Day-to-day temperature variability, atmospheric fronts, and circulation types: How they fit together?

This preliminary study builds on previous work on the climatology of atmospheric fronts over Europe and their relationship with day-to-day near-surface air temperature variability. Earlier analyses have shown that temperature responses to frontal passages exhibit substantial spatial and seasonal variability, suggesting the influence of multiple interacting atmospheric processes.

The present contribution focuses on the role of large-scale circulation in modulating day-to-day temperature differences (DTD) associated with atmospheric fronts. Fronts are identified using an objective detection method applied to ERA5 reanalysis data for the period 1961–2020 over Europe. The synoptic-scale circulation is characterized by the Jenkinson–Collison classification derived from sea level pressure fields and aggregated into a reduced set of circulation types.

The analysis considers both warm and cold fronts during winter and summer seasons. In addition to temperature changes, the relationship between circulation types and frontal occurrence is examined using conditional probabilities, which quantify how strongly individual circulation types favour the occurrence of a given front type relative to its climatological frequency. This framework enables a systematic assessment of the links between frontal passages, temperature variability, and large-scale circulation.

Preliminary results indicate that circulation types may influence both the occurrence of fronts and the associated temperature responses. However, the strength and spatial structure of these relationships vary considerably across Europe and between seasons, pointing to a complex interplay between frontal dynamics and atmospheric circulation.

Overall, this study represents a first step towards a more integrated understanding of temperature variability by combining objective front detection with circulation classification. Further work is needed to better quantify and interpret the identified relationships.