Downscaling transient climate change with a stochastic weather generator for the Geer catchment, Belgium

peer reviewedThe coarse resolution of climate models creates the need for future scenarios which are downscaled to an appropriate spatial scale. Considerable effort has been devoted to the development of downscaling methods but a number of important issues remain in the development of robust, usable climate scenarios. These include the incorporation of various sources of uncertainty into future scenarios and the production of scenarios at timescales relevant to planners. This paper describes a new procedure which addresses these issues by producing a multi-model ensemble of transient climate change scenarios. This method couples an existing stochastic rainfall model to a new, transient implementation of a weather generator, using changes projected by an ensemble of regional climate model (RCM) experiments. The methodology is demonstrated by the generation of transient scenarios of daily rainfall, temperature and potential evapotranspiration (PET) for the Geer catchment in Belgium for the period 2010 to 2085. The utility of these scenarios is demonstrated by assessing the changes projected by the simulated time series of several temperature indices. The Geer is projected to experience a decrease in the occurrence of frost days with a corresponding shortening of the frost season and lengthening of the growing season. By examining a large ensemble of transient scenarios the range of uncertainty in these projections is assessed, but further, it is suggested that additional information on the projected timing of specified threshold events or system responses may be provided which could aid planners in assessing the likely timescales of required interventions and adaptation responses.FP6 IP AquaTerr