Several model-based assessments predict a discernible increase in the depth of
seasonal thawing and circumpolar-scale warming of permafrost by the mid-21st century.
Quantitative estimates of the environmental and socioeconomic impacts of changing
climate in northern regions require robust projection of changes in permafrost, which in
turn depend on the availability of appropriate models and forcing data. We examined
four high-resolution, hemispheric-scale gridded sets of monthly temperature and
precipitation constructed using different interpolation routines and reanalysis of data from
a large number of weather stations. At many of 455 Russian weather stations, the four
data sets depart from empirical mean annual air temperatures averaged over the 15-year
period by 1–2C and in cumulative daily positive temperature sums (degree days of
thawing) by more than 200C days. A permafrost model, forced with the gridded climatic
data sets, was used to calculate the large-scale characteristics of permafrost in northern
Eurasia. We analyzed zonal-mean air and ground temperatures, depth of seasonal thawing,
and area occupied by near-surface permafrost in Eurasia north of 45N. The 0.5–1.0 C
difference in zonal-mean air temperature between the data sets translates into a range
of uncertainty of 10–20% in estimates of near-surface permafrost area, which is
comparable to the extent of changes projected for the following several decades. We
conclude that more observations and theoretical studies are needed to improve
characterization of baseline climatic conditions and to narrow the range of uncertainties in
model-based permafrost projections.
