Quantifying uncertainty in Gulf of Mexico forecasts stemming from uncertain initial conditions
KAUST DepartmentApplied Mathematics and Computational Science Program
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Online Publication Date2016-07-16
Print Publication Date2016-07
Permanent link to this recordhttp://hdl.handle.net/10754/621506
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AbstractPolynomial Chaos (PC) methods are used to quantify the impacts of initial conditions uncertainties on oceanic forecasts of the Gulf of Mexico circulation. Empirical Orthogonal Functions are used as initial conditions perturbations with their modal amplitudes considered as uniformly distributed uncertain random variables. These perturbations impact primarily the Loop Current system and several frontal eddies located in its vicinity. A small ensemble is used to sample the space of the modal amplitudes and to construct a surrogate for the evolution of the model predictions via a nonintrusive Galerkin projection. The analysis of the surrogate yields verification measures for the surrogate's reliability and statistical information for the model output. A variance analysis indicates that the sea surface height predictability in the vicinity of the Loop Current is limited to about 20 days. © 2016. American Geophysical Union. All Rights Reserved.
CitationIskandarani M, Le Hénaff M, Thacker WC, Srinivasan A, Knio OM (2016) Quantifying uncertainty in Gulf of Mexico forecasts stemming from uncertain initial conditions. Journal of Geophysical Research: Oceans 121: 4819–4832. Available: http://dx.doi.org/10.1002/2015JC011573.
SponsorsWe would like to thank the two anonymous reviewers whose comments were extremely helpful in improving the manuscript. This research was made possible in part by a grant from BP/The Gulf of Mexico Research Initiative to the CARTHE and DEEP-C Consortia, and by the Office of Naval Research, Award N00014-1010498. O. M. Knio was supported in part by the US Department of Energy (DOE), Office of Science, Office of Advanced Scientific Computing Research, under Award Number DE-SC0008789. M. Le Henaff received partial support for this work from the NOAA Quantitative Observing System Assessment Program (QOSAP, grant NA15OAR4320064) and the base funds of the NOAA Atlantic Oceanographic and Meteorological Laboratory. The altimeter products were produced by SSALTO/DUACS and distributed by AVISO (http://www.aviso.altimetry.fr/duacs/), with support from the Centre National dEtudes Spatiales (CNES). The model outputs used in the present study are available on GRIIDC website (https://data.gulfresearchinitiative.org/).
PublisherAmerican Geophysical Union (AGU)