Updated: Jun 8, 2020
Predicting climate change is incredibly important to determine how we can and should respond to impacts, just as forecasts for severe weather events allow us to prepare accordingly for what is to come and minimize harm. To make these predictions, climate scientists rely on computer models which use factors that influence climate change to simulate how our climate will look in the future. Older predictions are tested by comparing their predictions to current climate data. While any one model can show a high degree of accuracy, comparing the predictions of models with observed data is useful to check whether climate scientists and their predictions are generally on the right track . Recently, a team of researchers led by Dr. Zeke Hausfather of the University of Carolina, Berkeley, reviewed the predictions of historical models of global mean surface temperature to see if they matched current observations (1).
Accurate models must consider both the physics of climate patterns, and external factors that influence climate. 'Climate physics' refers to the processes that regulate our climate and the relationships between these factors. For example, researchers must correctly model heat absorbance properties of land and water to determine how they might interact with increased carbon dioxide (CO2) concentrations. External factors include anything that could speed up or slow down changes to the climate system, including, for example, greenhouse gas emissions or renewable energy technologies. External factors may be more difficult to predict because scientists would need to be predict potential societal, political, and behavioural changes, as well as natural events (e.g. volcano eruptions), that can contribute to climate change.
Dr. Hausfather and colleagues examine a total of 17 models developed between 1970 and the late 2000’s that looked at changes in global average surface temperature. These were taken from formal research articles and four previous IPCC reports. The team compared predictions from these historical models to current temperature patterns, to determine how well researchers then were able to predict the state of the climate now. It turns out that these models were quite adept, as 10 out of 17 projections matched with observed temperature changes. That number jumped up to 14 when accounting for differences in external factors. All this means is that some external factors had either not been accounted for or their impacts misestimated. The authors therefore conclude that climate models have been effectively describing the unfolding of climate patterns through time.
This is incredibly important: the review demonstrates that historical climate models of average global surface temperature accurately predicted present conditions. Since these early examples, climate models are only becoming more complex and thorough, and this study reveals that their predictions should be taken seriously. As models continue to develop, and account for increasingly complex factors, we can feel comfortable placing greater confidence in what the scientific community predicts about the effects of climate change.
1) Hausfather Z, Drake HF, Abbott T, Schmidt GA. Evaluating the performance of past climate model projections. Geophys Res Let. 2020; 47. DOI:10.1029/2019GL085378