A new weather generator based on spectral properties of surface air temperatures

We present a new weather generator, which simulates daily precipitation occurrence and daily maximum and minimum air temperature. Precipitation occurrence is simulated with a two-state, second-order Markov process, while maximum and minimum daily temperatures are simulated using spectral methods. Data generated at nine stations in the Southeastern USA are then compared to: (1) observed station data, and (2) data generated by a variant of the commonly used autoregressive weather generator. Precipitation occurrence simulation is found to be excellent for our study region. Maximum and minimum temperatures generated using the spectral weather generator are found to be superior to those generated by the autoregressive weather generator in terms of means and variances across multiple timescales as well as the number of freeze events, skewness of temperature distributions, and the relationship between daily minimum and maximum air temperatures. Both weather generators are found to slightly underestimate interannual variability in all three generated variables.