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Dataset . 2023
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ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2023
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ZENODO
Dataset . 2023
License: CC BY
Data sources: ZENODO
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Harmonising the land-use flux estimates of global models and national inventories for 2000-2020: background data

Authors: Grassi, Giacomo; Schwingshackl, Clemens; Gasser, Thomas; Houghton, Richard A.; Sitch, Steven; Canadell, Joseph G.; Cescatti, Alessandro; +25 Authors

Harmonising the land-use flux estimates of global models and national inventories for 2000-2020: background data

Abstract

This online repository includes all the relevant data used in the paper "Harmonizing the land-use flux estimates of global models and national inventories for 2000-2020" (Grassi et al. 2023), plus some additional methodological information, organised in the following files: 1) "Global models land CO2 data 2000-2020" (MS Excel Format), including for each country data for: a. Land-use CO2 fluxes from each of three Bookkeeping Models (BMs) used, and for different categories (net LULUCF, deforestation, forest, other transitions, organic soils). b. The ensemble mean of the ‘natural terrestrial sink’ estimated by 16 Dynamic Global Vegetation Models (DGVMs), filtered with maps of intact/non-intact forest. The global model data included here are consistent with those included in the Global Carbon Budget 2022 (Friedlingstein et al., 2022). 2) “National inventories LULUCF data 2000-2020” (version Dec 2022, MS Excel Format), including a comprehensive collection of LULUCF CO2 data based on countries' submissions to the United Nations Framework Convention on Climate Change (UNFCCC). The data here represent a slight update of the dataset included in Grassi et al. (2022). 3) “Processing steps for DGVM results”, describing the protocol used to filter the results of DGVMs with maps of intact/non-intact forest and further details on the maps (PDF Format). 4) “Intact and non-intact forest maps”, available in two files with different resolutions (0.5 and 0.05 degrees) in NetCDF format. Grassi et al. (2023) used the 0.5 degree resolution. 5) "IntactAndNonIntactForest_0.5deg_script.js", the Google Earth Engine Java script to produce the forest maps (.js/text format) For further details, please refer to: Grassi et al. (2023) Harmonising the land-use flux estimates of global models and national inventories for 2000-2020. Earth Syst. Sci. Data. Other references: Friedlingstein et al. (2022) Global Carbon Budget 2022, Earth Syst. Sci. Data, 14, 4811–4900. Grassi et al (2022) Carbon fluxes from land 2000–2020: bringing clarity to countries' reporting. Earth Syst. Sci. Data, 14, 4643-4666.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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