dc.rights.license | CC-BY-NC-ND | |
dc.contributor.advisor | Dijkstra, H.A. | |
dc.contributor.author | Nijsse, F.J.M.M. | |
dc.date.accessioned | 2017-07-19T17:01:36Z | |
dc.date.available | 2017-07-19T17:01:36Z | |
dc.date.issued | 2017 | |
dc.identifier.uri | https://studenttheses.uu.nl/handle/20.500.12932/26195 | |
dc.description.abstract | Emergent constraints are one of the tools to reduce uncertainty in climate model projec-tions. These are physically explainable empirical relationships between characteristicsof the current climate and long-term behavior that emerge in ensembles of climatemodels, where the long-term behavior is constrained using observations. So far, nogeneral mathematical framework describing emergent constraints has been proposed.In this work, we introduce a classification for emergent constraints, depending on theprocess under consideration: we distinguish between emergent constraints that modelvariability, mean state or feedback strength. In addition we present a mathematicalframework making use of linear response theory and apply this description to a setof conceptual (climate) models. We specifically focus on an emergent constraint that waspreviously found for the snow-albedo feedback. We conclude by discussing if and howthis framework can be applied to GCMs. | |
dc.description.sponsorship | Utrecht University | |
dc.format.extent | 924833 | |
dc.format.mimetype | application/pdf | |
dc.language.iso | en_US | |
dc.title | A mathematical approach to understandingemergent constraints | |
dc.type.content | Master Thesis | |
dc.rights.accessrights | Open Access | |
dc.subject.keywords | emergent constraints;linear response theory;climate | |
dc.subject.courseuu | Meteorology, Physical Oceanography and Climate | |