Permafrost is a key element of the cryosphere and an essential climate variable in the Global Climate Observing System. There is no remote-sensing method available to reliably monitor the permafrost thermal state. To estimate permafrost distribution at a hemispheric scale, we employ an equilibrium state model for the temperature at the top of the permafrost (TTOP model) for the 2000-2016 period, driven by remotely-sensed land surface temperatures, down-scaled ERA-Interim climate reanalysis data, tundra wetness classes and landcover map from the ESA Landcover Climate Change Initiative (CCI) project. Subgrid variability of ground temperatures due to snow and landcover variability is represented in the model using subpixel statistics. The results are validated against borehole measurements and reviewed regionally. The accuracy of the modelled mean annual ground temperature (MAGT) at the top of the permafrost is +/- 2 degrees C when compared to permafrost borehole data. The modelled permafrost area (MAGT 0) is around 21 x 10(6) km(2) (22% of exposed land area), which is approximately 2 x 10(6) km(2) less than estimated previously. Detailed comparisons at a regional scale show that the model performs well in sparsely vegetated tundra regions and mountains, but is less accurate in densely vegetated boreal spruce and larch forests.

Statistical correlations between seasonal air temperatures and snow depths and active layer depths and permafrost temperatures were analysed for tundra (Marre-Salle) and northern taiga (Nadym) sites in Western Siberia. Interannual variations in active layer depth in the tundra zone correlated with the average air temperature of the current summer, and in peatland and humid tundra, also with summer temperatures of the preceding 1-2 years. In the northern taiga zone, the active layer depth related to current summer air temperature and to a lesser extent, to spring and/or winter air temperatures. Variations in summer permafrost temperatures at 5-10 m depth were correlated with spring air temperatures in the current and preceding 1-2 years. The weather regime during the preceding 12 years, therefore, reinforced or weakened ground temperature variations in a given year. Overall, the most important factors influencing the permafrost regime were spring and summer air temperatures, and in one case snow depth. However, statistical links between meteorological and permafrost parameters varied between the tundra and northern taiga zones and among landscape types within each zone, emphasising the importance of analyses at short temporal scales and for individual terrain units. Copyright (C) 2009 John Wiley & Sons, Ltd.

Borehole temperature-depth profiles contain a record of surface ground temperature (SGT) changes with time and complement surface air temperature (SAT) analysis to infer climate change over multiple centuries. Ground temperatures are generally warmer than air temperatures due to solar radiation effects in the summer and the insulating effect of snow cover during the winter. The low thermal diffusivity of snow damps surface temperature variations; snow effectively acts as an insulator of the ground during the coldest part of the year. A numerical model of snow-ground thermal interactions is developed to investigate the effect of seasonal snow cover on annual ground temperatures. The model is parameterized in terms of three snow event parameters: onset time of the annual snow event, duration of the event, and depth of snow during the event. These parameters are commonly available from meteorological and remotely sensed data making the model broadly applicable. The model is validated using SAT, subsurface temperature from a depth of 10 cm, and snow depth data from the 6 years of observations at Emigrant Pass climate observatory in northwestern Utah and 217 station years of National Weather Service data from sites across North America. Measured subsurface temperature-time series are compared to changes predicted by the model. The model consistently predicts ground temperature changes that compare well with those observed. Sensitivity analysis of the model leads to a nonlinear relationship between the three snow event parameters (onset, duration, and depth of the annual snow event) and the influence snow has on mean annual SGT.

High-latitude ecosystems where the mean annual ground surface temperature is around or below 0 degreesC are highly sensitive to global warming. This is largely because these regions contain vast areas of permafrost, which begins to thaw when the mean annual temperature rises above freezing. The Geophysical Institute Permafrost Lab has developed a new interactive geographical information systems (GIS) model to estimate the long-term response of permafrost to changes in climate. An analytical approach is used for calculating both active layer thickness (ALT) and mean annual ground temperatures (MAGTs). When applied to long-term (decadal or longer time scale) averages, this approach shows an accuracy of +/-0.2-0.4degreesC for MAGTs and +/-0.1-0.3 in for ALT calculations. The relative errors do not exceed 32% for ALT calculations, but typically they are between 10 and 25%. A spatial statistical analysis of the data from 32 sites in Siberia indicated a confidence level of 75% to have a deviation between measured and calculated MAGTs of 0.2-0.4degreesC. A detailed analysis has been performed for two regional transects in Alaska and eastern Siberia that has validated the use of the model. The results obtained from this analysis show that a more economical (in terms of computational time) analytical approach could be successfully used instead of a full-scale numerical model in the regional and global scale analysis of permafrost spatial and temporal dynamics. This project has been a successful contribution to the Arctic Climate Impact Assessment project. Copyright (C) 2003 John Wiley Sons, Ltd.

The growth of four white spruce (Picea glauca) clonal islands ranging in age from ca. 98 years to more than 400 years was investigated in the shrub zone of the forest-tundra east of Churchill, Manitoba, Canada, The elongation of 20 similar-aged stems in each of the three youngest islands was monitored during 1988 and 1989. along with ground and air temperatures. Stems in the younger islands showed a more flexible response to both daily and annual variation in temperature, Younger islands showed faster recovery from frost events during elongation and longer periods of elongation in cooler years, Early spring warming that caused snowmelt to occur before the growing season appeared to result in moisture stress later in the period of elongation. In stems of spruce shrub, the branches are concentrated near ground level because growth is slow and adventitious buds develop on the stem after repeated loss of stem terminals through snow abrasion. In young trees, shading and increased moisture from trapped snow coincide with feather moss establishment and a deep active layer, resulting in higher ground temperatures and faster tree growth. It is during this early period of development that a tree may be best able to develop an erect stem. In later development, the lowest branches of trees become appressed, grow roots, and become second-order stems, and this process continues outward from the central stem. In older tree islands, peat accumulation and needle abrasion can lead to conditions less favourable for growth and maintenance of needles. Consequently, the canopy may thin, which reduces its ability to trap snow, When snow cover is reduced, lichen-heath establishes and permafrost intrudes into the mound. Subsequent growth of the secondary stems on the mound may be too slow to enable successful development of an erect stem. Thus. island development is largely dependent on changing ground temperatures, which become colder as peat accumulates and frost heaving elevates the mound. Warm spring and summer conditions appear to lead to unfavourable conditions for tree islands.

A functional model of the permafrost-climate system is applied at national scale, to produce a map of near-surface ground temperatures in the permafrost regions of Canada. The TTOP model links the temperature at the top of permafrost (TTOP) to the climate through seasonal surface transfer functions and subsurface thermal properties. The parameters in the model were compiled at national scale for Canada, although the topographic effects of the Western Cordillera were not incorporated into the analysis. The objective of the study was accomplished by implementing the TTOP model within a Geographical Information System. The TTOP map is evaluated against the published Ground Temperature Map of Canada. The published map shows ground temperatures according to a scale of temperature classes, so TTOP values were categorized into the same classes. Across the permafrost regions of Canada, 72.1% of the area is in the same class in both maps, while 27.7% differs by one temperature class. Only 0.2% of the area differs by two temperature classes. The results suggest that the TTOP model can provide a rational and functional basis for relating near-surface permafrost temperature and climate at national and regional scales. The model could be applied to the assessment of climate change impacts on the magnitude and distribution of permafrost temperatures. Copyright (C) 2001 John Wiley & Sons, Ltd.

Ground temperature monitoring has been proposed as a means of detecting climate change in permafrost regions, although it is well known that the relationship is not simple. This pager presents a functional model of the permafrost-climate relationship, which accommodates the geographical variations of climatic, surface and soil factors that control ground thermal regime. The model is used to analyse the impacts of climate change on ground temperatures and to assess the design and interpretation of ground temperature monitoring programs. The model suggests that lithologic conditions form the primary local influence on permafrost temperatures, followed by snowcover and vegetation. Results using the model suggest that simple monitoring of active layer depth does not provide a reliable indicator of changes in permafrost temperature conditions, and that monitoring at exposed bedrock sites will produce the most direct signal of climate change on the ground thermal regime.