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 conditionally independent of given for binary variable and multivariate, continuous variables and , 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 hPa, a component of wind at hPa, micro-meters, thermal emissions, convective available potential energy, and altitude.

生成讲解博客的中文版本

生成AI智能校验的中文版本