Modelling of data is becoming more important as scientists gather more and more information about how systems interact. Prof John Montgomery, head of the Auckland University Leigh Marine Laboratory, discusses how and why scientists use models, with climate change as an example.
Point of interest:
In this video, you’ll see a number of scientists working with models. The models cover research into weather, ocean currents and fisheries management.
PROF JOHN MONTGOMERY
Our ability to understand any complex system is going to really be helped if we can actually develop models. One of the best examples at the moment would be climate models, in that climate models have really become the interface between the science and the management.
And you’d think that climate is pretty complex, but we now have complete ocean circulation models, which allow us to predict what happens in the event of increasing CO2 levels – what the impact of that might be on climate, what the feedbacks of that will be on ocean circulation.
Having a predictive model gives you a very useful tool, both with respect to driving the management side of things but also with respect to prioritising and understanding what it is we don’t know. So if you take some of the ocean circulation models, for instance, one of the big unknowns is the interaction between the ocean and the ice caps. So one of the recent difficulties in terms of climate is that the north polar ice cap is melting much faster than the models would predict.
So there is predictive modelling, but there is also population modelling, which is the basis of fisheries management. So in order to understand the impacts of fishing pressure and the responses of fish populations to them, there are quite explicit models that feed in all we know about the biology of that species, what the catch rates are, and allow us to give good predictive models of how many fish we can take out of the stock next year.
Dr Peyman Zawar-Reza
NASA/Goddard Space Flight Center Scientific Visualization Studio
The Blue Marble Next Generation data is courtesy of Reto Stockli (NASA/GSFC) and NASA's Earth Observatory
Dr Sara Mikaloff-Fletcher
Canadian Broadcasting Corporation