Elisa Palazzi is a professor of climate science at the Department of Physics, University of Turin, and is affiliated with the Institute of Atmospheric Sciences and Climate of the Italian National Research Council. She works on the study of the climate system and Earth-System processes, with a focus on the current and expected impacts of rising temperatures in mountain regions. She has experience in science dissemination through public speeches at conferences, festival, schools and participation in TV and radio programs. She wrote two books and was author and presenter of a climate Podcast.
She is CICAP’s emeritus member.
Communicating uncertainty in the science of climate change
Carbon dioxide and other greenhouse gases released into the atmosphere have warmed and altered the Earth’s climate. The scientific community agrees in attributing most of the warming trend recorded in the last decades to emissions from human activities since naturally produced greenhouse gases have a different fingerprint from the man-made ones. Moreover, larger and more rapid changes are expected in the coming decades in the absence of immediate and effective mitigation actions.
The above phrases define strong and well established statements. But like any science, also climate science has uncertainties, especially when considering future projections from climate models – which are by their very nature approximate representations of the climate system. In general terms, uncertainties in constructing and applying climate models are classified into initial conditions, model structure (literally how we build a model), and boundary conditions or scenario uncertainty. The latter, in particular, means that future greenhouse gas emissions, whose behavior depends on unpredictable socio-economic and technological factors, are uncertain.
Since removing model uncertainty is not possible, understanding and quantifying it becomes essential because it is related to our overall ability to propose how human activities can be modified to mitigate our effects on climate and how we can adapt to unavoidable changes.
From a practical point of view, the problem quantifying uncertainty in climate model projections is addressed using the concept of model ensemble: since one single model has its own characteristics and can reproduce better or worse than another a certain variable or process, then using a model ensemble can provide diverse information and higher confidence will be placed on results that are common to an ensemble. An ensemble provides a framework for probabilistic analyses of future climate (e.g. the most or least probable future temperature increase for a given emission scenario) and uncertainties in climate model projections are often quantified as the spread of the model ensemble.
Also, the IPCC offers a robust framework to deal with uncertainty using a specific and well calibrated language to communicate probabilistic information while quantifying uncertainty.
Communicating uncertainties also beyond the science community and suggesting how to best use them in decision making are important steps to meet the challenges posed by the climate crisis.