Research Fellow

We seek to appoint a research fellow in Modelling of Marine Atmospheric Composition within the Institute for Climate and Atmospheric Science at the University of Leeds. The successful candidate will lead global atmospheric chemistry and Earth system modelling analysis to knowledge of global-scale impacts of natural volatile organic compound (VOC) emissions from the oceans. The work is funded under the UKRI COCO-VOC (Closing the budget in marine atmospheric Oxidative Capacity through the quantification of Oceanic VOC emissions) Large Grant project, involving 5 UK organisations, and a number of overseas partners. The project aims to quantify the impacts of reactive carbon emissions from the global oceans on the climate system, through improving understanding of VOC and OH cycling in the background atmosphere, and constraining the sensitivities of VOCs, aerosol, and the global atmospheric oxidative capacity to changes in anthropogenic and natural emissions. You will collaborate
extensively with UK and international partners from across the project.
In this role, you will develop and implement new model schemes, and design, run and analyse Earth system model simulations to quantify the role of sea-air exchange of reactive VOCs in modifying atmospheric oxidation chemistry and aerosol. You will quantify impacts of these VOC emissions on oxidative capacity, methane lifetime, and cloud condensation nuclei abundances, to estimate their role in the global climate system, and implications for anthropogenic radiative forcing. You will collaborate closely with partners from across the COCO-VOC project, using field measurements to constrain a sea-air transfer parameterisation, and to evaluate the Earth system model. You will have the opportunity to work with a wide range of research groups, and to take a leading and active role in national and international project meetings.
You will have a PhD in atmospheric science or climate science, expertise in atmospheric chemistry, and experience of running and analysing numerical models on high performance computing platforms. You will have a proven ability to tackle complex science problems using a combination of models and observations, and an enthusiasm to work closely with national and international collaborators across the varied disciplines of field measurements, laboratory measurements, and modelling.