Global environmental change scenarios typically distinguish between about 10-20 global regions. However, various studies need scenario information at a higher level of spatial detail. This paper presents a set of algorithms that fill this gap by providing downscaled scenario data for population, GDP and emissions at the national and grid levels. The proposed methodology is based on external-input-based downscaling for population, convergence-based downscaling for GDP and emissions, and linear algorithms to go to grid levels. The algorithms are applied to the IPCC-SRES scenarios, where the results seem to provide a credible basis for global environmental change assessments.
Below you find a list of downscaled data for the SRES scenarios.
The excel files contain population, per capita income and per capita emissions data for the 17 IMAGE world regions and for 224 countries (downscaled data).
The zip-files contain ascii-grid files (2000-2100) with gridded population data (total population per grid cell) and gridded gdp data (total gdp per grid cell).
ERRATUM: on June 26, 2007 the B1 scenario has been replaced as the previous version was mistaken with the A1b scenario