Assessment and Improvement of CLIGEN for Climate Change Impact Analysis in Australia

Abstract

Climate change is a complex phenomenon and can have considerable impact on hydrological and bio-physical systems as well as the society. To evaluate the impact of climate change, stochastic weather generators (SWG) are commonly used to produce synthetic weather sequences that are statistically similar to the observed weather data, and these SWGs have been widely used for downscaling global climate model (GCM) outputs. CLIGEN is one such weather generator that has been used for impact analysis. As a unique SWG, CLIGEN can produce variables describing storm patterns, including time to peak, peak intensity, and storm duration, in addition to precipitation amount and other daily weather variables. CLIGEN has been used for WEPP (Water Erosion Prediction Project) to predict runoff, soil erosion, and crop production. Although in recent years several research papers have been published to evaluate approaches that adjust CLIGEN parameters to simulate non-stationary climate change scenarios using observed data prior researches was limited to use simple approaches, e.g. multiplying the CLIGEN-generated daily precipitation by a fixed factor. The main goal of this research was to develop methodologies to adjust precipitation related parameters of CLIGEN for climate change impact analysis in two regions of Australia. On a broader scale, this research has three objectives: 1. To adjust relevant CLIGEN parameters when annual precipitation has changed abruptly and significantly; 2. To adjust relevant CLIGEN parameters when there is a significantly decreasing trend in annual precipitation; and 3. To validate the adjustment method in terms of simulated streamflow using conceptual hydrological models.