Adding fair scoring rules #2442
Replies: 4 comments 5 replies
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Hello, And thank you for your question. I've gone ahead and let our resident statistician know about this question. They're currently out of the office, but will respond to you as soon as they are back and able. |
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Note MET issue #2280 is a prerequisite to allow us to compute the fair Brier and fair RPS in VerPy from PCT output, as these scores require the probabilities to be un-binned ensemble relative frequencies, and this is our most urgent requirement. As Marion says, it would be useful if these scores were available more directly from MET or METplus, but not essential for us. As MET's IGN is the ignorance score based on a normal distribution (aka the Dawid-Sebastiani score), the fair ignorance score defined in section 3 of Siegert et al 2019 would be another possibility. It looks straightforward enough to code as a modification of IGN (it involves the digamma function |
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I agree that we should have these scores in MET (or downstream in METplus). You might get @bgbrowntollerud's opinion, though, as I believe she has more familiarity with fair scores than I have. |
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Roger - after the holidays, would it be possible for you to jump in and help us with getting this into METplus. Marion suggested you might be able to help by looking at the code to determine where to add it and advise us on how to test it. |
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Recent recommendations from an in-house ensemble verification workshop made the recommendation that we should move to using fair scores across all calculations. This is because we operate a very complex ensemble generation process where we only produce 3 new members every hour and then these are combined/lagged to create an 18-member ensemble over 6h. Our system VER does not compute these internally but they are easily derived in VerPy as it is a simple scaling of the score. Therefore, whilst it isn't essential for us to have MET be able to calculate them, as we can continue to use VerPy to do so, it would be beneficial for a MET-based system to provide such scores for users of the software that don't have access to something like VerPy. I will leave it up to developers to decide whether they want to add it to the core tool or only offer it in downstream options (as we do, e.g. metcalcpy).
Fair scoring rules will ensure that irrespective of how many members the ensemble has, you can compare them safely and equitably. We would also want to leverage this for the computation of HiRA metrics.
https://rmets.onlinelibrary.wiley.com/doi/full/10.1002/qj.2270
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