國立虎尾科技大學 |

Using ICESat-2 Satellite Altimeter Data to Improve Understanding of Thermodynamic and Dynamic Sea Ice Characteristics in the Ross Sea.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Using ICESat-2 Satellite Altimeter Data to Improve Understanding of Thermodynamic and Dynamic Sea Ice Characteristics in the Ross Sea./
Author:	Koo, Younghyun.
Description:	1 online resource (202 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 84-11, Section: B.
Contained By:	Dissertations Abstracts International84-11B.
Subject:	Remote sensing. -
Online resource:	click for full text (PQDT)
ISBN:	9798379580254

Using ICESat-2 Satellite Altimeter Data to Improve Understanding of Thermodynamic and Dynamic Sea Ice Characteristics in the Ross Sea.
Koo, Younghyun.

Using ICESat-2 Satellite Altimeter Data to Improve Understanding of Thermodynamic and Dynamic Sea Ice Characteristics in the Ross Sea. - 1 online resource (202 pages)

Source: Dissertations Abstracts International, Volume: 84-11, Section: B.

Thesis (Ph.D.)--The University of Texas at San Antonio, 2023.

Includes bibliographical references

The fine spatial resolution (~11 m of footprint) and precision (~2 cm of vertical precision) of NASA's ICESat-2 (IS2) satellite altimeter data allow us to detect sea ice deformation features, such as pressure ridges and leads. Moreover, the thermodynamic and dynamic sea ice processes can be investigated by monitoring sea ice deformation features for a large area over a regular period. However, the IS2 sea ice products (ATL07/ATL10) have critical problems in further accurate monitoring of sea ice: (1) spatial sparsity, (2) dark lead misclassification, and (3) incapability of thin/gray ice detection. In this study, I address these issues and improve the monitoring of sea ice freeboard in the Ross Sea using IS2 data. In Chapter 2, a geostatistical approach, kriging, is employed to address the spatial sparsity issue and interpolate the freeboard values where the IS2 tracks are not directly available. The freeboard maps retrieved from the kriging method exhibit the weekly distribution of sea ice freeboard and persistent polynya areas in the Ross Sea. In Chapter 3, instead of the original ATL07 decision tree algorithm, a data-driven neural network (NN) model is used to classify sea ice surface into open water, thin/gray ice, and snow-covered/thick ice. The NN approach shows a better performance in delineating the sea ice surface than the original ATL07 product, especially the separation of thin ice covers. In Chapter 4, the ability of IS2 to capture the thermodynamic and dynamic ice growth is assessed using in-situ sea ice mass balance array (SIMBA) buoys deployed in the central Arctic. The modal freeboard of the IS2 measurement agrees with the thermodynamic ice growth, but the mean and median IS2 freeboard involve the redistribution of sea ice thickness induced by sea ice deformation. Finally, in Chapter 5, taking advantage of IS2 data for monitoring dynamic sea ice processes, the spatiotemporal variations of pressure ridges in the Ross Sea are investigated. The southeast sector of the Ross Sea is highly deformed by a strong easterly wind and thick ice inflow in 2019-2020, but the transition in the atmospheric condition in 2021-2022 affects the distribution of deformation features. This result emphasizes the importance of atmospheric forcings on the thermodynamic and dynamic sea ice conditions in the Ross Sea.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798379580254Subjects--Topical Terms:

557272
Remote sensing.
Subjects--Index Terms:

Katabatic windsIndex Terms--Genre/Form:

554714
Electronic books.

Using ICESat-2 Satellite Altimeter Data to Improve Understanding of Thermodynamic and Dynamic Sea Ice Characteristics in the Ross Sea.
LDR:03824ntm a22004217 4500 001 1144802
005 20240611104922.5
006 m o d
007 cr mn ---uuuuu
008 250605s2023 xx obm 000 0 eng d
020 $a 9798379580254
035 $a (MiAaPQ)AAI30419136
035 $a AAI30419136
040 $a MiAaPQ $b eng $c MiAaPQ $d NTU
100 1 $a Koo, Younghyun. $3 1469950
245 1 0 $a Using ICESat-2 Satellite Altimeter Data to Improve Understanding of Thermodynamic and Dynamic Sea Ice Characteristics in the Ross Sea.
264 0 $c 2023
300 $a 1 online resource (202 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertations Abstracts International, Volume: 84-11, Section: B.
500 $a Advisor: Xie, Hongjie.
502 $a Thesis (Ph.D.)--The University of Texas at San Antonio, 2023.
504 $a Includes bibliographical references
520 $a The fine spatial resolution (~11 m of footprint) and precision (~2 cm of vertical precision) of NASA's ICESat-2 (IS2) satellite altimeter data allow us to detect sea ice deformation features, such as pressure ridges and leads. Moreover, the thermodynamic and dynamic sea ice processes can be investigated by monitoring sea ice deformation features for a large area over a regular period. However, the IS2 sea ice products (ATL07/ATL10) have critical problems in further accurate monitoring of sea ice: (1) spatial sparsity, (2) dark lead misclassification, and (3) incapability of thin/gray ice detection. In this study, I address these issues and improve the monitoring of sea ice freeboard in the Ross Sea using IS2 data. In Chapter 2, a geostatistical approach, kriging, is employed to address the spatial sparsity issue and interpolate the freeboard values where the IS2 tracks are not directly available. The freeboard maps retrieved from the kriging method exhibit the weekly distribution of sea ice freeboard and persistent polynya areas in the Ross Sea. In Chapter 3, instead of the original ATL07 decision tree algorithm, a data-driven neural network (NN) model is used to classify sea ice surface into open water, thin/gray ice, and snow-covered/thick ice. The NN approach shows a better performance in delineating the sea ice surface than the original ATL07 product, especially the separation of thin ice covers. In Chapter 4, the ability of IS2 to capture the thermodynamic and dynamic ice growth is assessed using in-situ sea ice mass balance array (SIMBA) buoys deployed in the central Arctic. The modal freeboard of the IS2 measurement agrees with the thermodynamic ice growth, but the mean and median IS2 freeboard involve the redistribution of sea ice thickness induced by sea ice deformation. Finally, in Chapter 5, taking advantage of IS2 data for monitoring dynamic sea ice processes, the spatiotemporal variations of pressure ridges in the Ross Sea are investigated. The southeast sector of the Ross Sea is highly deformed by a strong easterly wind and thick ice inflow in 2019-2020, but the transition in the atmospheric condition in 2021-2022 affects the distribution of deformation features. This result emphasizes the importance of atmospheric forcings on the thermodynamic and dynamic sea ice conditions in the Ross Sea.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2024
538 $a Mode of access: World Wide Web
650 4 $a Remote sensing. $3 557272
650 4 $a Climate change. $2 bicssc $3 1009004
650 4 $a Geographic information science. $3 1372545
650 4 $a Aerospace engineering. $3 686400
653 $a Katabatic winds
653 $a Polynyas
653 $a Pressure ridges
653 $a Sea ice leads
653 $a Southern Ocean
653 $a Ross Sea
655 7 $a Electronic books. $2 local $3 554714
690 $a 0799
690 $a 0404
690 $a 0370
690 $a 0538
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a The University of Texas at San Antonio. $b Civil & Environmental Engineering. $3 1465582
773 0 $t Dissertations Abstracts International $g 84-11B.
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30419136 $z click for full text (PQDT)