Gross domestic product (GDP) downscaling: a global gridded dataset consistent with the Shared Socioeconomic Pathways

• Main Authors: Wang, Tingting, Sun, Fubao
• Format: Dataset
• Language: unknown
• Published: Zenodo 2022
• Subjects: GDP; SSP; downscaling; Calvin; Geiger; Chateau; Antarc*; Antarctica
• Online Access: https://dx.doi.org/10.5281/zenodo.5880037; https://zenodo.org/record/5880037

In this project, we developed and presented a set of comparable spatially explicit global gridded gross domestic product (GDP) 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 the LitPop maps to disaggregate national GDP and over 800 provincial gross regional product (GRP, in 2005 PPP USD) across the globe in 2005 and to downscaled to a spatial resolution of 30 arc-seconds (~1 km at equator). National and supranational GDP projections in 2030-2100 under five SSPs were also downscaled to 1-km grids using NPP-VIIRS product as fixed NTL image in 2015 and the population projections of 0.125 arc-degreee, which are downscaled to 1-km based on LandScan population distribution pattern in 2015. We then upscaled this gridded GDP dataset to 0.25 arc-degree and provided here. There are 41 tif files (2005 and 2030 - 2100 at a ten-year interval for five SSPs) for each spatial resolution. The gridded GDP 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 gridded GDP data set offers the necessity and availability of using GDP projections of high resolution, especially in exposure, vulnerability, and resilience analysis for scenario-based climate change research under five SSPs. : {"references": ["Geiger, T.: Continuous national gross domestic product (GDP) time series for 195 countries: past observations (1850\u20132005) harmonized with future projections according to the Shared Socio-economic Pathways (2006\u20132100), Earth System Science Data, 10, 847\u2013856, 2018.", "Dellink, R., Chateau, J., Lanzi, E., and Magn\u00e9, B.: Long-term economic growth projections in the Shared Socioeconomic Pathways, Global Environmental Change, 42. 200-214, 2015.", "Riahi, K., Van Vuuren, D. P., Kriegler, E., Edmonds, J., O'neill, B. C., Fujimori, S., Bauer, N., Calvin, K., Dellink, R., and Fricko, O.: The shared socioeconomic pathways and their energy, land use, and greenhouse gas emissions implications: an overview, Global Environmental Change, 42, 153-168, 2017."]}