Retrieval of wintertime snow depth on Arctic sea ice and analysis of long-term variability using satellite passive measurements

학위논문(박사) -- 서울대학교대학원 : 자연과학대학 지구환경과학부, 2021.8. 손병주. A new satellite retrieval algorithm for wintertime snow depth on Arctic sea ice was developed based on the hydrostatic balance and thermodynamic steady-state of a snow-ice system. In this algorithm, snow depth is estimated from the passive infrared...

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Main Author: 시호연
Other Authors: 손병주, Hoyeon Shi, 자연과학대학 지구환경과학부
Format: Doctoral or Postdoctoral Thesis
Language:English
Published: 서울대학교 대학원 2021
Subjects:
550
Online Access:https://hdl.handle.net/10371/178927
https://dcollection.snu.ac.kr/common/orgView/000000167918
id ftseoulnuniv:oai:s-space.snu.ac.kr:10371/178927
record_format openpolar
spelling ftseoulnuniv:oai:s-space.snu.ac.kr:10371/178927 2023-05-15T14:29:22+02:00 Retrieval of wintertime snow depth on Arctic sea ice and analysis of long-term variability using satellite passive measurements 인공위성 수동 관측자료를 활용한 겨울철 북극 해빙지역 적설깊이 산출 및 장기변동성 분석 시호연 손병주 Hoyeon Shi 자연과학대학 지구환경과학부 2021 ix, 121 https://hdl.handle.net/10371/178927 https://dcollection.snu.ac.kr/common/orgView/000000167918 eng eng 서울대학교 대학원 000000167918 https://hdl.handle.net/10371/178927 https://dcollection.snu.ac.kr/common/orgView/000000167918 I804:11032-000000167918 000000000046▲000000000053▲000000167918▲ Snow depth Arctic sea ice Satellite Remote Sensing Climate Change 적설깊이 북극 해빙 인공위성 원격탐사 기후변화 550 Thesis Dissertation 2021 ftseoulnuniv 2023-02-10T02:30:28Z 학위논문(박사) -- 서울대학교대학원 : 자연과학대학 지구환경과학부, 2021.8. 손병주. A new satellite retrieval algorithm for wintertime snow depth on Arctic sea ice was developed based on the hydrostatic balance and thermodynamic steady-state of a snow-ice system. In this algorithm, snow depth is estimated from the passive infrared and microwave measurements, with the use of sea ice freeboard, snow surface temperature, and snow-ice interface temperature as inputs. The algorithm was validated against NASA's Operation IceBridge (OIB) measurements, and results indicate that the snow depth on the Arctic sea ice can be estimated with a high level of accuracy. To produce a long-term snow depth record in the Arctic basin-scale, sea ice freeboard was estimated from the satellite passive microwave (PMW) measurements. To do so, the snow-ice scattering optical depth from satellite PMW measurements was used as a predictor for the estimation of the total freeboard. Estimated PMW total freeboards were found to be in good agreement with OIB total freeboards. The wintertime snow depth records for the 2003-2020 period were produced by combining the PMW freeboard and satellite-derived temperatures. It was found that snow depth is highly dependent on sea ice type, likely due to the snow accumulation timing and period. The snow depth and its variability were greater on multiyear ice than on first-year ice. Besides, a significant reduction in mean snow depth was found, compared to the snow depth climatology for the 1954-1991 period. Regarding the temporal variations over the 2003-2020 period, regionally different snow depth trends are found; negative and positive snow depth trends were noted over the eastern and western parts of the Arctic Ocean, respectively. It is thought that the negative trends are related to sea ice type transition and delayed freeze onset, while the positive trends are related to increased precipitation amount. 겨울철 북극 해빙지역 적설깊이 산출을 위해 적설-해빙 시스템의 정역학적 평형 및 열역학적 정상상태(steady state)를 기반으로 한 새로운 인공위성 산출 알고리즘이 개발되었다. 개발된 알고리즘은 수동 마이크로파/적외선 ... Doctoral or Postdoctoral Thesis Arctic Basin Arctic Arctic Ocean Climate change Sea ice Seoul National University: S-Space Arctic Arctic Ocean
institution Open Polar
collection Seoul National University: S-Space
op_collection_id ftseoulnuniv
language English
topic Snow depth
Arctic sea ice
Satellite Remote Sensing
Climate Change
적설깊이
북극 해빙
인공위성 원격탐사
기후변화
550
spellingShingle Snow depth
Arctic sea ice
Satellite Remote Sensing
Climate Change
적설깊이
북극 해빙
인공위성 원격탐사
기후변화
550
시호연
Retrieval of wintertime snow depth on Arctic sea ice and analysis of long-term variability using satellite passive measurements
topic_facet Snow depth
Arctic sea ice
Satellite Remote Sensing
Climate Change
적설깊이
북극 해빙
인공위성 원격탐사
기후변화
550
description 학위논문(박사) -- 서울대학교대학원 : 자연과학대학 지구환경과학부, 2021.8. 손병주. A new satellite retrieval algorithm for wintertime snow depth on Arctic sea ice was developed based on the hydrostatic balance and thermodynamic steady-state of a snow-ice system. In this algorithm, snow depth is estimated from the passive infrared and microwave measurements, with the use of sea ice freeboard, snow surface temperature, and snow-ice interface temperature as inputs. The algorithm was validated against NASA's Operation IceBridge (OIB) measurements, and results indicate that the snow depth on the Arctic sea ice can be estimated with a high level of accuracy. To produce a long-term snow depth record in the Arctic basin-scale, sea ice freeboard was estimated from the satellite passive microwave (PMW) measurements. To do so, the snow-ice scattering optical depth from satellite PMW measurements was used as a predictor for the estimation of the total freeboard. Estimated PMW total freeboards were found to be in good agreement with OIB total freeboards. The wintertime snow depth records for the 2003-2020 period were produced by combining the PMW freeboard and satellite-derived temperatures. It was found that snow depth is highly dependent on sea ice type, likely due to the snow accumulation timing and period. The snow depth and its variability were greater on multiyear ice than on first-year ice. Besides, a significant reduction in mean snow depth was found, compared to the snow depth climatology for the 1954-1991 period. Regarding the temporal variations over the 2003-2020 period, regionally different snow depth trends are found; negative and positive snow depth trends were noted over the eastern and western parts of the Arctic Ocean, respectively. It is thought that the negative trends are related to sea ice type transition and delayed freeze onset, while the positive trends are related to increased precipitation amount. 겨울철 북극 해빙지역 적설깊이 산출을 위해 적설-해빙 시스템의 정역학적 평형 및 열역학적 정상상태(steady state)를 기반으로 한 새로운 인공위성 산출 알고리즘이 개발되었다. 개발된 알고리즘은 수동 마이크로파/적외선 ...
author2 손병주
Hoyeon Shi
자연과학대학 지구환경과학부
format Doctoral or Postdoctoral Thesis
author 시호연
author_facet 시호연
author_sort 시호연
title Retrieval of wintertime snow depth on Arctic sea ice and analysis of long-term variability using satellite passive measurements
title_short Retrieval of wintertime snow depth on Arctic sea ice and analysis of long-term variability using satellite passive measurements
title_full Retrieval of wintertime snow depth on Arctic sea ice and analysis of long-term variability using satellite passive measurements
title_fullStr Retrieval of wintertime snow depth on Arctic sea ice and analysis of long-term variability using satellite passive measurements
title_full_unstemmed Retrieval of wintertime snow depth on Arctic sea ice and analysis of long-term variability using satellite passive measurements
title_sort retrieval of wintertime snow depth on arctic sea ice and analysis of long-term variability using satellite passive measurements
publisher 서울대학교 대학원
publishDate 2021
url https://hdl.handle.net/10371/178927
https://dcollection.snu.ac.kr/common/orgView/000000167918
geographic Arctic
Arctic Ocean
geographic_facet Arctic
Arctic Ocean
genre Arctic Basin
Arctic
Arctic Ocean
Climate change
Sea ice
genre_facet Arctic Basin
Arctic
Arctic Ocean
Climate change
Sea ice
op_relation 000000167918
https://hdl.handle.net/10371/178927
https://dcollection.snu.ac.kr/common/orgView/000000167918
I804:11032-000000167918
000000000046▲000000000053▲000000167918▲
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