Life-cycle analysis of fog types in the Inn Valley, Austria

Fog and low stratus are a widespread phenomena worldwide, influencing the climate system and human activities. They reflect sunlight, reducing incoming solar radiation, yet also trap Earth’s thermal emission, leading to complex interactions that are not yet fully understood. Fog additionally supplies moisture to ecosystems. In terms of their impacts on human activities, fog reduces visibility, disrupting traffic systems, and, when combined with urban air pollution, can adversely affect human health. Although recent satellite-based research has advanced our understanding of fog and low clouds, accurate observations are still needed in order to describe fog life-cycle phases. Ground-based observations of fog life-cycle processes are essential for constraining the physical parametrization of fog formation and dissipation in weather and climate models.­

To fill these gaps, the Karlsruhe Institute of Technology (KIT), as part of ACTRIS (Aerosol, Clouds and Trace Gases Research Infrastructure), has recently developed a mobile facility: KLOCX (Karlsruhe Low Cloud Exploratory Platform). KLOCX combines in-situ and remote sensing instrumentation, delivering high-resolution vertical and temporal data on fog and low-cloud processes. Here, we analyze KLOCX observations from the TEAMx campaign in Austria’s Inn Valley, spanning the full fog season (winter 2024 – spring 2025). The study aims to identify how life cycle-phases differ among fog types and which mechanisms drive those differences. Our methodology comprised three stages: (1) fog event identification, (2) fog-types classification, and (3) life cycle-phases analysis. Thirty-five fog events were detected and classified by their main physical mechanism prior to fog onset, observing predominantly radiation fog (30 cases), followed by cloud-base lowering fog (3), and precipitation fog (2). These events served as the basis for applying an automated life-cycle algorithm that detected the start and end times of each phase using visibility trends and predefined thresholds. Our results show that the average durations of formation, maturity and dissipation phases vary across fog types. These findings improve our understanding of how complex topography interacts with local atmospheric conditions, which is essential for better models and forecasting accuracy.