Uncertainty Propagation in Coupled Atmosphere-Wave-Ocean Prediction System: A Study of Hurricane Earl (2010)
KAUST DepartmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Applied Mathematics and Computational Science Program
Online Publication Date2018-11-05
Print Publication Date2019-01
Permanent link to this recordhttp://hdl.handle.net/10754/630944
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AbstractThis study focuses on understanding the evolution of Hurricane Earl (2010) with respect to random perturbations in the storm’s initial strength, size, and asymmetry in wind distribution. We rely on the Unified Wave Interface-Coupled Model (UWIN-CM), a fully coupled atmosphere–wave–ocean system to generate a storm realization ensemble, and use polynomial chaos (PC) expansions to build surrogate models for time evolution of both the maximum wind speed and minimum sea level pressure in Earl. The resulting PC surrogate models provide statistical insights on probability distributions of model responses throughout the simulation time span. Statistical analysis of rapid intensification (RI) suggests that initial perturbations having intensified and counterclockwise-rotated winds are more likely to undergo RI. In addition, for the range of initial conditions considered RI seems mostly sensitive to azimuthally averaged maximum wind speed and asymmetry orientation, rather than storm size and asymmetry magnitude; this is consistent with global sensitivity analysis of PC surrogate models. Finally, we combine initial condition perturbations with a stochastic kinetic energy backscatter scheme (SKEBS) forcing in the UWIN-CM simulations and conclude that the storm tracks are substantially influenced by the SKEBS forcing perturbations, whereas the perturbations in initial conditions alone had only limited impact on the storm-track forecast.
CitationLi G, Curcic M, Iskandarani M, Chen SS, Knio OM (2019) Uncertainty Propagation in Coupled Atmosphere–Wave–Ocean Prediction System: A Study of Hurricane Earl (2010). Monthly Weather Review 147: 221–245. Available: http://dx.doi.org/10.1175/mwr-d-17-0371.1.
SponsorsWe thank three anonymous reviewers who helped improved this manuscript. This research was made possible in part by a grant from the Gulf of Mexico Research Initiative, and by the U.S. Department of Energy (DOE), Office of Science, Office of Advanced Scientific Computing Research, under Award DE-SC0008789, NASA Ocean Vector Wind Science Team Grant NNX14AM78G, and by the National Science Foundation under Grant 1639722 (an EarthCube-funded project). Computations were performed using the resources of the National Energy Research Scientific Computing Center, a DOE Office of Science user facility supported by the Office of Science of the U.S. Department of Energy under Contract DE-AC02-05CH11231. Data are publicly available (https://data.gulfresearchinitiative.org; Gulf of Mexico Research Initiative Information and Data Cooperative 2017).
PublisherAmerican Meteorological Society
JournalMonthly Weather Review