Sea ice lead fraction for Arctic from AMSR2 data, November 2012 to April 30 2020

Röhrs and Kaleschke (2012) found that thin ice has a unique signature in the emissivity radio in the vertical polarized brightness temperature channels at frequencies between 89.0 GHz and 18.7 GHz in winter. The different sea ice classes especially for water and thin ice are characterized by the emi...

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Main Authors: Li, Ming, Liang, Xi
Format: Dataset
Language:English
Published: PANGAEA 2024
Subjects:
Online Access:https://doi.pangaea.de/10.1594/PANGAEA.967508
https://doi.org/10.1594/PANGAEA.967508
id ftpangaea:oai:pangaea.de:doi:10.1594/PANGAEA.967508
record_format openpolar
spelling ftpangaea:oai:pangaea.de:doi:10.1594/PANGAEA.967508 2024-06-23T07:48:41+00:00 Sea ice lead fraction for Arctic from AMSR2 data, November 2012 to April 30 2020 Li, Ming Liang, Xi MEDIAN LATITUDE: 77.500000 * MEDIAN LONGITUDE: 180.000000 * SOUTH-BOUND LATITUDE: 65.000000 * WEST-BOUND LONGITUDE: 180.000000 * NORTH-BOUND LATITUDE: 90.000000 * EAST-BOUND LONGITUDE: 180.000000 * DATE/TIME START: 2012-11-01T00:00:00 * DATE/TIME END: 2020-04-30T00:00:00 2024 text/tab-separated-values, 1429 data points https://doi.pangaea.de/10.1594/PANGAEA.967508 https://doi.org/10.1594/PANGAEA.967508 en eng PANGAEA Li, Ming; Liu, Jiping; Qu, Meng; Zhang, Zhanhai; Liang, Xi (2022): An Analysis of Arctic Sea Ice Leads Retrieved from AMSR-E/AMSR2. Remote Sensing, 14(4), 969, https://doi.org/10.3390/rs14040969 Röhrs, J; Kaleschke, Lars (2012): An algorithm to detect sea ice leads by using AMSR-E passive microwave imagery. The Cryosphere, 6(2), 343-352, https://doi.org/10.5194/tc-6-343-2012 https://doi.pangaea.de/10.1594/PANGAEA.967508 https://doi.org/10.1594/PANGAEA.967508 CC-BY-4.0: Creative Commons Attribution 4.0 International Access constraints: unrestricted info:eu-repo/semantics/openAccess AMSR2 Arctic DATE/TIME lead fraction netCDF file netCDF file (File Size) Satellite imagery SATI Sea ice Dataset 2024 ftpangaea https://doi.org/10.1594/PANGAEA.96750810.3390/rs1404096910.5194/tc-6-343-2012 2024-06-04T23:51:55Z Röhrs and Kaleschke (2012) found that thin ice has a unique signature in the emissivity radio in the vertical polarized brightness temperature channels at frequencies between 89.0 GHz and 18.7 GHz in winter. The different sea ice classes especially for water and thin ice are characterized by the emissivity ratios above one. Following the proposed algorithm, we derive sea ice lead fraction from the AMSR2 brightness temperature data for the freezing season (November-April) north of 65°S. The spatial resolution of the data is 6.25 km. The steps are as follows. Firstly, the AMSR2 L1B brightness temperatures at frequencies of 18.7 GHz (TB,18.7V) and 89.0 GHz (TB,89V) are interpolated onto the NSIDC EASE grid with a spatial resolution of 6.25 km. Secondly, the brightness temperature radio r=TB,89V/TB,18.7V is calculated. Thirdly, a mean filter is used to enhance the signal of the leads. Finally, lead fraction which is defined as the area fraction of thin ice compared to other ice classes is computed. The proposed algorithm exhibits advanced ability in detecting sea ice leads in pack ice zone. It can detects leads wider than 3 km and resolves about 50% of the lead area compared to MODIS satellite images. File descriptions Period and temporal resolution: November 1, 2012, to April 30, 2020; Daily for freezing season: November 1 to April 30 Coverage and spatial resolution: Arctic north of 65°N Spatial resolution: 6.25 km x 6.25 km, NSIDC EASE grid. Geographic longitude: -180°E to 180°E Geographic latitude: from 65°N to 90°N Dimension: 1792 rows x 1216 column Format: NetCDF Dataset Arctic Arctic Sea ice The Cryosphere PANGAEA - Data Publisher for Earth & Environmental Science Arctic ENVELOPE(180.000000,180.000000,90.000000,65.000000)
institution Open Polar
collection PANGAEA - Data Publisher for Earth & Environmental Science
op_collection_id ftpangaea
language English
topic AMSR2
Arctic
DATE/TIME
lead fraction
netCDF file
netCDF file (File Size)
Satellite imagery
SATI
Sea ice
spellingShingle AMSR2
Arctic
DATE/TIME
lead fraction
netCDF file
netCDF file (File Size)
Satellite imagery
SATI
Sea ice
Li, Ming
Liang, Xi
Sea ice lead fraction for Arctic from AMSR2 data, November 2012 to April 30 2020
topic_facet AMSR2
Arctic
DATE/TIME
lead fraction
netCDF file
netCDF file (File Size)
Satellite imagery
SATI
Sea ice
description Röhrs and Kaleschke (2012) found that thin ice has a unique signature in the emissivity radio in the vertical polarized brightness temperature channels at frequencies between 89.0 GHz and 18.7 GHz in winter. The different sea ice classes especially for water and thin ice are characterized by the emissivity ratios above one. Following the proposed algorithm, we derive sea ice lead fraction from the AMSR2 brightness temperature data for the freezing season (November-April) north of 65°S. The spatial resolution of the data is 6.25 km. The steps are as follows. Firstly, the AMSR2 L1B brightness temperatures at frequencies of 18.7 GHz (TB,18.7V) and 89.0 GHz (TB,89V) are interpolated onto the NSIDC EASE grid with a spatial resolution of 6.25 km. Secondly, the brightness temperature radio r=TB,89V/TB,18.7V is calculated. Thirdly, a mean filter is used to enhance the signal of the leads. Finally, lead fraction which is defined as the area fraction of thin ice compared to other ice classes is computed. The proposed algorithm exhibits advanced ability in detecting sea ice leads in pack ice zone. It can detects leads wider than 3 km and resolves about 50% of the lead area compared to MODIS satellite images. File descriptions Period and temporal resolution: November 1, 2012, to April 30, 2020; Daily for freezing season: November 1 to April 30 Coverage and spatial resolution: Arctic north of 65°N Spatial resolution: 6.25 km x 6.25 km, NSIDC EASE grid. Geographic longitude: -180°E to 180°E Geographic latitude: from 65°N to 90°N Dimension: 1792 rows x 1216 column Format: NetCDF
format Dataset
author Li, Ming
Liang, Xi
author_facet Li, Ming
Liang, Xi
author_sort Li, Ming
title Sea ice lead fraction for Arctic from AMSR2 data, November 2012 to April 30 2020
title_short Sea ice lead fraction for Arctic from AMSR2 data, November 2012 to April 30 2020
title_full Sea ice lead fraction for Arctic from AMSR2 data, November 2012 to April 30 2020
title_fullStr Sea ice lead fraction for Arctic from AMSR2 data, November 2012 to April 30 2020
title_full_unstemmed Sea ice lead fraction for Arctic from AMSR2 data, November 2012 to April 30 2020
title_sort sea ice lead fraction for arctic from amsr2 data, november 2012 to april 30 2020
publisher PANGAEA
publishDate 2024
url https://doi.pangaea.de/10.1594/PANGAEA.967508
https://doi.org/10.1594/PANGAEA.967508
op_coverage MEDIAN LATITUDE: 77.500000 * MEDIAN LONGITUDE: 180.000000 * SOUTH-BOUND LATITUDE: 65.000000 * WEST-BOUND LONGITUDE: 180.000000 * NORTH-BOUND LATITUDE: 90.000000 * EAST-BOUND LONGITUDE: 180.000000 * DATE/TIME START: 2012-11-01T00:00:00 * DATE/TIME END: 2020-04-30T00:00:00
long_lat ENVELOPE(180.000000,180.000000,90.000000,65.000000)
geographic Arctic
geographic_facet Arctic
genre Arctic
Arctic
Sea ice
The Cryosphere
genre_facet Arctic
Arctic
Sea ice
The Cryosphere
op_relation Li, Ming; Liu, Jiping; Qu, Meng; Zhang, Zhanhai; Liang, Xi (2022): An Analysis of Arctic Sea Ice Leads Retrieved from AMSR-E/AMSR2. Remote Sensing, 14(4), 969, https://doi.org/10.3390/rs14040969
Röhrs, J; Kaleschke, Lars (2012): An algorithm to detect sea ice leads by using AMSR-E passive microwave imagery. The Cryosphere, 6(2), 343-352, https://doi.org/10.5194/tc-6-343-2012
https://doi.pangaea.de/10.1594/PANGAEA.967508
https://doi.org/10.1594/PANGAEA.967508
op_rights CC-BY-4.0: Creative Commons Attribution 4.0 International
Access constraints: unrestricted
info:eu-repo/semantics/openAccess
op_doi https://doi.org/10.1594/PANGAEA.96750810.3390/rs1404096910.5194/tc-6-343-2012
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