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

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.

Toward the Detection of Permafrost Using Land-Surface Temperature Mapping

“…Among the TIR imagers on these satellites, only MODIS provides daily measurements of LST. Numerical modeling studies based on the empirical relationship between the ground temperature and air temperature have taken advantage of the MODIS LST products (e.g., [27][28][29]) to derive static maps of the spatial distribution of permafrost. Recently, a numerical modeling study has combined the MODIS LST products with gridded air temperature data to derive time-series maps of permafrost extent [5].…”

Investigating the sensitivity of soil heterotrophic respiration to recent snow cover changes in Alaska using a satellite-based permafrost carbon model

“…Annual litterfall was assumed to be equal to annual NPP, without accounting for the impact of disturbance events. Our soil decomposition model uses multiple litter and soil organic carbon (SOC) pools to characterize the progressive decomposition of fresh litter to more recalcitrant materials, which include three litterfall pools and three SOC pools, with relatively fast turnover rates, and a deep SOC pool, with slow turnover rates (Thornton et al, 2002). The litterfall carbon inputs were first allocated to the three litterfall pools and then transferred to the SOC pools through progressive decomposition.…”

Surface temperature inversion characteristics in dissimilar valleys, Yukon Canada

“…Climate reanalysis data sets of 2 m air temperature offer a way to examine past, current, and future surface air temperature (SAT)/SLR patterns in remote locations (Compo et al 2011). Permafrost distribution modelling relies on the use of these data sets to understand the past, present, and future of MAAT (Obu et al 2019;Tao et al 2019;Qin et al 2020), but there are limitations to the ac-curacy of this, particularly in mountainous areas due to their coarse spatial resolutions (Etzelmüller 2013).…”