Application:

  • Extreme weather events, such as heavy precipitation or strong winds, can occur simultaneously, resulting in larger socio-economic impacts compared to the linear sum of their components. These are termed “compound extremes” and are challenging to predict even just a few days in advance.
  • Elucidating the nature of compound extremes is a critical step in advancing our understanding of the climate system and a pertinent societal goal.

Our innovation:

Our technology aims to improve the forecasts of compound extremes in a changing climate. We process in two steps:

  1. Characterization of compound extremes from both traditional and dynamical systems perspectives.
  2. Improvement of the prediction of compound extremes with an AI algorithm grounded in dynamical systems theory.

Advantages:

  • Use of dynamical systems (dealing with the change of any system that evolves in time), efficient for chaotic systems like Earth’s atmosphere and providing a highly informative, cheap, and efficient way of characterizing weather systems and extreme temperature events.
  • Combined information from the dynamical systems metrics and ensemble model (using a set of perturbed initial conditions to produce a range of probable future atmospheric states) predictions, giving better forecasts. Thus, more effective preventive measures can be taken, mitigating the storm consequences.
  • Flexible analysis algorithm, applicable to various regions and weather extremes worldwide

Opportunity:                

  • The applicability lies particularly in improving the ability to forecast compound extremes at short-medium range time scales to issue timely weather warnings.
  • The group seeks to collaborate with entrepreneurs and stakeholders that wish to integrate early weather warnings in their products and services.