Land-use harmonization datasets for annual global carbon budgets
<p>Land-use change has been the dominant source of anthropogenic carbon emissions for most of the historical period and is currently one of the largest and most uncertain components of the global carbon cycle. Advancing the scientific understanding on this topic requires that the best data be...
Main Authors: | , , , , , , , , , , |
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Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2021-08-01
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Series: | Earth System Science Data |
Online Access: | https://essd.copernicus.org/articles/13/4175/2021/essd-13-4175-2021.pdf |
Summary: | <p>Land-use change has been the dominant source of anthropogenic
carbon emissions for most of the historical period and is currently one of
the largest and most uncertain components of the global carbon cycle.
Advancing the scientific understanding on this topic requires that the best
data be used as input to state-of-the-art models in well-organized
scientific assessments. The Land-Use Harmonization 2 dataset (LUH2),
previously developed and used as input for simulations of the 6th Coupled Model Intercomparison
Project (CMIP6), has been
updated annually to provide required input to land models in the annual
Global Carbon Budget (GCB) assessments. Here we discuss the methodology for
producing these annual LUH2-GCB updates and extensions which incorporate
annual wood harvest data updates from the Food and Agriculture Organization
(FAO) of the United Nations for dataset years after 2015 and the History
Database of the Global Environment (HYDE) gridded cropland and grazing area
data updates (based on annual FAO cropland and grazing area data updates)
for dataset years after 2012, along with extrapolations to the current year
due to a lag of 1 or more years in the FAO data releases. The resulting
updated LUH2-GCB datasets have provided global, annual gridded land-use and
land-use-change data relating to agricultural expansion, deforestation, wood
harvesting, shifting cultivation, regrowth and afforestation, crop
rotations, and pasture management and are used by both bookkeeping models
and dynamic global vegetation models (DGVMs) for the GCB. For GCB 2019, a
more significant update to LUH2 was produced, LUH2-GCB2019
(<a href="https://doi.org/10.3334/ORNLDAAC/1851">https://doi.org/10.3334/ORNLDAAC/1851</a>, Chini et al., 2020b), to take
advantage of new data inputs that corrected cropland and grazing areas in
the globally important region of Brazil as far back as 1950. From 1951 to 2012
the LUH2-GCB2019 dataset begins to diverge from the version of LUH2 used for
the World Climate Research Programme's CMIP6, with peak differences in Brazil in the year 2000 for
grazing land (difference of 100 000 km<span class="inline-formula"><sup>2</sup></span>) and in the year 2009 for
cropland (difference of 77 000 km<span class="inline-formula"><sup>2</sup></span>), along with significant
sub-national reorganization of agricultural land-use patterns within Brazil.
The LUH2-GCB2019 dataset provides the base for future LUH2-GCB updates,
including the recent LUH2-GCB2020 dataset, and presents a starting point for
operationalizing the creation of these datasets to reduce time lags due to
the multiple input dataset and model latencies.</p> |
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ISSN: | 1866-3508 1866-3516 |