paciorek / precip-hmm-trends

Materials for the analysis of trends in precipitation patterns based on hidden Markov model stochastic weather generators.

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precip-hmm-trends

Materials for the analysis of trends in precipitation patterns based on hidden Markov model stochastic weather generators.

Preprint is available on arXiv.

Acknowledgments

This research was supported by the Director, Office of Science, Office of Biological and Environmental Research of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. I thank my CASCADE colleagues for suggestions, in particular Travis O'Brien, Mark Risser, and Michael Wehner.

This document was prepared as an account of work sponsored by the U.S. government. While this document is believed to contain correct information, neither the U.S. government nor any agency thereof, nor the Regents of the University of California, nor any of their employees, makes any warranty, express or implied, or assumes any legal responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by its trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the U.S. government or any agency thereof, or the Regents of the University of California. The views and opinions of authors expressed herein do not necessarily state or reflect those of the U.S. government or any agency thereof or the Regents of the University of California.

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Materials for the analysis of trends in precipitation patterns based on hidden Markov model stochastic weather generators.

License:BSD 3-Clause "New" or "Revised" License


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