Unveiling the ansiotropy of Antarctic ice across spatial scales using phase coherent radar

Climate change and the associated rise in temperatures have raised concerns about Antarctica's substantial contribution to sea level rise and climate change. Evaluating this impact involves utilizing ice flow models, where the implementation of ice rheology plays a crucial role in influencing predictions. Ice is an anisotropic material, meaning as ice flows, crystals within it align in response to compression and extension, forming what is known as "ice fabric." Ice fabric properties significantly affect ice flow dynamics. However, many models currently assume isotropic ice behavior, mainly due to limited observational data and the complexity involved in incorporating ice fabric anisotropy into the models. This assumption poses challenges in accurately predicting Antarctica's impact on sea level rise and climate change. To address this issue and improve the precision of ice flow models, it is essential to develop methodologies to enhance the quantity of observational data pertaining to ice fabric properties, which is the main focus of my doctoral research. Ice cores provide reliable ice fabric anisotropy observations but are impractical for expanding spatial coverage.Geophysical methods, including seismic and ultrasonic techniques, show potential. However, recent advancements in phase-coherent radar technology, specifically the phase-sensitive radio echo sounder (pRES radar), coupled with improved processing techniques, offer the most promise in bridging the observational gap in ice fabric properties. My thesis focuses on developing a data processing technique to estimate ice fabric properties from pRES radar measurements and mobilizing the pRES system to increase the quantity of the collected data. The initial phase of my doctoral research involves developing a nonlinear multivariable inverse algorithm, utilizing a matrix-based forward model to simulate radar backscattered signals in an anisotropic medium such as ice. In addition to that, I also developed a technique to approximate the full ice fabric orientation tensor, crucial for parameterizing ice fabric anisotropy in flow models. This method has undergone testing in three separate flow regimes in Antarctica, and the results have been validated through observations from nearby ice cores. Analyzing pRES measurements along a profile on an ice dome has demonstrated that estimated ice fabric anisotropy can reveal the Raymond effect, even when Raymond arches are absent. Although this method resolves ice fabric properties, it is limited by assumptions around initial model parameters, vertical eigenvector, and depth-invariant horizontal ice fabric orientation. The second phase of my research centers on modifying a commercial rover's hardware and software to develop a data acquisition system. The resultant system, named SLEDGE, is a customized ice rover, towing four pRES antennas in a quad-polarimetric setup on two sleds. It employs RTK GPS for precise positioning and drives autonomously to predefined locations and actively triggers the radar system capable of collecting data for profiles spanning several kilometers. A deployment to Antarctica as proof of concept yielded 23 kilometers of quad-polarimetric pRES measurements within 20 operational hours, covering 450 points. While the first deployment was a success, SLEDGE requires additional hardware and software refinement for future field deployment. Overall, the developed inverse approach and SLEDGE, together, show great potential to enhance the spatial coverage of ice fabric properties in the observational data archive—a necessary step towards parameterizing ice fabric anisotropy in ice flow models. Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Ershadi, M. Reza [verfasserIn]
Körperschaften:	Eberhard Karls Universität Tübingen [Grad-verleihende Institution]
Hochschulschrift:	Dissertation ; Eberhard Karls Universität Tübingen ; 2024

Format:	E-Book
Sprache:	Englisch

Erschienen:	Tübingen: 2023

Schlagwörter:	Radar Eis Anisotropie Roboter Antarktis
Formangabe:	Hochschulschrift

Umfang:	1 Online-Ressource (xiv, 110 Seiten) ; Illustrationen

Weitere Ausgabe:	Erscheint auch als Druck-Ausgabe Ershadi, M. Reza: Unveiling the ansiotropy of Antarctic ice across spatial scales using phase coherent radar - Tübingen, 2023

Links:	Link aufrufen Volltext Volltext Volltext Volltext Link aufrufen Link aufrufen

DOI / URN:	urn:nbn:de:bsz:21-dspace-1512680 10.15496/publikation-92608

Katalog-ID:	1882515102

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520			\|a Climate change and the associated rise in temperatures have raised concerns about Antarctica's substantial contribution to sea level rise and climate change. Evaluating this impact involves utilizing ice flow models, where the implementation of ice rheology plays a crucial role in influencing predictions. Ice is an anisotropic material, meaning as ice flows, crystals within it align in response to compression and extension, forming what is known as "ice fabric." Ice fabric properties significantly affect ice flow dynamics. However, many models currently assume isotropic ice behavior, mainly due to limited observational data and the complexity involved in incorporating ice fabric anisotropy into the models. This assumption poses challenges in accurately predicting Antarctica's impact on sea level rise and climate change. To address this issue and improve the precision of ice flow models, it is essential to develop methodologies to enhance the quantity of observational data pertaining to ice fabric properties, which is the main focus of my doctoral research. Ice cores provide reliable ice fabric anisotropy observations but are impractical for expanding spatial coverage.Geophysical methods, including seismic and ultrasonic techniques, show potential. However, recent advancements in phase-coherent radar technology, specifically the phase-sensitive radio echo sounder (pRES radar), coupled with improved processing techniques, offer the most promise in bridging the observational gap in ice fabric properties. My thesis focuses on developing a data processing technique to estimate ice fabric properties from pRES radar measurements and mobilizing the pRES system to increase the quantity of the collected data. The initial phase of my doctoral research involves developing a nonlinear multivariable inverse algorithm, utilizing a matrix-based forward model to simulate radar backscattered signals in an anisotropic medium such as ice. In addition to that, I also developed a technique to approximate the full ice fabric orientation tensor, crucial for parameterizing ice fabric anisotropy in flow models. This method has undergone testing in three separate flow regimes in Antarctica, and the results have been validated through observations from nearby ice cores. Analyzing pRES measurements along a profile on an ice dome has demonstrated that estimated ice fabric anisotropy can reveal the Raymond effect, even when Raymond arches are absent. Although this method resolves ice fabric properties, it is limited by assumptions around initial model parameters, vertical eigenvector, and depth-invariant horizontal ice fabric orientation. The second phase of my research centers on modifying a commercial rover's hardware and software to develop a data acquisition system. The resultant system, named SLEDGE, is a customized ice rover, towing four pRES antennas in a quad-polarimetric setup on two sleds. It employs RTK GPS for precise positioning and drives autonomously to predefined locations and actively triggers the radar system capable of collecting data for profiles spanning several kilometers. A deployment to Antarctica as proof of concept yielded 23 kilometers of quad-polarimetric pRES measurements within 20 operational hours, covering 450 points. While the first deployment was a success, SLEDGE requires additional hardware and software refinement for future field deployment. Overall, the developed inverse approach and SLEDGE, together, show great potential to enhance the spatial coverage of ice fabric properties in the observational data archive—a necessary step towards parameterizing ice fabric anisotropy in ice flow models.
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title_sort	unveiling the ansiotropy of antarctic ice across spatial scales using phase coherent radar
title_auth	Unveiling the ansiotropy of Antarctic ice across spatial scales using phase coherent radar
abstract	Climate change and the associated rise in temperatures have raised concerns about Antarctica's substantial contribution to sea level rise and climate change. Evaluating this impact involves utilizing ice flow models, where the implementation of ice rheology plays a crucial role in influencing predictions. Ice is an anisotropic material, meaning as ice flows, crystals within it align in response to compression and extension, forming what is known as "ice fabric." Ice fabric properties significantly affect ice flow dynamics. However, many models currently assume isotropic ice behavior, mainly due to limited observational data and the complexity involved in incorporating ice fabric anisotropy into the models. This assumption poses challenges in accurately predicting Antarctica's impact on sea level rise and climate change. To address this issue and improve the precision of ice flow models, it is essential to develop methodologies to enhance the quantity of observational data pertaining to ice fabric properties, which is the main focus of my doctoral research. Ice cores provide reliable ice fabric anisotropy observations but are impractical for expanding spatial coverage.Geophysical methods, including seismic and ultrasonic techniques, show potential. However, recent advancements in phase-coherent radar technology, specifically the phase-sensitive radio echo sounder (pRES radar), coupled with improved processing techniques, offer the most promise in bridging the observational gap in ice fabric properties. My thesis focuses on developing a data processing technique to estimate ice fabric properties from pRES radar measurements and mobilizing the pRES system to increase the quantity of the collected data. The initial phase of my doctoral research involves developing a nonlinear multivariable inverse algorithm, utilizing a matrix-based forward model to simulate radar backscattered signals in an anisotropic medium such as ice. In addition to that, I also developed a technique to approximate the full ice fabric orientation tensor, crucial for parameterizing ice fabric anisotropy in flow models. This method has undergone testing in three separate flow regimes in Antarctica, and the results have been validated through observations from nearby ice cores. Analyzing pRES measurements along a profile on an ice dome has demonstrated that estimated ice fabric anisotropy can reveal the Raymond effect, even when Raymond arches are absent. Although this method resolves ice fabric properties, it is limited by assumptions around initial model parameters, vertical eigenvector, and depth-invariant horizontal ice fabric orientation. The second phase of my research centers on modifying a commercial rover's hardware and software to develop a data acquisition system. The resultant system, named SLEDGE, is a customized ice rover, towing four pRES antennas in a quad-polarimetric setup on two sleds. It employs RTK GPS for precise positioning and drives autonomously to predefined locations and actively triggers the radar system capable of collecting data for profiles spanning several kilometers. A deployment to Antarctica as proof of concept yielded 23 kilometers of quad-polarimetric pRES measurements within 20 operational hours, covering 450 points. While the first deployment was a success, SLEDGE requires additional hardware and software refinement for future field deployment. Overall, the developed inverse approach and SLEDGE, together, show great potential to enhance the spatial coverage of ice fabric properties in the observational data archive—a necessary step towards parameterizing ice fabric anisotropy in ice flow models.
abstractGer	Climate change and the associated rise in temperatures have raised concerns about Antarctica's substantial contribution to sea level rise and climate change. Evaluating this impact involves utilizing ice flow models, where the implementation of ice rheology plays a crucial role in influencing predictions. Ice is an anisotropic material, meaning as ice flows, crystals within it align in response to compression and extension, forming what is known as "ice fabric." Ice fabric properties significantly affect ice flow dynamics. However, many models currently assume isotropic ice behavior, mainly due to limited observational data and the complexity involved in incorporating ice fabric anisotropy into the models. This assumption poses challenges in accurately predicting Antarctica's impact on sea level rise and climate change. To address this issue and improve the precision of ice flow models, it is essential to develop methodologies to enhance the quantity of observational data pertaining to ice fabric properties, which is the main focus of my doctoral research. Ice cores provide reliable ice fabric anisotropy observations but are impractical for expanding spatial coverage.Geophysical methods, including seismic and ultrasonic techniques, show potential. However, recent advancements in phase-coherent radar technology, specifically the phase-sensitive radio echo sounder (pRES radar), coupled with improved processing techniques, offer the most promise in bridging the observational gap in ice fabric properties. My thesis focuses on developing a data processing technique to estimate ice fabric properties from pRES radar measurements and mobilizing the pRES system to increase the quantity of the collected data. The initial phase of my doctoral research involves developing a nonlinear multivariable inverse algorithm, utilizing a matrix-based forward model to simulate radar backscattered signals in an anisotropic medium such as ice. In addition to that, I also developed a technique to approximate the full ice fabric orientation tensor, crucial for parameterizing ice fabric anisotropy in flow models. This method has undergone testing in three separate flow regimes in Antarctica, and the results have been validated through observations from nearby ice cores. Analyzing pRES measurements along a profile on an ice dome has demonstrated that estimated ice fabric anisotropy can reveal the Raymond effect, even when Raymond arches are absent. Although this method resolves ice fabric properties, it is limited by assumptions around initial model parameters, vertical eigenvector, and depth-invariant horizontal ice fabric orientation. The second phase of my research centers on modifying a commercial rover's hardware and software to develop a data acquisition system. The resultant system, named SLEDGE, is a customized ice rover, towing four pRES antennas in a quad-polarimetric setup on two sleds. It employs RTK GPS for precise positioning and drives autonomously to predefined locations and actively triggers the radar system capable of collecting data for profiles spanning several kilometers. A deployment to Antarctica as proof of concept yielded 23 kilometers of quad-polarimetric pRES measurements within 20 operational hours, covering 450 points. While the first deployment was a success, SLEDGE requires additional hardware and software refinement for future field deployment. Overall, the developed inverse approach and SLEDGE, together, show great potential to enhance the spatial coverage of ice fabric properties in the observational data archive—a necessary step towards parameterizing ice fabric anisotropy in ice flow models.
abstract_unstemmed	Climate change and the associated rise in temperatures have raised concerns about Antarctica's substantial contribution to sea level rise and climate change. Evaluating this impact involves utilizing ice flow models, where the implementation of ice rheology plays a crucial role in influencing predictions. Ice is an anisotropic material, meaning as ice flows, crystals within it align in response to compression and extension, forming what is known as "ice fabric." Ice fabric properties significantly affect ice flow dynamics. However, many models currently assume isotropic ice behavior, mainly due to limited observational data and the complexity involved in incorporating ice fabric anisotropy into the models. This assumption poses challenges in accurately predicting Antarctica's impact on sea level rise and climate change. To address this issue and improve the precision of ice flow models, it is essential to develop methodologies to enhance the quantity of observational data pertaining to ice fabric properties, which is the main focus of my doctoral research. Ice cores provide reliable ice fabric anisotropy observations but are impractical for expanding spatial coverage.Geophysical methods, including seismic and ultrasonic techniques, show potential. However, recent advancements in phase-coherent radar technology, specifically the phase-sensitive radio echo sounder (pRES radar), coupled with improved processing techniques, offer the most promise in bridging the observational gap in ice fabric properties. My thesis focuses on developing a data processing technique to estimate ice fabric properties from pRES radar measurements and mobilizing the pRES system to increase the quantity of the collected data. The initial phase of my doctoral research involves developing a nonlinear multivariable inverse algorithm, utilizing a matrix-based forward model to simulate radar backscattered signals in an anisotropic medium such as ice. In addition to that, I also developed a technique to approximate the full ice fabric orientation tensor, crucial for parameterizing ice fabric anisotropy in flow models. This method has undergone testing in three separate flow regimes in Antarctica, and the results have been validated through observations from nearby ice cores. Analyzing pRES measurements along a profile on an ice dome has demonstrated that estimated ice fabric anisotropy can reveal the Raymond effect, even when Raymond arches are absent. Although this method resolves ice fabric properties, it is limited by assumptions around initial model parameters, vertical eigenvector, and depth-invariant horizontal ice fabric orientation. The second phase of my research centers on modifying a commercial rover's hardware and software to develop a data acquisition system. The resultant system, named SLEDGE, is a customized ice rover, towing four pRES antennas in a quad-polarimetric setup on two sleds. It employs RTK GPS for precise positioning and drives autonomously to predefined locations and actively triggers the radar system capable of collecting data for profiles spanning several kilometers. A deployment to Antarctica as proof of concept yielded 23 kilometers of quad-polarimetric pRES measurements within 20 operational hours, covering 450 points. While the first deployment was a success, SLEDGE requires additional hardware and software refinement for future field deployment. Overall, the developed inverse approach and SLEDGE, together, show great potential to enhance the spatial coverage of ice fabric properties in the observational data archive—a necessary step towards parameterizing ice fabric anisotropy in ice flow models.
url	https://publikationen.uni-tuebingen.de/xmlui/handle/10900/151268/ http://hdl.handle.net/10900/151268 http://dx.doi.org/10.15496/publikation-92608 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 https://nbn-resolving.org/urn:nbn:de:bsz:21-dspace-1512680 https://d-nb.info/1323452494/34
author2	Eberhard Karls Universität Tübingen
author2Str	Eberhard Karls Universität Tübingen
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coordinates_geo2	Point ( +016.406259 -078.158559 )
allfields	urn:nbn:de:bsz:21-dspace-1512680 urn 10.15496/publikation-92608 doi 10900/151268 hdl (DE-627)1882515102 (DE-599)KXP1882515102 (OCoLC)1424951701 DE-627 ger DE-627 rda eng XA-DE-BW 551.31 DE-101 550 DE-101 Ershadi, M. Reza verfasserin (DE-588)1322590397 (DE-627)1882516443 aut Unveiling the ansiotropy of Antarctic ice across spatial scales using phase coherent radar vorgelegt von Mohammadreza Ershadi Tübingen 2023 1 Online-Ressource (xiv, 110 Seiten) Illustrationen Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Dissertation Eberhard Karls Universität Tübingen 2024 Climate change and the associated rise in temperatures have raised concerns about Antarctica's substantial contribution to sea level rise and climate change. Evaluating this impact involves utilizing ice flow models, where the implementation of ice rheology plays a crucial role in influencing predictions. Ice is an anisotropic material, meaning as ice flows, crystals within it align in response to compression and extension, forming what is known as "ice fabric." Ice fabric properties significantly affect ice flow dynamics. However, many models currently assume isotropic ice behavior, mainly due to limited observational data and the complexity involved in incorporating ice fabric anisotropy into the models. This assumption poses challenges in accurately predicting Antarctica's impact on sea level rise and climate change. To address this issue and improve the precision of ice flow models, it is essential to develop methodologies to enhance the quantity of observational data pertaining to ice fabric properties, which is the main focus of my doctoral research. Ice cores provide reliable ice fabric anisotropy observations but are impractical for expanding spatial coverage.Geophysical methods, including seismic and ultrasonic techniques, show potential. However, recent advancements in phase-coherent radar technology, specifically the phase-sensitive radio echo sounder (pRES radar), coupled with improved processing techniques, offer the most promise in bridging the observational gap in ice fabric properties. My thesis focuses on developing a data processing technique to estimate ice fabric properties from pRES radar measurements and mobilizing the pRES system to increase the quantity of the collected data. The initial phase of my doctoral research involves developing a nonlinear multivariable inverse algorithm, utilizing a matrix-based forward model to simulate radar backscattered signals in an anisotropic medium such as ice. In addition to that, I also developed a technique to approximate the full ice fabric orientation tensor, crucial for parameterizing ice fabric anisotropy in flow models. This method has undergone testing in three separate flow regimes in Antarctica, and the results have been validated through observations from nearby ice cores. Analyzing pRES measurements along a profile on an ice dome has demonstrated that estimated ice fabric anisotropy can reveal the Raymond effect, even when Raymond arches are absent. Although this method resolves ice fabric properties, it is limited by assumptions around initial model parameters, vertical eigenvector, and depth-invariant horizontal ice fabric orientation. The second phase of my research centers on modifying a commercial rover's hardware and software to develop a data acquisition system. The resultant system, named SLEDGE, is a customized ice rover, towing four pRES antennas in a quad-polarimetric setup on two sleds. It employs RTK GPS for precise positioning and drives autonomously to predefined locations and actively triggers the radar system capable of collecting data for profiles spanning several kilometers. A deployment to Antarctica as proof of concept yielded 23 kilometers of quad-polarimetric pRES measurements within 20 operational hours, covering 450 points. While the first deployment was a success, SLEDGE requires additional hardware and software refinement for future field deployment. Overall, the developed inverse approach and SLEDGE, together, show great potential to enhance the spatial coverage of ice fabric properties in the observational data archive—a necessary step towards parameterizing ice fabric anisotropy in ice flow models. (DE-588)4176765-2 (DE-627)105353906 (DE-576)209972866 Radar gnd (DE-588)4013994-3 (DE-627)106341448 (DE-576)208906185 Eis gnd (DE-588)4002073-3 (DE-627)106394541 (DE-576)208845631 Anisotropie gnd (DE-588)4050208-9 (DE-627)106183249 (DE-576)209086173 Roboter gnd (DE-588)4002208-0 (DE-627)106394169 (DE-576)208846158 Antarktis gnd Hochschulschrift (DE-588)4113937-9 (DE-627)105825778 (DE-576)209480580 gnd-content Eberhard Karls Universität Tübingen Grad-verleihende Institution (DE-588)36187-2 (DE-627)100833349 (DE-576)190344806 dgg Tübingen (DE-588)4061147-4 (DE-627)106136933 (DE-576)209138351 uvp Erscheint auch als Druck-Ausgabe Ershadi, M. Reza Unveiling the ansiotropy of Antarctic ice across spatial scales using phase coherent radar Tübingen, 2023 xiv, 110 Seiten (DE-627)1882515412 https://publikationen.uni-tuebingen.de/xmlui/handle/10900/151268/ Verlag kostenfrei Volltext http://hdl.handle.net/10900/151268 Resolving-System kostenfrei Volltext http://dx.doi.org/10.15496/publikation-92608 Resolving-System kostenfrei Volltext http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 Resolving-System kostenfrei Volltext https://nbn-resolving.org/urn:nbn:de:bsz:21-dspace-1512680 Resolving-System kostenfrei https://d-nb.info/1323452494/34 Langzeitarchivierung Nationalbibliothek kostenfrei GBV-ODiss GBV_ILN_20 ISIL_DE-84 SYSFLAG_1 GBV_KXP GBV_ILN_21 ISIL_DE-46 GBV_ILN_22 ISIL_DE-18 GBV_ILN_23 ISIL_DE-830 GBV_ILN_30 ISIL_DE-104 GBV_ILN_40 ISIL_DE-7 GBV_ILN_60 ISIL_DE-705 GBV_ILN_63 ISIL_DE-Wim2 GBV_ILN_70 ISIL_DE-89 GBV_ILN_105 ISIL_DE-841 GBV_ILN_110 ISIL_DE-Luen4 GBV_ILN_132 ISIL_DE-959 GBV_ILN_151 ISIL_DE-546 GBV_ILN_161 ISIL_DE-960 GBV_ILN_293 ISIL_DE-960-3 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2001 ISIL_DE-21 GBV_ILN_2403 ISIL_DE-LFER BO 20 01 0084 450810603X x 08-04-24 21 01 0046 4508122582 z 08-04-24 22 01 0018 4508139345 SUBolrd xu 08-04-24 23 01 0830 4508155308 olr-d x 08-04-24 30 01 0104 4508164765 z 08-04-24 40 01 0007 4508173071 xsn 08-04-24 60 01 0705 4508190057 OLRD z 08-04-24 63 01 3401 4508205909 ORD x 08-04-24 70 01 0089 4508213774 zdo 08-04-24 105 01 0841 4508359795 z 08-04-24 110 01 3110 4508223672 x 08-04-24 132 01 0959 4508234313 OLR-DISS x 08-04-24 151 01 0546 450825019X OLR-ODISS z 08-04-24 161 01 0960 4508256473 ORD z 08-04-24 293 01 3293 450829037X ORD z 08-04-24 370 01 4370 4508299415 x 08-04-24 2001 01 DE-21 4495867830 00 --%%-- --%%-- --%%-- --%%-- Elektronischer Volltext - Zugang über WWW l01 05-03-24 2403 01 DE-LFER 4508429858 00 --%%-- --%%-- n --%%-- l01 08-04-24 20 01 0084 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 21 01 0046 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 22 01 0018 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 23 01 0830 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 30 01 0104 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 40 01 0007 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 60 01 0705 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 63 01 3401 E-Book http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 LF 70 01 0089 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 105 01 0841 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 110 01 3110 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 132 01 0959 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 151 01 0546 Volltext http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 161 01 0960 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 293 01 3293 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 370 01 4370 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 2001 01 DE-21 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 2403 01 DE-LFER http://dx.doi.org/10.15496/publikation-92608 2403 01 DE-LFER http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 2001 01 DE-21 00 s Antarctica 2001 01 DE-21 01 s Phase Coherent Radar 2001 01 DE-21 02 s Rover 2001 01 DE-21 03 s ApRES 2001 01 DE-21 04 s Ice crystals 2001 01 DE-21 05 s Phase coherent radar 2001 01 DE-21 06 s Rover 2001 01 DE-21 07 s ApRES 2001 01 DE-21 08 s Ice crystals 2001 01 DE-21 09 s Antarctica 60 01 0705 10 ho 20 01 0084 OLRD 110 01 3110 OLRD 370 01 4370 OLRD 22 01 0018 SUBolrd 23 01 0830 olr-d 60 01 0705 OLRD 63 01 3401 ORD 132 01 0959 OLR-DISS 151 01 0546 OLR-ODISS 161 01 0960 ORD 293 01 3293 ORD 23 01 0830 2024-04-08 07:43:14
spelling	urn:nbn:de:bsz:21-dspace-1512680 urn 10.15496/publikation-92608 doi 10900/151268 hdl (DE-627)1882515102 (DE-599)KXP1882515102 (OCoLC)1424951701 DE-627 ger DE-627 rda eng XA-DE-BW 551.31 DE-101 550 DE-101 Ershadi, M. Reza verfasserin (DE-588)1322590397 (DE-627)1882516443 aut Unveiling the ansiotropy of Antarctic ice across spatial scales using phase coherent radar vorgelegt von Mohammadreza Ershadi Tübingen 2023 1 Online-Ressource (xiv, 110 Seiten) Illustrationen Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Dissertation Eberhard Karls Universität Tübingen 2024 Climate change and the associated rise in temperatures have raised concerns about Antarctica's substantial contribution to sea level rise and climate change. Evaluating this impact involves utilizing ice flow models, where the implementation of ice rheology plays a crucial role in influencing predictions. Ice is an anisotropic material, meaning as ice flows, crystals within it align in response to compression and extension, forming what is known as "ice fabric." Ice fabric properties significantly affect ice flow dynamics. However, many models currently assume isotropic ice behavior, mainly due to limited observational data and the complexity involved in incorporating ice fabric anisotropy into the models. This assumption poses challenges in accurately predicting Antarctica's impact on sea level rise and climate change. To address this issue and improve the precision of ice flow models, it is essential to develop methodologies to enhance the quantity of observational data pertaining to ice fabric properties, which is the main focus of my doctoral research. Ice cores provide reliable ice fabric anisotropy observations but are impractical for expanding spatial coverage.Geophysical methods, including seismic and ultrasonic techniques, show potential. However, recent advancements in phase-coherent radar technology, specifically the phase-sensitive radio echo sounder (pRES radar), coupled with improved processing techniques, offer the most promise in bridging the observational gap in ice fabric properties. My thesis focuses on developing a data processing technique to estimate ice fabric properties from pRES radar measurements and mobilizing the pRES system to increase the quantity of the collected data. The initial phase of my doctoral research involves developing a nonlinear multivariable inverse algorithm, utilizing a matrix-based forward model to simulate radar backscattered signals in an anisotropic medium such as ice. In addition to that, I also developed a technique to approximate the full ice fabric orientation tensor, crucial for parameterizing ice fabric anisotropy in flow models. This method has undergone testing in three separate flow regimes in Antarctica, and the results have been validated through observations from nearby ice cores. Analyzing pRES measurements along a profile on an ice dome has demonstrated that estimated ice fabric anisotropy can reveal the Raymond effect, even when Raymond arches are absent. Although this method resolves ice fabric properties, it is limited by assumptions around initial model parameters, vertical eigenvector, and depth-invariant horizontal ice fabric orientation. The second phase of my research centers on modifying a commercial rover's hardware and software to develop a data acquisition system. The resultant system, named SLEDGE, is a customized ice rover, towing four pRES antennas in a quad-polarimetric setup on two sleds. It employs RTK GPS for precise positioning and drives autonomously to predefined locations and actively triggers the radar system capable of collecting data for profiles spanning several kilometers. A deployment to Antarctica as proof of concept yielded 23 kilometers of quad-polarimetric pRES measurements within 20 operational hours, covering 450 points. While the first deployment was a success, SLEDGE requires additional hardware and software refinement for future field deployment. Overall, the developed inverse approach and SLEDGE, together, show great potential to enhance the spatial coverage of ice fabric properties in the observational data archive—a necessary step towards parameterizing ice fabric anisotropy in ice flow models. (DE-588)4176765-2 (DE-627)105353906 (DE-576)209972866 Radar gnd (DE-588)4013994-3 (DE-627)106341448 (DE-576)208906185 Eis gnd (DE-588)4002073-3 (DE-627)106394541 (DE-576)208845631 Anisotropie gnd (DE-588)4050208-9 (DE-627)106183249 (DE-576)209086173 Roboter gnd (DE-588)4002208-0 (DE-627)106394169 (DE-576)208846158 Antarktis gnd Hochschulschrift (DE-588)4113937-9 (DE-627)105825778 (DE-576)209480580 gnd-content Eberhard Karls Universität Tübingen Grad-verleihende Institution (DE-588)36187-2 (DE-627)100833349 (DE-576)190344806 dgg Tübingen (DE-588)4061147-4 (DE-627)106136933 (DE-576)209138351 uvp Erscheint auch als Druck-Ausgabe Ershadi, M. Reza Unveiling the ansiotropy of Antarctic ice across spatial scales using phase coherent radar Tübingen, 2023 xiv, 110 Seiten (DE-627)1882515412 https://publikationen.uni-tuebingen.de/xmlui/handle/10900/151268/ Verlag kostenfrei Volltext http://hdl.handle.net/10900/151268 Resolving-System kostenfrei Volltext http://dx.doi.org/10.15496/publikation-92608 Resolving-System kostenfrei Volltext http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 Resolving-System kostenfrei Volltext https://nbn-resolving.org/urn:nbn:de:bsz:21-dspace-1512680 Resolving-System kostenfrei https://d-nb.info/1323452494/34 Langzeitarchivierung Nationalbibliothek kostenfrei GBV-ODiss GBV_ILN_20 ISIL_DE-84 SYSFLAG_1 GBV_KXP GBV_ILN_21 ISIL_DE-46 GBV_ILN_22 ISIL_DE-18 GBV_ILN_23 ISIL_DE-830 GBV_ILN_30 ISIL_DE-104 GBV_ILN_40 ISIL_DE-7 GBV_ILN_60 ISIL_DE-705 GBV_ILN_63 ISIL_DE-Wim2 GBV_ILN_70 ISIL_DE-89 GBV_ILN_105 ISIL_DE-841 GBV_ILN_110 ISIL_DE-Luen4 GBV_ILN_132 ISIL_DE-959 GBV_ILN_151 ISIL_DE-546 GBV_ILN_161 ISIL_DE-960 GBV_ILN_293 ISIL_DE-960-3 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2001 ISIL_DE-21 GBV_ILN_2403 ISIL_DE-LFER BO 20 01 0084 450810603X x 08-04-24 21 01 0046 4508122582 z 08-04-24 22 01 0018 4508139345 SUBolrd xu 08-04-24 23 01 0830 4508155308 olr-d x 08-04-24 30 01 0104 4508164765 z 08-04-24 40 01 0007 4508173071 xsn 08-04-24 60 01 0705 4508190057 OLRD z 08-04-24 63 01 3401 4508205909 ORD x 08-04-24 70 01 0089 4508213774 zdo 08-04-24 105 01 0841 4508359795 z 08-04-24 110 01 3110 4508223672 x 08-04-24 132 01 0959 4508234313 OLR-DISS x 08-04-24 151 01 0546 450825019X OLR-ODISS z 08-04-24 161 01 0960 4508256473 ORD z 08-04-24 293 01 3293 450829037X ORD z 08-04-24 370 01 4370 4508299415 x 08-04-24 2001 01 DE-21 4495867830 00 --%%-- --%%-- --%%-- --%%-- Elektronischer Volltext - Zugang über WWW l01 05-03-24 2403 01 DE-LFER 4508429858 00 --%%-- --%%-- n --%%-- l01 08-04-24 20 01 0084 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 21 01 0046 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 22 01 0018 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 23 01 0830 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 30 01 0104 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 40 01 0007 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 60 01 0705 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 63 01 3401 E-Book http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 LF 70 01 0089 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 105 01 0841 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 110 01 3110 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 132 01 0959 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 151 01 0546 Volltext http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 161 01 0960 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 293 01 3293 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 370 01 4370 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 2001 01 DE-21 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 2403 01 DE-LFER http://dx.doi.org/10.15496/publikation-92608 2403 01 DE-LFER http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 2001 01 DE-21 00 s Antarctica 2001 01 DE-21 01 s Phase Coherent Radar 2001 01 DE-21 02 s Rover 2001 01 DE-21 03 s ApRES 2001 01 DE-21 04 s Ice crystals 2001 01 DE-21 05 s Phase coherent radar 2001 01 DE-21 06 s Rover 2001 01 DE-21 07 s ApRES 2001 01 DE-21 08 s Ice crystals 2001 01 DE-21 09 s Antarctica 60 01 0705 10 ho 20 01 0084 OLRD 110 01 3110 OLRD 370 01 4370 OLRD 22 01 0018 SUBolrd 23 01 0830 olr-d 60 01 0705 OLRD 63 01 3401 ORD 132 01 0959 OLR-DISS 151 01 0546 OLR-ODISS 161 01 0960 ORD 293 01 3293 ORD 23 01 0830 2024-04-08 07:43:14
allfields_unstemmed	urn:nbn:de:bsz:21-dspace-1512680 urn 10.15496/publikation-92608 doi 10900/151268 hdl (DE-627)1882515102 (DE-599)KXP1882515102 (OCoLC)1424951701 DE-627 ger DE-627 rda eng XA-DE-BW 551.31 DE-101 550 DE-101 Ershadi, M. Reza verfasserin (DE-588)1322590397 (DE-627)1882516443 aut Unveiling the ansiotropy of Antarctic ice across spatial scales using phase coherent radar vorgelegt von Mohammadreza Ershadi Tübingen 2023 1 Online-Ressource (xiv, 110 Seiten) Illustrationen Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Dissertation Eberhard Karls Universität Tübingen 2024 Climate change and the associated rise in temperatures have raised concerns about Antarctica's substantial contribution to sea level rise and climate change. Evaluating this impact involves utilizing ice flow models, where the implementation of ice rheology plays a crucial role in influencing predictions. Ice is an anisotropic material, meaning as ice flows, crystals within it align in response to compression and extension, forming what is known as "ice fabric." Ice fabric properties significantly affect ice flow dynamics. However, many models currently assume isotropic ice behavior, mainly due to limited observational data and the complexity involved in incorporating ice fabric anisotropy into the models. This assumption poses challenges in accurately predicting Antarctica's impact on sea level rise and climate change. To address this issue and improve the precision of ice flow models, it is essential to develop methodologies to enhance the quantity of observational data pertaining to ice fabric properties, which is the main focus of my doctoral research. Ice cores provide reliable ice fabric anisotropy observations but are impractical for expanding spatial coverage.Geophysical methods, including seismic and ultrasonic techniques, show potential. However, recent advancements in phase-coherent radar technology, specifically the phase-sensitive radio echo sounder (pRES radar), coupled with improved processing techniques, offer the most promise in bridging the observational gap in ice fabric properties. My thesis focuses on developing a data processing technique to estimate ice fabric properties from pRES radar measurements and mobilizing the pRES system to increase the quantity of the collected data. The initial phase of my doctoral research involves developing a nonlinear multivariable inverse algorithm, utilizing a matrix-based forward model to simulate radar backscattered signals in an anisotropic medium such as ice. In addition to that, I also developed a technique to approximate the full ice fabric orientation tensor, crucial for parameterizing ice fabric anisotropy in flow models. This method has undergone testing in three separate flow regimes in Antarctica, and the results have been validated through observations from nearby ice cores. Analyzing pRES measurements along a profile on an ice dome has demonstrated that estimated ice fabric anisotropy can reveal the Raymond effect, even when Raymond arches are absent. Although this method resolves ice fabric properties, it is limited by assumptions around initial model parameters, vertical eigenvector, and depth-invariant horizontal ice fabric orientation. The second phase of my research centers on modifying a commercial rover's hardware and software to develop a data acquisition system. The resultant system, named SLEDGE, is a customized ice rover, towing four pRES antennas in a quad-polarimetric setup on two sleds. It employs RTK GPS for precise positioning and drives autonomously to predefined locations and actively triggers the radar system capable of collecting data for profiles spanning several kilometers. A deployment to Antarctica as proof of concept yielded 23 kilometers of quad-polarimetric pRES measurements within 20 operational hours, covering 450 points. While the first deployment was a success, SLEDGE requires additional hardware and software refinement for future field deployment. Overall, the developed inverse approach and SLEDGE, together, show great potential to enhance the spatial coverage of ice fabric properties in the observational data archive—a necessary step towards parameterizing ice fabric anisotropy in ice flow models. (DE-588)4176765-2 (DE-627)105353906 (DE-576)209972866 Radar gnd (DE-588)4013994-3 (DE-627)106341448 (DE-576)208906185 Eis gnd (DE-588)4002073-3 (DE-627)106394541 (DE-576)208845631 Anisotropie gnd (DE-588)4050208-9 (DE-627)106183249 (DE-576)209086173 Roboter gnd (DE-588)4002208-0 (DE-627)106394169 (DE-576)208846158 Antarktis gnd Hochschulschrift (DE-588)4113937-9 (DE-627)105825778 (DE-576)209480580 gnd-content Eberhard Karls Universität Tübingen Grad-verleihende Institution (DE-588)36187-2 (DE-627)100833349 (DE-576)190344806 dgg Tübingen (DE-588)4061147-4 (DE-627)106136933 (DE-576)209138351 uvp Erscheint auch als Druck-Ausgabe Ershadi, M. Reza Unveiling the ansiotropy of Antarctic ice across spatial scales using phase coherent radar Tübingen, 2023 xiv, 110 Seiten (DE-627)1882515412 https://publikationen.uni-tuebingen.de/xmlui/handle/10900/151268/ Verlag kostenfrei Volltext http://hdl.handle.net/10900/151268 Resolving-System kostenfrei Volltext http://dx.doi.org/10.15496/publikation-92608 Resolving-System kostenfrei Volltext http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 Resolving-System kostenfrei Volltext https://nbn-resolving.org/urn:nbn:de:bsz:21-dspace-1512680 Resolving-System kostenfrei https://d-nb.info/1323452494/34 Langzeitarchivierung Nationalbibliothek kostenfrei GBV-ODiss GBV_ILN_20 ISIL_DE-84 SYSFLAG_1 GBV_KXP GBV_ILN_21 ISIL_DE-46 GBV_ILN_22 ISIL_DE-18 GBV_ILN_23 ISIL_DE-830 GBV_ILN_30 ISIL_DE-104 GBV_ILN_40 ISIL_DE-7 GBV_ILN_60 ISIL_DE-705 GBV_ILN_63 ISIL_DE-Wim2 GBV_ILN_70 ISIL_DE-89 GBV_ILN_105 ISIL_DE-841 GBV_ILN_110 ISIL_DE-Luen4 GBV_ILN_132 ISIL_DE-959 GBV_ILN_151 ISIL_DE-546 GBV_ILN_161 ISIL_DE-960 GBV_ILN_293 ISIL_DE-960-3 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2001 ISIL_DE-21 GBV_ILN_2403 ISIL_DE-LFER BO 20 01 0084 450810603X x 08-04-24 21 01 0046 4508122582 z 08-04-24 22 01 0018 4508139345 SUBolrd xu 08-04-24 23 01 0830 4508155308 olr-d x 08-04-24 30 01 0104 4508164765 z 08-04-24 40 01 0007 4508173071 xsn 08-04-24 60 01 0705 4508190057 OLRD z 08-04-24 63 01 3401 4508205909 ORD x 08-04-24 70 01 0089 4508213774 zdo 08-04-24 105 01 0841 4508359795 z 08-04-24 110 01 3110 4508223672 x 08-04-24 132 01 0959 4508234313 OLR-DISS x 08-04-24 151 01 0546 450825019X OLR-ODISS z 08-04-24 161 01 0960 4508256473 ORD z 08-04-24 293 01 3293 450829037X ORD z 08-04-24 370 01 4370 4508299415 x 08-04-24 2001 01 DE-21 4495867830 00 --%%-- --%%-- --%%-- --%%-- Elektronischer Volltext - Zugang über WWW l01 05-03-24 2403 01 DE-LFER 4508429858 00 --%%-- --%%-- n --%%-- l01 08-04-24 20 01 0084 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 21 01 0046 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 22 01 0018 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 23 01 0830 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 30 01 0104 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 40 01 0007 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 60 01 0705 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 63 01 3401 E-Book http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 LF 70 01 0089 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 105 01 0841 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 110 01 3110 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 132 01 0959 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 151 01 0546 Volltext http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 161 01 0960 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 293 01 3293 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 370 01 4370 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 2001 01 DE-21 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 2403 01 DE-LFER http://dx.doi.org/10.15496/publikation-92608 2403 01 DE-LFER http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 2001 01 DE-21 00 s Antarctica 2001 01 DE-21 01 s Phase Coherent Radar 2001 01 DE-21 02 s Rover 2001 01 DE-21 03 s ApRES 2001 01 DE-21 04 s Ice crystals 2001 01 DE-21 05 s Phase coherent radar 2001 01 DE-21 06 s Rover 2001 01 DE-21 07 s ApRES 2001 01 DE-21 08 s Ice crystals 2001 01 DE-21 09 s Antarctica 60 01 0705 10 ho 20 01 0084 OLRD 110 01 3110 OLRD 370 01 4370 OLRD 22 01 0018 SUBolrd 23 01 0830 olr-d 60 01 0705 OLRD 63 01 3401 ORD 132 01 0959 OLR-DISS 151 01 0546 OLR-ODISS 161 01 0960 ORD 293 01 3293 ORD 23 01 0830 2024-04-08 07:43:14
allfieldsGer	urn:nbn:de:bsz:21-dspace-1512680 urn 10.15496/publikation-92608 doi 10900/151268 hdl (DE-627)1882515102 (DE-599)KXP1882515102 (OCoLC)1424951701 DE-627 ger DE-627 rda eng XA-DE-BW 551.31 DE-101 550 DE-101 Ershadi, M. Reza verfasserin (DE-588)1322590397 (DE-627)1882516443 aut Unveiling the ansiotropy of Antarctic ice across spatial scales using phase coherent radar vorgelegt von Mohammadreza Ershadi Tübingen 2023 1 Online-Ressource (xiv, 110 Seiten) Illustrationen Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Dissertation Eberhard Karls Universität Tübingen 2024 Climate change and the associated rise in temperatures have raised concerns about Antarctica's substantial contribution to sea level rise and climate change. Evaluating this impact involves utilizing ice flow models, where the implementation of ice rheology plays a crucial role in influencing predictions. Ice is an anisotropic material, meaning as ice flows, crystals within it align in response to compression and extension, forming what is known as "ice fabric." Ice fabric properties significantly affect ice flow dynamics. However, many models currently assume isotropic ice behavior, mainly due to limited observational data and the complexity involved in incorporating ice fabric anisotropy into the models. This assumption poses challenges in accurately predicting Antarctica's impact on sea level rise and climate change. To address this issue and improve the precision of ice flow models, it is essential to develop methodologies to enhance the quantity of observational data pertaining to ice fabric properties, which is the main focus of my doctoral research. Ice cores provide reliable ice fabric anisotropy observations but are impractical for expanding spatial coverage.Geophysical methods, including seismic and ultrasonic techniques, show potential. However, recent advancements in phase-coherent radar technology, specifically the phase-sensitive radio echo sounder (pRES radar), coupled with improved processing techniques, offer the most promise in bridging the observational gap in ice fabric properties. My thesis focuses on developing a data processing technique to estimate ice fabric properties from pRES radar measurements and mobilizing the pRES system to increase the quantity of the collected data. The initial phase of my doctoral research involves developing a nonlinear multivariable inverse algorithm, utilizing a matrix-based forward model to simulate radar backscattered signals in an anisotropic medium such as ice. In addition to that, I also developed a technique to approximate the full ice fabric orientation tensor, crucial for parameterizing ice fabric anisotropy in flow models. This method has undergone testing in three separate flow regimes in Antarctica, and the results have been validated through observations from nearby ice cores. Analyzing pRES measurements along a profile on an ice dome has demonstrated that estimated ice fabric anisotropy can reveal the Raymond effect, even when Raymond arches are absent. Although this method resolves ice fabric properties, it is limited by assumptions around initial model parameters, vertical eigenvector, and depth-invariant horizontal ice fabric orientation. The second phase of my research centers on modifying a commercial rover's hardware and software to develop a data acquisition system. The resultant system, named SLEDGE, is a customized ice rover, towing four pRES antennas in a quad-polarimetric setup on two sleds. It employs RTK GPS for precise positioning and drives autonomously to predefined locations and actively triggers the radar system capable of collecting data for profiles spanning several kilometers. A deployment to Antarctica as proof of concept yielded 23 kilometers of quad-polarimetric pRES measurements within 20 operational hours, covering 450 points. While the first deployment was a success, SLEDGE requires additional hardware and software refinement for future field deployment. Overall, the developed inverse approach and SLEDGE, together, show great potential to enhance the spatial coverage of ice fabric properties in the observational data archive—a necessary step towards parameterizing ice fabric anisotropy in ice flow models. (DE-588)4176765-2 (DE-627)105353906 (DE-576)209972866 Radar gnd (DE-588)4013994-3 (DE-627)106341448 (DE-576)208906185 Eis gnd (DE-588)4002073-3 (DE-627)106394541 (DE-576)208845631 Anisotropie gnd (DE-588)4050208-9 (DE-627)106183249 (DE-576)209086173 Roboter gnd (DE-588)4002208-0 (DE-627)106394169 (DE-576)208846158 Antarktis gnd Hochschulschrift (DE-588)4113937-9 (DE-627)105825778 (DE-576)209480580 gnd-content Eberhard Karls Universität Tübingen Grad-verleihende Institution (DE-588)36187-2 (DE-627)100833349 (DE-576)190344806 dgg Tübingen (DE-588)4061147-4 (DE-627)106136933 (DE-576)209138351 uvp Erscheint auch als Druck-Ausgabe Ershadi, M. Reza Unveiling the ansiotropy of Antarctic ice across spatial scales using phase coherent radar Tübingen, 2023 xiv, 110 Seiten (DE-627)1882515412 https://publikationen.uni-tuebingen.de/xmlui/handle/10900/151268/ Verlag kostenfrei Volltext http://hdl.handle.net/10900/151268 Resolving-System kostenfrei Volltext http://dx.doi.org/10.15496/publikation-92608 Resolving-System kostenfrei Volltext http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 Resolving-System kostenfrei Volltext https://nbn-resolving.org/urn:nbn:de:bsz:21-dspace-1512680 Resolving-System kostenfrei https://d-nb.info/1323452494/34 Langzeitarchivierung Nationalbibliothek kostenfrei GBV-ODiss GBV_ILN_20 ISIL_DE-84 SYSFLAG_1 GBV_KXP GBV_ILN_21 ISIL_DE-46 GBV_ILN_22 ISIL_DE-18 GBV_ILN_23 ISIL_DE-830 GBV_ILN_30 ISIL_DE-104 GBV_ILN_40 ISIL_DE-7 GBV_ILN_60 ISIL_DE-705 GBV_ILN_63 ISIL_DE-Wim2 GBV_ILN_70 ISIL_DE-89 GBV_ILN_105 ISIL_DE-841 GBV_ILN_110 ISIL_DE-Luen4 GBV_ILN_132 ISIL_DE-959 GBV_ILN_151 ISIL_DE-546 GBV_ILN_161 ISIL_DE-960 GBV_ILN_293 ISIL_DE-960-3 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2001 ISIL_DE-21 GBV_ILN_2403 ISIL_DE-LFER BO 20 01 0084 450810603X x 08-04-24 21 01 0046 4508122582 z 08-04-24 22 01 0018 4508139345 SUBolrd xu 08-04-24 23 01 0830 4508155308 olr-d x 08-04-24 30 01 0104 4508164765 z 08-04-24 40 01 0007 4508173071 xsn 08-04-24 60 01 0705 4508190057 OLRD z 08-04-24 63 01 3401 4508205909 ORD x 08-04-24 70 01 0089 4508213774 zdo 08-04-24 105 01 0841 4508359795 z 08-04-24 110 01 3110 4508223672 x 08-04-24 132 01 0959 4508234313 OLR-DISS x 08-04-24 151 01 0546 450825019X OLR-ODISS z 08-04-24 161 01 0960 4508256473 ORD z 08-04-24 293 01 3293 450829037X ORD z 08-04-24 370 01 4370 4508299415 x 08-04-24 2001 01 DE-21 4495867830 00 --%%-- --%%-- --%%-- --%%-- Elektronischer Volltext - Zugang über WWW l01 05-03-24 2403 01 DE-LFER 4508429858 00 --%%-- --%%-- n --%%-- l01 08-04-24 20 01 0084 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 21 01 0046 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 22 01 0018 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 23 01 0830 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 30 01 0104 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 40 01 0007 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 60 01 0705 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 63 01 3401 E-Book http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 LF 70 01 0089 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 105 01 0841 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 110 01 3110 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 132 01 0959 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 151 01 0546 Volltext http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 161 01 0960 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 293 01 3293 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 370 01 4370 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 2001 01 DE-21 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 2403 01 DE-LFER http://dx.doi.org/10.15496/publikation-92608 2403 01 DE-LFER http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 2001 01 DE-21 00 s Antarctica 2001 01 DE-21 01 s Phase Coherent Radar 2001 01 DE-21 02 s Rover 2001 01 DE-21 03 s ApRES 2001 01 DE-21 04 s Ice crystals 2001 01 DE-21 05 s Phase coherent radar 2001 01 DE-21 06 s Rover 2001 01 DE-21 07 s ApRES 2001 01 DE-21 08 s Ice crystals 2001 01 DE-21 09 s Antarctica 60 01 0705 10 ho 20 01 0084 OLRD 110 01 3110 OLRD 370 01 4370 OLRD 22 01 0018 SUBolrd 23 01 0830 olr-d 60 01 0705 OLRD 63 01 3401 ORD 132 01 0959 OLR-DISS 151 01 0546 OLR-ODISS 161 01 0960 ORD 293 01 3293 ORD 23 01 0830 2024-04-08 07:43:14
allfieldsSound	urn:nbn:de:bsz:21-dspace-1512680 urn 10.15496/publikation-92608 doi 10900/151268 hdl (DE-627)1882515102 (DE-599)KXP1882515102 (OCoLC)1424951701 DE-627 ger DE-627 rda eng XA-DE-BW 551.31 DE-101 550 DE-101 Ershadi, M. Reza verfasserin (DE-588)1322590397 (DE-627)1882516443 aut Unveiling the ansiotropy of Antarctic ice across spatial scales using phase coherent radar vorgelegt von Mohammadreza Ershadi Tübingen 2023 1 Online-Ressource (xiv, 110 Seiten) Illustrationen Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Dissertation Eberhard Karls Universität Tübingen 2024 Climate change and the associated rise in temperatures have raised concerns about Antarctica's substantial contribution to sea level rise and climate change. Evaluating this impact involves utilizing ice flow models, where the implementation of ice rheology plays a crucial role in influencing predictions. Ice is an anisotropic material, meaning as ice flows, crystals within it align in response to compression and extension, forming what is known as "ice fabric." Ice fabric properties significantly affect ice flow dynamics. However, many models currently assume isotropic ice behavior, mainly due to limited observational data and the complexity involved in incorporating ice fabric anisotropy into the models. This assumption poses challenges in accurately predicting Antarctica's impact on sea level rise and climate change. To address this issue and improve the precision of ice flow models, it is essential to develop methodologies to enhance the quantity of observational data pertaining to ice fabric properties, which is the main focus of my doctoral research. Ice cores provide reliable ice fabric anisotropy observations but are impractical for expanding spatial coverage.Geophysical methods, including seismic and ultrasonic techniques, show potential. However, recent advancements in phase-coherent radar technology, specifically the phase-sensitive radio echo sounder (pRES radar), coupled with improved processing techniques, offer the most promise in bridging the observational gap in ice fabric properties. My thesis focuses on developing a data processing technique to estimate ice fabric properties from pRES radar measurements and mobilizing the pRES system to increase the quantity of the collected data. The initial phase of my doctoral research involves developing a nonlinear multivariable inverse algorithm, utilizing a matrix-based forward model to simulate radar backscattered signals in an anisotropic medium such as ice. In addition to that, I also developed a technique to approximate the full ice fabric orientation tensor, crucial for parameterizing ice fabric anisotropy in flow models. This method has undergone testing in three separate flow regimes in Antarctica, and the results have been validated through observations from nearby ice cores. Analyzing pRES measurements along a profile on an ice dome has demonstrated that estimated ice fabric anisotropy can reveal the Raymond effect, even when Raymond arches are absent. Although this method resolves ice fabric properties, it is limited by assumptions around initial model parameters, vertical eigenvector, and depth-invariant horizontal ice fabric orientation. The second phase of my research centers on modifying a commercial rover's hardware and software to develop a data acquisition system. The resultant system, named SLEDGE, is a customized ice rover, towing four pRES antennas in a quad-polarimetric setup on two sleds. It employs RTK GPS for precise positioning and drives autonomously to predefined locations and actively triggers the radar system capable of collecting data for profiles spanning several kilometers. A deployment to Antarctica as proof of concept yielded 23 kilometers of quad-polarimetric pRES measurements within 20 operational hours, covering 450 points. While the first deployment was a success, SLEDGE requires additional hardware and software refinement for future field deployment. Overall, the developed inverse approach and SLEDGE, together, show great potential to enhance the spatial coverage of ice fabric properties in the observational data archive—a necessary step towards parameterizing ice fabric anisotropy in ice flow models. (DE-588)4176765-2 (DE-627)105353906 (DE-576)209972866 Radar gnd (DE-588)4013994-3 (DE-627)106341448 (DE-576)208906185 Eis gnd (DE-588)4002073-3 (DE-627)106394541 (DE-576)208845631 Anisotropie gnd (DE-588)4050208-9 (DE-627)106183249 (DE-576)209086173 Roboter gnd (DE-588)4002208-0 (DE-627)106394169 (DE-576)208846158 Antarktis gnd Hochschulschrift (DE-588)4113937-9 (DE-627)105825778 (DE-576)209480580 gnd-content Eberhard Karls Universität Tübingen Grad-verleihende Institution (DE-588)36187-2 (DE-627)100833349 (DE-576)190344806 dgg Tübingen (DE-588)4061147-4 (DE-627)106136933 (DE-576)209138351 uvp Erscheint auch als Druck-Ausgabe Ershadi, M. Reza Unveiling the ansiotropy of Antarctic ice across spatial scales using phase coherent radar Tübingen, 2023 xiv, 110 Seiten (DE-627)1882515412 https://publikationen.uni-tuebingen.de/xmlui/handle/10900/151268/ Verlag kostenfrei Volltext http://hdl.handle.net/10900/151268 Resolving-System kostenfrei Volltext http://dx.doi.org/10.15496/publikation-92608 Resolving-System kostenfrei Volltext http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 Resolving-System kostenfrei Volltext https://nbn-resolving.org/urn:nbn:de:bsz:21-dspace-1512680 Resolving-System kostenfrei https://d-nb.info/1323452494/34 Langzeitarchivierung Nationalbibliothek kostenfrei GBV-ODiss GBV_ILN_20 ISIL_DE-84 SYSFLAG_1 GBV_KXP GBV_ILN_21 ISIL_DE-46 GBV_ILN_22 ISIL_DE-18 GBV_ILN_23 ISIL_DE-830 GBV_ILN_30 ISIL_DE-104 GBV_ILN_40 ISIL_DE-7 GBV_ILN_60 ISIL_DE-705 GBV_ILN_63 ISIL_DE-Wim2 GBV_ILN_70 ISIL_DE-89 GBV_ILN_105 ISIL_DE-841 GBV_ILN_110 ISIL_DE-Luen4 GBV_ILN_132 ISIL_DE-959 GBV_ILN_151 ISIL_DE-546 GBV_ILN_161 ISIL_DE-960 GBV_ILN_293 ISIL_DE-960-3 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2001 ISIL_DE-21 GBV_ILN_2403 ISIL_DE-LFER BO 20 01 0084 450810603X x 08-04-24 21 01 0046 4508122582 z 08-04-24 22 01 0018 4508139345 SUBolrd xu 08-04-24 23 01 0830 4508155308 olr-d x 08-04-24 30 01 0104 4508164765 z 08-04-24 40 01 0007 4508173071 xsn 08-04-24 60 01 0705 4508190057 OLRD z 08-04-24 63 01 3401 4508205909 ORD x 08-04-24 70 01 0089 4508213774 zdo 08-04-24 105 01 0841 4508359795 z 08-04-24 110 01 3110 4508223672 x 08-04-24 132 01 0959 4508234313 OLR-DISS x 08-04-24 151 01 0546 450825019X OLR-ODISS z 08-04-24 161 01 0960 4508256473 ORD z 08-04-24 293 01 3293 450829037X ORD z 08-04-24 370 01 4370 4508299415 x 08-04-24 2001 01 DE-21 4495867830 00 --%%-- --%%-- --%%-- --%%-- Elektronischer Volltext - Zugang über WWW l01 05-03-24 2403 01 DE-LFER 4508429858 00 --%%-- --%%-- n --%%-- l01 08-04-24 20 01 0084 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 21 01 0046 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 22 01 0018 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 23 01 0830 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 30 01 0104 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 40 01 0007 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 60 01 0705 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 63 01 3401 E-Book http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 LF 70 01 0089 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 105 01 0841 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 110 01 3110 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 132 01 0959 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 151 01 0546 Volltext http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 161 01 0960 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 293 01 3293 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 370 01 4370 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 2001 01 DE-21 http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 2403 01 DE-LFER http://dx.doi.org/10.15496/publikation-92608 2403 01 DE-LFER http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512680 2001 01 DE-21 00 s Antarctica 2001 01 DE-21 01 s Phase Coherent Radar 2001 01 DE-21 02 s Rover 2001 01 DE-21 03 s ApRES 2001 01 DE-21 04 s Ice crystals 2001 01 DE-21 05 s Phase coherent radar 2001 01 DE-21 06 s Rover 2001 01 DE-21 07 s ApRES 2001 01 DE-21 08 s Ice crystals 2001 01 DE-21 09 s Antarctica 60 01 0705 10 ho 20 01 0084 OLRD 110 01 3110 OLRD 370 01 4370 OLRD 22 01 0018 SUBolrd 23 01 0830 olr-d 60 01 0705 OLRD 63 01 3401 ORD 132 01 0959 OLR-DISS 151 01 0546 OLR-ODISS 161 01 0960 ORD 293 01 3293 ORD 23 01 0830 2024-04-08 07:43:14
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Reza</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(DE-588)1322590397</subfield><subfield code="0">(DE-627)1882516443</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Unveiling the ansiotropy of Antarctic ice across spatial scales using phase coherent radar</subfield><subfield code="c">vorgelegt von Mohammadreza Ershadi</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Tübingen</subfield><subfield code="c">2023</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (xiv, 110 Seiten)</subfield><subfield code="b">Illustrationen</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="502" ind1=" " ind2=" "><subfield code="b">Dissertation</subfield><subfield code="c">Eberhard Karls Universität Tübingen</subfield><subfield code="d">2024</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Climate change and the associated rise in temperatures have raised concerns about Antarctica's substantial contribution to sea level rise and climate change. Evaluating this impact involves utilizing ice flow models, where the implementation of ice rheology plays a crucial role in influencing predictions. Ice is an anisotropic material, meaning as ice flows, crystals within it align in response to compression and extension, forming what is known as "ice fabric." Ice fabric properties significantly affect ice flow dynamics. However, many models currently assume isotropic ice behavior, mainly due to limited observational data and the complexity involved in incorporating ice fabric anisotropy into the models. This assumption poses challenges in accurately predicting Antarctica's impact on sea level rise and climate change. To address this issue and improve the precision of ice flow models, it is essential to develop methodologies to enhance the quantity of observational data pertaining to ice fabric properties, which is the main focus of my doctoral research. Ice cores provide reliable ice fabric anisotropy observations but are impractical for expanding spatial coverage.Geophysical methods, including seismic and ultrasonic techniques, show potential. However, recent advancements in phase-coherent radar technology, specifically the phase-sensitive radio echo sounder (pRES radar), coupled with improved processing techniques, offer the most promise in bridging the observational gap in ice fabric properties. My thesis focuses on developing a data processing technique to estimate ice fabric properties from pRES radar measurements and mobilizing the pRES system to increase the quantity of the collected data. The initial phase of my doctoral research involves developing a nonlinear multivariable inverse algorithm, utilizing a matrix-based forward model to simulate radar backscattered signals in an anisotropic medium such as ice. In addition to that, I also developed a technique to approximate the full ice fabric orientation tensor, crucial for parameterizing ice fabric anisotropy in flow models. This method has undergone testing in three separate flow regimes in Antarctica, and the results have been validated through observations from nearby ice cores. Analyzing pRES measurements along a profile on an ice dome has demonstrated that estimated ice fabric anisotropy can reveal the Raymond effect, even when Raymond arches are absent. Although this method resolves ice fabric properties, it is limited by assumptions around initial model parameters, vertical eigenvector, and depth-invariant horizontal ice fabric orientation. The second phase of my research centers on modifying a commercial rover's hardware and software to develop a data acquisition system. The resultant system, named SLEDGE, is a customized ice rover, towing four pRES antennas in a quad-polarimetric setup on two sleds. It employs RTK GPS for precise positioning and drives autonomously to predefined locations and actively triggers the radar system capable of collecting data for profiles spanning several kilometers. A deployment to Antarctica as proof of concept yielded 23 kilometers of quad-polarimetric pRES measurements within 20 operational hours, covering 450 points. While the first deployment was a success, SLEDGE requires additional hardware and software refinement for future field deployment. 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title	Unveiling the ansiotropy of Antarctic ice across spatial scales using phase coherent radar
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title_short	Unveiling the ansiotropy of Antarctic ice across spatial scales using phase coherent radar
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GND_str_mv	Ershadi, M. Reza Ershadi, Mohammadreza Radio detecting and ranging Radartechnik Radar Eis Richtungsabhängigkeit Anisotropie Roboter Polargebiet (Süd) Südliches Polargebiet Südpolargebiet Antarktis Hochschulschrift Württembergische Universität Tübingen Königlich Württembergische Eberhard-Karls-Hochschule Accademia (Tübingen) K. Universität Tübingen Academia (Tübingen) Univ. Tübingen Eberhard Karls University Eberhard-Karls-Universität Tuebingen University Königlich Württembergische Eberhard-Karls-Universität K. Eberhard-Karls-Universität Universitet Karla-Ėbercharda Université (Tübingen) Universität Tübingen Accademia Tubingensis Universitas Tubingensis Württembergische Eberhard-Karls-Universität Königliche Universität Tübingen Tjubingenskij universitet Karla-Ėbercharda Tübingen University University of Tuebingen Ernst Bloch Universität Tübingen Königlich Württembergische Universität Tübingen Eberhard-Karls-Hochschule Universitas (Tübingen) Königliche Eberhard-Karls-Universität Academia Tubingensis University of Tubingen Landesuniversität Tübingen Eberhard-Karls-Universität Tübingen University of Tübingen Alma Mater Tubingensis Eberhard Karls Universität Tübingen Tüwingen Tūbingin توبنگن Tūbingan Universitätsstadt Tübingen Tūbīnġin Stadt Tübingen Tubingae Tubinga توبينغن Tjubingen Twingia توبینگن Tūbīnġan Tūbīngin Tübingen
GND_txt_mv	Ershadi, M. Reza Ershadi, Mohammadreza Radio detecting and ranging Radartechnik Radar Eis Richtungsabhängigkeit Anisotropie Roboter Polargebiet (Süd) Südliches Polargebiet Südpolargebiet Antarktis Hochschulschrift Württembergische Universität Tübingen Königlich Württembergische Eberhard-Karls-Hochschule Accademia (Tübingen) K. Universität Tübingen Academia (Tübingen) Univ. Tübingen Eberhard Karls University Eberhard-Karls-Universität Tuebingen University Königlich Württembergische Eberhard-Karls-Universität K. Eberhard-Karls-Universität Universitet Karla-Ėbercharda Université (Tübingen) Universität Tübingen Accademia Tubingensis Universitas Tubingensis Württembergische Eberhard-Karls-Universität Königliche Universität Tübingen Tjubingenskij universitet Karla-Ėbercharda Tübingen University University of Tuebingen Ernst Bloch Universität Tübingen Königlich Württembergische Universität Tübingen Eberhard-Karls-Hochschule Universitas (Tübingen) Königliche Eberhard-Karls-Universität Academia Tubingensis University of Tubingen Landesuniversität Tübingen Eberhard-Karls-Universität Tübingen University of Tübingen Alma Mater Tubingensis Eberhard Karls Universität Tübingen Tüwingen Tūbingin توبنگن Tūbingan Universitätsstadt Tübingen Tūbīnġin Stadt Tübingen Tubingae Tubinga توبينغن Tjubingen Twingia توبینگن Tūbīnġan Tūbīngin Tübingen
GND_txtF_mv	Ershadi, M. Reza Ershadi, Mohammadreza Radio detecting and ranging Radartechnik Radar Eis Richtungsabhängigkeit Anisotropie Roboter Polargebiet (Süd) Südliches Polargebiet Südpolargebiet Antarktis Hochschulschrift Württembergische Universität Tübingen Königlich Württembergische Eberhard-Karls-Hochschule Accademia (Tübingen) K. Universität Tübingen Academia (Tübingen) Univ. Tübingen Eberhard Karls University Eberhard-Karls-Universität Tuebingen University Königlich Württembergische Eberhard-Karls-Universität K. Eberhard-Karls-Universität Universitet Karla-Ėbercharda Université (Tübingen) Universität Tübingen Accademia Tubingensis Universitas Tubingensis Württembergische Eberhard-Karls-Universität Königliche Universität Tübingen Tjubingenskij universitet Karla-Ėbercharda Tübingen University University of Tuebingen Ernst Bloch Universität Tübingen Königlich Württembergische Universität Tübingen Eberhard-Karls-Hochschule Universitas (Tübingen) Königliche Eberhard-Karls-Universität Academia Tubingensis University of Tubingen Landesuniversität Tübingen Eberhard-Karls-Universität Tübingen University of Tübingen Alma Mater Tubingensis Eberhard Karls Universität Tübingen Tüwingen Tūbingin توبنگن Tūbingan Universitätsstadt Tübingen Tūbīnġin Stadt Tübingen Tubingae Tubinga توبينغن Tjubingen Twingia توبینگن Tūbīnġan Tūbīngin Tübingen
doi_str	10.15496/publikation-92608
callnumber-a	--%%--
up_date	2024-07-04T20:58:39.702Z
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Reza</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(DE-588)1322590397</subfield><subfield code="0">(DE-627)1882516443</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Unveiling the ansiotropy of Antarctic ice across spatial scales using phase coherent radar</subfield><subfield code="c">vorgelegt von Mohammadreza Ershadi</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Tübingen</subfield><subfield code="c">2023</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (xiv, 110 Seiten)</subfield><subfield code="b">Illustrationen</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="502" ind1=" " ind2=" "><subfield code="b">Dissertation</subfield><subfield code="c">Eberhard Karls Universität Tübingen</subfield><subfield code="d">2024</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Climate change and the associated rise in temperatures have raised concerns about Antarctica's substantial contribution to sea level rise and climate change. Evaluating this impact involves utilizing ice flow models, where the implementation of ice rheology plays a crucial role in influencing predictions. Ice is an anisotropic material, meaning as ice flows, crystals within it align in response to compression and extension, forming what is known as "ice fabric." Ice fabric properties significantly affect ice flow dynamics. However, many models currently assume isotropic ice behavior, mainly due to limited observational data and the complexity involved in incorporating ice fabric anisotropy into the models. This assumption poses challenges in accurately predicting Antarctica's impact on sea level rise and climate change. To address this issue and improve the precision of ice flow models, it is essential to develop methodologies to enhance the quantity of observational data pertaining to ice fabric properties, which is the main focus of my doctoral research. Ice cores provide reliable ice fabric anisotropy observations but are impractical for expanding spatial coverage.Geophysical methods, including seismic and ultrasonic techniques, show potential. However, recent advancements in phase-coherent radar technology, specifically the phase-sensitive radio echo sounder (pRES radar), coupled with improved processing techniques, offer the most promise in bridging the observational gap in ice fabric properties. My thesis focuses on developing a data processing technique to estimate ice fabric properties from pRES radar measurements and mobilizing the pRES system to increase the quantity of the collected data. The initial phase of my doctoral research involves developing a nonlinear multivariable inverse algorithm, utilizing a matrix-based forward model to simulate radar backscattered signals in an anisotropic medium such as ice. In addition to that, I also developed a technique to approximate the full ice fabric orientation tensor, crucial for parameterizing ice fabric anisotropy in flow models. This method has undergone testing in three separate flow regimes in Antarctica, and the results have been validated through observations from nearby ice cores. Analyzing pRES measurements along a profile on an ice dome has demonstrated that estimated ice fabric anisotropy can reveal the Raymond effect, even when Raymond arches are absent. Although this method resolves ice fabric properties, it is limited by assumptions around initial model parameters, vertical eigenvector, and depth-invariant horizontal ice fabric orientation. The second phase of my research centers on modifying a commercial rover's hardware and software to develop a data acquisition system. The resultant system, named SLEDGE, is a customized ice rover, towing four pRES antennas in a quad-polarimetric setup on two sleds. It employs RTK GPS for precise positioning and drives autonomously to predefined locations and actively triggers the radar system capable of collecting data for profiles spanning several kilometers. A deployment to Antarctica as proof of concept yielded 23 kilometers of quad-polarimetric pRES measurements within 20 operational hours, covering 450 points. While the first deployment was a success, SLEDGE requires additional hardware and software refinement for future field deployment. Overall, the developed inverse approach and SLEDGE, together, show great potential to enhance the spatial coverage of ice fabric properties in the observational data archive—a necessary step towards parameterizing ice fabric anisotropy in ice flow models.</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="0">(DE-588)4176765-2</subfield><subfield code="0">(DE-627)105353906</subfield><subfield code="0">(DE-576)209972866</subfield><subfield code="a">Radar</subfield><subfield code="2">gnd</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="0">(DE-588)4013994-3</subfield><subfield code="0">(DE-627)106341448</subfield><subfield code="0">(DE-576)208906185</subfield><subfield code="a">Eis</subfield><subfield code="2">gnd</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="0">(DE-588)4002073-3</subfield><subfield code="0">(DE-627)106394541</subfield><subfield code="0">(DE-576)208845631</subfield><subfield code="a">Anisotropie</subfield><subfield code="2">gnd</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="0">(DE-588)4050208-9</subfield><subfield code="0">(DE-627)106183249</subfield><subfield code="0">(DE-576)209086173</subfield><subfield code="a">Roboter</subfield><subfield code="2">gnd</subfield></datafield><datafield tag="651" ind1=" " ind2="7"><subfield code="0">(DE-588)4002208-0</subfield><subfield code="0">(DE-627)106394169</subfield><subfield code="0">(DE-576)208846158</subfield><subfield code="a">Antarktis</subfield><subfield code="2">gnd</subfield></datafield><datafield tag="655" ind1=" " ind2="7"><subfield code="a">Hochschulschrift</subfield><subfield code="0">(DE-588)4113937-9</subfield><subfield code="0">(DE-627)105825778</subfield><subfield code="0">(DE-576)209480580</subfield><subfield code="2">gnd-content</subfield></datafield><datafield tag="710" ind1="2" ind2=" "><subfield code="a">Eberhard Karls Universität Tübingen</subfield><subfield code="e">Grad-verleihende Institution</subfield><subfield code="0">(DE-588)36187-2</subfield><subfield code="0">(DE-627)100833349</subfield><subfield code="0">(DE-576)190344806</subfield><subfield code="4">dgg</subfield></datafield><datafield tag="751" ind1=" " ind2=" "><subfield code="a">Tübingen</subfield><subfield code="0">(DE-588)4061147-4</subfield><subfield code="0">(DE-627)106136933</subfield><subfield code="0">(DE-576)209138351</subfield><subfield code="4">uvp</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe</subfield><subfield code="a">Ershadi, M. 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Unveiling the ansiotropy of Antarctic ice across spatial scales using phase coherent radar

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