Millimeter-wavelength remote sensing of the atmospheric structure and composition of Venus

Microwave radiometric observations and radio occultations are capable of providing insight into the properties of the Venus atmosphere within and below layers of clouds which cover the entire planet. To interpret such observations, accurate models for the absorption of the atmospheric constituents of Venus are necessary. The objective of this research has been to further understanding of the millimeter-wavelength spectrum of Venus. Over 400 laboratory measurements have been made of the opacity of H2SO4 vapor at W, F, and Ka Band in mixtures containing up to 3 bars of CO2 at temperatures ranging from 535-585 K, simulating the conditions of the lower atmosphere of Venus. The results of these measurements and prior laboratory studies at microwave frequencies have been used to derive a model for H2SO4 vapor opacity valid at frequencies below 150 GHz. This model is incorporated into a microwave radiative transfer model of the Venus atmosphere, which has been used to predict the penetration depth of a radio occultation signal at 32 GHz. Low-noise images of Venus have also been developed from observations made using the CARMA and ALMA radio telescopes and compared against the emission spectrum produced by the model. Longitudinal brightness variations in these images are significantly lower than are seen in previous observations.

Level thesis:degree_level

Doctoral

Department dc:contributor.department

Electrical and Computer Engineering

Grantor dc:publisher

Georgia Institute of Technology

Year dc:date.issued

2020

Author dc:creator

• Akins, Alexander Brooks

Advisor dc:contributor.advisor

• Steffes, Paul G.

Committee members dc:contributor.committeemember

• Cohen, Morris
• Durgin, Gregory
• Scott, Waymond
• Schmidt, Britney

• Venus
• Atmosphere
• Remote
• Sensing
• Microwave
• Millimeter-wavelength
• Composition
• Sulfuric
• Acid
• Radiative
• Transfer

Language dc:language.iso

en_US

Handle dc:identifier.uri

http://hdl.handle.net/1853/62798

OAI identifier oai:identifier

oai:repository.gatech.edu:1853/62798