Calibrated and Systematic Characterization, Attribution, and Detection of Extremes (CASCADE)

Climate extremes are considered to be one of the most stressing forms of climate change by the IPCC. The risks to society and the natural environment are magnified when multiple types of extremes are coincident and collocated, e.g., simultaneous droughts and heat waves, downpours and storm surges (e.g., both caused by atmospheric rivers) in coastal zones, and other potentially destructive combinations of extreme weather events. We propose to label these phenomena as compound extremes. At present, however, the theory of extreme values that underpins much of the existing analysis of simulations and observations has been formulated for characterization of univariate phenomena, for example just drought severity, rather than that of multi-variate phenomena, for example coincident droughts and heat waves. Conventional extreme value theory is therefore unsuitable for quantifying the properties, in particular the magnitudes and return frequencies, of compound extremes. It is also unsuitable for quantifying the increasing risks of multi-sectoral impacts arising from changes in the frequency and severity of compound extremes in a warmer climate.

Three, five, and ten-year plan: We will develop the necessary theory for multi-variate extremes that will reduce to the classical Generalized Extreme Value (GEV) theory widely used to study these phenomena in the limit of a single variable. The conceptual breakthroughs and theoretical derivations required are already well underway with university colleagues. The longer-term challenge after the development of the statistical theory is learning how to interpret the multi-dimensional space of extremes in the context of impacts.

Project Term: 
2016 to 2021
Project Type: 
Science Focus Area (SFA)