Abstract
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.
Highlights
Permafrost is an important component of the climate system, and its variations can have significant impacts on climate and society
After comparing the spatial patterns of the AirMOSS retrievals with the Catchment Land Surface Model (CLSM)-simulated active layer thickness (ALT) results, we investigate the factors that affect the spatial variability of ALT through a series of idealized experiments
In our figures we show the standard deviation of the observed ALT as a very crude surrogate for the spatial representativeness error associated with the point-to-grid comparison
Summary
Permafrost is an important component of the climate system, and its variations can have significant impacts on climate and society. Of deep concern is a potential positive feedback loop by which carbon stored within permafrost regions is released through global warming, thereby adding greenhouse gases to the atmosphere that accelerate the warming further (Dorrepaal et al, 2009; Schuur et al, 2009; MacDougall et al, 2012; Schuur et al, 2015). Communities and infrastructure in ice-rich permafrost regions are vulnerable to land subsidence and infrastructure damage caused by permafrost thaw (Nelson et al, 2001; Liu et al, 2010; Guo and Sun, 2015). J. Tao et al.: Permafrost variability over the Northern Hemisphere based on the MERRA-2 reanalysis
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