Quantifying Causal Pathways of Teleconnections

Abstract

<p>Due to their relevance for regional weather and climate, teleconnections are an extremely active area of research. One key task is to quantify the contribution of a teleconnection to regional anomalies in both models and observations. This is, for instance, important to improve forecasts on time scales ranging from subseasonal to multidecadal, or to attribute ensemble spreads to changes in large-scale drivers. However, robustly estimating the effects of a teleconnection remains challenging due to the often simultaneous influences of multiple climate modes. While physical knowledge about the involved mechanisms is often available, how to extract a particular causal pathway from data are usually unclear.</p><p>In this talk I argue for adopting a causal inference-based framework in the statistical analysis of teleconnections to overcome this challenge. A causal approach requires explicitly including expert knowledge in the statistical analysis, which allows one to draw quantitative conclusions. I illustrate some of the key concepts of this theory with simple examples of well-known atmospheric teleconnections. Moreover, I show how the deductive nature of a causal approach can help to assess the <em>plausible</em> influence of Arctic sea ice loss on mid-latitude winter weather, thereby helping to reconcile differences between models and observations. I finally discuss the particular challenges and advantages a causal inference-based approach implies for climate science.</p><p> </p><p>References</p><p>Kretschmer, M., Adams, S. V., Arribas, A., Prudden, R., Robinson, N., Saggioro, E., & Shepherd, T. G. (2021). Quantifying Causal Pathways of Teleconnections, Bulletin of the American Meteorological Society, 102(12), E2247-E2263. Retrieved Jan 13, 2022, from https://journals.ametsoc.org/view/journals/bams/102/12/BAMS-D-20-0117.1.xml</p><p>Kretschmer, M., Zappa, G., and Shepherd, T. G. (2020), The role of Barents–Kara sea ice loss in projected polar vortex changes, <em>Weather and Climate Dynamics</em><em>,</em> doi: 10.5194/wcd-1-715-2020</p>