Ten years of measurements and modeling of soil temperature changes and their effects on permafrost in Northwestern Alaska

Batir, Joseph; Hornbach, Matthew J.; Blackwell, David

doi:10.1016/j.gloplacha.2016.11.009

Cited by 34 publications

(15 citation statements)

References 35 publications

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“…Mean annual near‐surface (2 cm) T s ( MAT s ) modeled with + T a + C a + P increased by 2.4–3.2 °C in lower features and by 2.9–4.7 °C in higher features after 70 years, less than the increase in mean MAT a of 6.2 °C (Table ). The modeled increases in MAT s relative to those in MAT a were similar to an increase in ground surface temperature of 0.44 ± 0.05 °C per decade with an increase in MAT a of 1.0 ± 0.8 °C per decade recorded in NW Alaska from 1996 to 2005 by Batir et al (). The model results indicated that changes in T s relative to T a were affected by changes in densities of surface vegetation and litter, so that the relationship between increases in T s and T a during climate change will depend on changes in surface cover.…”

Section: Discussionsupporting

confidence: 73%

Modeling Climate Change Impacts on an Arctic Polygonal Tundra: 1. Rates of Permafrost Thaw Depend on Changes in Vegetation and Drainage

2019

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Model projections of permafrost thaw during the next century diverge widely. Here we used ecosys to examine how climate change will affect permafrost thaw in a polygonal tundra at Barrow AK. The model was tested against diurnal and seasonal variation in energy exchange, soil heat flux, soil temperature (Ts), and active layer depth (ALD) measured during 2014 and 2015, and interannual variation in ALD measured from 1991 to 2015. During RCP 8.5 climate change from 2015 to 2085, increases in Ta and precipitation (P) to 6.2 °C and 27% above current values, and in atmospheric CO2 concentrations (Ca) to763 μmol mol−1, altered energy exchange by increasing leaf area index of dominant sedge relative to that of moss. Increased Ca and sedge leaf area index imposed greater stomatal control of transpiration and reduced soil heat fluxes, slowing soil warming, limiting increases in evapotranspiration, and thereby causing gradual soil wetting. Consequently, increases in surface Ts and ALD of 2.4–4.7 °C and 21–24 cm above current values were modeled after 70 years. ALD increase was slowed if model boundary conditions were altered to improve landscape drainage. These rates were smaller than those of earlier modeling studies, some of which did not account for changes in vegetation, but are closer to those derived from current studies of warming impacts in the region. Therefore, accounting for climate change effects on vegetation density and composition, and consequent effects on surface energy budgets, will cause slower increases in Ts and ALD to be modeled during climate change simulations.

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Section: Discussionsupporting

confidence: 73%

Modeling Climate Change Impacts on an Arctic Polygonal Tundra: 1. Rates of Permafrost Thaw Depend on Changes in Vegetation and Drainage

2019

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“…Permafrost soils underlie approximately one quarter (∼15 million km 2 ) of the land surface in the Northern Hemisphere (Brown et al, 1997;Jorgenson et al, 2001), and store a vast amount of frozen organic carbon (Hugelius et al, 2014;Schuur et al, 2015). Warming in Arctic regions is expected to lead to permafrost thawing, as has been observed from field data during the past several decades (Lachenbruch and Marshall, 1986;Romanovsky et al, 2002;Osterkamp, 2003;Hinzman et al, 2005;Osterkamp, 2007;Wu and Zhang, 2008;Batir et al, 2017;Farquharson et al, 2019). For example, a very recent field study in the Canadian High Arctic, a cold permafrost region, reported the observed active-layer thickness (ALT, annual maximum thaw depth) already exceeds the ALT projected for 2090 under RCP 4.5 (Representative Concentration Pathways) (Farquharson et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Evaluating integrated surface/subsurface permafrost thermal hydrology models in ATS (v0.88) against observations from a polygonal tundra site

Jan¹,

Coon²,

Painter³

2019

Preprint

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Abstract. Numerical simulations are essential tools for understanding the complex hydrologic response of Arctic regions to a warming climate. However, strong coupling among thermal and hydrological processes on the surface and in the subsurface and the significant role that subtle variations in surface topography have in regulating flow direction and surface storage lead to significant uncertainties. Careful model evaluation against field observations is thus important to build confidence. We evaluate the integrated surface/subsurface permafrost thermal hydrology models in the Advanced Terrestrial Simulator (ATS) against field observations from polygonal tundra at the Barrow Environmental Observatory. ATS couples a multiphase, three-dimensional representation of subsurface thermal hydrology with representations of overland nonisothermal flows, snow processes, and surface energy balance. We simulated thermal hydrology of three-dimensional ice-wedge polygons with generic but broadly representative surface microtopography. The simulations were forced by meteorological data and observed water table elevations in ice-wedge polygon troughs. With limited calibration of parameters appearing in the soil evaporation model, the three-year simulations agreed reasonably well with snow depth, summer water table elevations in the polygon center, and high-frequency soil temperature measurements at several depths in the trough, rim, and center of the polygon. Upscaled evaporation is in good agreement with flux tower observations. The simulations were found to be sensitive to parameters in the bare soil evaporation model, snowpack, and the lateral saturated hydraulic conductivity. The study provides new support for an emerging class of integrated surface/subsurface permafrost simulators, and provides an optimized set of model parameters for use in watershed-scale projections of permafrost dynamics in a warming climate.

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“…Permafrost variations, including pronounced permafrost degradation due to a warming climate, have been reported for many regions, including Alaska (Nicholas and Hinkel, 1996;Osterkamp and Romanovsky, 1996;Jorgenson et al, 2001;Hinkel and Nelson, 2003;Jafarov et al, 2012;Liu et al, 2012;Jones et al, 2016;Batir et al, 2017), Canada (Chen et al, 2003;James et al, 2013), Norway (Gisnas et al, 2013), Sweden (Pannetier and Frampton, 2016), Russia (Romanovsky et al, 2007(Romanovsky et al, , 2010, Mongolia (Sharkhuu and Sharkhuu, 2012), and the Qinghai-Tibet Plateau (Zhou et al, 2013;Wang et al, 2016a;Lu et al, 2017;Ran et al, 2018). For the entire Northern Hemisphere, rapidly accelerated permafrost degradation in recent years has been reported by Luo et al (2016) based on in situ measurements at a point scale or a spatially aggregated scale (up to 1000 m × 1000 m) from the Circumpolar Active Layer Monitoring (CALM) network.…”

Section: Introductionmentioning

confidence: 99%

Permafrost variability over the Northern Hemisphere based on the MERRA-2 reanalysis

et al. 2019

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Abstract. This study introduces and evaluates a comprehensive, model-generated dataset of Northern Hemisphere permafrost conditions at 81 km2 resolution. Surface meteorological forcing fields from the Modern-Era Retrospective Analysis for Research and Applications 2 (MERRA-2) reanalysis were used to drive an improved version of the land component of MERRA-2 in middle-to-high northern latitudes from 1980 to 2017. The resulting simulated permafrost distribution across the Northern Hemisphere mostly captures the observed extent of continuous and discontinuous permafrost but misses the ecosystem-protected permafrost zones in western Siberia. Noticeable discrepancies also appear along the southern edge of the permafrost regions where sporadic and isolated permafrost types dominate. The evaluation of the simulated active layer thickness (ALT) against remote sensing retrievals and in situ measurements demonstrates reasonable skill except in Mongolia. The RMSE (bias) of climatological ALT is 1.22 m (−0.48 m) across all sites and 0.33 m (−0.04 m) without the Mongolia sites. In northern Alaska, both ALT retrievals from airborne remote sensing for 2015 and the corresponding simulated ALT exhibit limited skill versus in situ measurements at the model scale. In addition, the simulated ALT has larger spatial variability than the remotely sensed ALT, although it agrees well with the retrievals when considering measurement uncertainty. Controls on the spatial variability of ALT are examined with idealized numerical experiments focusing on northern Alaska; meteorological forcing and soil types are found to have dominant impacts on the spatial variability of ALT, with vegetation also playing a role through its modulation of snow accumulation. A correlation analysis further reveals that accumulated above-freezing air temperature and maximum snow water equivalent explain most of the year-to-year variability of ALT nearly everywhere over the model-simulated permafrost regions.

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Ten years of measurements and modeling of soil temperature changes and their effects on permafrost in Northwestern Alaska

Cited by 34 publications

References 35 publications

Modeling Climate Change Impacts on an Arctic Polygonal Tundra: 1. Rates of Permafrost Thaw Depend on Changes in Vegetation and Drainage

Modeling Climate Change Impacts on an Arctic Polygonal Tundra: 1. Rates of Permafrost Thaw Depend on Changes in Vegetation and Drainage

Evaluating integrated surface/subsurface permafrost thermal hydrology models in ATS (v0.88) against observations from a polygonal tundra site

Permafrost variability over the Northern Hemisphere based on the MERRA-2 reanalysis

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