Scenarios are key tools in analyses of global environmental change. Often they consist of quantitative and qualitative components, where the qualitative aspects are expressed in narrative, or storyline, form. Fundamental challenges in scenario development and use include identifying a small set of compelling storylines that span a broad range of policy-relevant futures, documenting that the assumptions embodied in the storylines are internally consistent, and ensuring that the selected storylines are sufficiently comprehensive, that is, that descriptions of important kinds of future developments are not left out. The dominant approach to scenario design for environmental change research has been criticized for lacking sufficient means of ensuring that storylines are internally consistent. A consequence of this shortcoming could be an artificial constraint on the range of plausible futures considered. We demonstrate the application of a more systematic technique for the development of storylines called the cross-impact balance (CIB) method. We perform a case study on the scenarios published in the IPCC Special Report on Emissions Scenarios (SRES), which are widely used. CIB analysis scores scenarios in terms of internal consistency. It can also construct a very large number of scenarios consisting of combinations of assumptions about individual scenario elements and rank these combinations in terms of internal consistency. Using this method, we find that the four principal storylines employed in the SRES scenarios vary widely in internal consistency. One type of storyline involving highly carbon-intensive development is underrepresented in the SRES scenario set. We conclude that systematic techniques like CIB analysis hold promise for improving scenario development in global change research.