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Mercury (Hg) is a naturally occurring element that bonds with organic matter and, when converted to methylmercury, is a potent neurotoxicant. Here we estimate potential future releases of Hg from thawing permafrost for low and high greenhouse gas emissions scenarios using a mechanistic model. By 2200, the high emissions scenario shows annual permafrost Hg emissions to the atmosphere comparable to current global anthropogenic emissions. By 2100, simulated Hg concentrations in the Yukon River increase by 14% for the low emissions scenario, but double for the high emissions scenario. Fish Hg concentrations do not exceed United States Environmental Protection Agency guidelines for the low emissions scenario by 2300, but for the high emissions scenario, fish in the Yukon River exceed EPA guidelines by 2050. Our results indicate minimal impacts to Hg concentrations in water and fish for the low emissions scenario and high impacts for the high emissions scenario.

 

Abstract. This study investigates and compares soil moisture andhydrology projections of broadly used land models with permafrost processesand highlights the causes and impacts of permafrost zone soil moistureprojections. Climate models project warmer temperatures and increases inprecipitation (P) which will intensify evapotranspiration (ET) and runoff inland models. However, this study shows that most models project a long-termdrying of the surface soil (0–20 cm) for the permafrost region despiteincreases in the net air–surface water flux (P-ET). Drying is generallyexplained by infiltration of moisture to deeper soil layers as the activelayer deepens or permafrost thaws completely. Although most models agree ondrying, the projections vary strongly in magnitude and spatial pattern.Land models tend to agree with decadal runoff trends but underestimaterunoff volume when compared to gauge data across the major Arctic riverbasins, potentially indicating model structural limitations. Coordinatedefforts to address the ongoing challenges presented in this study will helpreduce uncertainty in our capability to predict the future Arctichydrological state and associated land–atmosphere biogeochemical processesacross spatial and temporal scales. 

A new resource makes it easier for researchers to explore predictions of how melting permafrost might affect carbon release, wetlands, and river deltas as they evolve and other interacting effects. 

Abstract. Recent observations of near-surface soil temperatures over the circumpolarArctic show accelerated warming of permafrost-affected soils. Theavailability of a comprehensive near-surface permafrost and active layerdataset is critical to better understanding climate impacts and toconstraining permafrost thermal conditions and its spatial distribution inland system models. We compiled a soil temperature dataset from 72 monitoringstations in Alaska using data collected by the U.S. Geological Survey, theNational Park Service, and the University of Alaska Fairbanks permafrostmonitoring networks. The array of monitoring stations spans a large range oflatitudes from 60.9 to 71.3^∘N and elevations from near sea level to∼1300m, comprising tundra and boreal forest regions. This datasetconsists of monthly ground temperatures at depths up to 1m,volumetric soil water content, snow depth, and air temperature during1997–2016. These data have been quality controlled in collection andprocessing. Meanwhile, we implemented data harmonization evaluation for theprocessed dataset. The final product (PF-AK, v0.1) is available at the ArcticData Center (https://doi.org/10.18739/A2KG55).

 

Interferometric synthetic aperture radar (InSAR) has been used to quantify a range of surface and near surface physical properties in permafrost landscapes. Most previous InSAR studies have utilized spaceborne InSAR platforms, but InSAR datasets over permafrost landscapes collected from airborne platforms have been steadily growing in recent years. Most existing algorithms dedicated toward retrieval of permafrost physical properties were originally developed for spaceborne InSAR platforms. In this study, which is the first in a two part series, we introduce a series of calibration techniques developed to apply a novel joint retrieval algorithm for permafrost active layer thickness retrieval to an airborne InSAR dataset acquired in 2017 by NASA's Uninhabited Aerial Vehicle Synthetic Aperture Radar over Alaska and Western Canada. We demonstrate how InSAR measurement uncertainties are mitigated by these calibration methods and quantify remaining measurement uncertainties with a novel method of modeling interferometric phase uncertainty using a Gaussian mixture model. Finally, we discuss the impact of native SAR resolution on InSAR measurements, the limitation of using few interferograms per retrieval, and the implications of our findings for cross‐comparison of airborne and spaceborne InSAR datasets acquired over Arctic regions underlain by permafrost.