Long time series (1984–2020) of albedo variations on the Greenland ice sheet from harmonized Landsat and Sentinel 2 imagery

Albedo is a key factor in modulating the absorption of solar radiation on ice surfaces. Satellite measurements have shown a general reduction in albedo across the Greenland ice sheet over the past few decades, particularly along the western margin of the ice sheet, a region known as the Dark Zone (a...

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Main Authors: Shunan Feng, Joseph Mitchell Cook, Alexandre Magno Anesio, Liane G. Benning, Martyn Tranter
Format: Article
Language:English
Published: Cambridge University Press 2023-10-01
Series:Journal of Glaciology
Subjects:
Online Access:https://www.cambridge.org/core/product/identifier/S0022143023000114/type/journal_article
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author Shunan Feng
Joseph Mitchell Cook
Alexandre Magno Anesio
Liane G. Benning
Martyn Tranter
author_facet Shunan Feng
Joseph Mitchell Cook
Alexandre Magno Anesio
Liane G. Benning
Martyn Tranter
author_sort Shunan Feng
collection DOAJ
description Albedo is a key factor in modulating the absorption of solar radiation on ice surfaces. Satellite measurements have shown a general reduction in albedo across the Greenland ice sheet over the past few decades, particularly along the western margin of the ice sheet, a region known as the Dark Zone (albedo < 0.45). Here we chose a combination of Landsat 4–8 and Sentinel 2 imagery to enable us to derive the longest record of albedo variations in the Dark Zone, running from 1984 to 2020. We developed a simple, pragmatic and efficient sensor transformation to provide a long time series of consistent, harmonized satellite imagery. Narrow to broadband conversion algorithms were developed from regression models of harmonized satellite data and in situ albedo from the Program for Monitoring of the Greenland Ice Sheet (PROMICE) automatic weather stations. The albedo derived from the harmonized Landsat and Sentinel 2 data shows that the maximum extent of the Dark Zone expanded rapidly between 2005 and 2007, increasing to ~280% of the average annual maximum extent of 2900 km2 to ~8000 km2 since. The Dark Zone is continuing to darken slowly, with the average annual minimum albedo decreasing at a rate of $\sim \!-0.0006 \pm 0.0004 \, {\rm a}^{-1}$ (p = 0.16, 2001–2020).
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spelling doaj.art-f56ee0aac378482f9eea6a14b3b2e8c82023-10-24T09:48:09ZengCambridge University PressJournal of Glaciology0022-14301727-56522023-10-01691225124010.1017/jog.2023.11Long time series (1984–2020) of albedo variations on the Greenland ice sheet from harmonized Landsat and Sentinel 2 imageryShunan Feng0https://orcid.org/0000-0002-8534-3066Joseph Mitchell Cook1https://orcid.org/0000-0002-9270-363XAlexandre Magno Anesio2https://orcid.org/0000-0003-2990-4014Liane G. Benning3https://orcid.org/0000-0001-9972-5578Martyn Tranter4https://orcid.org/0000-0003-2071-3094Department of Environmental Sciences, Aarhus University, Frederiksborgvej 399, DK-4000 Roskilde, DenmarkDepartment of Environmental Sciences, Aarhus University, Frederiksborgvej 399, DK-4000 Roskilde, DenmarkDepartment of Environmental Sciences, Aarhus University, Frederiksborgvej 399, DK-4000 Roskilde, DenmarkGFZ German Research Centre for Geosciences, Section Interface Geochemistry, Telegrafenberg, 14473 Potsdam, Germany Department of Earth Sciences, Free University of Berlin, 12249 Berlin, GermanyDepartment of Environmental Sciences, Aarhus University, Frederiksborgvej 399, DK-4000 Roskilde, DenmarkAlbedo is a key factor in modulating the absorption of solar radiation on ice surfaces. Satellite measurements have shown a general reduction in albedo across the Greenland ice sheet over the past few decades, particularly along the western margin of the ice sheet, a region known as the Dark Zone (albedo < 0.45). Here we chose a combination of Landsat 4–8 and Sentinel 2 imagery to enable us to derive the longest record of albedo variations in the Dark Zone, running from 1984 to 2020. We developed a simple, pragmatic and efficient sensor transformation to provide a long time series of consistent, harmonized satellite imagery. Narrow to broadband conversion algorithms were developed from regression models of harmonized satellite data and in situ albedo from the Program for Monitoring of the Greenland Ice Sheet (PROMICE) automatic weather stations. The albedo derived from the harmonized Landsat and Sentinel 2 data shows that the maximum extent of the Dark Zone expanded rapidly between 2005 and 2007, increasing to ~280% of the average annual maximum extent of 2900 km2 to ~8000 km2 since. The Dark Zone is continuing to darken slowly, with the average annual minimum albedo decreasing at a rate of $\sim \!-0.0006 \pm 0.0004 \, {\rm a}^{-1}$ (p = 0.16, 2001–2020).https://www.cambridge.org/core/product/identifier/S0022143023000114/type/journal_articleArctic glaciologyalbedodata harmonizationsnow/ice surface processes
spellingShingle Shunan Feng
Joseph Mitchell Cook
Alexandre Magno Anesio
Liane G. Benning
Martyn Tranter
Long time series (1984–2020) of albedo variations on the Greenland ice sheet from harmonized Landsat and Sentinel 2 imagery
Journal of Glaciology
Arctic glaciology
albedo
data harmonization
snow/ice surface processes
title Long time series (1984–2020) of albedo variations on the Greenland ice sheet from harmonized Landsat and Sentinel 2 imagery
title_full Long time series (1984–2020) of albedo variations on the Greenland ice sheet from harmonized Landsat and Sentinel 2 imagery
title_fullStr Long time series (1984–2020) of albedo variations on the Greenland ice sheet from harmonized Landsat and Sentinel 2 imagery
title_full_unstemmed Long time series (1984–2020) of albedo variations on the Greenland ice sheet from harmonized Landsat and Sentinel 2 imagery
title_short Long time series (1984–2020) of albedo variations on the Greenland ice sheet from harmonized Landsat and Sentinel 2 imagery
title_sort long time series 1984 2020 of albedo variations on the greenland ice sheet from harmonized landsat and sentinel 2 imagery
topic Arctic glaciology
albedo
data harmonization
snow/ice surface processes
url https://www.cambridge.org/core/product/identifier/S0022143023000114/type/journal_article
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