Quantifying the rarity of extreme multi-decadal trends: how unusual was the late twentieth century trend in the North Atlantic Oscillation?

• Published in: Climate dynamics Vol. 58; no. 5-6; pp. 1555 - 1568
• Main Authors: Eade, R., Stephenson, D. B., Scaife, A. A., Smith, D. M.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2022; Springer; Springer Nature B.V
• Subjects: Atmospheric forcing; Atmospheric pressure; Climate adaptation; Climate change; Climate models; Climate trends; Climatic indexes; Climatology; Correlation; Earth and Environmental Science; Earth Sciences; Environmental aspects; Extreme weather; Geophysics/Geodesy; Intercomparison; Modelling; North Atlantic Oscillation; Ocean-atmosphere interaction; Ocean-atmosphere system; Oceanography; Regional climates; Simulation; Stochastic models; Stochasticity; Time series; Trends; White noise; North Atlantic Ocean; Climate modelling; North Atlantic; Stochastic modelling; North Atlantic Oscillation; Extreme trends; Multi-decadal variability
• ISSN: 0930-7575; 1432-0894
• DOI: 10.1007/s00382-021-05978-4

Climate trends over multiple decades are important drivers of regional climate change that need to be considered for climate resilience. Of particular importance are extreme trends that society may not be expecting and is not well adapted to. This study investigates approaches to assess the likelihood of maximum moving window trends in historical records of climate indices by making use of simulations from climate models and stochastic time series models with short- and long-range dependence. These approaches are applied to assess the unusualness of the large positive trend that occurred in the North Atlantic Oscillation (NAO) index between the 1960s to 1990s. By considering stochastic models, we show that the chance of extreme trends is determined by the variance of the trend process, which generally increases when there is more serial correlation in the index series. We find that the Coupled Model Intercomparison Project (CMIP5 + 6) historical simulations have very rarely (around 1 in 200 chance) simulated maximum trends greater than the observed maximum. Consistent with this, the NAO indices simulated by CMIP models were found to resemble white noise, with almost no serial correlation, in contrast to the observed NAO which exhibits year-to-year correlation. Stochastic model best fits to the observed NAO suggest an unlikely chance (around 1 in 20) for there to be maximum 31-year NAO trends as large as the maximum observed since 1860. This suggests that current climate models do not fully represent important aspects of the mechanism for low frequency variability of the NAO.