Verification of solar irradiance probabilistic forecasts

Philippe Lauret, Mathieu David, Pierre Pinson

Research output: Contribution to journalJournal articleResearchpeer-review


We propose a framework for evaluating the quality of solar irradiance probabilistic forecasts. The verification framework is based on visual diagnostic tools and a set of scoring rules mostly originating from the weather forecast verification community. Two types of probabilistic forecasts are used as a basis to illustrate the application of these verification approaches. The first one consists in ensemble forecasts commonly provided by national or international meteorological centres. The second one originates from statistical methods and produces a set of discrete quantile forecasts, the nominal proportions of which span the unit interval. These probabilistic forecasts are evaluated for two selected sites that experience very different climatic conditions. The first site is located in the continental US while the second one is situated on La Réunion Island. Although visual diagnostic tools can help identify deficiencies in generated forecasts, it is recommended that a set of numerical scores be used to assess the quality of probabilistic forecasts. In particular, the Continuous Ranked Probability Score (CRPS) seems to have all the features needed to evaluate a probabilistic forecasting system and, as such, may become a standard for verifying solar irradiance probabilistic forecasts and by extension probabilistic forecasts of solar power generation.
Original languageEnglish
JournalSolar Energy
Pages (from-to)254-271
Publication statusPublished - 2019


  • Probabilistic solar forecasting
  • Evaluation framework
  • Diagnostic tools
  • Scoring rules
  • CRPS
  • Ignorance Score

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