A Comparison of Stochastic Precipitation Generation Models for the Potomac River Basin
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Gerson C. Kroiz, A Comparison of Stochastic Precipitation Generation Models for the Potomac River Basin, Spring 2020, http://hpcf-files.umbc.edu/research/papers/Kroiz_SeniorThesis2020.pdf
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Abstract
Weather ensembles are an integral part of weather forecasting and can also be used to test the sensitivity and performance of climate models. Among meteorological variables, simultaneous simulation of precipitation at multiple sites presents unique challenges since precipitation has a semi-continuous distribution. We compare Robertson’s hidden Markov model setup with Wilks’ Multivariate Markov Chain based generator to see how well they recreate the spatiotemporal characteristic of gridded satellite precipitation estimates. Our results show that the Wilks method does a better job of capturing spatial correlations, while the HMM model can estimate and simulate longer durations of time.