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      Neutral Tropical African CO 2 Exchange Estimated From Aircraft and Satellite Observations

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          Abstract

          Tropical lands play an important role in the global carbon cycle yet their contribution remains uncertain owing to sparse observations. Satellite observations of atmospheric carbon dioxide (CO 2) have greatly increased spatial coverage over tropical regions, providing the potential for improved estimates of terrestrial fluxes. Despite this advancement, the spread among satellite‐based and in‐situ atmospheric CO 2 flux inversions over northern tropical Africa (NTA), spanning 0–24°N, remains large. Satellite‐based estimates of an annual source of 0.8–1.45 PgC yr −1 challenge our understanding of tropical and global carbon cycling. Here, we compare posterior mole fractions from the suite of inversions participating in the Orbiting Carbon Observatory 2 (OCO‐2) Version 10 Model Intercomparison Project (v10 MIP) with independent in‐situ airborne observations made over the tropical Atlantic Ocean by the National Aeronautics and Space Administration (NASA) Atmospheric Tomography (ATom) mission during four seasons. We develop emergent constraints on tropical African CO 2 fluxes using flux‐concentration relationships defined by the model suite. We find an annual flux of 0.14 ± 0.39 PgC yr −1 (mean and standard deviation) for NTA, 2016–2018. The satellite‐based flux bias suggests a potential positive concentration bias in OCO‐2 B10 and earlier version retrievals over land in NTA during the dry season. Nevertheless, the OCO‐2 observations provide improved flux estimates relative to the in situ observing network at other times of year, indicating stronger uptake in NTA during the wet season than the in‐situ inversion estimates.

          Plain Language Summary

          Satellite carbon dioxide (CO 2) observations over land imply a major revision to our understanding of the global carbon cycle linked to large emissions from northern tropical Africa (NTA) during the dry season, from October to May. We use aircraft observations made over the Atlantic Ocean in four seasons to evaluate flux models driven by a range of ground and satellite observations. Our results show that models using satellite observations over land overestimate annual emissions from NTA by approximately 1 PgC yr −1, concentrated in the dry season. At other times of year, satellite CO 2 observations provide improved estimates of NTA exchange, with a stronger CO 2 uptake during the wet season.

          Key Points

          • Emergent constraints derived from aircraft carbon dioxide (CO2) measurements and inversions estimate a near neutral northern tropical African CO2 budget

          • Inversions using satellite observations overestimate annual emissions from northern tropical Africa (NTA) by approximately 1 PgC yr−1

          • Satellite CO2 observations imply a strong sink during the wet season over NTA

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          A large and persistent carbon sink in the world's forests.

          The terrestrial carbon sink has been large in recent decades, but its size and location remain uncertain. Using forest inventory data and long-term ecosystem carbon studies, we estimate a total forest sink of 2.4 ± 0.4 petagrams of carbon per year (Pg C year(-1)) globally for 1990 to 2007. We also estimate a source of 1.3 ± 0.7 Pg C year(-1) from tropical land-use change, consisting of a gross tropical deforestation emission of 2.9 ± 0.5 Pg C year(-1) partially compensated by a carbon sink in tropical forest regrowth of 1.6 ± 0.5 Pg C year(-1). Together, the fluxes comprise a net global forest sink of 1.1 ± 0.8 Pg C year(-1), with tropical estimates having the largest uncertainties. Our total forest sink estimate is equivalent in magnitude to the terrestrial sink deduced from fossil fuel emissions and land-use change sources minus ocean and atmospheric sinks.
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            Classifying drivers of global forest loss

            Global maps of forest loss depict the scale and magnitude of forest disturbance, yet companies, governments, and nongovernmental organizations need to distinguish permanent conversion (i.e., deforestation) from temporary loss from forestry or wildfire. Using satellite imagery, we developed a forest loss classification model to determine a spatial attribution of forest disturbance to the dominant drivers of land cover and land use change over the period 2001 to 2015. Our results indicate that 27% of global forest loss can be attributed to deforestation through permanent land use change for commodity production. The remaining areas maintained the same land use over 15 years; in those areas, loss was attributed to forestry (26%), shifting agriculture (24%), and wildfire (23%). Despite corporate commitments, the rate of commodity-driven deforestation has not declined. To end deforestation, companies must eliminate 5 million hectares of conversion from supply chains each year.
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              Is Open Access

              Global fire emissions estimates during 1997–2016

              Climate, land use, and other anthropogenic and natural drivers have the potential to influence fire dynamics in many regions. To develop a mechanistic understanding of the changing role of these drivers and their impact on atmospheric composition, long-term fire records are needed that fuse information from different satellite and in situ data streams. Here we describe the fourth version of the Global Fire Emissions Database (GFED) and quantify global fire emissions patterns during 1997–2016. The modeling system, based on the Carnegie–Ames–Stanford Approach (CASA) biogeochemical model, has several modifications from the previous version and uses higher quality input datasets. Significant upgrades include (1) new burned area estimates with contributions from small fires, (2) a revised fuel consumption parameterization optimized using field observations, (3) modifications that improve the representation of fuel consumption in frequently burning landscapes, and (4) fire severity estimates that better represent continental differences in burning processes across boreal regions of North America and Eurasia. The new version has a higher spatial resolution (0.25°) and uses a different set of emission factors that separately resolves trace gas and aerosol emissions from temperate and boreal forest ecosystems. Global mean carbon emissions using the burned area dataset with small fires (GFED4s) were 2.2  ×  10 15  grams of carbon per year (Pg C yr −1 ) during 1997–2016, with a maximum in 1997 (3.0 Pg C yr −1 ) and minimum in 2013 (1.8 Pg C yr −1 ). These estimates were 11 % higher than our previous estimates (GFED3) during 1997–2011, when the two datasets overlapped. This net increase was the result of a substantial increase in burned area (37 %), mostly due to the inclusion of small fires, and a modest decrease in mean fuel consumption (−19 %) to better match estimates from field studies, primarily in savannas and grasslands. For trace gas and aerosol emissions, differences between GFED4s and GFED3 were often larger due to the use of revised emission factors. If small fire burned area was excluded (GFED4 without the s for small fires), average emissions were 1.5 Pg C yr −1 . The addition of small fires had the largest impact on emissions in temperate North America, Central America, Europe, and temperate Asia. This small fire layer carries substantial uncertainties; improving these estimates will require use of new burned area products derived from high-resolution satellite imagery. Our revised dataset provides an internally consistent set of burned area and emissions that may contribute to a better understanding of multi-decadal changes in fire dynamics and their impact on the Earth system. GFED data are available from http://www.globalfiredata.org .
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                Journal
                Global Biogeochemical Cycles
                Global Biogeochemical Cycles
                American Geophysical Union (AGU)
                0886-6236
                1944-9224
                December 2023
                December 21 2023
                December 2023
                : 37
                : 12
                Affiliations
                [1 ] Atmospheric Chemistry Observations & Modeling Laboratory (ACOM) NSF National Center for Atmospheric Research (NSF NCAR) Boulder CO USA
                [2 ] Earth Observing Laboratory (EOL) NSF National Center for Atmospheric Research (NSF NCAR) Boulder CO USA
                [3 ] Cooperative Institute for Research in the Atmosphere Colorado State University Fort Collins CO USA
                [4 ] Global Modeling and Assimilation Office National Aeronautics and Space Administration Goddard Space Flight Center Greenbelt MD USA
                [5 ] Earth System Science Interdisciplinary Center University of Maryland College Park MD USA
                [6 ] School of Mathematics and Applied Statistics University of Wollongong Wollongong Australia
                [7 ] Jet Propulsion Laboratory California Institute of Technology Pasadena CA USA
                [8 ] Laboratoire des Sciences du Climat et de L’Environnement Institut Pierre‐Simon Laplace CEA‐CNRS‐UVSQ CEDEX France
                [9 ] Department of Earth & Environmental Sciences Lamont‐Doherty Earth Observatory Columbia University Palisades NY USA
                [10 ] Department of Physics University of Toronto Toronto ON Canada
                [11 ] Earth Science Division NASA Ames Research Center Moffett Field CA USA
                [12 ] National Institute for Environmental Studies Tsukuba Japan
                [13 ] Cooperative Institute for Research in Environmental Sciences University of Colorado Boulder Boulder CO USA
                [14 ] NOAA Global Monitoring Laboratory Boulder CO USA
                [15 ] State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric Physics Chinese Academy of Sciences Beijing China
                [16 ] Scripps Institution of Oceanography University of California San Diego CA USA
                [17 ] Centre for Atmospheric Sciences Indian Institute of Technology Delhi New Delhi India
                [18 ] NOAA Chemical Sciences Laboratory Boulder CO USA
                [19 ] Universities Space Research Association Columbia MD USA
                [20 ] NASA Goddard Space Flight Center Greenbelt MD USA
                [21 ] BeZero Carbon Ltd Gorsuch Place Senna Building, E2 8JF London UK
                [22 ] Department of Earth Sciences Vrije Universiteit Amsterdam 1081 HV The Netherlands
                [23 ] School of Engineering and Applied Science and Department of Earth and Planetary Sciences Harvard University Cambridge MA USA
                [24 ] Department of Atmospheric and Oceanic Science and Earth System Science Interdisciplinary Center University of Maryland College Park MD USA
                Article
                10.1029/2023GB007804
                2b01f0a2-f8a0-4ac6-a1e1-a37a631c580a
                © 2023

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