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

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 act...

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Main Authors: Y. Le Page, T. O. West, R. Link, P. Patel
Format: Article
Language:English
Published: Copernicus Publications 2016-09-01
Series:Geoscientific Model Development
Online Access:http://www.geosci-model-dev.net/9/3055/2016/gmd-9-3055-2016.pdf
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author Y. Le Page
T. O. West
R. Link
P. Patel
author_facet Y. Le Page
T. O. West
R. Link
P. Patel
author_sort Y. Le Page
collection DOAJ
description 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.
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spelling doaj.art-8ece0c1281aa4d23b07a662749f67bbb2022-12-21T17:56:42ZengCopernicus PublicationsGeoscientific Model Development1991-959X1991-96032016-09-01993055306910.5194/gmd-9-3055-2016Downscaling land use and land cover from the Global Change Assessment Model for coupling with Earth system modelsY. Le Page0T. O. West1R. Link2P. Patel3Centro de Estudos Florestais, Instituto Superior de Agronomia, Universidade de Lisboa Department Tapada da Ajuda, 1349-017 Lisbon, PortugalCentro de Estudos Florestais, Instituto Superior de Agronomia, Universidade de Lisboa Department Tapada da Ajuda, 1349-017 Lisbon, PortugalCentro de Estudos Florestais, Instituto Superior de Agronomia, Universidade de Lisboa Department Tapada da Ajuda, 1349-017 Lisbon, PortugalCentro de Estudos Florestais, Instituto Superior de Agronomia, Universidade de Lisboa Department Tapada da Ajuda, 1349-017 Lisbon, PortugalThe 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.http://www.geosci-model-dev.net/9/3055/2016/gmd-9-3055-2016.pdf
spellingShingle Y. Le Page
T. O. West
R. Link
P. Patel
Downscaling land use and land cover from the Global Change Assessment Model for coupling with Earth system models
Geoscientific Model Development
title Downscaling land use and land cover from the Global Change Assessment Model for coupling with Earth system models
title_full Downscaling land use and land cover from the Global Change Assessment Model for coupling with Earth system models
title_fullStr Downscaling land use and land cover from the Global Change Assessment Model for coupling with Earth system models
title_full_unstemmed Downscaling land use and land cover from the Global Change Assessment Model for coupling with Earth system models
title_short Downscaling land use and land cover from the Global Change Assessment Model for coupling with Earth system models
title_sort downscaling land use and land cover from the global change assessment model for coupling with earth system models
url http://www.geosci-model-dev.net/9/3055/2016/gmd-9-3055-2016.pdf
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