Editorial Type:
Article
Article Type:
Research Article

Quadratic Polynomial Regression Using Serial Observation Processing: Implementation within DART

Daniel Hodyss Naval Research Laboratory, Monterey, California

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Jeffrey L. Anderson Data Assimilation Research Section, National Center for Atmospheric Research, Boulder, Colorado

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Nancy Collins Data Assimilation Research Section, National Center for Atmospheric Research, Boulder, Colorado

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William F. Campbell Naval Research Laboratory, Monterey, California

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Patrick A. Reinecke Naval Research Laboratory, Monterey, California

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Print Publication:
01 Nov 2017
DOI:
https://doi.org/10.1175/MWR-D-17-0089.1
Page(s):
4467–4479
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Abstract

It is well known that the ensemble-based variants of the Kalman filter may be thought of as producing a state estimate that is consistent with linear regression. Here, it is shown how quadratic polynomial regression can be performed within a serial data assimilation framework. The addition of quadratic polynomial regression to the Data Assimilation Research Testbed (DART) is also discussed and its performance is illustrated using a hierarchy of models from simple scalar systems to a GCM.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Daniel Hodyss, daniel.hodyss@nrlmry.navy.mil

Abstract

It is well known that the ensemble-based variants of the Kalman filter may be thought of as producing a state estimate that is consistent with linear regression. Here, it is shown how quadratic polynomial regression can be performed within a serial data assimilation framework. The addition of quadratic polynomial regression to the Data Assimilation Research Testbed (DART) is also discussed and its performance is illustrated using a hierarchy of models from simple scalar systems to a GCM.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Daniel Hodyss, daniel.hodyss@nrlmry.navy.mil
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