Kaja Milczewska – email@example.com
As per annual tradition in the Meteorology Department, PhD students have chosen a distinguished scientist to visit the department for one week. Previous years’ visitors include Prof. Tapio Schneider (Caltech), Prof. Olivia Romppainmen-Martius (University of Bern), and Prof. Cecilia Bitz (University of Washington). This year’s winning vote was New York University’s Prof. Laure Zanna, who will be visiting the department virtually1 between 2 – 6th November.
Laure is an oceanographer and climate scientist whose career so far has spanned three continents, won her an American Meteorological Society (AMS) Early Careers’ award for “exceptionally creative” science this year, and netted her 600 citations in the last two years. Her research interests encompass ocean turbulence, climate dynamics, predictability, machine learning and more. Some of the many topics of her published papers include the uncertainty in projections of ocean heat uptake; ocean turbulence parametrisations; predictions of seasonal to decadal sea surface temperatures in the Atlantic using simple statistical models and machine learning to inform prediction of extreme events. Besides being an exceptional scientist, speaker and educator, Laure is a down-to-Earth and friendly person, described by the Climate Scientists podcast’s Dan Jones as ‘a really great person who helps to tie the whole community together’.
As someone who had received their PhD only just over a decade ago, we thought Laure would be the perfect candidate to inspire us and our science through sharing some of her academic experiences with us. Before her visit next week, Laure kindly answered some interview-style questions for this week’s Social Metwork blog post.
Q: What inspired you to research oceanography and climate in the first place?
A: I always enjoyed math and physics. The possibility of using these disciplines to study scientific problems that I could “see” was very appealing.
Q: Why were you drawn to machine learning?
A: The power of machine learning (ML) to advance fields such as natural processing language or computer science is indisputable. I was excited by the premise of ML for climate science. In particular, can ML help deepen our understanding of certain aspects of the climate systems (e.g. interactions between scales or interactions between the ocean and atmosphere)? Can ML improve the representation of small-scale processes in climate models? ML, by itself, is not enough but combined with our physical understanding of the climate system could push the field forward.
Q: Can you give us an idea of what’s the most exciting research you are working on right now?
A: This is impossible. I work on 2 main areas of research right now: understanding and parameterizing ocean mesoscale eddies and understanding the role of the oceans in climate. I am passionate and excited about both topics. Hopefully, you will hear about both of them during the week.
Q: When did you realise/decide you were going to remain in academia?
A: I decided that I wanted to try and stay in academia in the last year of my PhD. I was lucky enough to be able to.
Q: What is your favourite part of your job?
A: Working with my group! The students and postdocs in the group have different expertise but all are passionate about their research. They make the work and the research more fun, more challenging, and more inspiring.
We are honoured to have our invitation accepted by Laure and are eagerly anticipating answers to more of these kind of questions throughout next week’s conversations. Laure will be presenting a seminar titled, “Machine learning for physics-discovery and climate modelling” during the Monday Departmental Seminar series, as well as another seminar in the Climate and Ocean Dynamics research group, titled “Understanding past and future ocean warming”. She will also give a career-focused session at PhD group and, of course, engage with both the PhD students and staff on an individual basis during one-to-one meetings. We are grateful and delighted to be able to welcome Laure to the Meteorology department despite the various difficulties the year 2020 has posed on everyone, so come along to next week’s events!
1In true 2020 curve-ball style, of course.