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Peter Rochford edited this page Feb 6, 2017 · 29 revisions

Summary

This toolbox contains a collection of Matlab functions for calculating the skill of model predictions against observations. It includes metrics such as root-mean-square-error (RMSE) difference, centered root-mean-square (RMS) difference, and skill score (SS), as well as a collection of functions for producing target and Taylor diagrams. The more valuable feature of the toolbox are the plotting functions for target and Taylor diagrams and the ability to easily customize the diagrams.

Contents

The toolbox contains a primer on Taylor diagrams as well as an "Examples" folder that contains a collection of example Matlab scripts showing how to produce target and Taylor diagrams in a variety of formats. There are 6 examples for target diagrams and 7 examples for Taylor diagrams that successively progress from very simple to more customized figures. These series of examples provide an easy tutorial on how to use the various options of the target_diagram and taylor_diagram functions. They also provide a quick reference in future for how to produce the diagrams with specific features. The diagrams produced by each script are in Portable Network Graphics (PNG) format and have the same file name as the script with a "png" suffix. Examples of the diagrams produced can be found in the Examples folder with the same file name as the script and ending in '_example.png'. For example the diagram produced by target1.m is named target1_example.png. Follow the links below to navigate each of the target and Taylor diagram examples.

Target Diagrams

Taylor Diagrams

All Statistics

There is also a simple program in the Examples folder (all_stats.m) that provides examples of how to calculate the various skill metrics used or available in the toolbox. All the calculated skill metrics are written to an Excel file for easy viewing and manipulation.

  • bias_skill : Calculate the bias between two variables
  • brier_score : Calculate Brier score (BS) between two variables
  • centered_rms_dev : Calculate centered root-mean-square difference (CRMSD, E') between two variables
  • check_taylor_stats : Checks input statistics satisfy Taylor diagram relation to <1%.
  • rms_dev : Calculate the root-mean-square deviation (RMSD) between two variables
  • rmse : Calculate root-mean-square-error (RMSE) difference between two variables
  • skill_score_brier : Calculate Brier skill score (BSS) between two variables
  • skill_score_murphy : Calculate non-dimensional skill score (SS) between two variables