Dependence of drivers affects risks associated with compound events

By Jakob Zscheischler, Sonia I. Seneviratne. Science Advances, 2017

773 citations recorded by the source corpus.

Compound extremely hot and dry summers become more frequent with higher CO2 concentrations due to stronger interdependence. Compound climate extremes are receiving increasing attention because of their disproportionate impacts on humans and ecosystems. However, risks assessments generally focus on univariate statistics. We analyze the co-occurrence of hot and dry summers and show that these are correlated, inducing a much higher frequency of concurrent hot and dry summers than what would be assumed from the independent combination of the univariate statistics. Our results demonstrate how the dependence structure between variables affects the occurrence frequency of multivariate extremes. Assessments based on univariate statistics can thus strongly underestimate risks associated with given extremes, if impacts depend on multiple (dependent) variables. We conclude that a multivariate perspective is necessary to appropriately assess changes in climate extremes and their impacts and to design adaptation strategies.

Subfields: Ecology, Evolution, Behavior and Systematics, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/04a9890917e16cc92ae70b48d1597a9fc3f0d653

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology, Evolution, Behavior and Systematics

  1. Xuan Zhang
  2. Vijay P. Singh
  3. Zenchao Hao
  4. Fanghua Hao
  5. D. Ray
  6. D. Karoly
  7. Sonia I. Seneviratne

In Global and Planetary Change

  1. Jakob Zscheischler
  2. S. Lange
  3. Mathieu Vrac
  4. Zenchao Hao
  5. Erich Fischer
  6. Vijay P. Singh
  7. M. Widmann
  8. Fanghua Hao

Citations in the corpus