Consequences of the 2019 Greenland Ice Sheet Melt Episode on Albedo

In mid-June 2019, the Greenland ice sheet (GrIS) experienced an extreme early-season melt event. This, coupled with an earlier-than-average melt onset and low prior winter snowfall over western Greenland, led to a rapid decrease in surface albedo and greater solar energy absorption over the melt sea...

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Bibliographic Details
Published in:Remote Sensing
Main Authors: Arthur Elmes, Charlotte Levy, Angela Erb, Dorothy K. Hall, Ted A. Scambos, Nicolo DiGirolamo, Crystal Schaaf
Format: Article in Journal/Newspaper
Language:English
Published: MDPI AG 2021
Subjects:
cryosphere
Greenland ice sheet
albedo
radiative forcing
Science
Q
Greenland
Ice Sheet
Online Access:https://doi.org/10.3390/rs13020227
https://doaj.org/article/3276b09ffeb343cb83b2b2ba7e91c12a
Description
Summary:In mid-June 2019, the Greenland ice sheet (GrIS) experienced an extreme early-season melt event. This, coupled with an earlier-than-average melt onset and low prior winter snowfall over western Greenland, led to a rapid decrease in surface albedo and greater solar energy absorption over the melt season. The 2019 melt season resulted in significantly more melt than other recent years, even compared to exceptional melt years previously identified in the moderate-resolution imaging spectroradiometer (MODIS) record. The increased solar radiation absorbance in 2019 warmed the surface and increased the rate of meltwater production. We use two decades of satellite-derived albedo from the MODIS MCD43 record to show a significant and extended decrease in albedo in Greenland during 2019. This decrease, early in the melt season and continuing during peak summer insolation, caused increased radiative forcing of the ice sheet of 2.33 Wm −2 for 2019. Radiative forcing is strongly influenced by the dramatic seasonal differences in surface albedo experienced by any location experiencing persistent and seasonal snow-cover. We also illustrate the utility of the newly developed Landsat-8 albedo product for better capturing the detailed spatial heterogeneity of the landscape, leading to a more refined representation of the surface energy budget. While the MCD43 data accurately capture the albedo for a given 500 m pixel, the higher spatial resolution 30 m Landsat-8 albedos more fully represent the detailed landscape variations.

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