Popular Scientific Presentation
The meteorological research focuses upon the atmospheric boundary layer and the free troposphere – roughly spanning the lowest 10 kilometres of our atmosphere.
The research in boundary-layer meteorology is devoted to studies of the physical processes in the lowest few hundred meters or, at most first few kilometres, of the atmosphere. This is the direct atmospheric environment for humans, animals and plants living on the Earth's surface. The boundary layer is a highly turbulent environment, which acts as the link between the overlying atmosphere and the underlying land or ocean surface. Specifically, it is where vertical transports and exchanges of momentum, sensible heat, water vapour, carbon dioxide, methane and aerosols between the atmosphere and surface occur. A correct treatment of the atmospheric boundary layer is of crucial importance for weather forecasting, numerical simulations of climate change, abatement of air pollutants, effective use of wind energy and more.
The boundary-layer research in the meteorology group includes basic understanding of physical and chemical processes over land and water (air-sea and air-lake interactions), the importance of surface gravity waves on the atmosphere and ocean as well as more applied projects focusing on wind energy, noise propagation and air pollution. Our main tools are in-situ micrometeorological measurements from towers and drones, remotely sensed data and numerical models.
The research on the free troposphere – namely the atmospheric layer above the boundary layer – spans the drivers, predictability and impacts of extreme climate events. The focus is on the mid and high latitudes and on events such as temperature and precipitation extremes and windstorms. To understand the physical drivers of these events, we study processes ranging from hundreds (e.g. extratropical cyclones) to thousands of kilometres (e.g. planetary waves). The work on predictability combines this physical understanding with techniques from applied mathematics and machine learning to improve our ability to forecast the occurrence of extreme events on multiple timescales. Finally, the work on impacts considers effects on the biosphere, including agriculture, on the built environment and on energy production.