The Cryosphere, Volume 14, Issue 12


Anthology ID:
G20-240
Month:
Year:
2020
Address:
Venue:
GWF
SIG:
Publisher:
Copernicus GmbH
URL:
https://gwf-uwaterloo.github.io/gwf-publications/G20-240
DOI:
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The catastrophic thermokarst lake drainage events of 2018 in northwestern Alaska: fast-forward into the future
Ingmar Nitze | Sarah W. Cooley | Claude R. Duguay | Benjamin Jones | Guido Grosse

Abstract. Northwestern Alaska has been highly affected by changing climatic patterns with new temperature and precipitation maxima over the recent years. In particular, the Baldwin and northern Seward peninsulas are characterized by an abundance of thermokarst lakes that are highly dynamic and prone to lake drainage like many other regions at the southern margins of continuous permafrost. We used Sentinel-1 synthetic aperture radar (SAR) and Planet CubeSat optical remote sensing data to analyze recently observed widespread lake drainage. We then used synoptic weather data, climate model outputs and lake ice growth simulations to analyze potential drivers and future pathways of lake drainage in this region. Following the warmest and wettest winter on record in 2017/2018, 192 lakes were identified as having completely or partially drained by early summer 2018, which exceeded the average drainage rate by a factor of ∼ 10 and doubled the rates of the previous extreme lake drainage years of 2005 and 2006. The combination of abundant rain- and snowfall and extremely warm mean annual air temperatures (MAATs), close to 0 ∘C, may have led to the destabilization of permafrost around the lake margins. Rapid snow melt and high amounts of excess meltwater further promoted rapid lateral breaching at lake shores and consequently sudden drainage of some of the largest lakes of the study region that have likely persisted for millennia. We hypothesize that permafrost destabilization and lake drainage will accelerate and become the dominant drivers of landscape change in this region. Recent MAATs are already within the range of the predictions by the University of Alaska Fairbanks' Scenarios Network for Alaska and Arctic Planning (UAF SNAP) ensemble climate predictions in scenario RCP6.0 for 2100. With MAAT in 2019 just below 0 ∘C at the nearby Kotzebue, Alaska, climate station, permafrost aggradation in drained lake basins will become less likely after drainage, strongly decreasing the potential for freeze-locking carbon sequestered in lake sediments, signifying a prominent regime shift in ice-rich permafrost lowland regions.

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Snow cover duration trends observed at sites and predicted by multiple models
Richard Essery | Hyungjun Kim | Libo Wang | Paul Bartlett | Aaron Boone | Claire Brutel‐Vuilmet | Eleanor Burke | Matthias Cuntz | Bertrand Decharme | Emanuel Dutra | Xing Fang | Yeugeniy M. Gusev | Stefan Hagemann | Vanessa Haverd | Anna Kontu | Gerhard Krinner | Matthieu Lafaysse | Yves Lejeune | Thomas Marke | Danny Marks | Christoph Marty | Cécile B. Ménard | О. Н. Насонова | Tomoko Nitta | John W. Pomeroy | Gerd Schädler | В. А. Семенов | Tatiana G. Smirnova | Sean Swenson | Dmitry Turkov | Nander Wever | Hua Yuan

Abstract. The 30-year simulations of seasonal snow cover in 22 physically based models driven with bias-corrected meteorological reanalyses are examined at four sites with long records of snow observations. Annual snow cover durations differ widely between models, but interannual variations are strongly correlated because of the common driving data. No significant trends are observed in starting dates for seasonal snow cover, but there are significant trends towards snow cover ending earlier at two of the sites in observations and most of the models. A simplified model with just two parameters controlling solar radiation and sensible heat contributions to snowmelt spans the ranges of snow cover durations and trends. This model predicts that sites where snow persists beyond annual peaks in solar radiation and air temperature will experience rapid decreases in snow cover duration with warming as snow begins to melt earlier and at times of year with more energy available for melting.