Consistency, in a narrow sense, denotes the alignment between the forecast-optimization strategy and the verification directive. The current recommended deterministic solar forecast verification practice is to report the skill score based on root mean square error (RMSE), which would violate the notion of consistency if the forecasts are optimized under another strategy such as minimizing the mean absolute error (MAE). This paper overcomes such difficulty by proposing a so-called “potential RMSE skill score,” which depends only on (1) the cross-correlation between forecasts and observations and (2) the autocorrelation of observations. While greatly simplifying the calculation, the new skill score does not discriminate inconsistent forecasts as much, e.g., even MAE-optimized forecasts can attain a high RMSE skill score.
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March 2024
Research Article|
February 26 2024
Potential root mean square error skill score
Martin János Mayer
;
Martin János Mayer
a)
(Conceptualization, Data curation, Investigation, Methodology, Visualization, Writing – original draft)
1
Department of Energy Engineering, Faculty of Mechanical Engineering, Budapest University of Technology and Economics
, Műegyetem rkp. 3, H-1111 Budapest, Hungary
a)Author to whom correspondence should be addressed: mayer@energia.bme.hu
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Dazhi Yang
Dazhi Yang
(Methodology, Validation, Writing – review & editing)
2
School of Electrical Engineering and Automation, Harbin Institute of Technology
, Harbin, Heilongjiang, China
Search for other works by this author on:
a)Author to whom correspondence should be addressed: mayer@energia.bme.hu
J. Renewable Sustainable Energy 16, 016501 (2024)
Article history
Received:
November 10 2023
Accepted:
January 16 2024
Citation
Martin János Mayer, Dazhi Yang; Potential root mean square error skill score. J. Renewable Sustainable Energy 1 January 2024; 16 (1): 016501. https://doi.org/10.1063/5.0187044
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