Spatio-temporal variability of Antarctic sea-ice thickness and volume obtained from ICESat data using an innovative algorithm

We use total (sea ice plus snow) freeboard as estimated from Ice, Cloud and land Elevation Satellite (ICESat) Geophysical Laser Altimeter System (GLAS) observations to compute Antarctic sea-ice thickness and volume. In order to overcome assumptions made about the relationship between snow depth and...

Full description

Bibliographic Details
Published in:Remote Sensing of Environment
Main Authors: Li, H., Xie, H., Kern, S., Wan, W., Ozsoy, B., Ackley , S., Hong, Y.
Format: Article in Journal/Newspaper
Language:English
Published: 2018
Subjects:
Online Access:http://hdl.handle.net/21.11116/0000-0002-7718-E
id ftpubman:oai:pure.mpg.de:item_3008199
record_format openpolar
spelling ftpubman:oai:pure.mpg.de:item_3008199 2023-08-20T04:02:30+02:00 Spatio-temporal variability of Antarctic sea-ice thickness and volume obtained from ICESat data using an innovative algorithm Li, H. Xie, H. Kern, S. Wan, W. Ozsoy, B. Ackley , S. Hong, Y. 2018-12-15 http://hdl.handle.net/21.11116/0000-0002-7718-E eng eng info:eu-repo/semantics/altIdentifier/doi/10.1016/j.rse.2018.09.031 http://hdl.handle.net/21.11116/0000-0002-7718-E Remote Sensing of Environment info:eu-repo/semantics/article 2018 ftpubman https://doi.org/10.1016/j.rse.2018.09.031 2023-08-01T23:44:37Z We use total (sea ice plus snow) freeboard as estimated from Ice, Cloud and land Elevation Satellite (ICESat) Geophysical Laser Altimeter System (GLAS) observations to compute Antarctic sea-ice thickness and volume. In order to overcome assumptions made about the relationship between snow depth and total freeboard or biases in snow depth products from satellite microwave radiometry, we implement a new algorithm. We treat the sea ice-snow system as one layer with reduced density, which we approximate by means of a priori information about the snow depth to sea-ice thickness ratio. We derive this a priori information directly from ICESat total freeboard data using empirical equations relating in-situ measurements of total freeboard to snow depth or sea-ice thickness. We apply our new algorithm (one-layer method or OLM), which uses the buoyancy equation approach without the need for auxiliary snow depth data, to compute sea-ice thickness for every ICESat GLAS footprint from a valid total freeboard. An improved method for sea-ice volume retrieval is also used to derive ice volume at 6.25 km scale. Spatio-temporal variations of sea-ice thickness and volume are then analyzed in the circumpolar Antarctic as well as its six sea sectors: Pacific Ocean, Indian Ocean, Weddell East, Weddell West, Bell-Amund Sea, and Ross Sea, under both interannual and seasonal scales. Because the OLM algorithm relies on only one parameter, the total freeboard, and is independent of auxiliary snow depth information, it is believed to become a viable alternative sea-ice thickness retrieval method for satellite altimetry. Article in Journal/Newspaper Antarc* Antarctic Ross Sea Sea ice Max Planck Society: MPG.PuRe Antarctic Indian Pacific Ross Sea Weddell Remote Sensing of Environment 219 44 61
institution Open Polar
collection Max Planck Society: MPG.PuRe
op_collection_id ftpubman
language English
description We use total (sea ice plus snow) freeboard as estimated from Ice, Cloud and land Elevation Satellite (ICESat) Geophysical Laser Altimeter System (GLAS) observations to compute Antarctic sea-ice thickness and volume. In order to overcome assumptions made about the relationship between snow depth and total freeboard or biases in snow depth products from satellite microwave radiometry, we implement a new algorithm. We treat the sea ice-snow system as one layer with reduced density, which we approximate by means of a priori information about the snow depth to sea-ice thickness ratio. We derive this a priori information directly from ICESat total freeboard data using empirical equations relating in-situ measurements of total freeboard to snow depth or sea-ice thickness. We apply our new algorithm (one-layer method or OLM), which uses the buoyancy equation approach without the need for auxiliary snow depth data, to compute sea-ice thickness for every ICESat GLAS footprint from a valid total freeboard. An improved method for sea-ice volume retrieval is also used to derive ice volume at 6.25 km scale. Spatio-temporal variations of sea-ice thickness and volume are then analyzed in the circumpolar Antarctic as well as its six sea sectors: Pacific Ocean, Indian Ocean, Weddell East, Weddell West, Bell-Amund Sea, and Ross Sea, under both interannual and seasonal scales. Because the OLM algorithm relies on only one parameter, the total freeboard, and is independent of auxiliary snow depth information, it is believed to become a viable alternative sea-ice thickness retrieval method for satellite altimetry.
format Article in Journal/Newspaper
author Li, H.
Xie, H.
Kern, S.
Wan, W.
Ozsoy, B.
Ackley , S.
Hong, Y.
spellingShingle Li, H.
Xie, H.
Kern, S.
Wan, W.
Ozsoy, B.
Ackley , S.
Hong, Y.
Spatio-temporal variability of Antarctic sea-ice thickness and volume obtained from ICESat data using an innovative algorithm
author_facet Li, H.
Xie, H.
Kern, S.
Wan, W.
Ozsoy, B.
Ackley , S.
Hong, Y.
author_sort Li, H.
title Spatio-temporal variability of Antarctic sea-ice thickness and volume obtained from ICESat data using an innovative algorithm
title_short Spatio-temporal variability of Antarctic sea-ice thickness and volume obtained from ICESat data using an innovative algorithm
title_full Spatio-temporal variability of Antarctic sea-ice thickness and volume obtained from ICESat data using an innovative algorithm
title_fullStr Spatio-temporal variability of Antarctic sea-ice thickness and volume obtained from ICESat data using an innovative algorithm
title_full_unstemmed Spatio-temporal variability of Antarctic sea-ice thickness and volume obtained from ICESat data using an innovative algorithm
title_sort spatio-temporal variability of antarctic sea-ice thickness and volume obtained from icesat data using an innovative algorithm
publishDate 2018
url http://hdl.handle.net/21.11116/0000-0002-7718-E
geographic Antarctic
Indian
Pacific
Ross Sea
Weddell
geographic_facet Antarctic
Indian
Pacific
Ross Sea
Weddell
genre Antarc*
Antarctic
Ross Sea
Sea ice
genre_facet Antarc*
Antarctic
Ross Sea
Sea ice
op_source Remote Sensing of Environment
op_relation info:eu-repo/semantics/altIdentifier/doi/10.1016/j.rse.2018.09.031
http://hdl.handle.net/21.11116/0000-0002-7718-E
op_doi https://doi.org/10.1016/j.rse.2018.09.031
container_title Remote Sensing of Environment
container_volume 219
container_start_page 44
op_container_end_page 61
_version_ 1774712971866406912