Characterization of the Dynamics of Climate Systems and Identification of Missing Mechanisms Impacting the Long Term Predictive Capabilities of Global Climate Models Utilizing Dynamical Systems Approaches to the Analysis of Observed and Modeled Climate

Bhatt, Uma S.; Wackerbauer, Renate; Polyakov, Igor V.; Newman, David E.; Sanchez, Raul E.

doi:10.2172/1225814

Title: Characterization of the Dynamics of Climate Systems and Identification of Missing Mechanisms Impacting the Long Term Predictive Capabilities of Global Climate Models Utilizing Dynamical Systems Approaches to the Analysis of Observed and Modeled Climate

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Abstract

The goal of this research was to apply fractional and non-linear analysis techniques in order to develop a more complete characterization of climate change and variability for the oceanic, sea ice and atmospheric components of the Earth System. This research applied two measures of dynamical characteristics of time series, the R/S method of calculating the Hurst exponent and Renyi entropy, to observational and modeled climate data in order to evaluate how well climate models capture the long-term dynamics evident in observations. Fractional diffusion analysis was applied to ARGO ocean buoy data to quantify ocean transport. Self organized maps were applied to North Pacific sea level pressure and analyzed in ways to improve seasonal predictability for Alaska fire weather. This body of research shows that these methods can be used to evaluate climate models and shed light on climate mechanisms (i.e., understanding why something happens). With further research, these methods show promise for improving seasonal to longer time scale forecasts of climate.

Authors:

Bhatt, Uma S. ^[1]; Wackerbauer, Renate ^[2]; Polyakov, Igor V. ^[1]; Newman, David E. ^[2]; Sanchez, Raul E. ^[3]

Univ. of Alaska, Fairbanks, AK (United States). Dept. of Atmospheric Sciences
Univ. of Alaska, Fairbanks, AK (United States). Dept. of Physics
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Fusion Energy Division; Univ. Carlos III de Madrid (Spain)

Publication Date:: Fri Nov 13 00:00:00 EST 2015

Research Org.:: Univ. of Alaska, Fairbanks, AK (United States)

Sponsoring Org.:: USDOE Office of Science (SC)

OSTI Identifier:: 1225814

Report Number(s):: DOE-UAF-0001898-1

DOE Contract Number:: SC0001898

Resource Type:: Technical Report

Country of Publication:: United States

Language:: English

Subject:: 54 ENVIRONMENTAL SCIENCES; Climate; Global Climate Models; Climate indices; Hurst Exponent; Reyni entropy

Citation Formats


                    Bhatt, Uma S., Wackerbauer, Renate, Polyakov, Igor V., Newman, David E., and Sanchez, Raul E. Characterization of the Dynamics of Climate Systems and Identification of Missing Mechanisms Impacting the Long Term Predictive Capabilities of Global Climate Models Utilizing Dynamical Systems Approaches to the Analysis of Observed and Modeled Climate.  United States: N. p., 2015. 
        Web.  doi:10.2172/1225814.

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                    Bhatt, Uma S., Wackerbauer, Renate, Polyakov, Igor V., Newman, David E., & Sanchez, Raul E. Characterization of the Dynamics of Climate Systems and Identification of Missing Mechanisms Impacting the Long Term Predictive Capabilities of Global Climate Models Utilizing Dynamical Systems Approaches to the Analysis of Observed and Modeled Climate.  United States.  https://doi.org/10.2172/1225814

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                    Bhatt, Uma S., Wackerbauer, Renate, Polyakov, Igor V., Newman, David E., and Sanchez, Raul E. 2015.  
        "Characterization of the Dynamics of Climate Systems and Identification of Missing Mechanisms Impacting the Long Term Predictive Capabilities of Global Climate Models Utilizing Dynamical Systems Approaches to the Analysis of Observed and Modeled Climate".  United States.  https://doi.org/10.2172/1225814.  https://www.osti.gov/servlets/purl/1225814.

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@article{osti_1225814,

  title        = {Characterization of the Dynamics of Climate Systems and Identification of Missing Mechanisms Impacting the Long Term Predictive Capabilities of Global Climate Models Utilizing Dynamical Systems Approaches to the Analysis of Observed and Modeled Climate},

  author       = {Bhatt, Uma S. and Wackerbauer, Renate and Polyakov, Igor V. and Newman, David E. and Sanchez, Raul E.},

  abstractNote = {The goal of this research was to apply fractional and non-linear analysis techniques in order to develop a more complete characterization of climate change and variability for the oceanic, sea ice and atmospheric components of the Earth System. This research applied two measures of dynamical characteristics of time series, the R/S method of calculating the Hurst exponent and Renyi entropy, to observational and modeled climate data in order to evaluate how well climate models capture the long-term dynamics evident in observations. Fractional diffusion analysis was applied to ARGO ocean buoy data to quantify ocean transport. Self organized maps were applied to North Pacific sea level pressure and analyzed in ways to improve seasonal predictability for Alaska fire weather. This body of research shows that these methods can be used to evaluate climate models and shed light on climate mechanisms (i.e., understanding why something happens). With further research, these methods show promise for improving seasonal to longer time scale forecasts of climate.},

  doi          = {10.2172/1225814},

  url          = {https://www.osti.gov/biblio/1225814},
  journal      = {},
number       = ,

  volume       = ,

  place        = {United States},

  year         = {Fri Nov 13 00:00:00 EST 2015},

  month        = {Fri Nov 13 00:00:00 EST 2015}

}

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