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contributor authorKieu, Chanh Q.
contributor authorMoon, Zachary
date accessioned2017-06-09T16:46:07Z
date available2017-06-09T16:46:07Z
date copyright2016/10/01
date issued2016
identifier issn0003-0007
identifier otherams-73747.pdf
identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4215895
description abstracteather has long been projected to possess limited predictability due to the inherent chaotic nature of the atmosphere; small changes in initial conditions could lead to an entirely different state of the atmosphere after some period of time. Given such a limited range of predictability of atmospheric flows, a natural question is, how far in advance can we predict a hurricane?s intensity? In this study, it is shown first that the predictability of a hurricane?s intensity at the 4?5-day lead times is generally determined more by the large-scale environment than by a hurricane?s initial conditions. This result suggests that future improvement in hurricane longer-range intensity forecasts by numerical models will be most realized as a result of improvement in the large-scale environment rather than in the storm?s initial state. At the mature stage of a hurricane, direct estimation of the leading Lyapunov exponent using an axisymmetric model reveals, nevertheless, the existence of a chaotic attractor in the phase space of the hurricane scales. This finding of a chaotic maximum potential intensity (MPI) attractor provides direct information about the saturation of a hurricane?s intensity errors around 8 m s?1, which prevents the absolute intensity errors at the mature stage from being reduced below this threshold. The implication of such intensity error saturation to the limited range of hurricane intensity forecasts will be also discussed.
publisherAmerican Meteorological Society
titleHurricane Intensity Predictability
typeJournal Paper
journal volume97
journal issue10
journal titleBulletin of the American Meteorological Society
identifier doi10.1175/BAMS-D-15-00168.1
journal fristpage1847
journal lastpage1857
treeBulletin of the American Meteorological Society:;2016:;volume( 097 ):;issue: 010
contenttypeFulltext


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