Irradiance Forecasts Verification Using Murphy-Winkler Factorization: Performance of Three American NWP Models in 2024

Irradiance forecasts issued by numerical weather prediction (NWP) models are essential to managing photovoltaic power over day-ahead horizons. Clearly then, it is important for the forecast users to understand how well the forecasts perform. Traditional verification relies heavily on a suite of error metrics, also known as performance indicators or accuracy measures, which have several known pitfalls that often lead to inconclusive or disagreeing outcomes. On this point, Murphy-Winkler factorization, which is a distribution-oriented verification framework, has been advocated. In a nutshell, this approach decomposes the joint distribution of forecast and observation into four distinct components, each representing one or more qualitative measures that are relevant to verification. In this work, Murphy- Winkler factorization is applied to 1-12-h forecasts produced by three American NWP models, namely, the North American Mesoscale model, the Rapid Refresh model, and the High-Resolution Rapid Refresh model, over 2024. It is confirmed that the three models possess superiority in different aspects. The importance of clarifying the directives before verification is thus emphasized.