Articles | Volume 7, issue 1
https://doi.org/10.5194/ascmo-7-13-2021
https://doi.org/10.5194/ascmo-7-13-2021
16 Feb 2021
 | 16 Feb 2021

Novel measures for summarizing high-resolution forecast performance

Eric Gilleland

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Cited articles

Ahijevych, D., Gilleland, E., Brown, B. G., and Ebert, E. E.: Application of spatial verification methods to idealized and NWP-gridded precipitation forecasts, Weather Forecast., 24, 1485–1497, 2009. a, b, c, d, e
Baddeley, A. J.: Errors in binary images and an Lp version of the Hausdorff metric, Nieuw Arch. Wiskunde, 10, 157–183, 1992a. a, b, c, d
Baddeley, A. J.: An error metric for binary images, in: Robust Computer Vision Algorithms, edited by: Forstner, W. and Ruwiedel, S., Wichmann, 402 pp., 59–78, available at: https://pdfs.semanticscholar.org/aa50/669b71429f2ca54d64f93839a9da95ceba6b.pdf (last access: 14 May 2020), 1992b. a, b, c, d, e, f
Baddeley, A. and Turner, R.: spatstat: An R Package for Analyzing Spatial Point Patterns, J. Stat. Softw., 12, 1–42, available at: http://www.jstatsoft.org/v12/i06/ (last access: 11 February 2021), 2005. a
Baldwin, M. E. and Elmore, K. L.: Objective verification of high-resolution WRF forecasts during 2005 NSSL/SPC Spring Program, in: 21st Conf. on Weather Analysis and Forecasting/17th Conf. on Numerical Weather Prediction, Amer. Meteor. Soc., Washington, D.C., 11B4, 2005. a
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Short summary
Verifying high-resolution weather forecasts has become increasingly complicated, and simple, easy-to-understand summary measures are a good alternative. Recent work has demonstrated some common pitfalls with many such summaries. Here, new summary measures are introduced that do not suffer from these drawbacks, while still providing meaningful information.
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