An application of seasonal forecasts to the study of extreme meteorological events: the case of drought.

Characterizing hydrometeorological extreme events can be hampered by the limited availability of observations of past meteorological conditions. Seasonal forecasts, which are commonly used to represent the temporal evolution of the predictable components of the Earth system over periods of a few weeks or months, have been recently applied to obtain information about extreme events and their dynamical drivers: indeed, they have a spatial resolution which is generally higher than that of climate projections and they can be used in order to get a better description of the complex and non-linear interactions taking place between the individual components of the Earth system. In this work, an application of seasonal forecast for the study of meteorological drought over Europe is presented. The paper is organized in three steps. First of all, the realism of simulations provided by C3S multi-system seasonal forecasts is assessed through a bias correction method and a statistical characterization. Then, it is shown how the applied method allows an estimate of the probability of new precipitation deficit which is consistent with that obtained from observations alone over the period 1993-2022 and that presents a markedly reduced uncertainty. At last, the investigation of the 500 hPa geopotential anomaly associated with the most intense meteorological drought events simulated by the model suggests that seasonal forecasts can be a powerful tool to better understand the dynamical drivers of climate extremes at the regional scale and the role played by the involved teleconnections, as highlighted by the similarity with the circulation pattern of the 2022 spring-summer drought event.