This webinar introduces PrecipGen, which simulates daily precipitation using a first-order, 2-state Markov chain-gamma model with long-term correlations. The model leverages a Markov process to simulate changes between states over time, where the probability of a state change is dependent on the previous state. The precipitation rate is modeled by sampling from a gamma probability distribution.
PrecipGen builds upon the foundational work of Dee Allen Wright and the WGEN model from 1983, implemented in FORTRAN. This GoldSim iteration carries forward a legacy of reliability in precipitation simulation.
One of the unique features of this implementation is the option to incorporate long-term cyclic behavior. This is based on correlations found in the historical record. Users can make adjustments to an autocorrelation factor to modify the length of multi-year drought-deluge cycles.
Below is a video recording of the webinar presentation:
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