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Abstract The ongoing Arctic warming has been pronounced in winter and has been associated with an increase in downward longwave radiation. While previous studies have demonstrated that poleward moisture flux into the Arctic strengthens downward longwave radiation, less attention has been given to the impact of the accompanying increase in snowfall. Here, utilizing state-of-the-art sea ice models, we show that typical winter snowfall (snow water equivalent) anomalies of around 1.0 cm, accompanied by positive downward longwave radiation anomalies of ∼5 W m−2, can cause basinwide sea ice thinning by around 5 cm in the following spring over the Arctic seas in the Eurasian–Pacific seas. In extreme cases, this is followed by a shrinking of summer ice extent. In the winter of 2016/17, anomalously strong warm, moist air transport combined with ∼2.5-cm increase in snowfall (snow water equivalent) decreased spring ice thickness by ∼10 cm and decreased the following summer sea ice extent by 5%–30%. This study suggests that small changes in the pattern and volume of winter snowfall can strongly impact the sea ice thickness and extent in the following seasons.
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This content will become publicly available on November 1, 2026
Biases in radiative flux observations due to precipitation across the Arctic forest-tundra ecotone
Accurate measurement of net radiation in the high-latitude Arctic regions is challenging since rain and snow events often introduce substantial measurement errors. To reduce the precipitation-induced measurement errors of downward radiation, customized data-driven methods are developed to reconstruct downward radiative fluxes from the biased radiation measurements. This study uses four years of field data across ten plots covered with forest, trees, and tundra in the Polar Urals from July 2018 to July 2022. Rain and snow on the radiometers absorb and block shortwave radiation and emit longwave radiation, leading to underestimation of downward shortwave and overestimation of downward longwave radiation. Snow causes more errors than rain. Seasonal variation of reconstructed net radiation for three dominant vegetation types indicates that their differences are most pronounced in April and least in September. Furthermore, forest and tree plots consistently exhibit higher magnitudes of net radiation and longer seasons of positive net radiation than tundra plots. This study advances methodologies for reconstructing corrupted net radiation data in the Arctic and offers insights into the variability of net radiation patterns within the forest-tundra ecotone.
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- PAR ID:
- 10655771
- Publisher / Repository:
- Elsevier
- Date Published:
- Journal Name:
- Agricultural and Forest Meteorology
- Volume:
- 374
- Issue:
- C
- ISSN:
- 0168-1923
- Page Range / eLocation ID:
- 110814
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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