A stochastic weather generator based on a generalized linear model (GLM) approach is a commonly used tools to simulate a time series of daily weather. In this paper, we propose a multi-site weather generator with applications to historical data in South Korea. The proposed method extends the approach of Kim et al. (2012) by considering spatial dependence in the model. To reduce this phenomenon, we also incorporate a time series of seasonal mean precipitations of South Korea in the GLM weather generator as a covariate. Spatial dependence was incorporated into the model through a latent Gaussian process. We apply the proposed model to precipitation data provided by 62 stations in Korea from 1973{2011.