SEEPS4ALL: an open dataset for the verification of daily precipitation forecasts using station climate statistics

Abstract. Forecast verification is an essential task when developing a forecasting model. How well does a model perform? How does the forecast performance compare with previous versions or other models? Which aspects of the forecast could be improved? In weather forecasting, these questions apply in particular to precipitation, a key weather parameter with vital societal applications. Scores specifically designed to assess the performance of precipitation forecasts have been developed over the years. One example is the Stable and Equitable Error in Probability Space (SEEPS, Rodwell et al., 2010). The computation of this score is however not straightforward because it requires information about the precipitation climatology at the verification locations. More generally, climate statistics are key to assessing forecasts for extreme precipitation and high-impact events. Here, we introduce SEEPS4ALL, a set of data and tools that democratize the use of climate statistics for verification purposes. In particular, verification results for daily precipitation are showcased with both deterministic and probabilistic forecasts.