Record Details

Accounting for aerosol scattering in the remote sensing of greenhouse gas [electronic resource] / Qiong Zhang ; Yuk L. Yung, advisor.
Pasadena, California : California Institute of Technology, 2017.
1 online resource (xiii, 37 leaves) : digital (6 Mb), illustrations (some color).
CIT theses ; 2017
This thesis includes three different projects related to the remote sensing of Earth's atmosphere. The first part, comprising Chapter 2 and Chapter 3, focuses on the retrieval of Level 1 product, particularly the effect of aerosol scattering in the remote sensing of greenhouse gases. In Chapter 2, we study the aerosol induced bias in the retrieval of column averaged CO2 mixing ratios (X_[CO2]). Ground based remote sensing data from the California Laboratory for Atmospheric Remote Sensing Fourier Transform Spectrometer (CLARS-FTS) are used. We employ a numerical radiative transfer model to simulate the impacts of neglecting aerosol scattering on the CO_[2] and O_[2] slant column densities (SCDs) operationally retrieved from CLARS-FTS measurements. These simulations show that the CLARS-FTS operational retrieval algorithm likely underestimates CO-[2] and O_[2] abundances over the LA basin in scenes with moderate aerosol loading. The bias in the CO-[2] and O_[2] abundances due to neglecting aerosol scattering cannot be canceled by ratioing each other in the derivation of the operational product of X_[CO2]. We propose a method for approximately correcting the aerosol-induced bias. Results for CLARS X_[CO2] are compared to the direct-sun X-[CO2] retrievals from a nearby Total Carbon Column Observing Network (TCCON) station. In Chapter 3, we explain why large X_[CO2] retrieval errors are found over deserts in the space borne Orbiting Carbon Observatory-2 (OCO-2) data. We argue that these errors are caused by the surface albedo being close to a critical surface albedo ( łc). Over a surface with albedo close to łc, increasing the aerosol optical depth (AOD) does not change the continuum radiance. The spectral signature caused by changing the AOD is identical to that caused by changing the absorbing gas column. The degeneracy in the retrievals of AOD and X_[CO2] results in a loss of degrees of freedom (DOF) and information content (H). We employ a radiative transfer model to study the physical mechanism of X_[CO2] retrieval error over a surface with albedo close to łc. Based on retrieval tests over surfaces with different albedos, we conclude that over a surface with albedo close to łc, the X_[CO2] retrieval suffers from a significant loss of accuracy. In the Appendix, we put in a Chapter based on my work with Prof. Andrew Thompson on ocean The second part, mainly in Chapter 4, focuses on the application of Level 2 product. In this Chapter, we examine the uncertainties in middle atmospheric HOx chemistry by comparing the Aura Microwave Limb Sound (MLS) OH and HO_[2] measurements with the simulations of the Caltech-JPL KINETICS photochemical model. The model using the standard chemical kinetics underestimates OH and HO_[2] concentrations in the mesosphere. To resolve the discrepancies, we use MLS OH and HO_[2] measurements as benchmark to adjust the involved chemical rate coefficients within reasonable uncertainty ranges with an optimal estimation algorithm. The results show that four key reaction rate constants and the O_[2] cross section at Lyman- ł (121.6 nm) are the most sensitive parameters for determining the HO_[x] profiles. We conclude that the rate coefficient of H + O_[2] + M ́HO_[2] + M requires a very large adjustment beyond the uncertainty limits recommended in the NASA Data Evaluation, which suggests the need for future laboratory measurements. An alternative explanation is that radiative association plays a significant role in this process, i.e. H + O_[2] ́HO_[2] + hv, which has never been measured or computed. In the Appendix, we put in a Chapter based on my work with Prof. Andrew Thompson on ocean submesoscale turbulence.
Advisor and committee chair names found in the thesis' metadata record in the digital repository.
Dissertation note:
Thesis (Ph. D.) -- California Institute of Technology, 2017.
Bibliography, etc. note:
Includes bibliographical references.
Linked resources:
Caltech Connect
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 Record created 2017-11-08, last modified 2019-03-04

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