A dynamical adjustment perspective on extreme event attribution

Abstract

Abstract. Here we demonstrate that dynamical adjustment allows a straightforward approach to extreme event attribution within a conditional framework. We illustrate the potential of the approach with two iconic extreme events that occurred in 2010: the early winter European cold spell and the Russian summer heat wave. We use a dynamical adjustment approach based on constructed atmospheric circulation analogues to isolate the various contributions to these two extreme events using only observational and reanalysis datasets. Dynamical adjustment results confirm previous findings regarding the role of atmospheric circulation in the two extreme events and provide a quantitative estimate of the various dynamic and thermodynamic contributions to the event amplitude. Furthermore, the approach is also used to identify the drivers of the recent 1979–2018 trends in summer extreme maximum and minimum temperature changes over western Europe and western Asia. The results suggest a significant role of the dynamic component in explaining temperature extreme changes in different regions, including regions around the Black and Caspian Seas as well as central Europe and the coasts of western Europe. Finally, dynamical adjustment offers a simple and complementary storyline approach to extreme event attribution with the advantage that no climate model simulations are needed, making it a promising candidate for the fast-track component of any real-time extreme event attribution system.

Heat extremes in Western Europe are increasing faster than simulated due to missed atmospheric circulation changes

“…For extreme heat, the increase in the frequency and persistence of splitted midlatitude jet states over the last 40 years, possibly associated with the reported weakening of the mean summer zonal circulation [24], can explain about a third of the amplified trend in heatwave intensity [3]. Changes in atmospheric circulations around Europe that favor heat were also emphasized [25], in particular a positive trend in a dipole structure with a low pressure over the Eastern Atlantic [26][27] and a high pressure over the Mediterranean extended towards central Europe [28]. Yet, no increasing trend was found in blocking over Scandinavia that has led to the 2018 heat wave [14,29].…”

Impact of Internal Climate Variability on Wintertime Surface Air Temperature Trends Over Eurasia in the CESM1 Large Ensemble

“…Wallace et al. (2012) developed a dynamical adjustment method to extract the large‐scale atmospheric circulation‐related SAT changes, which has been widely used in the understanding and attribution of climate changes over the Northern Hemisphere (e.g., Deser et al., 2016; Gong et al., 2019a; Lehner et al., 2018; Smoliak et al., 2015; Terray, 2021; Zhuang et al., 2021). The portion extracted by the dynamical adjustment method is often referred to as the dynamical‐related SAT changes, and the residual portion is often referred to as the thermodynamical‐related SAT changes.…”

A range of outcomes: the combined effects of internal variability and anthropogenic forcing on regional climate trends over Europe

“…If models are correct in this regard, then dynamical adjustment can be used to parse the relative contributions of in-66 C. Deser and A. S. Phillips: Effects of internal variability and anthropogenic forcing on European climate ternal dynamics and forced thermodynamics to observed climate changes at middle and high latitudes (Wallace et al, 2013;Deser et al, 2016). A variety of dynamical adjustment algorithms has been developed and tested within the framework of a model LE (Deser et al, 2016;Lehner et al, 2017Lehner et al, , 2018Smoliak et al, 2015;Guo et al, 2019;Merrifield et al, 2017;Terray, 2021a;Sippel et al, 2019). These protocols are all based on statistical associations between patterns of SLP and temperature or precipitation deduced from long observational records.…”