Understanding climate change with computer models

Dr Helge Goessling, climate physicist at the Alfred Wegener Institute and head of the junior research group Seamless Sea Ice Prediciton (SSIP).

Polar predictions

Climate modelling

Sea ice

IPCC

Since the publication of the famous Charney Report in 1979, climate models have formed the backbone of climate research. In these models, we bring together our collective understanding of as many of the processes that are important in terms of climate development as possible, in the form of mathematical equations. The Alfred Wegener Institute has several decades of experience in ocean simulation and earned an international reputation for developing the global ocean/sea-ice model FESOM, which doesn’t divide the ocean’s surface into regular quadrilaterals, as usual, but instead into triangles that can be flexibly arranged. This makes it possible to model specific ocean regions – those where deep water forms, or those with an abundance of eddies, like the Gulf Stream and the Southern Ocean – in impressive detail. At the same time, other regions are modelled in less detail, to keep the computing power needed to a minimum. Since ca. 2010, the AWI has been using a coupled model that it developed from FESOM – the AWI Climate Model – which explicitly includes the atmosphere in its simulations. AWI researchers have used this model to provide, among other things, data for the IPCC’s Sixth Assessment Report, due to be published in 2021/22.

Alongside the well-known future-climate projections, the climate models are suitable for a wide range of applications. They make it possible to predict e.g. short-term fluctuations in sea-ice conditions, to shed light on past climate changes, to test geoengineering methods and to gain a better fundamental understanding of the complex climate system. The AWI also uses FESOM and the AWI Climate Model in a variety of ways for these purposes. Here the focus is mainly on the polar regions, including their ice sheets, shelves and sea ice – regions for which, thanks to its extensive infrastructure, the AWI has first-hand observational data that is especially valuable in terms of evaluating and further developing the models.