GCAM-Demeter-LU
This GCAM-Demeter-LU is made available under the Open Data Commons Attribution License:http://opendatacommons.org/licenses/by/1.0/. The dataset includes the projected global gridded land cover (excluding the Antarctic) for the period of 2015-2100 at 0.05-degree resolution and 5-year time step under...
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ftosti:oai:osti.gov:1615771 2023-07-30T03:59:18+02:00 GCAM-Demeter-LU Chen, Min Vernon, Chris R 2023-03-10 application/pdf http://www.osti.gov/servlets/purl/1615771 https://www.osti.gov/biblio/1615771 https://doi.org/10.25584/data.2020-04.1190/1615771 unknown http://www.osti.gov/servlets/purl/1615771 https://www.osti.gov/biblio/1615771 https://doi.org/10.25584/data.2020-04.1190/1615771 doi:10.25584/data.2020-04.1190/1615771 99 GENERAL AND MISCELLANEOUS 2023 ftosti https://doi.org/10.25584/data.2020-04.1190/1615771 2023-07-11T09:41:37Z This GCAM-Demeter-LU is made available under the Open Data Commons Attribution License:http://opendatacommons.org/licenses/by/1.0/. The dataset includes the projected global gridded land cover (excluding the Antarctic) for the period of 2015-2100 at 0.05-degree resolution and 5-year time step under fifteen SSP-RCP scenarios driven by five GCMs (i.e., gfdl, hadgem, ipsl, miroc, and noresm), using the Global Change Analysis Model (GCAM) and a geospatial downscaling model (Demeter). The data has been stored in self-describing NetCDF format. The dataset also includes the mean and standard deviation of the results driven by the five GCMs. More specifically, the data in each year includes grid-explicit fraction (in percent) of each of the 32 plant functional types that are widely used in current Earth system models. The NetCDF files are named as “GCAM_Demeter_LU_SSP_RCP_Model_Year.nc”, where “SSP” and “RCP” denote the SSP and RCP scenarios, including 'ssp1_rcp26', 'ssp1_rcp45', 'ssp1_rcp60', 'ssp2_rcp26', 'ssp2_rcp45', 'ssp2_rcp60', 'ssp3_rcp45', 'ssp3_rcp60', 'ssp4_rcp26', 'ssp4_rcp45', 'ssp4_rcp60', 'ssp5_rcp26', 'ssp5_rcp45', 'ssp5_rcp60', and 'ssp5_rcp85'. “Year” denotes the year of the land use data, and “GCM” denotes the source driving forcing data from five global climate models (gfdl, hadgem, ipsl, miroc, and noresm), or the mean (“modelmean”) and the standard deviation (“modelstd”) of the results from the five GCMs.See https://github.com/JGCRI/chen_et_al_2020a for details on how to reproduce this data. Rights and permissions Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated ... Other/Unknown Material Antarc* Antarctic SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy) Antarctic The Antarctic |
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SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy) |
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99 GENERAL AND MISCELLANEOUS |
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99 GENERAL AND MISCELLANEOUS Chen, Min Vernon, Chris R GCAM-Demeter-LU |
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99 GENERAL AND MISCELLANEOUS |
description |
This GCAM-Demeter-LU is made available under the Open Data Commons Attribution License:http://opendatacommons.org/licenses/by/1.0/. The dataset includes the projected global gridded land cover (excluding the Antarctic) for the period of 2015-2100 at 0.05-degree resolution and 5-year time step under fifteen SSP-RCP scenarios driven by five GCMs (i.e., gfdl, hadgem, ipsl, miroc, and noresm), using the Global Change Analysis Model (GCAM) and a geospatial downscaling model (Demeter). The data has been stored in self-describing NetCDF format. The dataset also includes the mean and standard deviation of the results driven by the five GCMs. More specifically, the data in each year includes grid-explicit fraction (in percent) of each of the 32 plant functional types that are widely used in current Earth system models. The NetCDF files are named as “GCAM_Demeter_LU_SSP_RCP_Model_Year.nc”, where “SSP” and “RCP” denote the SSP and RCP scenarios, including 'ssp1_rcp26', 'ssp1_rcp45', 'ssp1_rcp60', 'ssp2_rcp26', 'ssp2_rcp45', 'ssp2_rcp60', 'ssp3_rcp45', 'ssp3_rcp60', 'ssp4_rcp26', 'ssp4_rcp45', 'ssp4_rcp60', 'ssp5_rcp26', 'ssp5_rcp45', 'ssp5_rcp60', and 'ssp5_rcp85'. “Year” denotes the year of the land use data, and “GCM” denotes the source driving forcing data from five global climate models (gfdl, hadgem, ipsl, miroc, and noresm), or the mean (“modelmean”) and the standard deviation (“modelstd”) of the results from the five GCMs.See https://github.com/JGCRI/chen_et_al_2020a for details on how to reproduce this data. Rights and permissions Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated ... |
author |
Chen, Min Vernon, Chris R |
author_facet |
Chen, Min Vernon, Chris R |
author_sort |
Chen, Min |
title |
GCAM-Demeter-LU |
title_short |
GCAM-Demeter-LU |
title_full |
GCAM-Demeter-LU |
title_fullStr |
GCAM-Demeter-LU |
title_full_unstemmed |
GCAM-Demeter-LU |
title_sort |
gcam-demeter-lu |
publishDate |
2023 |
url |
http://www.osti.gov/servlets/purl/1615771 https://www.osti.gov/biblio/1615771 https://doi.org/10.25584/data.2020-04.1190/1615771 |
geographic |
Antarctic The Antarctic |
geographic_facet |
Antarctic The Antarctic |
genre |
Antarc* Antarctic |
genre_facet |
Antarc* Antarctic |
op_relation |
http://www.osti.gov/servlets/purl/1615771 https://www.osti.gov/biblio/1615771 https://doi.org/10.25584/data.2020-04.1190/1615771 doi:10.25584/data.2020-04.1190/1615771 |
op_doi |
https://doi.org/10.25584/data.2020-04.1190/1615771 |
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1772810050323087360 |