RB. Changes in timing of seasonal peak photosynthetic activity in northern ecosystems. GLOBAL CHANGE BIOLOGY 2019; 25:2382-2395. [PMID: 30943321 DOI: 10.1111/gcb.14638] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/11/2018] [Revised: 03/12/2019] [Accepted: 03/16/2019] [Indexed: 06/09/2023]
Abstract
Seasonality in photosynthetic activity is a critical component of seasonal carbon, water, and energy cycles in the Earth system. This characteristic is a consequence of plant's adaptive evolutionary processes to a given set of environmental conditions. Changing climate in northern lands (>30°N) alters the state of climatic constraints on plant growth, and therefore, changes in the seasonality and carbon accumulation are anticipated. However, how photosynthetic seasonality evolved to its current state, and what role climatic constraints and their variability played in this process and ultimately in carbon cycle is still poorly understood due to its complexity. Here, we take the "laws of minimum" as a basis and introduce a new framework where the timing (day of year) of peak photosynthetic activity (DOYPmax ) acts as a proxy for plant's adaptive state to climatic constraints on its growth. Our analyses confirm that spatial variations in DOYPmax reflect spatial gradients in climatic constraints as well as seasonal maximum and total productivity. We find a widespread warming-induced advance in DOYPmax (-1.66 ± 0.30 days/decade, p < 0.001) across northern lands, indicating a spatiotemporal dynamism of climatic constraints to plant growth. We show that the observed changes in DOYPmax are associated with an increase in total gross primary productivity through enhanced carbon assimilation early in the growing season, which leads to an earlier phase shift in land-atmosphere carbon fluxes and an increase in their amplitude. Such changes are expected to continue in the future based on our analysis of earth system model projections. Our study provides a simplified, yet realistic framework based on first principles for the complex mechanisms by which various climatic factors constrain plant growth in northern ecosystems.
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Affiliation(s)
- Taejin Park
- Department of Earth and Environment, Boston University, Boston, Massachusetts
| | - Chi Chen
- Department of Earth and Environment, Boston University, Boston, Massachusetts
| | - Marc Macias-Fauria
- School of Geography and the Environment, University of Oxford, Oxford, United Kingdom
| | - Hans Tømmervik
- Norwegian Institute for Nature Research, FRAM - High North Research Centre for Climate and the Environment, Tromsø, Norway
| | - Sungho Choi
- Rhombus Power Inc., NASA Ames Research Park, Moffett Field, California
| | - Alexander Winkler
- Max-Planck-Institute for Meteorology, Hamburg, Germany
- International Max-Planck Research School for Earth System Modeling, Hamburg, Germany
| | - Uma S Bhatt
- Geophysical Institute, University of Alaska Fairbanks, Fairbanks, Alaska
| | - Donald A Walker
- Institute of Arctic Biology, University of Alaska, Fairbanks, Alaska
| | - Shilong Piao
- College of Urban and Environmental Sciences, Peking University, Beijing, China
| | | | | | - Ranga B Myneni
- Department of Earth and Environment, Boston University, Boston, Massachusetts
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25
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He H, Wang S, Zhang L, Wang J, Ren X, Zhou L, Piao S, Yan H, Ju W, Gu F, Yu S, Yang Y, Wang M, Niu Z, Ge R, Yan H, Huang M, Zhou G, Bai Y, Xie Z, Tang Z, Wu B, Zhang L, He N, Wang Q, Yu G. Altered trends in carbon uptake in China's terrestrial ecosystems under the enhanced summer monsoon and warming hiatus. Natl Sci Rev 2019; 6:505-514. [PMID: 34691899 PMCID: PMC8291462 DOI: 10.1093/nsr/nwz021] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2018] [Revised: 11/16/2018] [Accepted: 02/15/2019] [Indexed: 11/14/2022] Open
Abstract
The carbon budgets in terrestrial ecosystems in China are strongly coupled with climate changes. Over the past decade, China has experienced dramatic climate changes characterized by enhanced summer monsoon and decelerated warming. However, the changes in the trends of terrestrial net ecosystem production (NEP) in China under climate changes are not well documented. Here, we used three ecosystem models to simulate the spatiotemporal variations in China's NEP during 1982-2010 and quantify the contribution of the strengthened summer monsoon and warming hiatus to the NEP variations in four distinct climatic regions of the country. Our results revealed a decadal-scale shift in NEP from a downtrend of -5.95 Tg C/yr2 (reduced sink) during 1982-2000 to an uptrend of 14.22 Tg C/yr2 (enhanced sink) during 2000-10. This shift was essentially induced by the strengthened summer monsoon, which stimulated carbon uptake, and the warming hiatus, which lessened the decrease in the NEP trend. Compared to the contribution of 56.3% by the climate effect, atmospheric CO2 concentration and nitrogen deposition had relatively small contributions (8.6 and 11.3%, respectively) to the shift. In conclusion, within the context of the global-warming hiatus, the strengthening of the summer monsoon is a critical climate factor that enhances carbon uptake in China due to the asymmetric response of photosynthesis and respiration. Our study not only revealed the shift in ecosystem carbon sequestration in China in recent decades, but also provides some insight for understanding ecosystem carbon dynamics in other monsoonal areas.
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Affiliation(s)
- Honglin He
- Synthesis Research Center of China's Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.,College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Shaoqiang Wang
- Synthesis Research Center of China's Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.,College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Li Zhang
- Synthesis Research Center of China's Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.,College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Junbang Wang
- Synthesis Research Center of China's Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Xiaoli Ren
- Synthesis Research Center of China's Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Lei Zhou
- Synthesis Research Center of China's Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Shilong Piao
- Sino-French Institute for Earth System Science, College of Urban and Environment Sciences, Peking University, Beijing 100871, China.,Key Laboratory of Alpine Ecology and Biodiversity, Institute of Tibetan Plateau Research, CAS Center for Excellence in Tibetan Plateau Earth Science, Chinese Academy of Sciences, Beijing 100085, China
| | - Hao Yan
- National Meteorological Center, China Meteorological Administration, Beijing 100081, China
| | - Weimin Ju
- International Institute for Earth System Science and Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Nanjing 210023, China
| | - Fengxue Gu
- Key Laboratory of Dryland Agriculture, MOA, Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Shiyong Yu
- School of Geography, Geomatics, and Planning, Jiangsu Normal University, Xuzhou 221116, China
| | - Yuanhe Yang
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Miaomiao Wang
- Synthesis Research Center of China's Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhongen Niu
- Synthesis Research Center of China's Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Rong Ge
- Synthesis Research Center of China's Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Huimin Yan
- Synthesis Research Center of China's Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.,College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Mei Huang
- Synthesis Research Center of China's Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Guoyi Zhou
- Key Laboratory of Vegetation Restoration and Management of Degraded Ecosystems, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou 510650, China
| | - Yongfei Bai
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
| | - Zongqiang Xie
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
| | - Zhiyao Tang
- Department of Ecology, College of Urban and Environmental Science, Key Laboratory for Earth Surface Processes of the Ministry of Education, Peking University, Beijing 100871, China
| | - Bingfang Wu
- Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China
| | - Leiming Zhang
- Synthesis Research Center of China's Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.,College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Nianpeng He
- Synthesis Research Center of China's Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.,College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Qiufeng Wang
- Synthesis Research Center of China's Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.,College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Guirui Yu
- Synthesis Research Center of China's Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.,College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
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26
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Ciais P, Tan J, Wang X, Roedenbeck C, Chevallier F, Piao SL, Moriarty R, Broquet G, Le Quéré C, Canadell JG, Peng S, Poulter B, Liu Z, Tans P. Five decades of northern land carbon uptake revealed by the interhemispheric CO2 gradient. Nature 2019; 568:221-225. [DOI: 10.1038/s41586-019-1078-6] [Citation(s) in RCA: 82] [Impact Index Per Article: 16.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2016] [Accepted: 01/25/2019] [Indexed: 11/09/2022]
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27
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Earth system models underestimate carbon fixation by plants in the high latitudes. Nat Commun 2019; 10:885. [PMID: 30792385 PMCID: PMC6385346 DOI: 10.1038/s41467-019-08633-z] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2018] [Accepted: 01/18/2019] [Indexed: 11/08/2022] Open
Abstract
Most Earth system models agree that land will continue to store carbon due to the physiological effects of rising CO2 concentration and climatic changes favoring plant growth in temperature-limited regions. But they largely disagree on the amount of carbon uptake. The historical CO2 increase has resulted in enhanced photosynthetic carbon fixation (Gross Primary Production, GPP), as can be evidenced from atmospheric CO2 concentration and satellite leaf area index measurements. Here, we use leaf area sensitivity to ambient CO2 from the past 36 years of satellite measurements to obtain an Emergent Constraint (EC) estimate of GPP enhancement in the northern high latitudes at two-times the pre-industrial CO2 concentration (3.4 ± 0.2 Pg C yr−1). We derive three independent comparable estimates from CO2 measurements and atmospheric inversions. Our EC estimate is 60% larger than the conventionally used multi-model average (44% higher at the global scale). This suggests that most models largely underestimate photosynthetic carbon fixation and therefore likely overestimate future atmospheric CO2 abundance and ensuing climate change, though not proportionately. The terrestrial biosphere absorbs a large fraction of emitted CO2, and thus, plays a critical role in climate change projections. Here, the authors use satellite leaf area and in-situ CO2 measurements to show that most Earth system models largely underestimate photosynthetic carbon fixation in high latitudes.
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28
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Gaubert B, Stephens BB, Basu S, Chevallier F, Deng F, Kort EA, Patra PK, Peters W, Rödenbeck C, Saeki T, Schimel D, Van der Laan-Luijkx I, Wofsy S, Yin Y. Global atmospheric CO 2 inverse models converging on neutral tropical land exchange, but disagreeing on fossil fuel and atmospheric growth rate. BIOGEOSCIENCES (ONLINE) 2019; 16:117-134. [PMID: 31708981 PMCID: PMC6839691 DOI: 10.5194/bg-16-117-2019] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
We have compared a suite of recent global CO2 atmospheric inversion results to independent airborne observations and to each other, to assess their dependence on differences in northern extratropical (NET) vertical transport and to identify some of the drivers of model spread. We evaluate posterior CO2 concentration profiles against observations from the High-Performance Instrumented Airborne Platform for Environmental Research (HIAPER) Pole-to-Pole Observations (HIPPO) aircraft campaigns over the mid-Pacific in 2009-2011. Although the models differ in inverse approaches, assimilated observations, prior fluxes, and transport models, their broad latitudinal separation of land fluxes has converged significantly since the Atmospheric Carbon Cycle Inversion Intercomparison (TransCom 3) and the REgional Carbon Cycle Assessment and Processes (RECCAP) projects, with model spread reduced by 80% since TransCom 3 and 70% since RECCAP. Most modeled CO2 fields agree reasonably well with the HIPPO observations, specifically for the annual mean vertical gradients in the Northern Hemisphere. Northern Hemisphere vertical mixing no longer appears to be a dominant driver of northern versus tropical (T) annual flux differences. Our newer suite of models still gives northern extratropical land uptake that is modest relative to previous estimates (Gurney et al., 2002; Peylin et al., 2013) and near-neutral tropical land uptake for 2009-2011. Given estimates of emissions from deforestation, this implies a continued uptake in intact tropical forests that is strong relative to historical estimates (Gurney et al., 2002; Peylin et al., 2013). The results from these models for other time periods (2004-2014, 2001-2004, 1992-1996) and reevaluation of the TransCom 3 Level 2 and RECCAP results confirm that tropical land carbon fluxes including deforestation have been near neutral for several decades. However, models still have large disagreements on ocean-land partitioning. The fossil fuel (FF) and the atmospheric growth rate terms have been thought to be the best-known terms in the global carbon budget, but we show that they currently limit our ability to assess regional-scale terrestrial fluxes and ocean-land partitioning from the model ensemble.
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Affiliation(s)
- Benjamin Gaubert
- Atmospheric Chemistry Observations & Modeling Laboratory (ACOM), National Center for Atmospheric Research, Boulder, CO, USA
| | - Britton B. Stephens
- Earth Observing Laboratory (EOL), National Center for Atmospheric Research, Boulder, CO, USA
| | - Sourish Basu
- Earth System Research Laboratory, National Oceanic and Atmospheric Administration, Boulder, CO, USA
- Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO, USA
| | - Frédéric Chevallier
- Laboratoire des Sciences du Climat et de l’Environnement, Institut Pierre-Simon Laplace, CEA-CNRS-UVSQ, Gif sur Yvette, 91191 CEDEX, France
| | - Feng Deng
- Department of Physics, University of Toronto, Toronto, Canada
| | - Eric A. Kort
- Climate and Space Sciences and Engineering, University of Michigan, Ann Arbor, MI, USA
| | - Prabir K. Patra
- RGGC/IACE/ACMPT, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokohama 236 0001, Japan
| | - Wouter Peters
- Meteorology and Air Quality, Wageningen University, Wageningen, the Netherlands
| | | | - Tazu Saeki
- Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba, Japan
| | - David Schimel
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| | | | - Steven Wofsy
- School of Engineering and Applied Science and Department of Earth and Planetary Sciences, Harvard University, Cambridge, MA, USA
| | - Yi Yin
- Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA, USA
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29
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Satellite and In Situ Observations for Advancing Global Earth Surface Modelling: A Review. REMOTE SENSING 2018. [DOI: 10.3390/rs10122038] [Citation(s) in RCA: 68] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
In this paper, we review the use of satellite-based remote sensing in combination with in situ data to inform Earth surface modelling. This involves verification and optimization methods that can handle both random and systematic errors and result in effective model improvement for both surface monitoring and prediction applications. The reasons for diverse remote sensing data and products include (i) their complementary areal and temporal coverage, (ii) their diverse and covariant information content, and (iii) their ability to complement in situ observations, which are often sparse and only locally representative. To improve our understanding of the complex behavior of the Earth system at the surface and sub-surface, we need large volumes of data from high-resolution modelling and remote sensing, since the Earth surface exhibits a high degree of heterogeneity and discontinuities in space and time. The spatial and temporal variability of the biosphere, hydrosphere, cryosphere and anthroposphere calls for an increased use of Earth observation (EO) data attaining volumes previously considered prohibitive. We review data availability and discuss recent examples where satellite remote sensing is used to infer observable surface quantities directly or indirectly, with particular emphasis on key parameters necessary for weather and climate prediction. Coordinated high-resolution remote-sensing and modelling/assimilation capabilities for the Earth surface are required to support an international application-focused effort.
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30
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Bastos A, Friedlingstein P, Sitch S, Chen C, Mialon A, Wigneron JP, Arora VK, Briggs PR, Canadell JG, Ciais P, Chevallier F, Cheng L, Delire C, Haverd V, Jain AK, Joos F, Kato E, Lienert S, Lombardozzi D, Melton JR, Myneni R, Nabel JEMS, Pongratz J, Poulter B, Rödenbeck C, Séférian R, Tian H, van Eck C, Viovy N, Vuichard N, Walker AP, Wiltshire A, Yang J, Zaehle S, Zeng N, Zhu D. Impact of the 2015/2016 El Niño on the terrestrial carbon cycle constrained by bottom-up and top-down approaches. Philos Trans R Soc Lond B Biol Sci 2018; 373:rstb.2017.0304. [PMID: 30297465 PMCID: PMC6178442 DOI: 10.1098/rstb.2017.0304] [Citation(s) in RCA: 49] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/22/2018] [Indexed: 11/12/2022] Open
Abstract
Evaluating the response of the land carbon sink to the anomalies in temperature and drought imposed by El Niño events provides insights into the present-day carbon cycle and its climate-driven variability. It is also a necessary step to build confidence in terrestrial ecosystems models' response to the warming and drying stresses expected in the future over many continents, and particularly in the tropics. Here we present an in-depth analysis of the response of the terrestrial carbon cycle to the 2015/2016 El Niño that imposed extreme warming and dry conditions in the tropics and other sensitive regions. First, we provide a synthesis of the spatio-temporal evolution of anomalies in net land–atmosphere CO2 fluxes estimated by two in situ measurements based on atmospheric inversions and 16 land-surface models (LSMs) from TRENDYv6. Simulated changes in ecosystem productivity, decomposition rates and fire emissions are also investigated. Inversions and LSMs generally agree on the decrease and subsequent recovery of the land sink in response to the onset, peak and demise of El Niño conditions and point to the decreased strength of the land carbon sink: by 0.4–0.7 PgC yr−1 (inversions) and by 1.0 PgC yr−1 (LSMs) during 2015/2016. LSM simulations indicate that a decrease in productivity, rather than increase in respiration, dominated the net biome productivity anomalies in response to ENSO throughout the tropics, mainly associated with prolonged drought conditions. This article is part of a discussion meeting issue ‘The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications’.
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Affiliation(s)
- Ana Bastos
- Department of Geography, Ludwig Maximilians University Munich, Luisenstr. 37, Munich D-80333, Germany .,Laboratoire des Sciences du Climat et de l'Environnement (LSCE), CEA-CNRS-UVSQ, UMR8212, Gif-sur-Yvette 91191, France
| | - Pierre Friedlingstein
- College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter EX4 4QF, UK
| | - Stephen Sitch
- College of Life and Environmental Sciences, University of Exeter, Exeter EX4 4RJ, UK
| | - Chi Chen
- Department of Earth and Environment, Boston University, Boston, MA 02215, USA
| | - Arnaud Mialon
- CESBIO, Université de Toulouse, CNES/CNRS/IRD/UPS, 31400 Toulouse, France
| | | | - Vivek K Arora
- Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada, University of Victoria, Victoria, British Columbia, Canada V8W2Y2
| | - Peter R Briggs
- CSIRO Oceans and Atmosphere, Canberra, ACT 2601, Australia
| | - Josep G Canadell
- Global Carbon Project, CSIRO Oceans and Atmosphere, Canberra, ACT 2601, Australia
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement (LSCE), CEA-CNRS-UVSQ, UMR8212, Gif-sur-Yvette 91191, France
| | - Frédéric Chevallier
- Laboratoire des Sciences du Climat et de l'Environnement (LSCE), CEA-CNRS-UVSQ, UMR8212, Gif-sur-Yvette 91191, France
| | - Lei Cheng
- State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, People's Republic of China
| | - Christine Delire
- Centre National de Recherches Météorologiques, CNRM, Unité 3589 CNRS/Meteo-France/Université Fédérale de Toulouse, Av G Coriolis, Toulouse 31057, France
| | - Vanessa Haverd
- CSIRO Oceans and Atmosphere, Canberra, ACT 2601, Australia
| | - Atul K Jain
- Department of Atmospheric Sciences, University of Illinois, Urbana, IL 61801, USA
| | - Fortunat Joos
- Climate and Environmental Physics, Physics Institute and Oeschger Centre for Climate Change Research, University of Bern, Bern CH-3012, Switzerland
| | - Etsushi Kato
- Institute of Applied Energy (IAE), Minato, Tokyo 105-0003, Japan
| | - Sebastian Lienert
- Climate and Environmental Physics, Physics Institute and Oeschger Centre for Climate Change Research, University of Bern, Bern CH-3012, Switzerland
| | - Danica Lombardozzi
- Climate and Global Dynamics Division, National Center for Atmospheric Research, Boulder, CO 80302, USA
| | - Joe R Melton
- Climate Processes Section, Environment and Climate Change Canada, Downsview, Ontario, Canada V8W2Y2
| | - Ranga Myneni
- Department of Earth and Environment, Boston University, Boston, MA 02215, USA
| | | | - Julia Pongratz
- Department of Geography, Ludwig Maximilians University Munich, Luisenstr. 37, Munich D-80333, Germany.,Max Planck Institute for Meteorology, Hamburg 20146, Germany
| | - Benjamin Poulter
- NASA Goddard Space Flight Center, Biospheric Sciences Lab, Greenbelt, MD 20816, USA
| | | | - Roland Séférian
- Centre National de Recherches Météorologiques, CNRM, Unité 3589 CNRS/Meteo-France/Université Fédérale de Toulouse, Av G Coriolis, Toulouse 31057, France
| | - Hanqin Tian
- International Center for Climate and Global Change Research, School of Forestry and Wildlife Sciences, Auburn University, 602 Duncan Drive, Auburn, AL 36849, USA
| | - Christel van Eck
- Department of Geoscience, Environment and Society, CP 160/02, Université Libre de Bruxelles, Brussels 1050, Belgium
| | - Nicolas Viovy
- Laboratoire des Sciences du Climat et de l'Environnement (LSCE), CEA-CNRS-UVSQ, UMR8212, Gif-sur-Yvette 91191, France
| | - Nicolas Vuichard
- Laboratoire des Sciences du Climat et de l'Environnement (LSCE), CEA-CNRS-UVSQ, UMR8212, Gif-sur-Yvette 91191, France
| | - Anthony P Walker
- Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | | | - Jia Yang
- International Center for Climate and Global Change Research, School of Forestry and Wildlife Sciences, Auburn University, 602 Duncan Drive, Auburn, AL 36849, USA
| | - Sönke Zaehle
- Max Planck Institute for Biogeochemistry, 07745 Jena, Germany
| | - Ning Zeng
- Department of Atmospheric and Oceanic Science and Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD 100029, USA.,State Key Laboratory of Numerical Modelling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Beijing 20740, People's Republic of China
| | - Dan Zhu
- Laboratoire des Sciences du Climat et de l'Environnement (LSCE), CEA-CNRS-UVSQ, UMR8212, Gif-sur-Yvette 91191, France
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31
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Zhang X, Wang YP, Peng S, Rayner PJ, Ciais P, Silver JD, Piao S, Zhu Z, Lu X, Zheng X. Dominant regions and drivers of the variability of the global land carbon sink across timescales. GLOBAL CHANGE BIOLOGY 2018; 24:3954-3968. [PMID: 29665215 DOI: 10.1111/gcb.14275] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2018] [Revised: 03/29/2018] [Accepted: 03/30/2018] [Indexed: 06/08/2023]
Abstract
Net biome productivity (NBP) dominates the observed large variation of atmospheric CO2 annual increase over the last five decades. However, the dominant regions controlling inter-annual to multi-decadal variability of global NBP are still controversial (semi-arid regions vs. temperate or tropical forests). By developing a theory for partitioning the variance of NBP into the contributions of net primary production (NPP) and heterotrophic respiration (Rh ) at different timescales, and using both observation-based atmospheric CO2 inversion product and the outputs of 10 process-based terrestrial ecosystem models forced by 110-year observational climate, we tried to reconcile the controversy by showing that semi-arid lands dominate the variability of global NBP at inter-annual (<10 years) and tropical forests dominate at multi-decadal scales (>30 years). Results further indicate that global NBP variability is dominated by the NPP component at inter-annual timescales, and is progressively controlled by Rh with increasing timescale. Multi-decadal NBP variations of tropical rainforests are modulated by the Pacific Decadal Oscillation (PDO) through its significant influences on both temperature and precipitation. This study calls for long-term observations for the decadal or longer fluctuations in carbon fluxes to gain insights on the future evolution of global NBP, particularly in the tropical forests that dominate the decadal variability of land carbon uptake and are more effective for climate mitigation.
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Affiliation(s)
- Xuanze Zhang
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Ying-Ping Wang
- South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China
- CSIRO Oceans and Atmosphere, Aspendale, VIC, Australia
| | - Shushi Peng
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Peter J Rayner
- School of Earth Sciences, University of Melbourne, Melbourne, VIC, Australia
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Jeremy D Silver
- School of Earth Sciences, University of Melbourne, Melbourne, VIC, Australia
| | - 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 Plateau Earth Science, Chinese Academy of Sciences, Beijing, China
| | - Zaichun Zhu
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Xingjie Lu
- Department of Botany and Microbiology, University of Oklahoma, Norman, Oklahoma
| | - Xiaogu Zheng
- Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
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32
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Land use change and El Niño-Southern Oscillation drive decadal carbon balance shifts in Southeast Asia. Nat Commun 2018; 9:1154. [PMID: 29559637 PMCID: PMC5861034 DOI: 10.1038/s41467-018-03374-x] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2017] [Accepted: 02/05/2018] [Indexed: 11/08/2022] Open
Abstract
An integrated understanding of the biogeochemical consequences of climate extremes and land use changes is needed to constrain land-surface feedbacks to atmospheric CO2 from associated climate change. Past assessments of the global carbon balance have shown particularly high uncertainty in Southeast Asia. Here, we use a combination of model ensembles to show that intensified land use change made Southeast Asia a strong source of CO2 from the 1980s to 1990s, whereas the region was close to carbon neutral in the 2000s due to an enhanced CO2 fertilization effect and absence of moderate-to-strong El Niño events. Our findings suggest that despite ongoing deforestation, CO2 emissions were substantially decreased during the 2000s, largely owing to milder climate that restores photosynthetic capacity and suppresses peat and deforestation fire emissions. The occurrence of strong El Niño events after 2009 suggests that the region has returned to conditions of increased vulnerability of carbon stocks. The carbon balance in Southeast Asia is highly uncertain. Here, the authors show that land use changes and occurrence of strong El Niño control decadal shifts in the carbon balance of this region.
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33
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Oda T, Maksyutov S, Andres RJ. The Open-source Data Inventory for Anthropogenic Carbon dioxide (CO 2), version 2016 (ODIAC2016): A global, monthly fossil-fuel CO 2 gridded emission data product for tracer transport simulations and surface flux inversions. EARTH SYSTEM SCIENCE DATA 2018; 10:87-107. [PMID: 31662803 PMCID: PMC6818511 DOI: 10.5194/essd-10-87-2018] [Citation(s) in RCA: 94] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
The Open-source Data Inventory for Anthropogenic CO2 (ODIAC) is a global high-spatial resolution gridded emission data product that distributes carbon dioxide (CO2) emissions from fossil fuel combustion. The emission spatial distributions are estimated at a 1×1 km spatial resolution over land using power plant profiles (emission intensity and geographical location) and satellite-observed nighttime lights. This paper describes the year 2016 version of the ODIAC emission data product (ODIAC2016) and presents analyses that help guiding data users, especially for atmospheric CO2 tracer transport simulations and flux inversion analysis. Since the original publication in 2011, we have made modifications to our emission modeling framework in order to deliver a comprehensive global gridded emission data product. Major changes from the 2011 publication are 1) the use of emissions estimates made by the Carbon Dioxide Information Analysis Center (CDIAC) at the Oak Ridge National Laboratory (ORNL) by fuel type (solid, liquid, gas, cement manufacturing, gas flaring and international aviation and marine bunkers), 2) the use of multiple spatial emission proxies by fuel type such as nightlight data specific to gas flaring and ship/aircraft fleet tracks and 3) the inclusion of emission temporal variations. Using global fuel consumption data, we extrapolated the CDIAC emissions estimates for the recent years and produced the ODIAC2016 emission data product that covers 2000-2015. Our emission data can be viewed as an extended version of CDIAC gridded emission data product, which should allow data users to impose global fossil fuel emissions in more comprehensive manner than original CDIAC product. Our new emission modeling framework allows us to produce future versions of ODIAC emission data product with a timely update. Such capability has become more significant given the CDIAC/ORNL's shutdown. ODIAC data product could play an important role to support carbon cycle science, especially modeling studies with space-based CO2 data collected near real time by ongoing carbon observing missions such as Japanese Greenhouse Observing SATellite (GOSAT), NASA's Orbiting Carbon Observatory 2 (OCO-2) and upcoming future missions. The ODIAC emission data product including the latest version of the ODIAC emission data (ODIAC2017, 2000-2016), is distributed from http://db.cger.nies.go.jp/dataset/ODIAC/ with a DOI.
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Affiliation(s)
- Tomohiro Oda
- Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
- Goddard Earth Sciences Technology and Research, Universities Space Research Association, Columbia, MD, USA
| | - Shamil Maksyutov
- Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba, Ibaraki, Japan
| | - Robert J Andres
- Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, Oak Ridge, TN, USA
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34
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A Fast Atmospheric Trace Gas Retrieval for Hyperspectral Instruments Approximating Multiple Scattering—Part 2: Application to XCO2 Retrievals from OCO-2. REMOTE SENSING 2017. [DOI: 10.3390/rs9111102] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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35
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The Orbiting Carbon Observatory (OCO-2) tracks 2-3 peta-gram increase in carbon release to the atmosphere during the 2014-2016 El Niño. Sci Rep 2017; 7:13567. [PMID: 29051612 PMCID: PMC5648889 DOI: 10.1038/s41598-017-13459-0] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2016] [Accepted: 09/25/2017] [Indexed: 11/09/2022] Open
Abstract
The powerful El Niño event of 2015-2016 - the third most intense since the 1950s - has exerted a large impact on the Earth's natural climate system. The column-averaged CO2 dry-air mole fraction (XCO2) observations from satellites and ground-based networks are analyzed together with in situ observations for the period of September 2014 to October 2016. From the differences between satellite (OCO-2) observations and simulations using an atmospheric chemistry-transport model, we estimate that, relative to the mean annual fluxes for 2014, the most recent El Niño has contributed to an excess CO2 emission from the Earth's surface (land + ocean) to the atmosphere in the range of 2.4 ± 0.2 PgC (1 Pg = 1015 g) over the period of July 2015 to June 2016. The excess CO2 flux is resulted primarily from reduction in vegetation uptake due to drought, and to a lesser degree from increased biomass burning. It is about the half of the CO2 flux anomaly (range: 4.4-6.7 PgC) estimated for the 1997/1998 El Niño. The annual total sink is estimated to be 3.9 ± 0.2 PgC for the assumed fossil fuel emission of 10.1 PgC. The major uncertainty in attribution arise from error in anthropogenic emission trends, satellite data and atmospheric transport.
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36
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Shirai T, Ishizawa M, Zhuravlev R, Ganshin A, Belikov D, Saito M, Oda T, Valsala V, Gomez-Pelaez AJ, Langenfelds R, Maksyutov S. A decadal inversion of CO 2 using the Global Eulerian-Lagrangian Coupled Atmospheric model (GELCA): sensitivity to the ground-based observation network. TELLUS. SERIES B, CHEMICAL AND PHYSICAL METEOROLOGY 2017; 69:1291158. [PMID: 32848290 PMCID: PMC7447134 DOI: 10.1080/16000889.2017.1291158] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
We present an assimilation system for atmospheric carbon dioxide (CO2) using a Global Eulerian-Lagrangian Coupled Atmospheric model (GELCA), and demonstrate its capability to capture the observed atmospheric CO2 mixing ratios and to estimate CO2 fluxes. With the efficient data handling scheme in GELCA, our system assimilates non-smoothed CO2 data from observational data products such as the Observation Package (ObsPack) data products as constraints on surface fluxes. We conducted sensitivity tests to examine the impact of the site selections and the prior uncertainty settings of observation on the inversion results. For these sensitivity tests, we made five different site/data selections from the ObsPack product. In all cases, the time series of the global net CO2 flux to the atmosphere stayed close to values calculated from the growth rate of the observed global mean atmospheric CO2 mixing ratio. At regional scales, estimated seasonal CO2 fluxes were altered, depending on the CO2 data selected for assimilation. Uncertainty reductions (URs) were determined at the regional scale and compared among cases. As measures of the model-data mismatch, we used the model-data bias, root-mean-square error, and the linear correlation. For most observation sites, the model-data mismatch was reasonably small. Regarding regional flux estimates, tropical Asia was one of the regions that showed a significant impact from the observation network settings. We found that the surface fluxes in tropical Asia were the most sensitive to the use of aircraft measurements over the Pacific, and the seasonal cycle agreed better with the results of bottom-up studies when the aircraft measurements were assimilated. These results confirm the importance of these aircraft observations, especially for constraining surface fluxes in the tropics.
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Affiliation(s)
- T Shirai
- Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba, Japan
| | - M Ishizawa
- Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba, Japan
| | - R Zhuravlev
- Central Aerological Observatory, Dolgoprudny, Russia
| | - A Ganshin
- Central Aerological Observatory, Dolgoprudny, Russia
| | - D Belikov
- Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba, Japan
- Tomsk State University, Tomsk, Russia
- National Institute of Polar Research, Tachikawa, Japan
| | - M Saito
- Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba, Japan
| | - T Oda
- Goddard Earth Sciences Technology and Research, Universities Space Research Association, Columbia, MD, USA / Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
| | - V Valsala
- Indian Institute for Tropical Meteorology
| | - A J Gomez-Pelaez
- Izaña Atmospheric Research Center, Meteorological State Agency of Spain, Izaña, Spain
| | - R Langenfelds
- Oceans and Atmosphere Flagship, Commonwealth Scientific and Industrial Research Organization, Aspendale, Australia
| | - S Maksyutov
- Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba, Japan
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Bastos A, Janssens IA, Gouveia CM, Trigo RM, Ciais P, Chevallier F, Peñuelas J, Rödenbeck C, Piao S, Friedlingstein P, Running SW. European land CO2 sink influenced by NAO and East-Atlantic Pattern coupling. Nat Commun 2016; 7:10315. [PMID: 26777730 PMCID: PMC4735626 DOI: 10.1038/ncomms10315] [Citation(s) in RCA: 58] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2015] [Accepted: 11/27/2015] [Indexed: 11/20/2022] Open
Abstract
Large-scale climate patterns control variability in the global carbon sink. In Europe, the North-Atlantic Oscillation (NAO) influences vegetation activity, however the East-Atlantic (EA) pattern is known to modulate NAO strength and location. Using observation-driven and modelled data sets, we show that multi-annual variability patterns of European Net Biome Productivity (NBP) are linked to anomalies in heat and water transport controlled by the NAO-EA interplay. Enhanced NBP occurs when NAO and EA are both in negative phase, associated with cool summers with wet soils which enhance photosynthesis. During anti-phase periods, NBP is reduced through distinct impacts of climate anomalies in photosynthesis and respiration. The predominance of anti-phase years in the early 2000s may explain the European-wide reduction of carbon uptake during this period, reported in previous studies. Results show that improving the capability of simulating atmospheric circulation patterns may better constrain regional carbon sink variability in coupled carbon-climate models.
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Affiliation(s)
- Ana Bastos
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, F-91191 Gif-sur-Yvette, France
- Instituto Dom Luiz, IDL, Faculdade de Ciências, Universidade de Lisboa, Lisboa 1749-016, Portugal
| | - Ivan A. Janssens
- Department of Biology, University of Antwerp, Universiteitsplein 1, 2610 Wilrijk, Belgium
| | - Célia M. Gouveia
- Instituto Dom Luiz, IDL, Faculdade de Ciências, Universidade de Lisboa, Lisboa 1749-016, Portugal
| | - Ricardo M. Trigo
- Instituto Dom Luiz, IDL, Faculdade de Ciências, Universidade de Lisboa, Lisboa 1749-016, Portugal
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, F-91191 Gif-sur-Yvette, France
| | - Frédéric Chevallier
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, F-91191 Gif-sur-Yvette, France
| | - Josep Peñuelas
- CREAF, Cerdanyola del Vallès, Catalonia, 08193 Barcelona, Spain
- CSIC, Global Ecology Unit CREAF-CSIC-UAB, Cerdanyola del Vallès, Catalonia, 08193 Barcelona, Spain
| | | | - Shilong Piao
- Department of Ecology, College of Urban and Environmental Sciences, Peking University 5 Yiheyuan Road, Haidian District, Beijing 100871, China
| | - Pierre Friedlingstein
- College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter EX4 4QF, UK
| | - Steven W. Running
- Numerical Terradynamic Simulation Group, University of Montana, Missoula, Montana 59812, USA
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38
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Poulter B, Frank D, Ciais P, Myneni RB, Andela N, Bi J, Broquet G, Canadell JG, Chevallier F, Liu YY, Running SW, Sitch S, van der Werf GR. Contribution of semi-arid ecosystems to interannual variability of the global carbon cycle. Nature 2014; 509:600-3. [PMID: 24847888 DOI: 10.1038/nature13376] [Citation(s) in RCA: 380] [Impact Index Per Article: 38.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2013] [Accepted: 04/10/2014] [Indexed: 11/09/2022]
Abstract
The land and ocean act as a sink for fossil-fuel emissions, thereby slowing the rise of atmospheric carbon dioxide concentrations. Although the uptake of carbon by oceanic and terrestrial processes has kept pace with accelerating carbon dioxide emissions until now, atmospheric carbon dioxide concentrations exhibit a large variability on interannual timescales, considered to be driven primarily by terrestrial ecosystem processes dominated by tropical rainforests. We use a terrestrial biogeochemical model, atmospheric carbon dioxide inversion and global carbon budget accounting methods to investigate the evolution of the terrestrial carbon sink over the past 30 years, with a focus on the underlying mechanisms responsible for the exceptionally large land carbon sink reported in 2011 (ref. 2). Here we show that our three terrestrial carbon sink estimates are in good agreement and support the finding of a 2011 record land carbon sink. Surprisingly, we find that the global carbon sink anomaly was driven by growth of semi-arid vegetation in the Southern Hemisphere, with almost 60 per cent of carbon uptake attributed to Australian ecosystems, where prevalent La Niña conditions caused up to six consecutive seasons of increased precipitation. In addition, since 1981, a six per cent expansion of vegetation cover over Australia was associated with a fourfold increase in the sensitivity of continental net carbon uptake to precipitation. Our findings suggest that the higher turnover rates of carbon pools in semi-arid biomes are an increasingly important driver of global carbon cycle inter-annual variability and that tropical rainforests may become less relevant drivers in the future. More research is needed to identify to what extent the carbon stocks accumulated during wet years are vulnerable to rapid decomposition or loss through fire in subsequent years.
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Affiliation(s)
- Benjamin Poulter
- 1] Montana State University, Institute on Ecosystems and the Department of Ecology, Bozeman, Montana 59717, USA [2] Laboratoire des Sciences du Climat et de l'Environnement (LSCE), CEA CNRS UVSQ, 91191 Gif Sur Yvette, France
| | - David Frank
- 1] Swiss Federal Research Institute WSL, Dendroclimatology, Zürcherstrasse 111, Birmensdorf 8903, Switzerland [2] Oeschger Centre for Climate Change Research, University of Bern, CH-3012 Bern, Switzerland
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement (LSCE), CEA CNRS UVSQ, 91191 Gif Sur Yvette, France
| | - Ranga B Myneni
- Department of Earth and Environment, Boston University, 685 Commonwealth Avenue, Boston, Massachusetts 02215, USA
| | - Niels Andela
- Faculty of Earth and Life Sciences, VU University Amsterdam, 1085 De Boelelaan, 1081HV, Amsterdam, The Netherlands
| | - Jian Bi
- Department of Earth and Environment, Boston University, 685 Commonwealth Avenue, Boston, Massachusetts 02215, USA
| | - Gregoire Broquet
- Laboratoire des Sciences du Climat et de l'Environnement (LSCE), CEA CNRS UVSQ, 91191 Gif Sur Yvette, France
| | - Josep G Canadell
- Global Carbon Project, CSIRO, Marine and Atmospheric Research, Canberra, Australian Capital Territory 2601, Australia
| | - Frederic Chevallier
- Laboratoire des Sciences du Climat et de l'Environnement (LSCE), CEA CNRS UVSQ, 91191 Gif Sur Yvette, France
| | - Yi Y Liu
- ARC Centre of Excellence for Climate Systems Science & Climate Change Research Centre, University of New South Wales, Sydney, New South Wales 2052, Australia
| | - Steven W Running
- Department of Ecosystem and Conservation Sciences, University of Montana, Missoula, Montana 59812, USA
| | - Stephen Sitch
- College of Engineering, Computing and Mathematics, University of Exeter, Exeter EX4 4QF, UK
| | - Guido R van der Werf
- Faculty of Earth and Life Sciences, VU University Amsterdam, 1085 De Boelelaan, 1081HV, Amsterdam, The Netherlands
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40
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Peng S, Piao S, Ciais P, Myneni RB, Chen A, Chevallier F, Dolman AJ, Janssens IA, Peñuelas J, Zhang G, Vicca S, Wan S, Wang S, Zeng H. Asymmetric effects of daytime and night-time warming on Northern Hemisphere vegetation. Nature 2013; 501:88-92. [PMID: 24005415 DOI: 10.1038/nature12434] [Citation(s) in RCA: 184] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2012] [Accepted: 07/04/2013] [Indexed: 11/09/2022]
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41
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Niwa Y, Machida T, Sawa Y, Matsueda H, Schuck TJ, Brenninkmeijer CAM, Imasu R, Satoh M. Imposing strong constraints on tropical terrestrial CO2fluxes using passenger aircraft based measurements. ACTA ACUST UNITED AC 2012. [DOI: 10.1029/2012jd017474] [Citation(s) in RCA: 68] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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42
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Broquet G, Chevallier F, Rayner P, Aulagnier C, Pison I, Ramonet M, Schmidt M, Vermeulen AT, Ciais P. A European summertime CO2biogenic flux inversion at mesoscale from continuous in situ mixing ratio measurements. ACTA ACUST UNITED AC 2011. [DOI: 10.1029/2011jd016202] [Citation(s) in RCA: 52] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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43
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Pickett-Heaps CA, Rayner PJ, Law RM, Ciais P, Patra PK, Bousquet P, Peylin P, Maksyutov S, Marshall J, Rödenbeck C, Langenfelds RL, Steele LP, Francey RJ, Tans P, Sweeney C. Atmospheric CO2inversion validation using vertical profile measurements: Analysis of four independent inversion models. ACTA ACUST UNITED AC 2011. [DOI: 10.1029/2010jd014887] [Citation(s) in RCA: 38] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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