文章基本信息

标题：Global gridded GDP data set consistent with the shared socioeconomic pathways
本地全文：下载
作者：tingtingWang ; Fubao Sun
期刊名称：Scientific Data
电子版ISSN：2052-4463
出版年度：2022
卷号：9
期号：1
页码：1-10
DOI：10.1038/s41597-022-01300-x
语种：English
出版社：Nature Publishing Group
摘要：The vulnerability, exposure and resilience of socioeconomic activities to future climate extremes call for high-resolution gridded GDP in climate change adaptation and mitigation research . While global socioeconomic projections are provided mainly at the national level, and downscaling approaches using nighttime light (NtL) images or gridded population data can increase the uncertainty due to limitations . Therefore, we adopt an NTL-population-based approach, which exhibits higher accuracy in socioeconomic disaggregation . Gross regional product of over 800 provinces, which covering over 60% of the global land surface and accounted for more than 80% of GDP in 2005, were used as input .We present a frst set of comparable spatially explicit global gridded GDP projections with fne spatial resolutions of 30 arc-seconds and 0.25 arc-degrees for the historical period of 2005 and for 2030–2100 at 10-year intervals under the fve SSPs, accounting for the two-child policy in China . This gridded GDP projection dataset can broaden the applicability of GDP data, the availability of which is necessary for socioeconomic and climate change research .