YaBeSH Engineering and Technology Library

    • Journals
    • PaperQuest
    • YSE Standards
    • YaBeSH
    • Login
    View Item 
    •   YE&T Library
    • AMS
    • Journal of Climate
    • View Item
    •   YE&T Library
    • AMS
    • Journal of Climate
    • View Item
    • All Fields
    • Source Title
    • Year
    • Publisher
    • Title
    • Subject
    • Author
    • DOI
    • ISBN
    Advanced Search
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Archive

    A Hidden Markov Model Perspective on Regimes and Metastability in Atmospheric Flows

    Source: Journal of Climate:;2008:;volume( 021 ):;issue: 008::page 1740
    Author:
    Franzke, Christian
    ,
    Crommelin, Daan
    ,
    Fischer, Alexander
    ,
    Majda, Andrew J.
    DOI: 10.1175/2007JCLI1751.1
    Publisher: American Meteorological Society
    Abstract: In this study, data from three atmospheric models are analyzed to investigate the existence of atmospheric flow regimes despite nearly Gaussian statistics of the planetary waves in these models. A hierarchy of models is used, which describes the atmospheric circulation with increasing complexity. To systematically identify atmospheric regimes, the presence of metastable states in the data is searched for by fitting so-called hidden Markov models (HMMs) to the time series. A hidden Markov model is designed to describe the situation in which part of the information of the system is unknown or hidden and another part is observed. Within the context of this study, some representative variable of planetary-scale flow (e.g., mean zonal flow or leading principal component) is known (?observed?), but its dynamics may depend crucially on the overall flow configuration, which is unknown. The behavior of this latter, ?hidden? variable is described by a Markov chain. If the Markov chain possesses metastable (or quasi persistent) states, they are identified as regimes. In this perspective, regimes can be present even though the observed data have a nearly Gaussian probability distribution. The parameters of the HMMs are fit to the time series using a maximum-likelihood approach; well-established and robust numerical methods are available to do this. Possible metastability of the Markov chain is assessed by inspecting the eigenspectrum of the associated transition probability matrix. The HMM procedure is first applied to data from a simplified model of barotropic flow over topography with a large-scale mean flow. This model exhibits regime behavior of its large-scale mean flow for sufficiently high topography. In the case of high topography, the authors find three regimes, two of which correspond to zonal flow and the third to blocking. Next, a three-layer quasigeostrophic model is used as a prototype atmospheric general circulation model (GCM). Its first empirical orthogonal function (EOF) is similar to the Arctic Oscillation (AO) and exhibits metastability. For this model, two regime states are found: one corresponding to the positive phase of the AO with large amplitude and decreased variability of the streamfunction field, and another corresponding to the negative AO phase with small amplitude and increased variability. Finally, the authors investigate a comprehensive GCM. The leading four EOFs of this model show no signs of metastability. The results of the barotropic flow over topography and of the quasigeostrophic model suggest that the observed small skewness of planetary wave probability density functions (PDFs) is an imprint of blocked circulation states.
    • Download: (2.265Mb)
    • Show Full MetaData Hide Full MetaData
    • Item Order
    • Go To Publisher
    • Price: 5000 Rial
    • Statistics

      A Hidden Markov Model Perspective on Regimes and Metastability in Atmospheric Flows

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/4207005
    Collections
    • Journal of Climate

    Show full item record

    contributor authorFranzke, Christian
    contributor authorCrommelin, Daan
    contributor authorFischer, Alexander
    contributor authorMajda, Andrew J.
    date accessioned2017-06-09T16:19:25Z
    date available2017-06-09T16:19:25Z
    date copyright2008/04/01
    date issued2008
    identifier issn0894-8755
    identifier otherams-65746.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4207005
    description abstractIn this study, data from three atmospheric models are analyzed to investigate the existence of atmospheric flow regimes despite nearly Gaussian statistics of the planetary waves in these models. A hierarchy of models is used, which describes the atmospheric circulation with increasing complexity. To systematically identify atmospheric regimes, the presence of metastable states in the data is searched for by fitting so-called hidden Markov models (HMMs) to the time series. A hidden Markov model is designed to describe the situation in which part of the information of the system is unknown or hidden and another part is observed. Within the context of this study, some representative variable of planetary-scale flow (e.g., mean zonal flow or leading principal component) is known (?observed?), but its dynamics may depend crucially on the overall flow configuration, which is unknown. The behavior of this latter, ?hidden? variable is described by a Markov chain. If the Markov chain possesses metastable (or quasi persistent) states, they are identified as regimes. In this perspective, regimes can be present even though the observed data have a nearly Gaussian probability distribution. The parameters of the HMMs are fit to the time series using a maximum-likelihood approach; well-established and robust numerical methods are available to do this. Possible metastability of the Markov chain is assessed by inspecting the eigenspectrum of the associated transition probability matrix. The HMM procedure is first applied to data from a simplified model of barotropic flow over topography with a large-scale mean flow. This model exhibits regime behavior of its large-scale mean flow for sufficiently high topography. In the case of high topography, the authors find three regimes, two of which correspond to zonal flow and the third to blocking. Next, a three-layer quasigeostrophic model is used as a prototype atmospheric general circulation model (GCM). Its first empirical orthogonal function (EOF) is similar to the Arctic Oscillation (AO) and exhibits metastability. For this model, two regime states are found: one corresponding to the positive phase of the AO with large amplitude and decreased variability of the streamfunction field, and another corresponding to the negative AO phase with small amplitude and increased variability. Finally, the authors investigate a comprehensive GCM. The leading four EOFs of this model show no signs of metastability. The results of the barotropic flow over topography and of the quasigeostrophic model suggest that the observed small skewness of planetary wave probability density functions (PDFs) is an imprint of blocked circulation states.
    publisherAmerican Meteorological Society
    titleA Hidden Markov Model Perspective on Regimes and Metastability in Atmospheric Flows
    typeJournal Paper
    journal volume21
    journal issue8
    journal titleJournal of Climate
    identifier doi10.1175/2007JCLI1751.1
    journal fristpage1740
    journal lastpage1757
    treeJournal of Climate:;2008:;volume( 021 ):;issue: 008
    contenttypeFulltext
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian
     
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian