The application of a simple carbon balance model, combined with a data assimilation approach, has the potential to improve the process understanding embedded in models, which is used to predict responses of the carbon cycle to climate change.
Convective parameterizations are widely believed to be essential for realistic simulations of the atmosphere, but are crude in today's weather and climate models. CLEX researchers, report on what happens when a number of these models are run with these schemes simply turned off.
This study evaluated GCMs for common drought metrics during the past 55 years. It found different models can produce very different simulations of drought, depending on the type of drought and metric analysed. The study points to a need to improve GCMs for droughts to reduce uncertainties in future projections.
This interdisciplinary project will apply methods from statistical physics, which are only beginning to be used in the environmental sciences, to better exploit such data, advance our basic understanding, and produce more useful models for weather and climate changes.
This PhD project will use climate model simulations to examine how sensitive attribution assessments of high-impact heatwaves to human emissions of carbon dioxide are to the representation of key physical processes.
With major developments in climate modelling we are significantly closing the gap that used to exist between what business needs to know and what climate science/engineering can provide. This project will merge climate science and engineering to address the key question industry asks – what is the future economic viability of renewable projects?
This PhD will use sophisticated alternatives for removing systematic biases in the lateral boundary conditions of such experiments, with the aim of assessing the extent of change that results in the resulting extreme storm. Outcomes here can help define how we design Civil Engineering infrastructure in warming climates.
Using novel techniques developed by the supervisory team, the PhD candidate will evaluate the role of diabatic processes in the ENSO cycle, and how they may change in the future, using new observations and state-of-the-art model simulations. This research is critical to improving our ability to project future climate change.
This project will connect plant water use and stomatal conductance models differentiated by vegetation-soil systems with land surface models to provide new insight into the impacts of the built environment on moisture fluxes that influence heatwave intensity. Then it will investigate the climate impacts of the dynamic response of greenery in extreme heat conditions.
In contrast to expectations, tropical thunderstorms without cold pools actually intensify, demonstrating unequivocally that cold pools can be detrimental to convection. Further investigations suggest that organised systems become maintained through atmospheric wave-convection interactions, which is a significantly different process to the established theory.