Moist Processes as Triggers for Tipping Points in Weather–Climate Interactions

The characteristics of weather systems depend on the particular thermodynamic and dynamic context within which they develop. As such, changes in the climate system are expected to influence the weather. Since moist processes have a first order effect on the development of weather systems, it is important to understand how phase changes of water affect the response of weather to changes in climate.

We have conducted a set of experiments designed to assess the role of moist processes in the interactions among weather and climate. Weather events of interest include: mesoscale convective systems, orographic precipitation, mid-latitude cyclones, and tropical cyclones. The fundamental challenge is to quantify the manner in which simultaneous changes in environmental factors influence weather-related outcomes (e.g., precipitation). The difficulty arises from the fact that weather systems are complex: they are influenced by multiple different control factors, and exhibit nonlinear responses.

We show how ensembles of simulations, machine learning techniques, and data assimilation theory can be used as effective tools for examining multivariate weather-climate interactions. We also highlight the fact that many types of weather system exhibit strong transitions in behavior as the climate system warms, and these transitions are highly sensitive to the operation of moist processes.