This research has been funded by the U.S. Department of Energy under the Wind Forecast Improvement Project (WFIP), Award DE-EE0003080, and by NOAA/Earth System Research Laboratory. The authors wish to acknowledge Joseph Olson from the NOAA/ESRL/GSD group for providing the RAP model outputs, Barb DeLuisi from the NOAA/ESRL/PSD group for maintaining the RT&M website, and three anonymous reviewers for the helpful comments.
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The RT&M is coded in Matlab, and users can download the main code, functions and instructions, and the data used for this study to test the RT&M, before running it on their own datasets. When the RT&M is run, a GUI opens and the user can choose several options, some of which will be introduced in the subsequent narrative of the paper, and the others are explained in a readme file, downloadable with the RT&M. We also created an executable version of the code for users that do not have Matlab. In this case they will not be able to modify the Matlab code, but can still use the GUI. When a user runs the RT&M, he or she can select whether the input data will be wind speed or power, according to what type of data are available.
When a user runs the RT&M using the downloadable GUI, he or she can choose whether to run the RT&M over individual sites and then average the statistics, or to run the RT&M on the aggregated sites.
When a user runs the RT&M using the downloadable GUI, overlapping points will be shown with blue squares.
When a user runs the RT&M using the downloadable GUI, he or she could also choose different time windows and power thresholds by modifying the Matlab code, but the minimum possible time window that can be chosen is equal to 2 times the resolution of the data, in our case the minimum time window would be equal to 2 × 10 min = 20 min.
When a user runs the RT&M using the downloadable GUI, he or she can choose to run the RT&M averaging the ramp skill scores in all of the score matrix elements equally, or apply the weighting function introduced here to weight the extreme events (or create their own weighting matrix, according to his or her needs, by modifying the Matlab code itself).