ERC Stories - Understanding turbulence: the key to weather prediction
"Turbulence is the key to the atmospheric ‘machine’," says Prof. Zilitinkevich. "We cannot understand weather systems if we do not understand the connections between their parts." According to Prof. Zilitinkevich, for almost a century, turbulence has been understood in an oversimplified form, based on an assumption that it could be split into two parts: 'mean flow' (organised motion which can be analysed using classical mechanics) and 'turbulence' (chaotic motion which must be analysed using statistical methods). This approach works well for engineering applications, but in the field of geophysical turbulence – such as climate and weather – these methods face increasing difficulties. In the atmosphere or ocean, the density of the medium changes with height. This leads to stratification, instability and phenomena such as convection. The classical paradigm has not been able to deal with these phenomena satisfactorily. New paradigm "We are now seeing a scientific revolution in this field," says Prof. Zilitinkevich. "Atmospheric turbulence can now be seen as having three parts: regular flow, chaotic turbulence and self-organised structures." Self-organisation leads to long-lived structures, such as convective cells or rolls in the atmosphere or ocean. This new understanding means that both researchers and operational modellers need to account for these different types of movements and their role in energy and matter exchange in the atmosphere and ocean. "Heat exchange between the upper ocean and lower atmosphere is controlled by turbulence," explains Prof. Zilitinkevich. "Most thermal energy is in the ocean not the atmosphere, but we experience climate anthropocentrically as a characteristic of the near-surface part of the atmosphere, the atmospheric ‘planetary boundary layer’ (PBL)." His PBL-PMES project aims to revise thoroughly the physics theories used to model PBLs. Not only will this lead to better understanding of heat exchange between land, sea and air, but researchers will also gain insight into phenomena like shallow stable atmospheric PBLs which trap smog and pollution in the air above cities. Prof. Zilitinkevich expects his research to lead to radical changes in scientific understanding of weather and climate and in the success of forecasting models. "Within a decade, we should have incomparably better weather and climate predictions," he says. "Microclimates, such as local climate change due to land-use change, will be modelled with greater accuracy." The new theoretical framework will then be implemented in modern weather-forecasting and air-pollution models. Until recently, one of the biggest limiting factors in weather prediction has been the spatial resolution of the models, restricted by the power of supercomputers. But new improved physics means it is now the models that need to be revised. "We are co-operating with a very good network of operational weather-modelling groups around Europe," says Prof. Zilitinkevich. "By the end of next year we hope to have some practical results from the Finnish Meteorological Institute – and we are also working with MétéoFrance and the Danish Meteorological Institute." In addition, the project is working to validate its theories with astrophysicists, helping to explain convection in stars and the sun, as well as accretion disks around black holes. "We are lucky in that we can now combine two hot new areas of research,” says Prof. Zilitinkevich, “a new theory of turbulence and a new demand for turbulence applications in climate models" Project details: - Principal investigator: Professor Sergej S. Zilitinkevich - Host institution: Finnish Meteorological Institute (FMI), Finland - Project: Atmospheric planetary boundary layers: physics, modelling and role in Earth system (PBL-PMES) - ERC call: Advanced Grant 2008 - ERC funding: EUR 2.4 million - Project duration: five years – Prof. Zilitinkevich's PBL-PMES project website