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  • 1
    Publication Date: 2023-11-21
    Description: The global forest age dataset (GFAD v.1.1) provides a correction to GFAD v1.0, as well as its uncertainties. GFAD describes the age distributions of plant functional types (PFT) on a 0.5-degree grid. Each grid cell contains information on the fraction of each PFT within an age class. The four PFTs, needleaf evergreen (NEEV), needleleaf deciduous (NEDE), broadleaf evergreen (BREV) and broadleaf deciduous (BRDC) are mapped from the MODIS Collection 5.1 land cover dataset, crosswalking land cover types to PFT fractions. The source of data for the age distributions is from country-level forest inventory for temperate and high-latitude countries, and from biomass for tropical countries. The inventory and biomass data are related to fifteen age classes defined in ten-year intervals, from 1-10 up to a class greater than 150 years old. The uncertainties are estimated for the inventory derived forest age classes as +/- 40% of the mean age. For the areas where age is derived from aboveground biomass, the uncertainty is derived from the 5th and 95th percentile estimates of biomass, but using the same age-aboveground biomass curves. The GFAD dataset represents the 2000-2010 era.
    Type: Dataset
    Format: application/zip, 30.3 MBytes
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  • 2
    Publication Date: 2023-11-21
    Description: The global forest age dataset (GFAD) describes the age distributions of plant functional types (PFT) on a 0.5-degree grid. Each grid cell contains information on the fraction of each PFT within an age class. The four PFTs, needleaf evergreen (NEEV), needleleaf deciduous (NEDE), broadleaf evergreen (BREV) and broadleaf deciduous (BRDC) are mapped from the MODIS Collection 5.1 land cover dataset, crosswalking land cover types to PFT fractions. The source of data for the age distributions is from country-level forest inventory for temperate and high-latitude countries, and from biomass for tropical countries. The inventory and biomass data are related to fifteen age classes defined in ten-year intervals, from 1-10 up to a class greater than 150 years old. The GFAD dataset represents the 2000-2010 era.
    Type: Dataset
    Format: application/zip, 10.1 MBytes
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  • 3
    Publication Date: 2021-01-05
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
    Format: application/pdf
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  • 4
    Publication Date: 2023-02-08
    Description: Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate – the “global carbon budget” – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesize data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFOS) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2010–2019), EFOS was 9.6 ± 0.5 GtC yr−1 excluding the cement carbonation sink (9.4 ± 0.5 GtC yr−1 when the cement carbonation sink is included), and ELUC was 1.6 ± 0.7 GtC yr−1. For the same decade, GATM was 5.1 ± 0.02 GtC yr−1 (2.4 ± 0.01 ppm yr−1), SOCEAN 2.5 ±  0.6 GtC yr−1, and SLAND 3.4 ± 0.9 GtC yr−1, with a budget imbalance BIM of −0.1 GtC yr−1 indicating a near balance between estimated sources and sinks over the last decade. For the year 2019 alone, the growth in EFOS was only about 0.1 % with fossil emissions increasing to 9.9 ± 0.5 GtC yr−1 excluding the cement carbonation sink (9.7 ± 0.5 GtC yr−1 when cement carbonation sink is included), and ELUC was 1.8 ± 0.7 GtC yr−1, for total anthropogenic CO2 emissions of 11.5 ± 0.9 GtC yr−1 (42.2 ± 3.3 GtCO2). Also for 2019, GATM was 5.4 ± 0.2 GtC yr−1 (2.5 ± 0.1 ppm yr−1), SOCEAN was 2.6 ± 0.6 GtC yr−1, and SLAND was 3.1 ± 1.2 GtC yr−1, with a BIM of 0.3 GtC. The global atmospheric CO2 concentration reached 409.85 ± 0.1 ppm averaged over 2019. Preliminary data for 2020, accounting for the COVID-19-induced changes in emissions, suggest a decrease in EFOS relative to 2019 of about −7 % (median estimate) based on individual estimates from four studies of −6 %, −7 %, −7 % (−3 % to −11 %), and −13 %. Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2019, but discrepancies of up to 1 GtC yr−1 persist for the representation of semi-decadal variability in CO2 fluxes. Comparison of estimates from diverse approaches and observations shows (1) no consensus in the mean and trend in land-use change emissions over the last decade, (2) a persistent low agreement between the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) an apparent discrepancy between the different methods for the ocean sink outside the tropics, particularly in the Southern Ocean. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this data set (Friedlingstein et al., 2019; Le Quéré et al., 2018b, a, 2016, 2015b, a, 2014, 2013). The data presented in this work are available at https://doi.org/10.18160/gcp-2020 (Friedlingstein et al., 2020).
    Type: Article , PeerReviewed
    Format: text
    Format: archive
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