A Novel Algorithm for Inferring the Vertical Distribution of Trace Gases Using Remote Sensing Measurements

Author: Parker, Harrison Alexander

Year: 2023

Degree: Dissertation (Ph.D.)

Advisor: Wennberg, Paul O.

Committee Members: Frankenberg, Christian; Okumura, Mitchio; Seinfeld, John H.; Wennberg, Paul O.

Option: Environmental Science and Engineering

DOI: 10.7907/xfkf-8t80

Abstract

Remote sensing is a powerful tool that is used to diagnose sources, sinks, and fluxes of trace gases across different spatial and temporal scales. Ground-based remote sensing measurements of column-averaged dry mole fractions (DMF) of gases such as carbon dioxide (CO₂) and carbon monoxide (CO) made by the Total Carbon Column Observing Network (TCCON) are used to validate space-based measurements and better understand the carbon cycle. Surface signals of gas exchange can be masked in the total column values, however, limiting their use in assessment of local surface fluxes. Retrievals of the vertical distribution of trace gases can be used to obtain gas exchange information that is more directly related to changes at the surface but require high precision measurements with less temporal resolution than the TCCON total column measurements. In this thesis, I develop an algorithm, the Temporal Atmospheric Retrieval Determining Information from Secondary Scaling (TARDISS), that infers vertical information, or ‘partial columns’, from existing, quality-controlled total column data. The TARDISS algorithm does not fit the solar spectra but rather begins with trace gas column retrievals obtained from different spectral bands using the standard TCCON retrievals. TARDISS takes advantage of the fact that different bands have different sensitivities to the same trace gas as a function of altitude and solar zenith angle. We use the TARDISS partial column data to examine estimated surface fluxes in the North American boreal forest and compare them to surface fluxes estimated from tall tower in situ measurements. We also outline changes in air quality from the sudden change in traffic behavior from the COVID-19 lockdown which serves as motivation for the use of the TARDISS-derived lower partial column CO data to examine recent changes in air quality in the South Coast Air Basin.

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