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格陵兰冰盖表面融化因雪线迁移和裸冰暴露而加剧。

Greenland Ice Sheet surface melt amplified by snowline migration and bare ice exposure.

作者信息

Ryan J C, Smith L C, van As D, Cooley S W, Cooper M G, Pitcher L H, Hubbard A

机构信息

Institute at Brown for Environment and Society, Brown University, Providence, RI, USA.

Department of Geography, University of California, Los Angeles, Los Angeles, CA, USA.

出版信息

Sci Adv. 2019 Mar 6;5(3):eaav3738. doi: 10.1126/sciadv.aav3738. eCollection 2019 Mar.

DOI:10.1126/sciadv.aav3738
PMID:30854432
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6402853/
Abstract

Greenland Ice Sheet mass loss has recently increased because of enhanced surface melt and runoff. Since melt is critically modulated by surface albedo, understanding the processes and feedbacks that alter albedo is a prerequisite for accurately forecasting mass loss. Using satellite imagery, we demonstrate the importance of Greenland's seasonally fluctuating snowline, which reduces ice sheet albedo and enhances melt by exposing dark bare ice. From 2001 to 2017, this process drove 53% of net shortwave radiation variability in the ablation zone and amplified ice sheet melt five times more than hydrological and biological processes that darken bare ice itself. In a warmer climate, snowline fluctuations will exert an even greater control on melt due to flatter ice sheet topography at higher elevations. Current climate models, however, inaccurately predict snowline elevations during high melt years, portending an unforeseen uncertainty in forecasts of Greenland's runoff contribution to global sea level rise.

摘要

由于地表融化和径流增加,格陵兰冰盖的质量损失近来有所加剧。由于融化受到地表反照率的关键调节,了解改变反照率的过程和反馈是准确预测质量损失的前提条件。利用卫星图像,我们证明了格陵兰季节性波动雪线的重要性,它通过暴露深色裸冰降低了冰盖反照率并增强了融化。从2001年到2017年,这一过程驱动了消融区53%的净短波辐射变化,并且使冰盖融化量比使裸冰变暗的水文和生物过程放大了五倍多。在气候变暖的情况下,由于高海拔地区冰盖地形更平缓,雪线波动将对融化产生更大的控制作用。然而,当前的气候模型在高融化年份对雪线高度的预测不准确,这预示着格陵兰径流对全球海平面上升的预测存在不可预见的不确定性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0183/6402853/8807ab49abb9/aav3738-F6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0183/6402853/fd9b8e19b19b/aav3738-F1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0183/6402853/998b4e9af271/aav3738-F2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0183/6402853/8c98a7dfe0eb/aav3738-F3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0183/6402853/854d13399af8/aav3738-F4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0183/6402853/4e7e9b4e75ae/aav3738-F5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0183/6402853/8807ab49abb9/aav3738-F6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0183/6402853/fd9b8e19b19b/aav3738-F1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0183/6402853/998b4e9af271/aav3738-F2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0183/6402853/8c98a7dfe0eb/aav3738-F3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0183/6402853/854d13399af8/aav3738-F4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0183/6402853/4e7e9b4e75ae/aav3738-F5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0183/6402853/8807ab49abb9/aav3738-F6.jpg

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