Title: Atmospheric chemistry and transport: from surface air quality to the middle stratosphere
Abstract: Over the last few decades, new technologies in the form of observational satellites, measurement instruments, and model simulations have enabled the scientific community to make substantial strides to understand the drivers, mechanics, and impacts of climate change. This dissertation utilizes an aggregate of these data types in an effort to produce a more comprehensive view of important atmospheric processes from earth’s surface to the middle stratosphere.
One aspect of this work uses satellite measurements to detect near-surface air quality extreme events. The U.S.A. and E.U. have extensive surface site networks for monitoring, enabling them to better mitigate the effects of poor air quality. Unfortunately, this infrastructure is not available globally, especially in areas with exceptionally poor air quality and large populations and thus high exposure. My approach is to use measurements taken from the Ozone Monitoring Instrument (OMI), aboard the NASA satellite Aura, to detect air quality extreme events observed by the dense surface-site networks in the USA and EU. The UC Irvine Chemistry-Transport Model (UCI CTM), which can accurately identify extreme events observed by the surface networks, is then used as a transfer standard to extend our satellite detection globally. We find that the skill of OMI to detect extreme events is regionally dependent with strong agreement with the model in South America and Southern Africa.
Next, this dissertation examines nitrous oxide (N 2 O), a long-lived greenhouse gas that affects atmospheric chemistry and climate. I use satellite measurements of N 2 O, ozone (O 3 ), and temperature from the Aura Microwave Limb Sounder (MLS) instrument to calculate stratospheric loss of N 2 O, and thus its atmospheric lifetime. Using chemistry transport models (CTMs), we verify the observed stratospheric sink and follow the loss signal down to the surface and compare with surface observations. Stratospheric loss has a strong seasonal cycle and is further modulated by the Quasi-Biennial Oscillation (QBO); these cycles are seen equally in both observations and the models. When filtered for interannual variability, the modeled surface signal is QBO-caused, and it reproduces the observed pattern, highlighting the potential role of the QBO in tropospheric chemistry and composition, as well as in model evaluation. The observed annual surface signal in the northern hemisphere (NH) matches well with the models run without emissions, indicating the annual cycle is driven mostly by stratosphere-troposphere exchange (STE) flux of N 2 O-depleted air and not surface N 2 O emissions. In the southern hemisphere (SH), all three models disagree and thus provide no guidance, except for indicating that modeling STE in the SH remains a major model uncertainty. Parallel model simulations of CFCl 3 (F11), which has greater stratospheric loss that N 2 O and possibly surreptitious emissions, show that its interannual variations parallel those of N 2 O, and thus the observed N 2 O variability can identify the stratospheric component of the observed CFCl 3 variability.
Finally, we use our work on N 2 O to test modeled STE flux of ozone (O 3 ). The stratosphere is an important source of O 3 in the troposphere affecting atmospheric chemistry and air quality. However, transport from the stratosphere is extremely difficult to validate and quantify based on surface fluctuations of O 3 due to its large budget terms (sources and sinks) in the troposphere. Therefore, we use N 2 O and F11 as proxies for atmospheric chemistry and transport related to O 3 STE. We find that N 2 O, F11, and O 3 STE are closely linked, indicating that air depleted in N 2 O and F11 and simultaneously rich in O 3 accumulates in the lower stratosphere before crossing the tropopause coincidentally. When partitioned by hemisphere we find deviations between the STE fluxes of the different species, especially in the SH, driven by the Antarctic winter vortex. Satellite measurements from SCI-SAT ACE-FTS are used to constrain our modeled STE and help evaluate this major model uncertainty.