VIRTUAL | Yorkshire Local Centre Annual PhD Showcase

SPEAKERS: Eszter Kovacs, Jonathan Coney, Lauren Burton

SUMMARY: Every year RMetS Yorkshire welcomes 3 PhD students from the Institute for Climate and Atmospheric Science (ICAS) to showcase their work. These talks demonstrate topics being studied in the fields of meteorology & climate, & their applications to society. No prior scientific knowledge necessary!

FIRST SPEAKER: Eszter Kovacs

TITLE: Algae with a chance of clouds: How does ocean biology relate to cloudiness in the Southern Ocean?

ABSTRACT: We’re seeing more cloud droplets in Southern Ocean and Antarctic clouds than we would expect. DMS produced by phytoplankton has long been suspected to be the culprit behind this, and while correlations have been shown between the seasonal cycles of the two, we still don’t quite understand the extent of the influence that DMS has on clouds. Satellite data allows us to investigate what happens in this remote, pristine region without the effect of anthropogenic emissions.

SECOND SPEAKER: Lauren Burton

TITLE: Back to the Future Part IV: Palaeoclimates

ABSTRACT: Climate change is the biggest problem faced by humanity. Our projections of future climate have significantly improved and increased in confidence over the last few decades but it is impossible to know for certain what the climate of the future will look like. However, we can use climate models to simulate a range of possible futures and also look back in Earth’s history to times which had a similar climate. In this talk you will be transported “Back to the Future” to the Pliocene, a time 3 million years ago where temperatures and sea level were higher, precipitation was increased and ice sheets were smaller. Is this an analogue for our future?

THIRD SPEAKER: Jonathan Coney

TITLE: Hold on to your hats/sheep: Mountain Weather

ABSTRACT: My PhD is all about mountain weather processes. So far I’ve been focusing on trapped lee waves (gravity waves) triggered by the flow of air over orography. The Met Office’s operational high resolution Numerical Weather Prediction model, UKV, resolves lee wave activity in its output but cannot segment it into regions of “waves” and “no waves”. I’ve been developing a tool using machine learning to recognise regions of lee wave activity over the UK from the model output, with a view to make a climatology of wave activity over the UK.
I’ll be talking a bit about my research and why the Met Office care about forecasting lee waves. I’ll also talk more generally about mountain weather, and perhaps a bit about mountain weather in song – don’t worry though, I won’t subject you to my singing.