GCAM-Demeter LU dataset

Chen, Min; Vernon, Chris

doi:10.25584/data.2020-04.1188/1614678

Title: GCAM-Demeter LU dataset (in EN)

Dataset
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Abstract

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.

Authors:

Chen, Min; Vernon, Chris

PNNL

Publication Date:: Mon Apr 13 00:00:00 EDT 2020

Other Number(s):: Project ID: 68344; Instrument ID: 85000; Upload ID: 1188

DOE Contract Number:: AC05-76RL01830

Research Org.:: Pacific Northwest National Laboratory 2; PNNL

Sponsoring Org.:: SC-23

Subject:: 54 ENVIRONMENTAL SCIENCES

OSTI Identifier:: 1614678

DOI:: https://doi.org/10.25584/data.2020-04.1188/1614678

Citation Formats


                    Chen, Min, and Vernon, Chris. GCAM-Demeter LU dataset.  United States: N. p., 2020. 
        Web.  doi:10.25584/data.2020-04.1188/1614678.

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                    Chen, Min, & Vernon, Chris. GCAM-Demeter LU dataset.  United States.  doi:https://doi.org/10.25584/data.2020-04.1188/1614678

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                    Chen, Min, and Vernon, Chris. 2020.  
"GCAM-Demeter LU dataset".  United States.  doi:https://doi.org/10.25584/data.2020-04.1188/1614678.  https://www.osti.gov/servlets/purl/1614678. Pub date:Mon Apr 13 00:00:00 EDT 2020

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@article{osti_1614678,

  title        = {GCAM-Demeter LU dataset},

  author       = {Chen, Min and Vernon, Chris},

  abstractNote = {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.},

  doi          = {10.25584/data.2020-04.1188/1614678},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Mon Apr 13 00:00:00 EDT 2020},

  month        = {Mon Apr 13 00:00:00 EDT 2020}

}

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DOI: https://doi.org/10.25584/data.2020-04.1188/1614678

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