Partitioning Uncertainties in Climate Change Model Ensembles

• Activity Number: 575
• Type: Contributed
• Date/Time: Wednesday, August 6, 2014 : 2:00 PM to 3:50 PM
• Sponsor: Section on Statistics and the Environment
• Author(s): Stacey Alexeeff*+ and Stephan R. Sain and Claudia Tebaldi
• Companies: NCAR and NCAR and NCAR
• Keywords: pattern scaling ; Multimodel ensembles ; temperature ; uncertainty

Abstract

Multimodel ensembles are now being used to study climate change by averaging model projections to provide more stable estimates. However, dependencies exist between models and uncertainties are present in the models, scenarios, and internal variability. In addition, there are many scenarios that could be of interest to explore by climate models but the number of models run is limited by computational power. Pattern scaling has been introduced as a way to study temperature and precipitation change in climate model projections. Using historical runs and control runs from the Coupled Model Intercomparison Project 5, we explore ways of partitioning the uncertainties of climate models into additive components. These components of variability can then be used in conjunction with pattern scaling to model scenarios that have not been run by climate models. We explore how different two scenarios need to be in order to justify climate model simulations, how many ensemble members are needed for that model, and when pattern scaling can be most effective. We apply this approach to future temperature and precipitation projections.