A multi-model framework for climate change impact assessment

Abstract

The chapter aims to estimate the climate change impacts within a probabilistic multi-model framework. The suggested approach attempts to improve the reliability of the climate change impact assessment approach by considering the three main sources of uncertainty. Climate change impacts on the climate variables in Iran’s Zayandeh-Rud River Basin have been evaluated.Multi-model ensemble scenarios are used to deal with the uncertainty in climate change projection for the study period (2015-2044). The probabilistic multi-model ensemble scenarios, which include the 15 GCMs, are used to project the temperature and precipitation for the near future period (2015-2044) under 50 % risk level of climate change. Downscaled climate variables suggest that generally temperature will rise in the Zayandeh-Rud River Basin while the level of temperature increase varies between. The maximum monthly precipitation reduction will occur in winter. This can be of considerable importance for the basin having a semiarid Mediterranean climate in which winter precipitation is the main source of renewable water supply. In the proposed framework, the uncertainties of GCMs, emission scenarios, and climate variability of daily time series are handled by the combination of change factors and a weather generator. Covering the full range of potential climate change, such framework can provide the valuable lessons to policy maker for adapting to climate change. The Zayandeh-Rud River Basin has been constantly facing the water stress problem during the past 60 years. The results of the climate change impacts on the basin’s climate variables can provide the policy insights for regional water managers to address well the water scarcity in the near future.