Estimating Meltwater Drainage Onset Timing and Duration of Landfast Ice in the Canadian Arctic Archipelago Using AMSR-E Passive Microwave Data

Meltwater drainage onset (DO) timing and drainage duration (DD) related to snowmelt-water redistribution are both important for understanding not only the Arctic energy and heat budgets but also the salt/heat balance of the mixed layer in the ocean and sea-ice ecosystem. We present DO and DD as dete...

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Published in:Remote Sensing
Main Author: Yasuhiro Tanaka
Format: Text
Language:English
Published: Multidisciplinary Digital Publishing Institute 2020
Subjects:
Online Access:https://doi.org/10.3390/rs12061033
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spelling ftmdpi:oai:mdpi.com:/2072-4292/12/6/1033/ 2023-08-20T03:59:18+02:00 Estimating Meltwater Drainage Onset Timing and Duration of Landfast Ice in the Canadian Arctic Archipelago Using AMSR-E Passive Microwave Data Yasuhiro Tanaka 2020-03-23 application/pdf https://doi.org/10.3390/rs12061033 EN eng Multidisciplinary Digital Publishing Institute Engineering Remote Sensing https://dx.doi.org/10.3390/rs12061033 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 12; Issue 6; Pages: 1033 sea ice melt pond landfast ice meltwater drainage arctic passive microwave AMSR-E Text 2020 ftmdpi https://doi.org/10.3390/rs12061033 2023-07-31T23:16:39Z Meltwater drainage onset (DO) timing and drainage duration (DD) related to snowmelt-water redistribution are both important for understanding not only the Arctic energy and heat budgets but also the salt/heat balance of the mixed layer in the ocean and sea-ice ecosystem. We present DO and DD as determined from the time series of Advanced Microwave Scanning Radiometer-Earth observing system (AMSR-E) melt pond fraction (MPF) estimates in an area with Canadian landfast ice. To address the lack of evaluation on a day-by-day basis for the AMSR-E MPF estimate, we first compared AMSR-E MPF with the daily Medium Resolution Imaging Spectrometer (MERIS) MPF. The AMSR-E MPF estimate correlates significantly with the MERIS MPF (r = 0.73–0.83). The estimate has a product quality similar to the MERIS MPF only when the albedo is around 0.5–0.7 and a positive bias of up to 10% in areas with an albedo of 0.7–0.9, including melting snow. The DO/DD estimates are determined by using a polynomial regression curve fitted on the time series of the AMSR-E MPF. The DOs/DDs from time series of the AMSR-E and MERIS MPFs are compared, revealing consistency in both DD and DO. The DO timing from 2006 to 2011 is correlated with melt onset timing. To the best of our knowledge, our study provides the first large-scale information on both DO timing and DD. Text albedo Arctic Archipelago Arctic Canadian Arctic Archipelago Sea ice MDPI Open Access Publishing Arctic Canadian Arctic Archipelago Remote Sensing 12 6 1033
institution Open Polar
collection MDPI Open Access Publishing
op_collection_id ftmdpi
language English
topic sea ice
melt pond
landfast ice
meltwater drainage
arctic
passive microwave
AMSR-E
spellingShingle sea ice
melt pond
landfast ice
meltwater drainage
arctic
passive microwave
AMSR-E
Yasuhiro Tanaka
Estimating Meltwater Drainage Onset Timing and Duration of Landfast Ice in the Canadian Arctic Archipelago Using AMSR-E Passive Microwave Data
topic_facet sea ice
melt pond
landfast ice
meltwater drainage
arctic
passive microwave
AMSR-E
description Meltwater drainage onset (DO) timing and drainage duration (DD) related to snowmelt-water redistribution are both important for understanding not only the Arctic energy and heat budgets but also the salt/heat balance of the mixed layer in the ocean and sea-ice ecosystem. We present DO and DD as determined from the time series of Advanced Microwave Scanning Radiometer-Earth observing system (AMSR-E) melt pond fraction (MPF) estimates in an area with Canadian landfast ice. To address the lack of evaluation on a day-by-day basis for the AMSR-E MPF estimate, we first compared AMSR-E MPF with the daily Medium Resolution Imaging Spectrometer (MERIS) MPF. The AMSR-E MPF estimate correlates significantly with the MERIS MPF (r = 0.73–0.83). The estimate has a product quality similar to the MERIS MPF only when the albedo is around 0.5–0.7 and a positive bias of up to 10% in areas with an albedo of 0.7–0.9, including melting snow. The DO/DD estimates are determined by using a polynomial regression curve fitted on the time series of the AMSR-E MPF. The DOs/DDs from time series of the AMSR-E and MERIS MPFs are compared, revealing consistency in both DD and DO. The DO timing from 2006 to 2011 is correlated with melt onset timing. To the best of our knowledge, our study provides the first large-scale information on both DO timing and DD.
format Text
author Yasuhiro Tanaka
author_facet Yasuhiro Tanaka
author_sort Yasuhiro Tanaka
title Estimating Meltwater Drainage Onset Timing and Duration of Landfast Ice in the Canadian Arctic Archipelago Using AMSR-E Passive Microwave Data
title_short Estimating Meltwater Drainage Onset Timing and Duration of Landfast Ice in the Canadian Arctic Archipelago Using AMSR-E Passive Microwave Data
title_full Estimating Meltwater Drainage Onset Timing and Duration of Landfast Ice in the Canadian Arctic Archipelago Using AMSR-E Passive Microwave Data
title_fullStr Estimating Meltwater Drainage Onset Timing and Duration of Landfast Ice in the Canadian Arctic Archipelago Using AMSR-E Passive Microwave Data
title_full_unstemmed Estimating Meltwater Drainage Onset Timing and Duration of Landfast Ice in the Canadian Arctic Archipelago Using AMSR-E Passive Microwave Data
title_sort estimating meltwater drainage onset timing and duration of landfast ice in the canadian arctic archipelago using amsr-e passive microwave data
publisher Multidisciplinary Digital Publishing Institute
publishDate 2020
url https://doi.org/10.3390/rs12061033
geographic Arctic
Canadian Arctic Archipelago
geographic_facet Arctic
Canadian Arctic Archipelago
genre albedo
Arctic Archipelago
Arctic
Canadian Arctic Archipelago
Sea ice
genre_facet albedo
Arctic Archipelago
Arctic
Canadian Arctic Archipelago
Sea ice
op_source Remote Sensing; Volume 12; Issue 6; Pages: 1033
op_relation Engineering Remote Sensing
https://dx.doi.org/10.3390/rs12061033
op_rights https://creativecommons.org/licenses/by/4.0/
op_doi https://doi.org/10.3390/rs12061033
container_title Remote Sensing
container_volume 12
container_issue 6
container_start_page 1033
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