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

The 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 to meet users' needs. These include the assessment of uncertainty for future scenarios, and the production of scenarios at time scales relevant to stakeholders. This paper describes a methodology which addresses these issues by producing a multi-model ensemble of transient climate-change scenarios. The 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 experiments. The methodology is demonstrated by the generation of transient scenarios of daily rainfall, temperature and potential evapotranspiration for the Geer catchment in Belgium for the period 2010-2085. 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 an 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. This could aid stakeholders in assessing the likely time scales of required interventions and adaptation responses.