Christopher H. O’Reilly, Daniel J. Befort, Antje Weisheimer, Tim Woollings, Andrew Ballinger & Gabriele Hegerl
communications earth & environment
Work Package 5
Natural variability in the climate has a strong influence on climate trends, alongside anthropogenic forcings such as rising levels of greenhouse gases. Representing the internal variability of the climate system in models is key to producing reliable projections, particularly regional projections. However, studies have shown that climate models do not simulate this variability accurately and especially underestimate the fluctuations occurring on decadal timescales. This paper compensates for the missing variability by creating synthetic projections with variability consistent with the large-scale observed atmospheric circulation. Using these synthetic ensemble data, the team found increased uncertainty in the projected 21st century temperature and rainfall changes over the northern extratropics, particularly over Europe. These are also associated with increased probabilities of extreme seasons in the future. These findings will inform climate policies aimed at helping communities mitigate or adapt to the future impacts that climate change may bring at the regional scale.
Natural internal variability has a strong influence on climate variability and trends, particularly when looking at climate on a regional scale outside the tropics. This partly explains why different areas have seen very different climatic trends over recent decades, despite the background of persistent global warming. Internal variability is expected to maintain its influence in the climate of the future, including over North America and Eurasia. The variability in these areas is primarily driven by large-scale atmospheric circulation. The importance of internal variability means that climate models must accurately represent it if they are to make reliable predictions and projections of future climate. Recent studies, however, have highlighted disparities between the observed variability and that seen in models, with a pronounced underestimation of the observed variability on decadal timescales in state-of-the-art climate models. This study looks at the effect of this underestimation on future climate model projections, using a new method to correct for the missing observed internal variability in model simulations. Improved climate model projections are a key part of informing climate policy, as is updating that policy as modelling innovations are made.
The team found that current climate projections for North America and Eurasia significantly underestimate the uncertainty range produced by internal variability in the climate system over the 21st century. By using observational datasets of atmospheric circulation, the researchers were able to adjust their climate model ensembles to have similar variability to that seen in observations. This resulted in significantly higher levels of uncertainty in the projections than without this adjustment, affecting climate variables such as projected future winter and summer temperature and precipitation changes. This expands the range of plausible future realizations indicated by the models and significantly alters the likelihood of seeing extreme seasons. It also blurs the line between regional projections of the impacts of different future climate scenarios, such as the impacts of 1.5°C or 2°C of global warming. Understanding the risk of future climate hazards, particularly extreme events, is an important part of developing effective climate policy to reduce the impacts of these hazards.
This paper analysed data from the MPI-GE, a large, 99-member ensemble of climate simulations. The simulations are forced using observational data over the historical period 1850-2005, then continued from 2006 to 2100 following the medium-emissions RCP4.5 scenario. Data from the CMIP5 and CMIP6 ensembles were also analysed for comparison. Sea-level pressure data from four separate datasets was then used to adjust the projections so they have similar variability to that related to large-scale atmospheric circulation in the observational data. These constrained projections were then compared to their ‘raw’ counterparts to isolate the effect of accurately reproducing internal climate variability on the uncertainty of projected future changes on temperature and precipitation over the northern extratropics.
These findings may alter how we should consider future uncertainty in climate projections. Some climate impacts may therefore be more likely than previous projections have suggested. This information is potentially useful for policymakers in designing effective policies to mitigate and adapt to the range of possible impacts of future climate change.
Internal climate variability will play a major role in determining change on regional scales under global warming. In the extratropics, large-scale atmospheric circulation is responsible for much of observed regional climate variability, from seasonal to multidecadal timescales. However, the extratropical circulation variability on multidecadal timescales is systematically weaker in coupled climate models. Here we show that projections of future extratropical climate from coupled model simulations significantly underestimate the projected uncertainty range originating from large-scale atmospheric circulation variability. Using observational datasets and large ensembles of coupled climate models, we produce synthetic ensemble projections constrained to have variability consistent with the large-scale atmospheric circulation in observations. Compared to the raw model projections, the synthetic observationally-constrained projections exhibit an increased uncertainty in projected 21st century temperature and precipitation changes across much of the Northern extratropics. This increased uncertainty is also associated with an increase of the projected occurrence of future extreme seasons.