Matching Items (3)
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- All Subjects: Planetary Science
- Creators: Robinson, Mark
- Status: Published
Description
This project focuses on using Neutral Gas and Ion Mass Spectrometer (NGIMS) density data for carbon dioxide, oxygen, carbon monoxide, and nitrogen during deep dip campaigns 5, 6, and 8. Density profiles obtained from NGIMS were plotted against simulated density profiles from the Mars Global Ionosphere-Thermosphere Model (MGITM). Averaged temperature profiles were also plotted for the three deep dip campaigns, using NGIMS data and MGITM output. MGITM was also used as a tool to uncover potential heat balance terms needed to reproduce the mean density and temperature profiles measured by NGIMS.
This method of using NGIMS data as a validation tool for MGITM simulations has been tested previously using dayside data from deep dip campaigns 2 and 8. In those cases, MGITM was able to accurately reproduce the measured density and temperature profiles; however, in the deep dip 5 and 6 campaigns, the results are not quite the same, due to the highly variable nature of the nightside thermosphere. MGITM was able to fairly accurately reproduce the density and temperature profiles for deep dip 5, but the deep dip 6 model output showed unexpected significant variation. The deep dip 6 results reveal possible changes to be made to MGITM to more accurately reflect the observed structure of the nighttime thermosphere. In particular, upgrading the model to incorporate a suitable gravity wave parameterization should better capture the role of global winds in maintaining the nighttime thermospheric structure.
This project reveals that there still exist many unknowns about the structure and dynamics of the night side of the Martian atmosphere, as well as significant diurnal variations in density. Further study is needed to uncover these unknowns and their role in atmospheric mass loss.
This method of using NGIMS data as a validation tool for MGITM simulations has been tested previously using dayside data from deep dip campaigns 2 and 8. In those cases, MGITM was able to accurately reproduce the measured density and temperature profiles; however, in the deep dip 5 and 6 campaigns, the results are not quite the same, due to the highly variable nature of the nightside thermosphere. MGITM was able to fairly accurately reproduce the density and temperature profiles for deep dip 5, but the deep dip 6 model output showed unexpected significant variation. The deep dip 6 results reveal possible changes to be made to MGITM to more accurately reflect the observed structure of the nighttime thermosphere. In particular, upgrading the model to incorporate a suitable gravity wave parameterization should better capture the role of global winds in maintaining the nighttime thermospheric structure.
This project reveals that there still exist many unknowns about the structure and dynamics of the night side of the Martian atmosphere, as well as significant diurnal variations in density. Further study is needed to uncover these unknowns and their role in atmospheric mass loss.
ContributorsRobinson, Jenna (Author) / Desch, Steven (Thesis director) / Hervig, Richard (Committee member) / School of Earth and Space Exploration (Contributor) / School for the Future of Innovation in Society (Contributor) / School of International Letters and Cultures (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Jupiter’s moon Europa is an active target of research because of its unique geology and its potential for habitability. Europa’s icy chaos disrupts and transforms the previous terrain, suggesting melting is involved. Chaos occurs alongside several types of endogenic surface features. These microfeatures are under <100 km2 in area and include uplifts and domes, pits, spots, and hybrid features. The distribution of microfeatures is known in the ~10% of the Europa’s surface that are covered by the regional mosaics (“RegMaps”). The efforts to connect microfeature formation to any kind of heat transport in Europa are confounded because microfeatures are difficult to identify outside of RegMaps because of low image resolutions. Finding microfeatures outside of RegMaps would provide new observational constraints for microfeature formation models.
First, I mapped microfeatures across four of Europa’s RegMaps and validated them against other mapping datasets. Microchaos features are the most numerous, followed by pits, domes, then hybrids. Spots are the least common features, and the smallest. Next, I mapped features in low-resolution images that covered the E15RegMap01 area to determine error rates and sources of omission or misclassification for features mapped in low-resolution images. Of all features originally mapped in the RegMap, pits and domes were the least likely to be re-mapped or positively identified (24.2% and 5%, respectively). Chaos, spots, and hybrids were accurately classified over 70% of the time. Quantitatively classifying these features using discriminant function analysis yielded comparable values of accuracy when compared to a human mapper. Finally, nearest-neighbor clustering analyses were used to show that pits are clustered in all regions, while chaos, domes, and hybrids vary in terms of their spatial clustering.
This work suggests that the most likely processes for microfeature formations is either the evolution of liquid water sills within Europa’s ice shell or cryovolcanism. Future work extending to more areas outside of the RegMaps can further refine microfeature formation models. The detection of liquid water at or near the surface is a major goal of multiple upcoming Europa missions; this work provides predictions that can be directly tested by these missions to maximize their scientific return.
First, I mapped microfeatures across four of Europa’s RegMaps and validated them against other mapping datasets. Microchaos features are the most numerous, followed by pits, domes, then hybrids. Spots are the least common features, and the smallest. Next, I mapped features in low-resolution images that covered the E15RegMap01 area to determine error rates and sources of omission or misclassification for features mapped in low-resolution images. Of all features originally mapped in the RegMap, pits and domes were the least likely to be re-mapped or positively identified (24.2% and 5%, respectively). Chaos, spots, and hybrids were accurately classified over 70% of the time. Quantitatively classifying these features using discriminant function analysis yielded comparable values of accuracy when compared to a human mapper. Finally, nearest-neighbor clustering analyses were used to show that pits are clustered in all regions, while chaos, domes, and hybrids vary in terms of their spatial clustering.
This work suggests that the most likely processes for microfeature formations is either the evolution of liquid water sills within Europa’s ice shell or cryovolcanism. Future work extending to more areas outside of the RegMaps can further refine microfeature formation models. The detection of liquid water at or near the surface is a major goal of multiple upcoming Europa missions; this work provides predictions that can be directly tested by these missions to maximize their scientific return.
ContributorsNoviello, Jessica (Author) / Rhoden, Alyssa R (Thesis advisor) / Christensen, Philip R. (Philip Russel) (Thesis advisor) / Williams, David A. (Committee member) / Robinson, Mark (Committee member) / Scowen, Paul (Committee member) / Arizona State University (Publisher)
Created2019
Description
Affect is a domain of psychology that includes attitudes, emotions, interests, and values. My own affect influenced the choice of topics for my dissertation. After examining asteroid interiors and the Moon’s thermal evolution, I discuss the role of affect in online science education. I begin with asteroids, which are collections of smaller objects held together by gravity and possibly cohesion. These “rubble-pile” objects may experience the Brazil Nut Effect (BNE). When a collection of particles of similar densities, but of different sizes, is shaken, smaller particles will move parallel to the local gravity vector while larger objects will do the opposite. Thus, when asteroids are shaken by impacts, they may experience the BNE as possibly evidenced by large boulders seen on their surfaces. I found while the BNE is plausible on asteroids, it is confined to only the outer layers. The Moon, which formed with a Lunar Magma Ocean (LMO), is the next topic of this work. The LMO is due to the Moon forming rapidly after a giant impact between the proto-Earth and another planetary body. The first 80% of the LMO solidified rapidly at which point a floatation crust formed and slowed solidification of the remaining LMO. Impact bombardment during this cooling process, while an important component, has not been studied in detail. Impacts considered here are from debris generated during the formation of the Moon. I developed a thermal model that incorporates impacts and find that impacts may have either expedited or delayed LMO solidification. Finally, I return to affect to consider the differences in attitudes towards science between students enrolled in fully-online degree programs and those enrolled in traditional, in-person degree programs. I analyzed pre- and post-course survey data from the online astrobiology course Habitable Worlds. Unlike their traditional program counterparts, students enrolled in online programs started the course with better attitudes towards science and also further changed towards more positive attitudes during the course. Along with important conclusions in three research fields, this work aims to demonstrate the importance of affect in both scientific research and science education.
ContributorsDingatantrige Perera, Jude Viranga (Author) / Asphaug, Erik (Thesis advisor) / Semken, Steven (Thesis advisor) / Anbar, Ariel (Committee member) / Elkins-Tanton, Linda T. (Committee member) / Robinson, Mark (Committee member) / Arizona State University (Publisher)
Created2017