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    A Marginal Adjustment Rank Histogram Filter for Non-Gaussian Ensemble Data Assimilation 

    Source: Monthly Weather Review:;2020:;volume( 148 ):;issue: 008:;page 3361
    Author(s): Anderson, Jeffrey L.
    Publisher: American Meteorological Society
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    A Quantile-Conserving Ensemble Filter Framework. Part II: Regression of Observation Increments in a Probit and Probability Integral Transformed Space 

    Source: Monthly Weather Review:;2023:;volume( 151 ):;issue: 010:;page 2759
    Author(s): Anderson, Jeffrey L.
    Publisher: American Meteorological Society
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    Barotropic Stationary States and Persistent Anomalies in the Atmosphere 

    Source: Journal of the Atmospheric Sciences:;1992:;Volume( 049 ):;issue: 018:;page 1709
    Author(s): Anderson, Jeffrey L.
    Publisher: American Meteorological Society
    Abstract: A robust algorithm, capable of finding nearly stationary solutions of the unforced barotropic vorticity equation near to observed atmospheric streamfunctions, is presented. When applied to observed persistent anomaly ...
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    A Simulation of Atmospheric Blocking with a Forced Barotropic Model 

    Source: Journal of the Atmospheric Sciences:;1995:;Volume( 052 ):;issue: 015:;page 2593
    Author(s): Anderson, Jeffrey L.
    Publisher: American Meteorological Society
    Abstract: Nearly stationary states (NSSs) of the barotropic vorticity equation (BVE) on the sphere that are closely related to observed atmospheric blocking patterns have recently been derived. Examining the way such NSSs affect ...
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    Selection of Initial Conditions for Ensemble Forecasts in a Simple Perfect Model Framework 

    Source: Journal of the Atmospheric Sciences:;1996:;Volume( 053 ):;issue: 001:;page 22
    Author(s): Anderson, Jeffrey L.
    Publisher: American Meteorological Society
    Abstract: An extremely simple chaotic model, the three-variable Lorenz convective model, is used in a perfect model setting to study the selection of initial conditions for ensemble forecasts. Observations with a known distribution ...
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    The Robustness of Barotropic Unstable Modes in a Zonally Varying Atmosphere 

    Source: Journal of the Atmospheric Sciences:;1991:;Volume( 048 ):;issue: 022:;page 2393
    Author(s): Anderson, Jeffrey L.
    Publisher: American Meteorological Society
    Abstract: The unstable normal modes of the barotropic vorticity equation, linearized around an observed zonally varying atmospheric flow, have been related to patterns of observed low-frequency variability. The sensitivity of this ...
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    The Impact of Dynamical Constraints on the Selection of Initial Conditions for Ensemble Predictions: Low-Order Perfect Model Results 

    Source: Monthly Weather Review:;1997:;volume( 125 ):;issue: 011:;page 2969
    Author(s): Anderson, Jeffrey L.
    Publisher: American Meteorological Society
    Abstract: A number of operational atmospheric prediction centers now produce ensemble forecasts of the atmosphere. Because of the high-dimensional phase spaces associated with operational forecast models, many centers use constraints ...
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    A Local Least Squares Framework for Ensemble Filtering 

    Source: Monthly Weather Review:;2003:;volume( 131 ):;issue: 004:;page 634
    Author(s): Anderson, Jeffrey L.
    Publisher: American Meteorological Society
    Abstract: Many methods using ensemble integrations of prediction models as integral parts of data assimilation have appeared in the atmospheric and oceanic literature. In general, these methods have been derived from the Kalman ...
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    A Method for Producing and Evaluating Probabilistic Forecasts from Ensemble Model Integrations 

    Source: Journal of Climate:;1996:;volume( 009 ):;issue: 007:;page 1518
    Author(s): Anderson, Jeffrey L.
    Publisher: American Meteorological Society
    Abstract: The binned probability ensemble (BPE) technique is presented as a method for producing forecasts of the probability distribution of a variable using an ensemble of numerical model integrations. The ensemble forecasts are ...
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    Reducing Correlation Sampling Error in Ensemble Kalman Filter Data Assimilation 

    Source: Monthly Weather Review:;2015:;volume( 144 ):;issue: 003:;page 913
    Author(s): Anderson, Jeffrey L.
    Publisher: American Meteorological Society
    Abstract: nsemble Kalman filters are widely used for data assimilation in large geophysical models. Good results with affordable ensemble sizes require enhancements to the basic algorithms to deal with insufficient ensemble variance ...
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