Abstract
Stochastic weather generator is a statistical model that generates maximum temperature (Tmax), minimum temperature (Tmin) and daily precipitation using information of weather and climate. This model is one of the ways to reflect long-term climate change or to generate a consistent daily weather sequence for weather forecast which have a seasonality. Recently, a generalized linear model (GLM) has been considered to fit stochastic weather generators to the daily data, which is useful for explaining the characteristics or trends of climate periodicity. It is also useful to add various phenomena that affect the daily weather to variables and use them to relate them to the results. Therefore, we introduce the model that generate a precipitation occurrence, Tmax and Tmin using GLM and then generate a diurnal temperature range (DTR) using proposed model.
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