Engineering topics

Julie M. Nicely

Publications and source records attributed to Julie M. Nicely.

3 records

NASA NTRS2023

An Observation-Based, Reduced-Form Model for Oxidation in the Remote Marine Troposphere

The hydroxyl radical (OH) fuels atmospheric chemical cycling as the main sink for methane and a driver of the formation and loss of many air pollutants, but direct OH observations are sparse. We develop and evaluate an observation-based proxy for short term, spatial variations in OH (Proxy OH ) in the remote marine troposphere using unprecedented and comprehensive measurements from the NASA Atmospheric Tomography (ATom) airborne campaign. Proxy OH is a reduced form of the OH steady-state equation representing the dominant OH production and loss pathways in the remote marine troposphere, according to box model simulations of OH constrained with ATom observations. Proxy OH comprises only eight variables that are generally observed by routine ground- or satellite-based instruments. ProxyOH scales linearly with in situ [OH] spatial variations along the ATom flight tracks (median r 2 = 0.90, interquartile range = 0.80 – 0.94 across 2 km altitude by 20° latitudinal regions). We deconstruct spatial variations in Proxy OH as a first-order approximation of the sensitivity of OH variations to individual terms. Two terms modulate within-region Proxy OH variations—water vapor (H 2 O) and, to a lesser extent, nitric oxide (NO). This implies that a limited set of observations could offer a novel avenue for observation-based mapping of OH spatial variations over much of the remote marine troposphere. Both H 2 O and NO are expected to change with climate, while NO also varies strongly with human activities. We also illustrate the utility of Proxy OH as a process-based approach for evaluating inter-model differences in remote marine tropospheric OH.

Colleen B. Baublitz↗

NASA NTRS2020

Missing OH Reactivity in the Global Marine Boundary Layer

The hydroxyl radical (OH) reacts with thousands of chemical species in the atmosphere, initiating their removal and the chemical reaction sequences that produce ozone, secondary aerosols, and gas-phase acids. OH reactivity, which is the inverse of OH lifetime,influences the OH abundance and the ability of OH to cleanse the atmosphere. The NASA Atmospheric Tomography (ATom) campaign used instruments on the NASA DC-8 aircraft to measure OH reactivity and more than 100 trace chemical species. ATom presented a unique opportunity to test the completeness of the OH reactivity calculated from the chemical species measurements by comparing it to the measured OH reactivity over two oceans across four seasons. Although, throughout much of the free troposphere, the calculated OH reactivity was below the limit-of-detection for the ATom instrument used to measure OH reactivity, the instrument was able to measure the OH reactivity in and just above the marine boundary layer. The mean measured value of OH reactivity in the marine boundary layer across all latitudes and all ATom deployments was 1.9 s-1, which is 0.5 s-1larger than the mean calculated OH reactivity. The missing OH reactivity, the difference between the measured and calculated OH reactivity, varied between 0 s-1to 3.5 s-1, with the highest values over the Northern Hemisphere Pacific Ocean. Correlations of missing OH reactivity with formaldehyde, dimethyl sulfide, butanal, and sea surface temperature suggest the presence of unmeasured or unknown volatile organic compounds or oxygenated volatile organic compounds associated with ocean emissions.

NASA Atmospheric Tomography (ATom)↗

NASA NTRSDate not supplied

Airborne observations in support of a satellite observation-based OH product

This presentation outlines work to date analyzing airborne observations to improve a satellite observation-based hydroxyl radical (OH) column product by interrogating model chemistry processes. Anderson et al., 2023, established a machine learning method to combine satellite observations of O3, CO, NO2, HCHO, H2O, and aerosol optical depth, along with analyzed sea surface temperatures, for the prediction of tropospheric column OH (TCOH). Since the TCOH machine learning model was trained on output from the MERRA-2 GMI model simulation, we seek to identify if any model deficiencies may yield errors in the TCOH prediction. By evaluating F0AM box model simulations and neural networks trained to reproduce in situ OH concentrations, together with output reaction rates and interpretability metrics, respectively, we validate the Anderson et al. TCOH model and assess the largest contributors to uncertainties.

Hydroxyl, oxidizing capacity, troposphere, airborn↗