@article{368c8b2db3874f259a24ad215d3666cf,
title = "Practical rare event sampling for extreme mesoscale weather",
abstract = "Extreme mesoscale weather, including tropical cyclones, squall lines, and floods, can be enormously damaging and yet challenging to simulate; hence, there is a pressing need for more efficient simulation strategies. Here, we present a new rare event sampling algorithm called quantile diffusion Monte Carlo (quantile DMC). Quantile DMC is a simple-to-use algorithm that can sample extreme tail behavior for a wide class of processes. We demonstrate the advantages of quantile DMC compared to other sampling methods and discuss practical aspects of implementing quantile DMC. To test the feasibility of quantile DMC for extreme mesoscale weather, we sample extremely intense realizations of two historical tropical cyclones, 2010 Hurricane Earl and 2015 Hurricane Joaquin. Our results demonstrate quantile DMC's potential to provide low-variance extreme weather statistics while highlighting the work that is necessary for quantile DMC to attain greater efficiency in future applications.",
author = "Webber, {Robert J.} and Plotkin, {David A.} and O'Neill, {Morgan E.} and Abbot, {Dorian S.} and Jonathan Weare",
note = "Funding Information: We acknowledge support from that National Science Foundation (NSF) under NSF Award No. 1623064. R.J.W. and J.W. are supported by the Advanced Scientific Computing Research Program within the U.S. Department of Energy (DOE) O ce of Science through award DE-SC0014205. R.J.W. was supported by NSF RTG Award No. 1547396 at the University of Chicago and by a Mac-Cracken Fellowship at New York University. D.A.P. was supported by the DOE Computational Science Graduate Fellowship Program of the O ce of Science and National Nuclear Security. M.E.O. was partially supported by the T.C. Chamberlin Postdoctoral Fellowship at the University of Chicago. The work was completed with resources provided by the University of Chicago Research Computing Center. R.J.W. acknowledges Alicia Zhao for her gracious and patient editorial assistance. Funding Information: We acknowledge support from that National Science Foundation (NSF) under NSF Award No. 1623064. R.J.W. and J.W. are supported by the Advanced Scientific Computing Research Program within the U.S. Department of Energy (DOE) Office of Science through award DE-SC0014205. R.J.W. was supported by NSF RTG Award No. 1547396 at the University of Chicago and by a MacCracken Fellowship at New York University. Publisher Copyright: {\textcopyright} 2019 Author(s).",
year = "2019",
month = may,
day = "1",
doi = "10.1063/1.5081461",
language = "English (US)",
volume = "29",
journal = "Chaos",
issn = "1054-1500",
publisher = "American Institute of Physics Publising LLC",
number = "5",
}