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    Ensemble State Estimation for Nonlinear Systems Using Polynomial Expansions in the Innovation 

    Source: Monthly Weather Review:;2011:;volume( 139 ):;issue: 011:;page 3571
    Author(s): Hodyss, Daniel
    Publisher: American Meteorological Society
    Abstract: new framework is presented for understanding how a nonnormal probability density function (pdf) may affect a state estimate and how one might usefully exploit the nonnormal properties of the pdf when constructing a state ...
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    Accounting for Skewness in Ensemble Data Assimilation 

    Source: Monthly Weather Review:;2012:;volume( 140 ):;issue: 007:;page 2346
    Author(s): Hodyss, Daniel
    Publisher: American Meteorological Society
    Abstract: practical data assimilation algorithm is presented that explicitly accounts for skewness in the prior distribution. The algorithm operates as a global solve (all observations are considered at once) using a minimization-based ...
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    A Theory for Why Even Simple Covariance Localization Is So Useful in Ensemble Data Assimilation 

    Source: Monthly Weather Review:;2023:;volume( 151 ):;issue: 003
    Author(s): Morzfeld, Matthias; Hodyss, Daniel
    Publisher: American Meteorological Society
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    The Resonant Excitation of Baroclinic Waves by the Divergent Circulation of Recurving Tropical Cyclones 

    Source: Journal of the Atmospheric Sciences:;2010:;Volume( 067 ):;issue: 011:;page 3600
    Author(s): Hodyss, Daniel; Hendricks, Eric
    Publisher: American Meteorological Society
    Abstract: This paper explores the hypothesis that a tropical cyclone (TC) may produce baroclinic waves through the divergent circulation that arises from its low-level inflow and upper-level outflow. The model setting is a ...
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    How Sampling Errors in Covariance Estimates Cause Bias in the Kalman Gain and Impact Ensemble Data Assimilation 

    Source: Monthly Weather Review:;2023:;volume( 151 ):;issue: 009:;page 2413
    Author(s): Hodyss, Daniel; Morzfeld, Matthias
    Publisher: American Meteorological Society
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    A Theory for Why Even Simple Covariance Localization Is So Useful in Ensemble Data Assimilation 

    Source: Monthly Weather Review:;2023:;volume( 151 ):;issue: 003:;page 717
    Author(s): Morzfeld, Matthias; Hodyss, Daniel
    Publisher: American Meteorological Society
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    A Deeper Analysis of Center-Finding Techniques for Tropical Cyclones in Mesoscale Models. Part I: Low-Wavenumber Analysis 

    Source: Journal of Applied Meteorology and Climatology:;2015:;volume( 055 ):;issue: 003:;page 531
    Author(s): Ryglicki, David R.; Hodyss, Daniel
    Publisher: American Meteorological Society
    Abstract: deeper analysis of possible errors and inconsistencies in the analysis of vortex asymmetries owing to the placement of centers of tropical cyclones (TCs) in mesoscale models is presented. Previous works have established ...
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    Linear Anelastic Equations for Atmospheric Vortices 

    Source: Journal of the Atmospheric Sciences:;2007:;Volume( 064 ):;issue: 008:;page 2947
    Author(s): Hodyss, Daniel; Nolan, David S.
    Publisher: American Meteorological Society
    Abstract: A linear anelastic-vortex model is derived using assumptions appropriate to waves on vortices with scales similar to tropical cyclones. The equation set is derived through application of a multiple-scaling technique, such ...
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    Adaptive Ensemble Covariance Localization in Ensemble 4D-VAR State Estimation 

    Source: Monthly Weather Review:;2011:;volume( 139 ):;issue: 004:;page 1241
    Author(s): Bishop, Craig H.; Hodyss, Daniel
    Publisher: American Meteorological Society
    Abstract: n adaptive ensemble covariance localization technique, previously used in ?local? forms of the ensemble Kalman filter, is extended to a global ensemble four-dimensional variational data assimilation (4D-VAR) scheme. The ...
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    Square Root and Perturbed Observation Ensemble Generation Techniques in Kalman and Quadratic Ensemble Filtering Algorithms 

    Source: Monthly Weather Review:;2013:;volume( 141 ):;issue: 007:;page 2561
    Author(s): Hodyss, Daniel; Campbell, William F.
    Publisher: American Meteorological Society
    Abstract: he main goal of this work is to present a new square root ensemble generation technique that is consistent with a recently developed extension of Kalman-based linear regression algorithms such that they may perform nonlinear ...
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    DSpace software copyright © 2002-2015  DuraSpace
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