When climate scientists are to predict the climate of the future, they generally always use more than one single climate model. The more models used, the greater the quantity of data.
If the data are to become useful, enabling, for example, the right decision-making in relation to climate-proofing of cities and coast lines, climate scientists need to delve further into their statistical toolbox. That is the opinion of a group of Nordic researchers who, in the autumn of 2017, published the article ’New vigour involving statisticians to overcome ensemble fatigue’.
Senior Scientist Martin Drews, DTU Management Engineering, is one of the authors behind the article:
“The climate models are our best estimate of how the world will look when the climate changes. But it’s often necessary to boil down the increasing volumes of data so they become user relevant. Here, advanced statistics can help, and this is currently an untapped potential within climate research.”
Demand for local projections
Climate scientists are, among other things, seeing an increasing demand for ultra-local climate projections, explains Martin Drews:
“Today, authorities or urban planners, for example, want to know the future climate of a single city or harbour. In this context, the solution is not solely to perform more climate model runs, but also to become better at analysing the runs with the right statistical tools. Statistics can, in fact, help us organise and find the correct information in a giant sea of data,” says Martin Drews.
A well-known problem with the climate models is the uncertainty connected with the calculations, i.e. how likely it is that the model calculations are actually spot on in relation to reality. Martin Drews explains:
“One uncertainty may, for example, be the calculation of how a global temperature increase affects the global sea level. These are uncertainties which we can extract from the results from the climate model runs and examine separately, using advanced statistical methods which are already available. This means that we can become more precise in our predictions,” he says.
Statistics reinforce Denmark’s climate change adaptation
The Danish Meteorological Institute (DMI) is co-author of the article in Nature Climate Change. DMI is to prepare a climate atlas for Denmark which can be used for planning of climate change adaptation and will in this connection utilize statistical analyses, explains Peter Langen, Climate Scientist at DMI.
“It’s crucial for the quality of the climate atlas that we’ve statisticians on the team. Only with their assistance will we be able to deliver data which make it possible to weigh risks and potential costs relative to the likelihood of a specific event occurring.”
Source : DTU