Identifying the Causes of Pyrocumulonimbus (PyroCb)

Emiliano Diaz Salas-Porras (1) , Kenza Tazi (2) , Ashwin Braude (3) , Daniel Okoh (4) , Kara D. Lamb (5) , Duncan Watson-Parris (6) , Paula Harder (7) , Nis Meinert

1 IPL - Image Processing Laboratory
2 Department of Engineering [Cambridge]
3 PLANETO - LATMOS
4 CAR-NASRDA - Centre for Atmospheric Research
5 Department of Earth and Environmental Engineering [New York]
6 AOPP - Department of Atmospheric, Oceanic and Planetary Physics [Oxford]
7 Fraunhofer ITWM - Fraunhofer Institute of Industrial Mathematics

A first causal discovery analysis from observational data of pyroCb (storm clouds generated from extreme wildfires) is presented. Invariant Causal Prediction was used to develop tools to understand the causal drivers of pyroCb formation. This includes a conditional independence test for testing Y ⊥ ⊥ E|X for binary variable Y and multivariate, continuous variables X and E, and a greedy-ICP search algorithm that relies on fewer conditional independence tests to obtain a smaller more manageable set of causal predictors. With these tools, we identified a subset of seven causal predictors which are plausible when contrasted with domain knowledge: surface sensible heat flux, relative humidity at 850 hPa, a component of wind at 250 hPa, 13.3 µm thermal emissions, convective available potential energy, and altitude.

Domains: Meteorology

Emiliano Diaz Salas-Porras, Kenza Tazi, Ashwin Braude, Daniel Okoh, Kara D. Lamb, et al.. Identifying the Causes of Pyrocumulonimbus (PyroCb). 2022. ⟨insu-03861004⟩