skip to main content

This content will become publicly available on March 17, 2016

Title: Data Assimilation in the ADAPT Photospheric Flux Transport Model

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.
 [1] ;  [1] ;  [2] ;  [2]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  2. AFRL, Albuquerque, NM (United States)
Publication Date:
OSTI Identifier:
Report Number(s):
Journal ID: ISSN 0038-0938; PII: 666
Grant/Contract Number:
Accepted Manuscript
Journal Name:
Solar Physics
Additional Journal Information:
Journal Volume: 290; Journal Issue: 4; Journal ID: ISSN 0038-0938
Research Org:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org:
Country of Publication:
United States
79 ASTRONOMY AND ASTROPHYSICS; 97 MATHEMATICS AND COMPUTING; Solar magnetic fields; photosphere; data assimilation