The Dynamics of Megafire Smoke Plumes in Climate Models: Why a Converged Solution Matters for Physical Interpretations

As the climate system warms, megafires have become more frequent with devastating effects. A byproduct of these events is the creation of smoke plumes that can rise into the stratosphere and spread across the globe where they reside for many months. To gain a deeper understanding of the plume dynamics, global climate simulations of a megafire were performed at a wide range of grid spacings from 2.0 degrees down to 7 km, including a 7 km nonhydrostatic experiment. The analysis focuses on how the resolved dynamics affects the specification of the plume characteristics such as injection height and black carbon (BC) mass. Prior studies initialize the smoke plume at one or a few grid points and this is shown here to produce severely dissipative dynamics. In order to validate such simulations with observations, enhancements of the plume characteristics to offset the dissipation is necessary. Using a numerically converged simulation, sensitivity tests show that to approximate the observed stratospheric lifetime, a reduction in BC fraction by 50% is necessary for external mixtures. The vorticity dynamics of the plume is also analyzed with a Lagrangian budget to understand the mechanisms responsible for the evolution of a collocated anticyclonic vortex. The results can be distilled down into a simple conceptual model. As the plume rises, the air diverges at the top of the updraft where the largest concentrations of smoke are found. This divergence induces a dilution of the background cyclonic absolute vorticity producing an anticyclonic vortex. Vortex decay occurs from opposite arguments. Plain Language Summary Recently, there has been an increase in large and intense wildfires ("megafires") across the Earth in response to global warming. These megafire events produce large amounts of smoke that can rise high up in the atmosphere to a level well above clouds and weather. The smoke can stay at these high levels for long periods of time and spread across much of the Earth, which blocks sunlight from reaching the surface. It is important to understand the properties of these smoke plumes and how to correctly predict their consequences on human life. However, uncertainties in both observations and models make it difficult to achieve these goals. In particular, models contain various sources of uncertainty that can interact in complex ways. In this paper, we show that previous research has used a model grid spacing that does not sample the plume accurately, which leads to errors that affect the interpretation of the smoke properties, evolution of the plume and potential climatic effects. By choosing a model grid spacing that accurately samples the plume structure, the errors in the dynamics component of the model can be minimized, providing a baseline for reducing uncertainty in other parts of the system.