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The paper describes a method for the spatial interpolation of the site-specific LARS-WG stochastic weather generator to produce 'realistic' daily weather data for the gaps between observed sites. One of the uses of LARS-WG has been site-scale climate change impact assessments. However, such assessments are often applied across regions and so there is a need for an interpolation method to provide input daily weather at many sites or grid-boxes where observed weather data is not available. The interpolation method devised combines the local interpolation of the weather generator parame- ters from observed sites near the unobserved location with the use of globally interpolated monthly mean statistics for a large number of sites. Thin plate smoothing splines with elevation as an indepen- dent variable were used for the global interpolation of mean monthly rainfall and temperature. The data sets used allow daily weather to be generated for any location in Great Britain and the methodol- ogy was tested at 3 locations with different local characteristics. The interpolation method showed a good performance at the 3 sites when compared to the observed data, the main differences occurring when the spline method was unable to reproduce closely the observed mean values. The limitations of the interpolation method, its applicability to other regions and its potential use in climate change and other studies are also discussed.

Spatial interpolation of the LARS-WG stochastic weather generator in Great Britain