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Meet our Experts: Marie Pontoppidan

Marie is a climate scientist at NORCE. She is an expert in regional modelling and is involved in work package 2 in CONFER, where she works in the atmospheric modelling group.

Tell me a bit about your role at NORCE

I started in NORCE back in 2015. At that time, we were in an early phase of building up our co-production competence, and I was lucky to be part of a project involving co-production of climate knowledge in Western Norway, primarily related to precipitation – one of our large challenges here. Fortunately, we were further funded and were able to expand this kind of project into a larger national project in Norway having some of the same objectives. I did my PhD in the national project, working with regional climate models and focusing on precipitation and, at the same time, trying to corporate with non-academic partners to make sure knowledge was transferred – in both directions! The work with partners outside academia was super motivating and I have since proceeded research in various projects involving co-production.

Why are you excited about the CONFER project and what do you think it could achieve?

I’m proud to be part of an international effort to improve the daily lives of people. I’m proud that my knowledge and my work can actually contribute to a better seasonal forecast in the region. I think CONFER can achieve this by having a large co-production commitment so we can learn from the locals, having a team of world-leading scientists and by cooperating with ICPAC who can guide the implementation of scientific improvements into operational routines. Besides, better seasonal forecasting, which I’m contributing to, is super exciting and valuable for the remaining world too.

What is your specific role in CONFER?

My work is in the atmospheric modelling group in work package 2. We try to find ways of improving the seasonal forecast in close collaboration with colleagues at ICPAC. More specifically I started the project by looking at some of the systematic biases in the global simulations that are fed into our local simulations over the Horn of Africa. We think that if we remove some of these systematic biases the output may become more reliable. We also plan to investigate whether the seasonal forecast can benefit from being run at a much finer grid than what is done today, this has been the case for longer climate simulations so it could very well also improve the seasonal forecasts in the region.