Mid-summer snow-free albedo across the Arctic tundra was mostly stable or increased over the past two decades. (1st December 2022)

• Record Type: Journal Article
• Authors: Plekhanova, Elena; Kim, Jin-Soo; Oehri, Jacqueline; Erb, Angela; Schaaf, Crystal; Schaepman-Strub, Gabriela
• Is Part Of: Environmental research letters. Volume 17:Number 12(2022)
• Publication Date: 2022-12-01
• Subjects: albedo -- Arctic -- tundra -- vegetation -- spectral albedo -- climate models -- biomass; Environmental sciences -- Periodicals; Human ecology -- Research -- Periodicals; Environmental health -- Periodicals; 333.7
• DOI: 10.1088/1748-9326/aca5a1
• Languages: English
• ISSNs: 1748-9326

Abstract

Abstract: Arctic vegetation changes, such as increasing shrub-cover, are expected to accelerate climate warming through increased absorption of incoming radiation and corresponding decrease in summer shortwave albedo. Here we analyze mid-summer shortwave land-surface albedo and its change across the pan-Arctic region based on MODerate resolution Imaging Spectroradiometer satellite observations over the past two decades (2000–2021). In contrast to expectations, we show that terrestrial mid-summer shortwave albedo has not significantly changed in 82% of the pan-Arctic region, while 14% show an increase and 4% a decrease. The total median significant change was 0.014 over the past 22 years. By analyzing the visible and near-/shortwave-infrared range separately, we demonstrate that the slight increase arises from an albedo increase in the near-/shortwave infrared domain while being partly compensated by a decrease in visible albedo. A similar response was found across different tundra vegetation types. We argue that this increase in reflectance is typical with increasing biomass as a result of increased multiple reflection in the canopy. However, CMIP6 global land surface model albedo predictions showed the opposite sign and different spatial patterns of snow-free summer albedo change compared to satellite-derived results. We suggest that a more sophisticated vegetation parametrization might reduce this discrepancy, and provide albedo estimates per vegetation type.