This proposed research will combine NASA-sponsored aircraft and satellite observations with lightning assimilation and large-eddy simulations (LES) to answer fundamental scientific questions about…

This is a $553,099 grant awarded by NASA's Shared Services Center to Atmospheric & Environmental Research Inc. (AER), a subsidiary of Verisk Analytics, Inc. The grant will fund research to study the effects of deep convective transport on atmospheric composition and climate. The research will combine NASA aircraft and satellite observations with lightning data assimilation and large-eddy simulations to address key science questions related to how global atmospheric changes impact regional air quality and future ozone, climate, and air quality. AER has extensive experience in this area, having participated in NASA's previous airborne campaigns. The research is not associated with a set-aside contract and will be performed in Lexington, Massachusetts, with a final completion date of July 6, 2026.

This proposed research will combine NASA-sponsored aircraft and satellite observations with lightning assimilation and large-eddy simulations (LES) to answer fundamental scientific questions about deep convective trace gas transport. Deep convective transport significantly affects the chemical composition and water vapor content of the upper troposphere and lower stratosphere. For example, the rapid convective transport of ozone (O3) and its precursors can substantially increase O3 production in the upper troposphere. Deep convection also lofts trace gases into stronger upper-level winds, facilitating long-range transport and long-distance effects on atmospheric composition. However, this transport remains a challenging process to simulate in climate and chemical transport models, in large part due to the inadequate parameterization of deep convection. For these reasons, deep convective transport was a major focus of the NASA deep convective clouds and chemistry (DC3) and studies of emissions and atmospheric composition, clouds and climate coupling by regional surveys (SEAC4RS) airborne campaigns. In this research, we will analyze deep convective trace gas transport during DC3 and SEAC4RS. Our team participated in SEAC4RS as part of the meteorological forecast team and has extensive experience combining aircraft observations with high-resolution modeling to study deep convective processes. We will use the largely unexplored SEAC4RS convective dataset along with the extensively studied DC3 dataset to address the following science questions from the NASA atmospheric composition focus area: what are the effects of global atmospheric composition and climate changes on regional air quality? And how will future changes in atmospheric composition affect ozone, climate, and global air quality? We also will be directly addressing the primary unifying scientific goal of DC3 and SEAC4RS, which was to understand how radiatively and chemically important atmospheric constituents are transported vertically through the atmospheric column from the ground to the lower stratosphere. We will interrogate five different cases spanning a wide range of convective modes, including a supercell (DC3), a mesoscale convective system (DC3), airmass and prefrontal convection (SEAC4RS), and marine convection (SEAC4RS). Aircraft and satellite observations of atmospheric kinematics (e.g., vertical velocity), cloud properties (e.g., cloud top height), and trace gases will provide insight into the mesoscale and dynamical characteristics of the sampled convection and its vertical redistribution of pollution. A novel yet demonstrated lightning data assimilation method will be used to improve the timing and location of parameterized deep convection in the weather research and forecasting model with chemistry (WRF-chem). The improved sub-grid convection from the lightning assimilation will provide a more realistic comparison of simulated sub-grid convective transport with aircraft observations of trace gases. Idealized WRF-LES will then be performed at ~100 m grid spacing. The results will be integrated with aircraft observations to understand the physical processes modulating the accurate simulation of deep convective trace gas transport. Finally, these new insights into deep convective transport will be translated into model improvement pathways for the climate and composition communities.