scholarly journals Supplementary material to "Downscaling land use and land cover from the Global Change Assessment Model for coupling with Earth system models"

2016 ◽  
Author(s):  
Yannick Le Page ◽  
Tris O’Brien West ◽  
Robert Link ◽  
Pralit Patel
Keyword(s):  
Land Use ◽  
Global Change ◽  
Land Cover ◽  
Assessment Model ◽  
Earth System ◽  
Change Assessment ◽  
System Models ◽  
Global Change Assessment Model ◽  
Supplementary Material ◽  
Earth System Models

scholarly journals Downscaling land use and land cover from the Global Change Assessment Model for coupling with Earth system models

2016 ◽  
Vol 9 (9) ◽  
pp. 3055-3069 ◽  
Author(s):  
Yannick Le Page ◽  
Tris O. West ◽  
Robert Link ◽  
Pralit Patel
Keyword(s):  
Land Use ◽  
Global Change ◽  
Land Cover ◽  
Integrated Assessment Model ◽  
Assessment Model ◽  
Critical Parameters ◽  
Reference Scenario ◽  
Change Assessment ◽  
Global Change Assessment Model ◽  
Wide Range

Abstract. The Global Change Assessment Model (GCAM) is a global integrated assessment model used to project future societal and environmental scenarios, based on economic modeling and on a detailed representation of food and energy production systems. The terrestrial module in GCAM represents agricultural activities and ecosystems dynamics at the subregional scale, and must be downscaled to be used for impact assessments in gridded models (e.g., climate models). In this study, we present the downscaling algorithm of the GCAM model, which generates gridded time series of global land use and land cover (LULC) from any GCAM scenario. The downscaling is based on a number of user-defined rules and drivers, including transition priorities (e.g., crop expansion preferentially into grasslands rather than forests) and spatial constraints (e.g., nutrient availability). The default parameterization is evaluated using historical LULC change data, and a sensitivity experiment provides insights on the most critical parameters and how their influence changes regionally and in time. Finally, a reference scenario and a climate mitigation scenario are downscaled to illustrate the gridded land use outcomes of different policies on agricultural expansion and forest management. Several features of the downscaling can be modified by providing new input data or changing the parameterization, without any edits to the code. Those features include spatial resolution as well as the number and type of land classes being downscaled, thereby providing flexibility to adapt GCAM LULC scenarios to the requirements of a wide range of models and applications. The downscaling system is version controlled and freely available.

scholarly journals Downscaling land use and land cover from the Global Change Assessment Model for coupling with Earth system models

2016 ◽  
Author(s):  
Yannick Le Page ◽  
Tris O’Brien West ◽  
Robert Link ◽  
Pralit Patel
Keyword(s):  
Land Use ◽  
Global Change ◽  
Land Cover ◽  
Integrated Assessment Model ◽  
Assessment Model ◽  
Critical Parameters ◽  
Reference Scenario ◽  
Change Assessment ◽  
Global Change Assessment Model ◽  
Wide Range

Abstract. The Global Change Assessment Model (GCAM) is a global integrated assessment model used to project future societal and environmental scenarios, based on economic modeling and on a detailed representation of food and energy production systems. The terrestrial module in GCAM represents agricultural activities and ecosystems dynamics at the sub-regional scale, and must be downscaled to be used for impact assessments in gridded models (e.g. climate models). In this study, we present the downscaling algorithm of the GCAM model, which generates gridded time series of global land use and land cover (LULC) from any GCAM scenario. The downscaling is based on a number of user-defined rules and drivers, including transition priorities (e.g. crop expansion preferentially into grasslands rather than forests) and spatial constraints (e.g. nutrient availability). The default parameterization is evaluated using historical LULC change data, and a sensitivity experiment provides insights on the most critical parameters and how their influence changes regionally and in time. Finally, a reference scenario and a climate mitigation scenario are downscaled to illustrate the gridded land use outcomes of different policies on agricultural expansion and forest management. Several features of the downscaling can be modified by providing new input data or changing the parameterization, without any edits to the code. Those features include spatial resolution as well as the number and type of land classes being downscaled, thereby providing flexibility to adapt GCAM LULC scenarios to the requirements of a wide range of models and applications. The downscaling system is version controlled and freely available.

scholarly journals Mapping past human land use using archaeological data: A new classification for global land use synthesis and data harmonization

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0246662 ◽  
Author(s):  
Kathleen D. Morrison ◽  
Emily Hammer ◽  
Oliver Boles ◽  
Marco Madella ◽  
Nicola Whitehouse ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Classification Scheme ◽  
Earth System ◽  
Land Use Systems ◽  
System Models ◽  
The Past ◽  
The Earth ◽  
Earth System Models ◽  
Past Land Use

In the 12,000 years preceding the Industrial Revolution, human activities led to significant changes in land cover, plant and animal distributions, surface hydrology, and biochemical cycles. Earth system models suggest that this anthropogenic land cover change influenced regional and global climate. However, the representation of past land use in earth system models is currently oversimplified. As a result, there are large uncertainties in the current understanding of the past and current state of the earth system. In order to improve representation of the variety and scale of impacts that past land use had on the earth system, a global effort is underway to aggregate and synthesize archaeological and historical evidence of land use systems. Here we present a simple, hierarchical classification of land use systems designed to be used with archaeological and historical data at a global scale and a schema of codes that identify land use practices common to a range of systems, both implemented in a geospatial database. The classification scheme and database resulted from an extensive process of consultation with researchers worldwide. Our scheme is designed to deliver consistent, empirically robust data for the improvement of land use models, while simultaneously allowing for a comparative, detailed mapping of land use relevant to the needs of historical scholars. To illustrate the benefits of the classification scheme and methods for mapping historical land use, we apply it to Mesopotamia and Arabia at 6 kya (c. 4000 BCE). The scheme will be used to describe land use by the Past Global Changes (PAGES) LandCover6k working group, an international project comprised of archaeologists, historians, geographers, paleoecologists, and modelers. Beyond this, the scheme has a wide utility for creating a common language between research and policy communities, linking archaeologists with climate modelers, biodiversity conservation workers and initiatives.

scholarly journals Scenario-Based Analysis on the Structural Change of Land Uses in China

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Qian Xu ◽  
Qunou Jiang ◽  
Kai Cao ◽  
Xing Li ◽  
Xiangzheng Deng
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Global Change ◽  
Land Use Change ◽  
Global Environmental Change ◽  
Structure Change ◽  
Assessment Model ◽  
Change Assessment ◽  
Global Change Assessment Model ◽  
The Impact

Land Use/Land Cover change (LUCC) is a key aspect of global environmental change, which has a significant impact on climate change. In the background of increasing global warming resulting from greenhouse effect, to understand the impact of land use change on climate change is necessary and meaningful. In this study, we choose China as the study area and explore the possible land use change trends based on the AgLU module and ERB module of global change assessment model (GCAM model and Global Change Assessment Model). We design three scenarios based on socioeconomic development and simulated the corresponding structure change of land use according to the three scenarios with different parameters. Then we simulate the different emission of CO2under different scenarios based on the simulation results of structure change of land use. At last, we choose the most suitable scenario that could control the emission of CO2best and obtain the relatively better land use structure change for adaption of climate change. Through this research we can provide a theoretical basis for the future land use planning to adapt to climate change.

scholarly journals Plant functional type mapping for earth system models

2011 ◽  
Vol 4 (3) ◽  
pp. 2081-2121 ◽  
Author(s):  
B. Poulter ◽  
P. Ciais ◽  
E. Hodson ◽  
H. Lischke ◽  
F. Maignan ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Climate Variability ◽  
Forest Cover ◽  
Plant Functional Type ◽  
Earth System ◽  
Functional Type ◽  
System Models ◽  
Satellite Sensors ◽  
Earth System Models

Abstract. The sensitivity of global carbon and water cycling to climate variability is coupled directly to land cover and the distribution of vegetation. To investigate biogeochemistry-climate interactions, earth system models require a representation of vegetation distributions that are either prescribed from remote sensing data or simulated via biogeography models. However, the abstraction of earth system state variables in models means that data products derived from remote sensing need to be post-processed for model-data assimilation. Dynamic global vegetation models (DGVM) rely on the concept of plant functional types (PFT) to group shared traits of thousands of plant species into just several classes. Available databases of observed PFT distributions must be relevant to existing satellite sensors and their derived products, and to the present day distribution of managed lands. Here, we develop four PFT datasets based on land-cover information from three satellite sensors (EOS-MODIS 1 km and 0.5 km, SPOT4-VEGETATION 1 km, and ENVISAT-MERIS 0.3 km spatial resolution) that are merged with spatially-consistent Köppen-Geiger climate zones. Using a beta (β) diversity metric to assess reclassification similarity, we find that the greatest uncertainty in PFT classifications occur most frequently between cropland and grassland categories, and in dryland systems between shrubland, grassland and forest categories because of differences in the minimum threshold required for forest cover. The biogeography-biogeochemistry DGVM, LPJmL, is used in diagnostic mode with the four PFT datasets prescribed to quantify the effect of land-cover uncertainty on climatic sensitivity of gross primary productivity (GPP) and transpiration fluxes. Our results show that land-cover uncertainty has large effects in arid regions, contributing up to 30 % (20 %) uncertainty in the sensitivity of GPP (transpiration) to precipitation. The availability of plant functional type datasets that are consistent with current satellite products and adapted for earth system models is an important component for reducing the uncertainty of terrestrial biogeochemistry to climate variability.

scholarly journals From land use to land cover: restoring the afforestation signal in a coupled integrated assessment–earth system model and the implications for CMIP5 RCP simulations

2014 ◽  
Vol 11 (22) ◽  
pp. 6435-6450 ◽  
Author(s):  
A. V. Di Vittorio ◽  
L. P. Chini ◽  
B. Bond-Lamberty ◽  
J. Mao ◽  
X. Shi ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Integrated Assessment ◽  
Coupled Model ◽  
Assessment Model ◽  
Carbon Gain ◽  
Climate Projections ◽  
Full Potential ◽  
Earth System ◽  
Intergovernmental Panel

Abstract. Climate projections depend on scenarios of fossil fuel emissions and land use change, and the Intergovernmental Panel on Climate Change (IPCC) AR5 parallel process assumes consistent climate scenarios across integrated assessment and earth system models (IAMs and ESMs). The CMIP5 (Coupled Model Intercomparison Project Phase 5) project used a novel "land use harmonization" based on the Global Land use Model (GLM) to provide ESMs with consistent 1500–2100 land use trajectories generated by historical data and four IAMs. A direct coupling of the Global Change Assessment Model (GCAM), GLM, and the Community ESM (CESM) has allowed us to characterize and partially address a major gap in the CMIP5 land coupling design: the lack of a corresponding land cover harmonization. For RCP4.5, CESM global afforestation is only 22% of GCAM's 2005 to 2100 afforestation. Likewise, only 17% of GCAM's 2040 afforestation, and zero pasture loss, were transmitted to CESM within the directly coupled model. This is a problem because GCAM relied on afforestation to achieve RCP4.5 climate stabilization. GLM modifications and sharing forest area between GCAM and GLM within the directly coupled model did not increase CESM afforestation. Modifying the land use translator in addition to GLM, however, enabled CESM to include 66% of GCAM's afforestation in 2040, and 94% of GCAM's pasture loss as grassland and shrubland losses. This additional afforestation increases CESM vegetation carbon gain by 19 PgC and decreases atmospheric CO2 gain by 8 ppmv from 2005 to 2040, which demonstrates that CESM without additional afforestation simulates a different RCP4.5 scenario than prescribed by GCAM. Similar land cover inconsistencies exist in other CMIP5 model results, primarily because land cover information is not shared between models. Further work to harmonize land cover among models will be required to increase fidelity between IAM scenarios and ESM simulations and realize the full potential of scenario-based earth system simulations.

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