Assessment of Climate Projections Using Ensembles of CMIP5 GCMs and Developing a Probable Future Scenario for Evaluation of Possible Future Changes

Thursday, 18 December 2014
Ali Ahmadalipour1, Arun Rana1 and Hamid Moradkhani2, (1)Portland State University, Portland, OR, United States, (2)Portland State University, Civil and Environmental Engineering, Portland, OR, United States
Global climatic change is expected to have severe effects on natural systems along with various socio-economic aspects of human life. Global Climate Models (GCMs) are widely used to study the impacts in future, with varied projections/simulations from the entire participating member GCMs. This has urged scientific communities across the world try to improve the understandings of future climate conditions, and reduce the uncertainties associated with them. In the present study, we have used various multi-modelling methods, both deterministic and probabilistic, to reduce the model uncertainties, in historical time period of 1970-2000. The analysis is performed for uncertainty bounds of precipitation and temperature using 10 selected Global Climate Models (GCMs) from Climate Model Inter-comparison project Phase 5 (CMIP5) dataset over 10 sub-basins of Columbia River Basin (CRB). All the multi-modelling methods are applied and evaluated in accordance to their performance indicator using Taylor diagrams on simulating past climate for all 10 sub-basins. The best performing multi-model method, on basis of performance of all the climatic parameters, is chosen for a particular sub-basin and same is used to develop a probable future scenario for the period of 2010-2099. All the analysis and computations are performed on statistically downscaled GCM data to increase the accuracy and better capture the uncertainty bounds on sub-basin scale, as well as enhancing the ability of multi-modeling techniques. All the future time series are used to assess the uncertainties of climatic parameters for climate change analysis. Results have brought insight into each of the multi-modelling techniques i.e. highlighting the pros and cons of all the applied methods. It was also inferred that multi-modelling techniques varied from basin to basin and with different variables, as per their capabilities to capture the observation spread/uncertainty. Eventually, the different ensemble time series for future period provided much better insight of the climate, on sub-basin scale, for Columbia River Basin.