Taylor diagrams are mathematical diagrams designed to graphically indicate which of several approximate representations (or models) of a system, process, or phenomenon is most realistic. This diagram, invented by Karl E. Taylor in 1994 (published in 2001[1]) facilitates the comparative assessment of different models. It is used to quantify the degree of correspondence between the modeled and observed behavior in terms of three statistics: the Pearson correlation coefficient, the root-mean-square error (RMSE) error, and the standard deviation.
Although Taylor diagrams have primarily been used to evaluate models designed to study climate and other aspects of Earth's environment,[2] they can be used for purposes unrelated to environmental science (e.g., to quantify and visually display how well fusion energy models represent reality[3]).
Taylor diagrams can be constructed with a number of different open source and commercial software packages, including: GrADS,[4][5] IDL,[6] MATLAB,[7][8][9] NCL,[10] Python,[11][12] R,[13] and CDAT.[14]
^Taylor, K.E. (2001). "Summarizing multiple aspects of model performance in a single diagram". J. Geophys. Res.106: 7183–7192. Bibcode:2001JGR...106.7183T. doi:10.1029/2000JD900719.
^"Google Scholar". scholar.google.com.
^Terry, P.W.; et al. (2008). "Validation in fusion research: Towards guidelines and best practices". Phys. Plasmas. 15. arXiv:0801.2787. Bibcode:2008PhPl...15f2503T. doi:10.1063/1.2928909.
^"Calculate statistics used in Taylor diagram in GrADS".
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