Circumpolar permafrost maps and geohazard indices for near-future infrastructure risk assessments

Karjalainen, Olli; Aalto, Juha; Luoto, Miska; Westermann, Sebastian; Romanovsky, V. E.; Nelson, Frederick E.; Etzelmüller, Bernd; Hjort, Jan

doi:10.1038/sdata.2019.37

Cited by 66 publications

(36 citation statements)

References 111 publications

(128 reference statements)

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“…We found that the performance of ERA5L is intermediate between the two maps (Table 2). Whereas Karjalainen et al (2019b) found that the predictive accuracy of their statistical model was similar between permafrost and non-permafrost regions, our results show ERA5L and TTOP soil temperature agree less with observations in permafrost regions than in nonpermafrost regions (Table 2; Fig. 3).…”

Section: Soil Temperaturecontrasting

confidence: 81%

“…It incorporates new soil and snow hydrology (Balsamo et al, 2009;Dutra et al, 2010), revised soil thermal conductivity (Peters-Lidard et al, 1998), vegetation seasonality (Boussetta et al, 2013), and bare soil evaporation (Albergel et al, 2012). These improvements are expected to make ERA5L more accurate for many land applications; with a spatial resolution of 0.1 • , ERA5L is the first global reanalysis product at an intermediate spatial scale between Earth system land surface models (e.g., Melton et al, 2019;Chadburn et al, 2015) and statisticaland/or remote-sensing-based permafrost products (e.g., Obu et al, 2019;Karjalainen et al, 2019b).…”

Section: Introductionmentioning

confidence: 99%

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The ERA5-Land soil temperature bias in permafrost regions

et al. 2020

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Abstract. ERA5-Land (ERA5L) is a reanalysis product derived by running the land component of ERA5 at increased resolution. This study evaluates ERA5L soil temperature in permafrost regions based on observations and published permafrost products. We find that ERA5L overestimates soil temperature in northern Canada and Alaska but underestimates it in mid–low latitudes, leading to an average bias of −0.08 ∘C. The warm bias of ERA5L soil is stronger in winter than in other seasons. As calculated from its soil temperature, ERA5L overestimates active-layer thickness and underestimates near-surface (<1.89 m) permafrost area. This is thought to be due in part to the shallow soil column and coarse vertical discretization of the land surface model and to warmer simulated soil. The soil temperature bias in permafrost regions correlates well with the bias in air temperature and with maximum snow height. A review of the ERA5L snow parameterization and a simulation example both point to a low bias in ERA5L snow density as a possible cause for the warm bias in soil temperature. The apparent disagreement of station-based and areal evaluation techniques highlights challenges in our ability to test permafrost simulation models. While global reanalyses are important drivers for permafrost simulation, we conclude that ERA5L soil data are not well suited for informing permafrost research and decision making directly. To address this, future soil temperature products in reanalyses will require permafrost-specific alterations to their land surface models.

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Section: Soil Temperaturecontrasting

confidence: 81%

Section: Introductionmentioning

confidence: 99%

The ERA5-Land soil temperature bias in permafrost regions

et al. 2020

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“…ERA5L is currently available for 2001-2018, and it will eventually be extended back to 1950 and updated to the present time with little delay. (Karjalainen et al, 2019a). While ERA5L, TTOP and CP maps represent permafrost distribution with binary information (i.e.…”

Section: Era5 and Era5-landmentioning

confidence: 99%

The ERA5-Land Soil-Temperature Bias in Permafrost Regions

Cao¹,

Gruber²,

Zheng³

et al. 2020

Preprint

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Abstract. ERA5-Land (ERA5L) is a reanalysis product derived by running the land component of ERA5 at increased resolution. This study evaluates its soil temperature in permafrost regions based on observations and published permafrost products. Soil in ERA5L is predicted too warm in northern Canada and Alaska, but too cold in mid-low latitudes, leading to an average bias of −0.08 °C. The warm bias of ERA5L soil is stronger in winter than in other seasons. Diagnosed from its soil temperature, ERA5L overestimates active-layer thickness and underestimates near-surface (

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“…Given the lack of high-resolution circum-Arctic model projections of permafrost thaw and subsidence, recent risk assessment studies of infrastructure failure have used statistical approaches and suggested that fundamental engineering structures in the Arctic are at risk by mid-century (Hjort et al, 2018;Karjalainen et al, 2019). Such statistical approaches allow accounting for various sources of local-scale information such as ground ice content, sediment type, or slope gradient at comparatively low computational costs.…”

Section: Introductionmentioning

confidence: 99%

Consequences of permafrost degradation for Arctic infrastructure – bridging the model gap between regional and engineering scales

Deimling¹,

Lee²,

Ingeman‐Nielsen³

et al. 2020

Preprint

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Abstract. Infrastructure built on perennially frozen ice-rich ground relies heavily on thermally stable subsurface conditions. Climate warming-induced deepening of ground thaw puts such infrastructure at risk of failure. For better assessing the risk of large-scale future damage to Arctic infrastructure, improved strategies for model-based approaches are urgently needed. We used the laterally-coupled one-dimensional heat conduction model CryoGrid3 to simulate permafrost degradation affected by linear infrastructure. We present a case study of a gravel road built on continuous permafrost (Dalton highway, Alaska) and forced our model under historical and strong future warming conditions (following the RCP8.5 scenario). As expected, the presence of a gravel road in the model leads to higher net heat flux entering the ground compared to a reference run without infrastructure, and thus a higher rate of thaw. Further, our results suggest that road failure is likely a consequence of lateral destabilization due to talik formation in the ground beside the road, rather than a direct consequence of a top-down thawing and deepening of the active layer below the road centre. In line with previous studies, we identify enhanced snow accumulation and ponding (both a consequence of infrastructure presence) as key factors for increased soil temperatures and road degradation. Using differing horizontal model resolutions we show that it is possible to capture these key factors and their impact on thawing dynamics with a low number of lateral model units, underlining the potential of our model approach for use in pan-arctic risk assessments. Our results suggest a general two-phase behaviour of permafrost degradation: an initial phase of slow and gradual thaw, followed by a strong increase in thawing rates after exceedance of a critical ground warming. The timing of this transition and the magnitude of thaw rate acceleration differ strongly between undisturbed tundra and infrastructure-affected permafrost ground. Our model results suggest that current model-based approaches which do not explicitly take into account infrastructure in their designs are likely to strongly underestimate the timing of future Arctic infrastructure failure. By using a laterally-coupled one-dimensional model to simulate linear infrastructure, we infer results in line with outcomes from more complex 2D- and 3D-models, but our model's computational efficiency allows us to account for long-term climate change impacts on infrastructure from permafrost degradation. Our model simulations underline that it is crucial to consider climate warming when planning and constructing infrastructure on permafrost as a transition from a stable to a highly unstable state can well occur within the service life time (about 30 years) of such a construction. Such a transition can even be triggered in the coming decade by climate change for infrastructure built on high northern latitude continuous permafrost that displays cold and relatively stable conditions today.

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Circumpolar permafrost maps and geohazard indices for near-future infrastructure risk assessments

Cited by 66 publications

References 111 publications

The ERA5-Land soil temperature bias in permafrost regions

The ERA5-Land soil temperature bias in permafrost regions

The ERA5-Land Soil-Temperature Bias in Permafrost Regions

Consequences of permafrost degradation for Arctic infrastructure – bridging the model gap between regional and engineering scales

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