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High-resolution global population projections dataset developed with CMIP6 RCP and SSP scenarios for year 2010–2100

Olén, Niklas Boke LU and Lehsten, Veiko LU (2022) In Data in Brief 40.
Abstract

We present a novel, global 30 arc seconds (∼1 km at the equator) population projection dataset covering each year from 2010 to 2100 that is consistent with both country level population and gridded urban fractions from the Coupled Model Intercomparison Project 6 (CMIP6). While IPCC population projections until 2100 are available at country level for Socio-Economic Pathways (SSPs), land cover (including the urban fraction) is only available for Representative Concentration Pathways (RCPs). To perform simulations of e.g., future supply and demand for agricultural products, fine scale projections of population density are needed for combinations of SSPs and RCPs. Therefore, we generated a 30 arc seconds dataset consistent with both SSPs... (More)

We present a novel, global 30 arc seconds (∼1 km at the equator) population projection dataset covering each year from 2010 to 2100 that is consistent with both country level population and gridded urban fractions from the Coupled Model Intercomparison Project 6 (CMIP6). While IPCC population projections until 2100 are available at country level for Socio-Economic Pathways (SSPs), land cover (including the urban fraction) is only available for Representative Concentration Pathways (RCPs). To perform simulations of e.g., future supply and demand for agricultural products, fine scale projections of population density are needed for combinations of SSPs and RCPs. Therefore, we generated a 30 arc seconds dataset consistent with both SSPs and RCPs within the framework of the IPCC. This data set is useful in applications where spatially explicit projections of aspects of global change are investigated at a fine spatial scale. For example, if a link function between night-time lights and population density is found based on current satellite images and recent population density data, a projection of night-time light lights can be generated by using this link function with our projected population density. Such a projection can for example be used to evaluate the potential for future light pollution.

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author
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organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Global, IPCC, Modelling, Population, Scenarios
in
Data in Brief
volume
40
article number
107804
publisher
Elsevier
external identifiers
  • pmid:35071702
  • scopus:85122744924
ISSN
2352-3409
DOI
10.1016/j.dib.2022.107804
language
English
LU publication?
yes
id
4e1f1f48-7848-4b3b-8667-5090b067741b
date added to LUP
2022-03-01 12:25:13
date last changed
2024-03-21 06:00:46
@article{4e1f1f48-7848-4b3b-8667-5090b067741b,
  abstract     = {{<p>We present a novel, global 30 arc seconds (∼1 km at the equator) population projection dataset covering each year from 2010 to 2100 that is consistent with both country level population and gridded urban fractions from the Coupled Model Intercomparison Project 6 (CMIP6). While IPCC population projections until 2100 are available at country level for Socio-Economic Pathways (SSPs), land cover (including the urban fraction) is only available for Representative Concentration Pathways (RCPs). To perform simulations of e.g., future supply and demand for agricultural products, fine scale projections of population density are needed for combinations of SSPs and RCPs. Therefore, we generated a 30 arc seconds dataset consistent with both SSPs and RCPs within the framework of the IPCC. This data set is useful in applications where spatially explicit projections of aspects of global change are investigated at a fine spatial scale. For example, if a link function between night-time lights and population density is found based on current satellite images and recent population density data, a projection of night-time light lights can be generated by using this link function with our projected population density. Such a projection can for example be used to evaluate the potential for future light pollution.</p>}},
  author       = {{Olén, Niklas Boke and Lehsten, Veiko}},
  issn         = {{2352-3409}},
  keywords     = {{Global; IPCC; Modelling; Population; Scenarios}},
  language     = {{eng}},
  publisher    = {{Elsevier}},
  series       = {{Data in Brief}},
  title        = {{High-resolution global population projections dataset developed with CMIP6 RCP and SSP scenarios for year 2010–2100}},
  url          = {{http://dx.doi.org/10.1016/j.dib.2022.107804}},
  doi          = {{10.1016/j.dib.2022.107804}},
  volume       = {{40}},
  year         = {{2022}},
}