The simulation output data, and then used as the weather generator
input using LARS-WG. LARS-WG is a stochastic weather
generator model generating daily weather time series statistically
similar to the observed weather (Wilks and Wilby 1999). WGs were
adopted in climate change impact studies as a computationally inexpensive
tool to generate scenarios with high temporal and spatial
resolutions based on the output from a GCM (Barrow and Semenov
1995; Dubrovsky et al. 2005; Hansen 2002; Wilks 1992; Wilks and
Wilby 1999). Furthermore, for this research goodness of fit tests
based on chi-square statistic and empirical distribution function
(EDF) [statistics Kolmogorov–Smirnov (KS) and Anderson darling
(AD) test] are used for evaluating the suitability of different probability
distributions.