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Potential root mean square error skill score

  • Martin János Mayer*
  • , Dazhi Yang
  • *Corresponding author for this work
  • Budapest University of Technology and Economics
  • School of Electrical Engineering and Automation, Harbin Institute of Technology

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Article number016501
JournalJournal of Renewable and Sustainable Energy
Volume16
Issue number1
DOIs
StatePublished - 1 Jan 2024
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

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