Astronomy and Astrophysics – Astrophysics
Scientific paper
Dec 2011
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011agufmsh13a1929g&link_type=abstract
American Geophysical Union, Fall Meeting 2011, abstract #SH13A-1929
Astronomy and Astrophysics
Astrophysics
[3245] Mathematical Geophysics / Probabilistic Forecasting, [3315] Atmospheric Processes / Data Assimilation, [7536] Solar Physics, Astrophysics, And Astronomy / Solar Activity Cycle
Scientific paper
Data assimilation for the global solar magnetic fields face a number of challenges. For instance, photospheric fields tend to form similar bi-pole patterns on various spatial scales. An ensemble data assimilation, such as the ensemble Kalman filter (EnKF), if not applied properly can produce unphysical bi-pole patterns in the northern and southern hemisphere of the sun. These unphysical patters are a result of artificial correlations between the equatorial and pole regions of the sun within the ensemble data assimilation. In order to suppress these artificial correlations, a spatial localization technique for the assimilation must be implemented. The key is to determine the physically relevant correlation length scale. In this talk we present the implementation of the local ensemble transform Kalman filter (LETKF) for the assimilation of data within ADAPT. An overview of the LETKF, its advantages, and implementation to ADAPT will be presented. Additionally, the spatial correlation technique to obtain the relevant length scale will also be presented. Results show an improvement in the assimilation regarding the structure of the model state, and the total suppression of unphysical bi-pole patterns in the northern and southern poles.
Godinez Humberto C.
Koller Josef
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