Spatially explicit global gross domestic product (GDP) data set consistent with the Shared Socioeconomic Pathways

• Main Authors: Wang, Tingting (10831973), Sun, Fubao (10831976)
• Format: Dataset
• Language: unknown
• Published: 2020
• Subjects: Medicine; Ecology; Cancer; Inorganic Chemistry; GDP and GRP; SSP; downscaling; Antarc*; Antarctica
• Online Access: https://doi.org/10.5281/zenodo.4770851

In this project, we presented a set of comparable spatially explicit global gross cell product (GCP) for both historical period (2005 as representative) and for future projections from 2030 to 2100 at a ten-year interval for all five SSPs. The DMSP-OLS nighttime light (NTL) images and the LandScan Global Population database were used to generate LitPop map, which reduces the limitations of saturation problem of using NTL images alone or the assumption of even GDP per capita within an administrative boundary of gridded data set in GDP disaggregation. We used this LitPop map to disaggregate national GDP and gross regional product (GRP, in 2005 PPP USD) across the globe in 2005, and national and supranational GDP projections from five SSPs to spatial resolutions of 30 arc-seconds (~1 km at equator) and 0.25 degree. There are 41 tif files (2005 and 2030 - 2100 at a ten-year interval for five SSPs) for each spatial resolution. The GCP are distributed over land with value of zero filled in the Antarctica, oceans and some desert or wilderness areas (non-illuminated and depopulated zones). The spatial extents are 60S - 90N and 180E - 180W in standard WGS84 coordinate system. These spatial explicit GCP data set offers the necessity and availability of using GCP projections of high resolution, especially in exposure, vulnerability, and resilience analysis for scenario-based climate change research for all five SSPs.