Large Scale Natural Convection Boundary Layers with Non-Boussinesq Effects. This proposal aims to understand and predict heat transfer by turbulent natural convection in two scenarios, firstly at very large environmental scales, such as occur on melting Antarctic ice sheets, and secondly convection involving very large temperature differences such as occur in solar thermal power plants and industrial processes. These natural convection flow regimes are incredibly difficult to investigate directl ....Large Scale Natural Convection Boundary Layers with Non-Boussinesq Effects. This proposal aims to understand and predict heat transfer by turbulent natural convection in two scenarios, firstly at very large environmental scales, such as occur on melting Antarctic ice sheets, and secondly convection involving very large temperature differences such as occur in solar thermal power plants and industrial processes. These natural convection flow regimes are incredibly difficult to investigate directly but by focusing on the fundamental dynamics of the turbulent flows using large scale numerical simulations and innovative experiments, the project is expected to develop better analytical and computational models which will underpin improvements in
global ocean models and improve energy efficiency.Read moreRead less
Global integration of microbial community and climate data. Microbial communities in the environment control the cycling of carbon and nutrients on Earth, but climate models do not directly incorporate microbial inputs. This interdisciplinary project will link planetary-scale climate modelling data with novel large-scale microbial community analysis, using climate information to provide insight into the fantastic diversity of microbial processes on our planet. The interdisciplinary approach will ....Global integration of microbial community and climate data. Microbial communities in the environment control the cycling of carbon and nutrients on Earth, but climate models do not directly incorporate microbial inputs. This interdisciplinary project will link planetary-scale climate modelling data with novel large-scale microbial community analysis, using climate information to provide insight into the fantastic diversity of microbial processes on our planet. The interdisciplinary approach will inform the next generation of climate models and better predict our future climate’s feedbacks. Conversely, it will make progress on the grand challenge of understanding microbial community function by enabling microbial ecology to be treated as a data-intensive machine learning problem.Read moreRead less