Downscaling drivers of global environmental change: enabling use of global SRES scenarios at the national and grid levels
Interaction between human and environmental systems has become an important focal point of research of the last decades. An important aspect of this relationship is scale. As different phenomena take place at different spatial scales, the preferred spatial scale depends on the analysis undertaken. In the case of studies that look into long-term future changes of the global environment and/or its driving forces, the scale of large global regions is often the most useful level of analysis.
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.
A MNP report "Downscaling drivers of global environmental change. Enabling use of global SRES scenarios at the national and grid levels" has been published in 2006. Downscaled data is available on the webpage of this report.
- to the report
|Author(s)||Vuuren DP van ; Lucas PL ; Hilderink H|
|Publication||Global Environ Change 2007; 17(1):114-30|