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Title: NLFFF extrapolations of AR10978 — analysis volumes      
NLFFF extrapolations of AR10978 — analysis volumes Brief description The results from a study to discern the dependence on spatial resolution by the various nonlinear force-free field (NLFFF) extrapolation methods are described in DeRosa et al. (2015). This dataset contains the analysis volumes from all 71 NLFFF extrapolations that were analyzed as part of the study. All bin levels for all methods are available, with the exception of the magnetofrictional solution for bin level 3. For the Grad-Rubin methods, both the N and P solutions are available. The data and metadata are stored in the nonproprietary HDF5 format, for which bindings exist in C, C++, Fortran90, IDL, Java, MATLAB, Python, R, and many other languages. Filename convention The filenames below use the following convention: binXX_opti.h5 : analysis volumes for the optimization method for bin level XX binXX_magf.h5 : analysis volumes for the magnetofrictional method for bin level XX binXX_cfit.Y.h5 : analysis volumes for the CFIT code for bin level XX, where Y indicates either the N or P solution binXX_femq.Y.h5 : analysis volumes for the FEMQ code for bin level XX, where Y indicates either the N or P solution binXX_xtra.Y.h5 : analysis volumes for the XTRAPOL code for bin level XX, where Y indicates either the N or P solution Data and metadata contained in each file For each case, the data file contains the following arrays: NLF: four-dimensional array containing Bx, By, and Bz as a function of x, y, and z XINDEX: index of x dimension, in Mm YINDEX: index of y dimension, in Mm ZINDEX: index of z dimension, in Mm
DeRosa, M.L.; Wheatland, M.S.; Leka, K.D.; Barnes, G.; Amari, T.; Canou, A.; Gilchrist, S.A.; Thalmann, J.K.; Valori, G.; Wiegelmann, T.; Schrijver, C.J.; Malanushenko, A.; Sun, X.; Régnier, S., 2015, "NLFFF extrapolations of AR10978 — analysis volumes",, Harvard Dataverse, V1
DeRosa, M.L.
Wheatland, M.S.
Leka, K.D.
Barnes, G.
Amari, T.
Canou, A.
Gilchrist, S.A.
Thalmann, J.K.
Valori, G.
Wiegelmann, T.
Schrijver, C.J.
Malanushenko, A.
Sun, X.
Régnier, S.
Harvard University
Dataverse Network Project