GCAM-Demeter LU dataset ...
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...
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Pacific Northwest National Laboratory 2; PNNL
2020
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Online Access: | https://dx.doi.org/10.25584/data.2020-04.1188/1614678 https://www.osti.gov/servlets/purl/1614678/ |
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ftdatacite:10.25584/data.2020-04.1188/1614678 2023-05-15T13:56:56+02:00 GCAM-Demeter LU dataset ... Chen, Min Vernon, Chris 2020 https://dx.doi.org/10.25584/data.2020-04.1188/1614678 https://www.osti.gov/servlets/purl/1614678/ en eng Pacific Northwest National Laboratory 2; PNNL 54 ENVIRONMENTAL SCIENCES dataset Specialized Mix Dataset 2020 ftdatacite https://doi.org/10.25584/data.2020-04.1188/1614678 2023-04-03T13:08:57Z 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', ... Dataset Antarc* Antarctic DataCite Metadata Store (German National Library of Science and Technology) Antarctic The Antarctic |
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Open Polar |
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DataCite Metadata Store (German National Library of Science and Technology) |
op_collection_id |
ftdatacite |
language |
English |
topic |
54 ENVIRONMENTAL SCIENCES |
spellingShingle |
54 ENVIRONMENTAL SCIENCES Chen, Min Vernon, Chris GCAM-Demeter LU dataset ... |
topic_facet |
54 ENVIRONMENTAL SCIENCES |
description |
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', ... |
format |
Dataset |
author |
Chen, Min Vernon, Chris |
author_facet |
Chen, Min Vernon, Chris |
author_sort |
Chen, Min |
title |
GCAM-Demeter LU dataset ... |
title_short |
GCAM-Demeter LU dataset ... |
title_full |
GCAM-Demeter LU dataset ... |
title_fullStr |
GCAM-Demeter LU dataset ... |
title_full_unstemmed |
GCAM-Demeter LU dataset ... |
title_sort |
gcam-demeter lu dataset ... |
publisher |
Pacific Northwest National Laboratory 2; PNNL |
publishDate |
2020 |
url |
https://dx.doi.org/10.25584/data.2020-04.1188/1614678 https://www.osti.gov/servlets/purl/1614678/ |
geographic |
Antarctic The Antarctic |
geographic_facet |
Antarctic The Antarctic |
genre |
Antarc* Antarctic |
genre_facet |
Antarc* Antarctic |
op_doi |
https://doi.org/10.25584/data.2020-04.1188/1614678 |
_version_ |
1766264546661498880 |