Extreme Windstorm “Kristin”: Representation across the model spectrum

This talk will focus on the devastating small-scale cyclonic windstorm “Kristin” that hit central Portugal in the early hours of 28^th January 2026. This was reportedly the most costly European windstorm since “Lothar” hit France 26 years ago.

After describing the dynamical setting, including critical juxtaposition of an upper level jet and the surface feature, and the storm‘s morphology, including strong radar-based evidence of a sting jet, the surface impacts in both Portugal and Spain will be highlighted. These included 15 fatalities, Portugal’s biggest ever power outage, with over 5000 km of power lines damaged or destroyed, 15 million trees uprooted or snapped and an estimated €7.2 billion in losses in Iberia.

Next the handling by various forecast models, and reanalysis products, will be elaborated. Due in part to Kristin’s small size there was a strong link between the accuracy of model output and model spatial resolution. But even at higher resolution other problems are apparent, such as the generation of some unrealistic initial conditions in mean sea level pressure via the ECMWF EDA (ensemble of data assimilations). Also there was high uncertainty in cyclone track, such that red warnings issued by the Portuguese Met Service (IPMA) initially covered an area much larger than the area eventually impacted.

Machine learning model output, from ECMWF’s AIFS systems, will be included in discussion, highlighting the extra challenges of using such systems. These include temporal discretization (currently 6h), lack of a gust diagnostic and the potential for noisy output.

The practical implications of all these issues, for forecasting in a life-critical operational setting, will be discussed.

Similarities between storm Kristin and other notable small-scale European windstorms, such as Xola from 2009, will also be touched on.