Identifying the Causes of Pyrocumulonimbus (PyroCb)
This provides a causal understanding of PyroCb formation for atmospheric science and wildfire management, though it is incremental as it applies existing causal methods to a new domain.
The study tackled the problem of identifying causal drivers of pyrocumulonimbus (PyroCb) formation from observational data, resulting in the identification of seven plausible causal predictors, including surface sensible heat flux and relative humidity at 850 hPa.
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 $Y$ conditionally independent of $E$ given $X$ 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, $13.3$ micro-meters, thermal emissions, convective available potential energy, and altitude.