The interaction between atmospheric chemistry and ozone (O₃) in the upper troposphere–lower stratosphere (UTLS) presents a major uncertainty in understanding the effects of aviation on climate. In this study, two configurations of the atmospheric model from the Community Earth System Model (CESM), Community Atmosphere Model with Chemistry, Version 4 (CAM4) and Version 5 (CAM5), are used to evaluate the effects of aircraft nitrogen oxide (NO_x = NO + NO₂) emissions on ozone and the background chemistry in the UTLS. CAM4 and CAM5 simulations were both performed with extensive tropospheric and stratospheric chemistry including 133 species and 330 photochemical reactions. CAM5 includes direct and indirect aerosol effects on clouds using a modal aerosol module (MAM), whereby CAM4 uses a bulk aerosol module, which can only simulate the direct effect. To examine the accuracy of the aviation NO_x-induced ozone distribution in the two models, results from the CAM5 and CAM4 simulations are compared to ozonesonde data. Aviation NO_x emissions for 2006 were obtained from the AEDT (Aviation Environmental Design Tool) global commercial aircraft emissions inventory. Differences between simulated O₃ concentrations and ozonesonde measurements averaged at representative levels in the troposphere and different regions are 13% in CAM5 and 18% in CAM4. Results show a localized increase in aviation-induced O₃ concentrations at aviation cruise altitudes that stretches from 40° N to the North Pole. The results indicate a greater and more disperse production of aviation NO_x-induced ozone in CAM5, with the annual tropospheric mean O₃ perturbation of 1.2 ppb (2.4%) for CAM5 and 1.0 ppb (1.9%) for CAM4. The annual mean O₃ perturbation peaks at about 8.2 ppb (6.4%) and 8.8 ppb (5.2%) in CAM5 and CAM4, respectively. Aviation emissions also result in increased hydroxyl radical (OH) concentrations and methane (CH₄) loss rates, reducing the tropospheric methane lifetime in CAM5 and CAM4 by 1.69 and 1.40%, respectively. Aviation NO_x emissions are associated with an instantaneous change in global mean short-term O₃ radiative forcing (RF) of 40.3 and 36.5 mWm⁻² in CAM5 and CAM4, respectively.

Recent extreme heat events, especially those that have occurred in the Western United States (WUS), are fueling wildfires and funneling smoke at an unprecedented level, impacting air/water quality and leading to an increase in respiratory hospitalizations. Under greenhouse warming, extreme weather conditions that favor wildfire ignition are expected to occur more frequently over the contiguous United States (CONUS). Therefore, predicting wildfire danger under a changing climate is essential in managing future wildfires and protecting the welfare of people and the environment. In response to mitigating wildfire risks, the Canadian Fire Weather Index (FWI) was developed to provide a numeric rating representing the intensity of a spreading fire. In this work, we utilized fine-scale (0.25° x 0.25°) daily meteorological inputs from thirty-five general circulation models in NASA Earth Exchange Global Daily Downscaled Projections Coupled Model Intercomparison Project Phase 6 (NEX-GDDP-CMIP6) data to calculate the FWI. Using the daily maximum temperature, relative humidity, wind speed, and precipitation from NEX-GDDP-CMIP6, we calculated the FWI of historical and future simulations from the periods of 1950 to 2100 under different emission scenarios (Shared Socioeconomic Pathways 2-4.5 and 5-8.5). We have analyzed the FWI for the GISS-E2-1-G model, which indicates a 2-3% increase per decade in future fire danger under both emission-pathway-driven climate scenarios during the dry season in the Southwestern US. We have found that the FWI climatology in the Southwestern US during the Summer presents high to extreme fire danger (> 50) and higher FWI values in the future compared to historical observations. Moreover, we have explored the uncertainties across multiple models using NEX-GDDP-CMIP6 statistically downscaled data and found a significant spread of the FWI across the models for historical observations and future simulations. To correlate the link between the FWI and actual fire occurrence, we will calculate the FWI using reanalysis data (MERRA-2) and validate the FWI with actual fire occurrence data from Global Fire Emissions Database (GFED) with a special emphasis on the WUS. While supporting the US NCA and NASA’s Climate Adaptation Service Investigator (CASI), we will also try to contribute FWI to NASA’s FireSense, an initiative to bring an Earth systems approach to improving wildfire and wildland fire management.