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Institution

Alaska Department of Natural Resources

GovernmentAnchorage, Alaska, United States
About: Alaska Department of Natural Resources is a government organization based out in Anchorage, Alaska, United States. It is known for research contribution in the topics: Arctic & Permafrost. The organization has 42 authors who have published 50 publications receiving 1157 citations.
Topics: Arctic, Permafrost, Global warming, Tundra, Storm


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Journal ArticleDOI
TL;DR: In this paper, the authors use field and remote sensing observations to document polygon succession due to ice-wedge degradation and trough development in ten Arctic localities over subdecadal timescales.
Abstract: Ice wedges are common features of the subsurface in permafrost regions. They develop by repeated frost cracking and ice vein growth over hundreds to thousands of years. Ice-wedge formation causes the archetypal polygonal patterns seen in tundra across the Arctic landscape. Here we use field and remote sensing observations to document polygon succession due to ice-wedge degradation and trough development in ten Arctic localities over sub-decadal timescales. Initial thaw drains polygon centres and forms disconnected troughs that hold isolated ponds. Continued ice-wedge melting leads to increased trough connectivity and an overall draining of the landscape. We find that melting at the tops of ice wedges over recent decades and subsequent decimetre-scale ground subsidence is a widespread Arctic phenomenon. Although permafrost temperatures have been increasing gradually, we find that ice-wedge degradation is occurring on sub-decadal timescales. Our hydrological model simulations show that advanced ice-wedge degradation can significantly alter the water balance of lowland tundra by reducing inundation and increasing runoff, in particular due to changes in snow distribution as troughs form. We predict that ice-wedge degradation and the hydrological changes associated with the resulting differential ground subsidence will expand and amplify in rapidly warming permafrost regions. The polygonal patterns in permafrost regions are caused by the formation of ice wedges. Observations of polygon evolution reveal that rapid ice-wedge melting has occurred across the Arctic since 1950, altering tundra hydrology.

527 citations

Journal ArticleDOI
TL;DR: Crone et al. as mentioned in this paper measured the moment magnitude of the 3 November 2002 Denali earthquake and estimated the average surface slip on the Susitna Glacier, Denali, and Totschunda faults.
Abstract: The 3 November 2002 Denali fault, Alaska, earthquake resulted in 341 km of surface rupture on the Susitna Glacier, Denali, and Totschunda faults. The rupture proceeded from west to east and began with a 48-km-long break on the previously unknown Susitna Glacier thrust fault. Slip on this thrust averaged about 4 m (Crone et al. , 2004). Next came the principal surface break, along 226 km of the Denali fault, with average right-lateral offsets of 4.5–5.1 m and a maximum offset of 8.8 m near its eastern end. The Denali fault trace is commonly left stepping and north side up. About 99 km of the fault ruptured through glacier ice, where the trace orientation was commonly influenced by local ice fabric. Finally, slip transferred southeastward onto the Totschunda fault and continued for another 66 km where dextral offsets average 1.6–1.8 m. The transition from the Denali fault to the Totschunda fault occurs over a complex 25-km-long transfer zone of right-slip and normal fault traces. Three methods of calculating average surface slip all yield a moment magnitude of M w 7.8, in very good agreement with the seismologically determined magnitude of M 7.9. A comparison of strong-motion inversions for moment release with our slip distribution shows they have a similar pattern. The locations of the two largest pulses of moment release correlate with the locations of increasing steps in the average values of observed slip. This suggests that slip-distribution data can be used to infer moment release along other active fault traces. Online Material : Descriptions and photographs of localities with offset measurements.

186 citations

Journal ArticleDOI
TL;DR: In this paper, the authors combine radiocarbon dating of lake bubble trace-gas methane (113 measurements) and soil organic carbon (289 measurements) for lakes in Alaska, Canada, Sweden and Siberia with numerical modelling of thaw and remote sensing of thermokarst shore expansion.
Abstract: Warming thaws permafrost, releasing carbon that can cause more warming. Radiocarbon, soil carbon, and remote sensing data suggest that 0.2–2.5 Pg of carbon has been emitted from permafrost as CO2 and CH4 around Arctic lakes since the 1950s. Permafrost thaw exposes previously frozen soil organic matter to microbial decomposition. This process generates methane and carbon dioxide, and thereby fuels a positive feedback process that leads to further warming and thaw1. Despite widespread permafrost degradation during the past ∼40 years2,3,4, the degree to which permafrost thaw may be contributing to a feedback between warming and thaw in recent decades is not well understood. Radiocarbon evidence of modern emissions of ancient permafrost carbon is also sparse5. Here we combine radiocarbon dating of lake bubble trace-gas methane (113 measurements) and soil organic carbon (289 measurements) for lakes in Alaska, Canada, Sweden and Siberia with numerical modelling of thaw and remote sensing of thermokarst shore expansion. Methane emissions from thermokarst areas of lakes that have expanded over the past 60 years were directly proportional to the mass of soil carbon inputs to the lakes from the erosion of thawing permafrost. Radiocarbon dating indicates that methane age from lakes is nearly identical to the age of permafrost soil carbon thawing around them. Based on this evidence of landscape-scale permafrost carbon feedback, we estimate that 0.2 to 2.5 Pg permafrost carbon was released as methane and carbon dioxide in thermokarst expansion zones of pan-Arctic lakes during the past 60 years.

141 citations

Journal ArticleDOI
TL;DR: In this article, the authors present some of the most important findings from a diversity of research and management projects from 1970 to 2004 to understand the biology, ecology, and control of this important forest insect, and the causes and effects of their outbreaks.

103 citations

Journal ArticleDOI
TL;DR: The 2015 Alaska fire season burned 5.1 million acres, the second largest burned area since 1940, exceeded only by the 2004 Alaska wildfire season when 6.2 million acres burned as mentioned in this paper.
Abstract: Introduction. The 2015 Alaska fire season burned 5.1 million acres, the second largest burned area since 1940, exceeded only by the 2004 Alaska fire season when 6.2 million acres burned (Fig. 4.1a). Despite a below normal end-of-winter snowpack and an unseasonably warm spring with earlier snowmelt, which dried fuels early in the season, scattered showers and cool temperatures kept 2015 fire activity near normal through early June. During the first half of June, several days of maximum temperatures exceeded 30 ̊C, relative humidity (RH) values were in the teens, and long daylight hours quickly dried surface and subsurface (duff) forest-floor fuels. Beginning June 19, a period of vigorous thunderstorm activity resulted in an unprecedented weeklong lightning event with 36 000 strikes in three days. During this period, 65 000+ strikes in Alaska gave rise to nearly 270 ignitions of the preconditioned fuels. Burned acreage increased by 3.8 million acres (Fig. 4.1b) in the two and a half weeks following those starts (Fig. 4.1c). Lightning ignitions caused 99.5% of the acreage burned in Alaska in 2015. A westerly shift in upper-level winds by mid-July brought cool and damp weather that curtailed fire growth, and most extant fires burned little acreage after July 15. This pattern highlights a significant difference between Alaska’s top two fire seasons: 2004 burned significant acreage in July and again in August during extended warm and dry late summer weather, while 2015 saw the bulk of fire activity concentrated from mid-June to mid-July. These different pathways to large fire seasons demonstrate the importance of intraseasonal weather variability and the timing of dynamical features. Yet, underlying each case are the common requirements of: heat, extremely dry fuels, and ignition. One question that arises is whether the extremely warm and dry, yet convective, conditions of 2015 might be driven by anthropogenic climate change. This attribution study is a model-based test of the hypothesis that anthropogenic climate change increases the likelihood of fire seasons as extreme as 2015 through increasing flammability of fuels.

52 citations


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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20231
20213
20206
20193
20182
20174