skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Data Assimilation in the ADAPT Photospheric Flux Transport Model

Abstract

Global maps of the solar photospheric magnetic flux are fundamental drivers for simulations of the corona and solar wind and therefore are important predictors of geoeffective events. However, observations of the solar photosphere are only made intermittently over approximately half of the solar surface. The Air Force Data Assimilative Photospheric Flux Transport (ADAPT) model uses localized ensemble Kalman filtering techniques to adjust a set of photospheric simulations to agree with the available observations. At the same time, this information is propagated to areas of the simulation that have not been observed. ADAPT implements a local ensemble transform Kalman filter (LETKF) to accomplish data assimilation, allowing the covariance structure of the flux-transport model to influence assimilation of photosphere observations while eliminating spurious correlations between ensemble members arising from a limited ensemble size. We give a detailed account of the implementation of the LETKF into ADAPT. Advantages of the LETKF scheme over previously implemented assimilation methods are highlighted.

Authors:
 [1];  [1];  [2];  [2]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  2. AFRL, Albuquerque, NM (United States)
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1215514
Report Number(s):
LA-UR-14-27938
Journal ID: ISSN 0038-0938; PII: 666
Grant/Contract Number:
AC52-06NA25396
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Solar Physics
Additional Journal Information:
Journal Volume: 290; Journal Issue: 4; Journal ID: ISSN 0038-0938
Publisher:
Springer
Country of Publication:
United States
Language:
English
Subject:
79 ASTRONOMY AND ASTROPHYSICS; 97 MATHEMATICS AND COMPUTING; Solar magnetic fields; photosphere; data assimilation

Citation Formats

Hickmann, Kyle S., Godinez, Humberto C., Henney, Carl J., and Arge, C. Nick. Data Assimilation in the ADAPT Photospheric Flux Transport Model. United States: N. p., 2015. Web. doi:10.1007/s11207-015-0666-3.
Hickmann, Kyle S., Godinez, Humberto C., Henney, Carl J., & Arge, C. Nick. Data Assimilation in the ADAPT Photospheric Flux Transport Model. United States. doi:10.1007/s11207-015-0666-3.
Hickmann, Kyle S., Godinez, Humberto C., Henney, Carl J., and Arge, C. Nick. Tue . "Data Assimilation in the ADAPT Photospheric Flux Transport Model". United States. doi:10.1007/s11207-015-0666-3. https://www.osti.gov/servlets/purl/1215514.
@article{osti_1215514,
title = {Data Assimilation in the ADAPT Photospheric Flux Transport Model},
author = {Hickmann, Kyle S. and Godinez, Humberto C. and Henney, Carl J. and Arge, C. Nick},
abstractNote = {Global maps of the solar photospheric magnetic flux are fundamental drivers for simulations of the corona and solar wind and therefore are important predictors of geoeffective events. However, observations of the solar photosphere are only made intermittently over approximately half of the solar surface. The Air Force Data Assimilative Photospheric Flux Transport (ADAPT) model uses localized ensemble Kalman filtering techniques to adjust a set of photospheric simulations to agree with the available observations. At the same time, this information is propagated to areas of the simulation that have not been observed. ADAPT implements a local ensemble transform Kalman filter (LETKF) to accomplish data assimilation, allowing the covariance structure of the flux-transport model to influence assimilation of photosphere observations while eliminating spurious correlations between ensemble members arising from a limited ensemble size. We give a detailed account of the implementation of the LETKF into ADAPT. Advantages of the LETKF scheme over previously implemented assimilation methods are highlighted.},
doi = {10.1007/s11207-015-0666-3},
journal = {Solar Physics},
number = 4,
volume = 290,
place = {United States},
year = {Tue Mar 17 00:00:00 EDT 2015},
month = {Tue Mar 17 00:00:00 EDT 2015}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record

Citation Metrics:
Cited by: 25 works
Citation information provided by
Web of Science

Save / Share: