COMPARISON OF THE WGEN AND LARS-WG STOCHASTIC WEATHER GENERATORS FOR DIVERSE CLIMATES

Stochastic weather generators are used in a wide range of studies, suc h as hydrological applications, environmental management and agricultu ral risk assessments. Such studies often require long series of daily weather data for risk assessment and weather generators can produce ti me series of synthetic daily weather data of any length. Weather gener ators are also used to interpolate observed data to produce synthetic weather data at new sites, and they have recently been employed in the construction of climate change scenarios. Any generator should be tes ted to ensure that the data that it produces is satisfactory for the p urposes for which it is to be used,The accuracy required will depend o n the application of the data, and the performance of the generator ma y vary considerably for different climates. The aim of this paper is t o test and compare 2 commonly-used weather generators, namely WGEN and LARS-WG, at 18 sites in the USA, Europe and Asia, chosen to represent a range of climates. Statistical tests were selected to compare a var iety of different weather characteristics of the observed and syntheti c weather data such as, for example, the lengths of wet and dry series , the distribution of precipitation and the lengths of frost spells. T he LARS-WG generator used more complex distributions for weather varia bles and tended to match the observed data more closely than WGEN, alt hough there are certain characteristics of the data that neither gener ator reproduced accurately. The implications for the development and u se of stochastic weather generators are discussed.