This talk is presented as a Zoom Webinar and requires a passcode. For anyone outside the department; If you would like to attend, email Lan Lewis, [email protected]

ABSTRACT:

Teleconnections are sources of predictability for regional weather and climate but the relative contributions of different teleconnections to regional anomalies are usually not understood and often highly contested. To close this important knowledge gap, progress is needed in analysing and quantifying teleconnection pathways. What is sought in teleconnections are causal relationships between climate features in physically separated regions, yet the usual approach to quantifying teleconnections is through correlations — even though it is widely recognized that correlations do not imply causality. Here we argue for the use of causal inference theory and causal networks to overcome these challenges. We describe some of the key concepts of this theory and illustrate them with concrete examples of atmospheric teleconnections. We further discuss the particular challenges and advantages these imply for climate science and argue that a systematic causal approach to statistical inference should become standard practice in the study of teleconnections.