Arctic RCM simulations of temperature and precipitation derived indices relevant to future frozen ground conditions

Global and Planetary Change 80–81 (2012) 136–148

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Arctic RCM simulations of temperature and precipitation derived indices relevant to future frozen ground conditions A. Rinke a,⁎, H. Matthes a, J.H. Christensen b, c, P. Kuhry d, V.E. Romanovsky e, f, K. Dethloff a a

Alfred Wegener Institute for Polar and Marine Research, Potsdam, Germany Danish Meteorological Institute, Copenhagen, Denmark Greenland Climate Research Centre, Nuuk, Greenland d Stockholm University, Department of Physical Geography and Quaternary Geology, Stockholm, Sweden e Geophysical Institute, University of Alaska, Fairbanks, USA f Earth Cryosphere Institute, Tyumen, Russia b c

a r t i c l e

i n f o

Article history: Received 3 December 2010 Accepted 22 October 2011 Available online 28 October 2011 Keywords: Arctic climate change air temperature permafrost regional climate model

a b s t r a c t A regional climate model with high horizontal resolution (25 km) is used to downscale 20-year-long time slices of present-day (1980–1999) and future (2046–2065, 2080–2099) Arctic climate, as simulated by the ECHAM5/MPI-OM general circulation model under the A1B emission scenario. Changes in simulated air temperature and derived indices at the end of the century indicate that significant impacts on permafrost conditions should be expected. But the magnitude of the change is regionally conditioned beyond what is obvious: Warm permafrost in the sporadic to discontinuous zone is threatened and may degrade or even complete thaw before the end of the century. A decrease in freezing and increase in thawing degree-days is interpreted as potential decrease in seasonal freeze depth and increase in active layer thickness (ALT). We show that for some regions increasing maximum summer temperature is associated with an increase of interannual temperature variability in summer, while in other regions decreased maximum summer temperatures are related to decreased variability. The occurrence of warm/cold summers and spells changes significantly in the future time slices using the present-day criteria for classification. Taken together this implies a regionally varying exposure to significant change in permafrost conditions. In addition to these aspects of the general warming trend that would promote an increase in ALT and a northward shift of the southern permafrost boundary, an analysis of the occurrence of warm summers and spells highlight some particularly vulnerable regions for permafrost degradation (e.g. West Siberian Plain, Laptev Sea coast, Canadian Archipelago), but also some less vulnerable regions (e.g. Mackenzie Mountains). © 2011 Elsevier B.V. All rights reserved.

1. Introduction For the end of the 21st century, the IPCC (2007) projects a mean increase in Arctic annual mean surface air temperature of 5 K (relative to the period 1980–1999) under the A1B SRES emission scenario, with a range of 2.8–7.8 K in the individual global climate models. Such a large warming will likely have profound consequences for many components in the Arctic system (e.g., Hinzman et al., 2005). While the impacts on sea ice and ocean are widely discussed, only few climate modelling studies investigate the possible effects on the circum-Arctic frozen ground (e.g., Lawrence and Slater, 2005; Yamaguchi et al., 2005). The main reason for this is the still very limited and poor representation of frozen ground processes and permafrost-climate interactions in the climate models (Riseborough ⁎ Corresponding author at: Alfred Wegener Institute for Polar and Marine Research, Telegrafenberg A43, D-14473 Potsdam, Germany. Tel.: + 49 331 2882130; fax: + 49 331 2882178. E-mail address: [email protected] (A. Rinke). 0921-8181/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.gloplacha.2011.10.011

et al., 2008). Until recently the transient response of permafrost to projected climate change has usually been modelled using processbased permafrost models driven by climate model-generated climate scenarios (e.g., Sazonova et al., 2004; Anisimov and Reneva, 2006; Romanovsky et al., 2007a; Stendel et al., 2007; Sushama et al., 2007; Marchenko et al., 2008; Zhang et al., 2008). Based on recently improved incorporation of permafrost within a global climate model, Lawrence et al. (2008) discuss severe permafrost degradation during the 21st century, but Sazonova et al. (2004) showed that the spatial extent and temporal dynamics of the thawing permafrost zone vary significantly among different models. Furthermore, analyses of observed data show that the increase of Arctic near-surface air temperature in recent decades are neither spatially nor temporally uniform (e.g., Serreze et al., 2000). Because of a strong correspondence between near-surface air and ground temperature (Romanovsky et al., 2007b) and the spatially heterogeneous surface and ground characteristics of the Arctic, future changes in ground temperature are likely to be even more non-uniform. This points to the usefulness and need of horizontally high-resolution

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simulations, and one of the accepted tools for this is the method of dynamical downscaling with a regional climate model (RCM). However, the land surface schemes in Arctic RCMs and global models (GCMs) in general are still quite simple; e.g. most of the models include only few ground layers in a rather shallow column, lateral flow of water and energy and sub-grid heterogeneity of ground and snow properties are not considered, and interactions between permafrost, snow cover and vegetation are not included (see the review by Riseborough et al., 2008). Because of this limited description of frozen ground processes in Arctic climate models and thus poor direct permafrost simulations, our approach here is to analyze and interpret selected key atmospheric drivers of change in frozen ground without going into the details of the below surface behaviour of the RCM used for the present analysis. Thus, we wish to use atmospheric properties as far as possible to infer information about the drivers of change in sub-soil properties. Using a RCM at a horizontally high-resolution (25 km), we discuss in the present paper circum-Arctic future changes in air temperature and derived indices which are relevant to frozen ground conditions. We emphasize that we limit and focus our analysis on air temperature, precipitation and related measures, although other factors (e.g., snow, vegetation, soil organic layer, hydrology, etc.) are involved in changes of frozen ground as well. The specific goal of this paper is to examine the magnitude and spatial variability in some of the most important air temperature and precipitation-relevant measures that may influence frozen ground conditions within the 21st century, whereby these changes are documented for two future time slices (mid and end of the 21st century). The paper continues in Section 2 with a description of the performed RCM simulations and analysis methods. Afterwards, the results are discussed in Section 3. Finally, Section 4 presents a summary and some conclusions.

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ECHAM5/MPI-OM 20th century simulation covering the period 1860–2000. CTRL describes one realization of the 20th century climate with anthropogenic forcing (greenhouse gases, sulfate), (ii) and (iii) 2046–2065 and 2080–2099 from the ECHAM5/MPI-OM A1B SRES simulation over 2001–2100. These experiments are described in detail at http://www-pcmdi.llnl.gov/ipcc/model_documentation/ECHAM5_MPIOM.htm and referred to by Muller and Roeckner (2006). In our paper the changes “2046–2065 minus CTRL” and “2080– 2099 minus CTRL” are discussed. As we focus here on changes over Arctic land masses, generally all information about glaciated and non-land areas of the model domain have been masked out to increase legibility. In the following analysis, summer covers JuneAugust (JJA) and winter includes December–February (DJF). 2.2. Analysis The most important air temperature and some precipitation-related measures are discussed which determine ground temperature changes and therefore freeze/thaw depths and permafrost distribution.

2.1. Model and simulations

2.2.1. Annual air temperature and snow cover index Air temperature and its variability drive the ground temperature which is an important indicator of frozen ground status. The mean annual air temperature (MAAT) is based on the simulated 2-m air temperature. The continentality is described by the amplitude of the annual cycle in 2-m air temperature and has been calculated as the difference between the mean July and January temperatures. The net insulating effect of snow on ground temperature depends upon various snow characteristics (e.g., timing of the snowfall, duration, thickness, density). To describe an integrated quantity, the snow cover index (SCI) according to Zhang et al. (2001) has been calculated. The SCI integrates the daily snow thickness over winter, and is therewith a combined measure of duration and thickness of snow cover. According to the HIRHAM formulation, a fixed snow density of 300 kg/m 3 has been used to convert the modelled snow water equivalent to snow thickness.

The RCM employed in this study is the HIRHAM model which has been already applied for frozen ground simulations (Christensen and Kuhry, 2000; Saha et al., 2006; Stendel et al., 2007; Rinke et al., 2008). HIRHAM uses the physical parameterization package of the global model ECHAM4 (Roeckner et al., 1996), which includes descriptions of radiation, convection, clouds, planetary boundary layer, gravity wave drag, and land processes. Parameters of the land-surface characteristics are prescribed by the data set of Christensen et al. (2001), whereby the vegetation fraction, leaf area index and background albedo are seasonally varying. The soil model uses a column with a total depth of 10 m (divided into 5 layers) for ground temperature calculation and a bucket scheme for soil moisture. The integration domain covers the circum-Arctic region, i.e. the area north of ~ 60°N. The model is configured at a 25 km horizontal resolution and 19 vertical levels. Several studies demonstrated the good model's skill at capturing the present-day air temperature and its spatio-temporal variability (e.g., Matthes et al., 2010; Rinke et al., 2010). Although the model can also reproduce well the observed spatial patterns of the snow water equivalent, it underestimates its magnitude in the Russian Arctic (Saha et al., 2006). For this study, HIRHAM has been initialized and forced at its boundaries by output of the IPCC AR4 simulations of the global model ECHAM5/MPI-OM (Marsland et al., 2003; Roeckner et al., 2003). Its resolution was T63(~2°)/L31 for the atmosphere, and 1.5°/L40 for the ocean. Forcing at the lower boundary includes sea surface temperature and sea ice concentration, updated daily. The lateral boundaries were updated every 6 h. Three 20-year-long time periods have been downscaled with HIRHAM for the Arctic domain: (i) 1980–1999 (referred to as CTRL) from the

2.2.2. Ground temperature and degree-days Two measures of ground temperature changes are discussed to characterize the changes in permafrost and active layer thickness (ALT): the mean annual ground temperature (MAGT) and the thawing degree-days (TDD) based on the ground surface temperature. The MAGT characterizes the permafrost, whereby the 4 th model soil layer at 2.7 m depth is used, because the 3 rd model layer is at 80 cm depth, which in many cases wouldpstill ffiffiffiffiffiffiffiffiffiffi be within the active layer. ALT is related to TDD via ALT ¼ f  TDD, whereby the factor f characterizes vegetation and soil properties. If one estimates ALT changes assuming no changes in vegetation, as we do in our model approach, ALT changes are described by TDD changes. Additionally, freezing degree-days (FDD) have been calculated to characterize the duration and magnitude of below freezing temperatures. FDD is defined as the sum of the absolute daily-averaged temperatures for all days with temperatures below 0 °C during the freezing season, while TDD sums those with temperatures above 0 °C during the thawing season. We define the period from which FDD is calculated to be July-June, and the period for TDD to be January–December to ensure that the entire cold and warm seasons are captured in the calculations (Frauenfeld et al., 2007). FDD and TDD have been calculated based on the ground surface temperature (temperature of the 1 st model soil layer at 3 cm depth). Due to the fact that the ground surface temperature is used, the effects of both air temperature and snow are taken into account. Saha et al. (2006) presented the HIRHAMsimulated present-day maps of FDD and TDD and showed a good agreement with observations (Zhang et al., 2005). The poor representation of specific permafrost properties in HIRHAM (e.g. Christensen and Kuhry, 2000) does not allow for direct comparison

2. Simulations and analysis

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of modelled ALT to observations and therefore will require an offline calculation either simplified as above or using a more advanced algorithm. Furthermore, modelling active layer in a realistic manner will require great attention to the soil type as texture (incl. organic layer) and moisture play such important roles. Stendel and Christensen (2002) showed how offline calculated ALT vary for different soil types and water contents and therewith provide examples about the great variability in anticipated ALT response using the different land cover and ground types in a model. However, an exhaustive treatment of ALT showing modelled results for regions and soil types is beyond the scope of this paper. 2.2.3. Summer air temperature ALT is significantly influenced by summer air temperature, whereby the interannual variability of thaw depth is driven by the summer air temperature variability. The latter has been computed as the standard deviation of the 20 seasonal means. Extreme summer temperatures are analyzed to cover conditions of extreme thaw depths and permafrost thawing. If TSj is the averaged mean summer air temperature of year j in the 20-year period, the maximum summer temperature has been calculated as TSmax = max(TSj), i.e. it is the single warmest mean summer temperature of the 20 years. Accordingly, the minimum summer temperature is the coldest mean summer temperature in the 20 years, TSmin = min(TSj). It is to note that these are not just late/early years in the 20-year sequences. An individual summer is defined as “warm” if the summer maximum temperature (average of summer daily maximum temperature, TSXj) is above a certain threshold, which is the maximum temperature from the 20 individual mean summer temperatures. Thus, the threshold is the single warmest mean summer temperature of the 20-year period. Let TSj be the averaged mean air temperature of summer j in the 20-year-long period (j = 1,2,…,20), then an individual summer k is considered warm if TSXk > max(TSj). Analogous, a summer is called “cold” if the summer minimum temperature of year k, TSNk, is below the coldest individual mean summer temperature of the 20-year period: TSNk b min(TSj). 2.2.4. Warm and cold spells The occurrence of consecutive warm years is investigated because of their relevance for steadily increasing permafrost temperature and thus for creating favourable conditions for active layer increase and permafrost thawing. Consecutive cold years have been calculated too; they favour decreasing permafrost temperature. Further, we calculate warm-spell years which count the number of years per 20-year-long period where, in intervals of at least 3 consecutive years, the year-maximum air temperature (average of year daily maximum temperature; TX) is above a certain threshold. Let TXj be the averaged maximum air temperature and Tj the averaged mean air temperature of year j in the 20-year-long period (j = 1,2,…,20). To calculate warm-spell years, we count the number of years, in intervals of at least 3 consecutive years, where TXj > max(Tj). Analogous, cold-spell years have been calculated. If TNj is the averaged minimum air temperature of year j, then cold-spell years are the number of years, in intervals of at least 3 consecutive years, where TNj b min (Tj). Thus here, the year-minimum temperature has to be below the coldest of the 20 year-mean temperatures. Three measures of these spells have been calculated: “spells duration” which is the total count of spell years, “number” which is the number of such spell events, and “length” which gives the mean length of the spells. For the calculation of spells on the seasonal scale, the same definitions but with the seasonal temperature have been used. Additionally, warm spells in the thaw period (March-September) are considered. For this, we investigate long-lasting warm (based on an absolute temperature threshold, i.e. daily mean air temperature> 12 °C) spells in the thaw season (defined as the period between the first occurrence of 6 consecutive days with daily mean temperature >0 °C and the first

occurrence of 6 consecutive days with daily mean temperature b 0 °C). Long-lasting signifies that the warm temperature must persist at least over 30 consecutive days. As an absolute threshold is applied we can expect a latitudinal trend in this analysis. 2.2.5. Precipitation On top of temperature extremes, extreme precipitation can trigger frozen ground changes. In this regard, warm-spell years are most important if they are also wet (in summer), because such events could trigger potential permafrost collapse. If cold-spell years go along with a dry summer, those conditions contribute to more effectively decreasing ground temperature. Further, a warm summer is particularly of relevance for the frozen ground state if it follows a snowy winter because the latter establishes a precondition for faster and deeper ground warming and thawing. The extreme precipitation events have been defined as the 75th and 25th percentiles of the seasonal precipitation distribution of the 20-year CTRL time slice. Thus, an individual summer is considered to be “wet” if its precipitation sum is above the 75th percentile calculated from the 20 summer precipitation sums of the CTRL period. Analogous, a summer is “dry” if its precipitation is below the 25th percentile of CTRL summer precipitation. An individual winter is defined as “snowy” if its precipitation is above the 75th percentile of the winter precipitation distribution of the 20-year CTRL period. Additionally we calculated the snowy winters based on the winter SCI distribution. Independently of which of these two variables is applied to identify snowy winters, the results are the same and therefore only those for the SCI-determined snowy winters are presented. 3. Results 3.1. Mean changes between future and present-day climate This section describes the mean future changes, referring to the CTRL climate. Beside the mean changes “future minus CTRL” of the temperature and related indices, also the changes in the occurrence of warm/cold summers and spells are discussed. Their definitions/ thresholds are based here on the CTRL conditions. Therefore, these results emphasize the pronounced overall warming effect in all its aspects relevant to frozen ground changes. 3.1.1. Mean annual air temperature (MAAT) The MAAT provides a rough estimation of permafrost distribution (Brown et al., 1998) and is one factor that controls frozen ground temperature. An increase in MAAT is expected to cause an increase in ALT (Romanovsky and Osterkamp, 1997), especially in the regions with warm permafrost (mean annual temperatures in permafrost between 0 °C and −2 °C), an initiation of permafrost thawing, and a possible move of the outer boundaries of seasonally frozen ground and permafrost northward and upwards in altitude. The projected increase of MAAT is very pronounced within and at the end of the 21st century (Fig. 1). The warming over land is up to 8 K, with marked regional differences. While a warming of more than 4 K is still largely restricted to the Taimyr Peninsula in the mid of the century, the same warming or more occurs over almost all of today's areas of discontinuous and continuous permafrost at the end of the century. Additionally, the air temperature increase is characterized by a distinct seasonality (largest circum-Arctic-mean warming of 10.3 K in winter, smallest warming of 3.4 K in summer, at the end of the 21st century); see details in Rinke and Dethloff (2008). Such notable magnitude in the warming of air temperature is expected to directly impact the ground temperature: considerable winter warming over warm (just below 0 °C) permafrost areas can inhibit the complete freezing of the active layer and promote the formation of taliks, while strong spring warming can accelerate thawing of the seasonally frozen layer. These seasonal temperature increases are projected to occur

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Fig. 1. Upper panel: Simulated annual mean 2-m air temperature changes (K; color) and winter snow cover index changes (cm-day; white dots: decrease, black dots: increase up to 200 cm-day, black crosses: increase over 200 cm-day). Lower panel: simulated change of continentality (K; color), and present-day (CTRL) continentality (K; black isolines). Changes are “2046–65 minus CTRL” and “2080–99 minus CTRL”.

over most of the Arctic permafrost areas, leading to conditions where warming and increase of thickness of the active layer may occur. However, it should be noted that the actual soil temperature changes in those seasons will be also influenced by changes in snow depth and snow cover duration and possible changes in vegetation. 3.1.2. Winter snow cover index (SCI) and continentality Fig. 1 includes the SCI changes which consider the combined effect of changes in duration and thickness of snow cover. The figure shows that the future SCI changes vary in different parts of the Arctic. We calculate an increased SCI over most of the present-day continuous permafrost areas, particularly over Northern and Central Siberia with large areas showing an increase over 200 cm-day at the end of the century. This indicates that in those areas where a pronounced increase of MAAT is calculated, the integrated snow effect is an additional ground insulating effect supporting the ground warming. By contrast, the integrated snow effect over Northern Europe, West Russian Arctic, Southern Alaska and Southern Siberia is a reduced SCI in the future and therefore a reduced winter snow insulating effect. The continentality influences the strength of the warming effect of snow on ground, such that snow has substantially less/stronger impact on the ground warming in maritime/continental areas. In other words, a larger continentality implies a larger warming amplitude of snow insulation effect (Romanovsky, 1987). For that purpose, Fig. 1 presents the simulated future changes in continentality. The changes are relatively moderate (ranging from −4.5 K to + 1.5 K) at the mid

of the century. However, the decrease in continentality is pronounced at the end of the century and associated with a stronger increase in winter temperature than in summer temperature. A decrease in continentality of 3–9 K is simulated over today's areas of discontinuous and continuous permafrost. This may additionally influence the snow insulating effects on top of those caused by the snow depth (SCI) changes. For example, over the West Russian Arctic, the projected decreased SCI reduces the snow insulating effect and thus does not trigger the ground warming in winter. And, the projected reduced continentality goes along the same line and decreases the snow warming effect too. In contrast, both the effects of snow depth and continentality changes on snow insulation counteract over North East Siberia (e.g. Laptev Sea area). There, an increased SCI supports ground warming while a decreased continentality does not, i.e. decreased continentality reduces the strength of the snow warming effect set up by the increased snow depth. Further, warmer winter temperatures may slightly increase the thermal conductivity of snow that also will slightly decrease its warming effect on the ground temperatures. In summary, the effect of air temperature increase on ground warming is expected to vary in a very complex matter in different parts of the Arctic land mass. 3.1.3. Mean annual ground temperature (MAGT) and degree-days (TDD, FDD) Driven by the MAAT changes, a pronounced MAGT warming of up to 8 K at the end of the century is projected (Fig. 2). The figure highlights

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Fig. 2. Upper panel: Simulated annual mean ground temperature changes at 2.7 m depth (K). White dots mark those areas where it is calculated to alter from negative values in CTRL to positive values in future. Middle panel: Simulated changes of thawing degree-days (K; color) and freezing degree-days (K; dashed isolines, increments of 200 K), calculated from ground surface temperature (ground temperature at 3 cm depth); Changes are “2046–65 minus CTRL” and “2080–99 minus CTRL.” Lower panel: Ratio of square-rooted thawing degree-days “future/CTRL”; black isolines: “2046–65/CTRL” and color: “2080–99/CTRL”.

also those areas where MAGT is projected to alter from negative values at present to positive values in the future. This temperature change is calculated over present-day sporadic and discontinuous permafrost areas indicating that there the upper-layer of permafrost is expected to become unstable and start thawing and degrade, particularly at the

end of the century. The calculations of area where MAGT changes from below to above 0 °C indicate a 10% (20%) loss in near-surface permafrost extent by the mid (end) of the 21st century. The simulations show significant changes in both FDD and TDD (Fig. 2). FDD are projected to decrease by almost half at the end of

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the century compared to present-day. And by means of Fig. 1 it becomes clear that the large-scale temperature changes basically control the FDD. By contrast, the TDD increase exhibits distinct regional-scale variations, mainly associated with the proximity to the Arctic Ocean coasts and with topography, where cold ocean waters and high mountain ranges attenuate the increase in TDD. For example, a less severe increase in TDD is projected for the Mackenzie Mountains and Brooks Range in North America as well as the Ural Mountains and the Verkhoyansk and Chersky Ranges in Russia, suggesting the frozen ground there might be less impacted by warming air temperatures. Considering the overall range within the circumArctic domain, the TDD are projected to increase by 30% to 70% (over lowland) to 100% to 130% (over mountains) at the end of the century. Averaged over the Arctic land area, TDD are projected to increase by a third at the end of the century. Hence, according to the TDD-ALT relationship (Section 2.2.2.), ALT is expected to increase by the factor of 1.14. Fig. 2 shows the detailed regional patterns of the estimated ALT ratio (again based on the square-rooted TDDs) between future and present-day simulations. It indicates that ALT is projected to increase regionally differentiated by a factor ranging from 1.2 to 2 by 2100. The lower values are found over eastern Siberian lowland, northern Canada, western Russia, and northern Europe, while the more vulnerable regions are the western Siberian lowland, mid Siberian highland, far eastern Siberia, parts of Canadian Archipelago, and Alaska. Applied to potential frozen ground changes, the calculated changes in FDD and TDD indicate a decreased seasonal freeze depth (mainly controlled by an increase in winter air temperature and snow depth) and an increased ALT (especially in response to summer air temperature increase). These projections are in line with recent observed trends (e.g., Osterkamp, 2005; Romanovsky et al., 2007b). 3.1.4. Summer air temperature Ground temperature and ALT are influenced by summer air temperature, although the thickness and duration of the late snow cover (especially in the areas with warm permafrost) and local factors (microtopography, vegetation cover, soil characteristics, etc.) play an important role as well. Warmer summer air temperatures in the future are expected to thicken and warm the active layer during summer, which could cause significantly later or incomplete freeze-up of this layer in winter. 3.1.4.1. Interannual variability in summer. In the top ground layer where seasonal freezing and thawing occur, the summer air temperature variability drives the interannual variability of thaw depth. Particularly in the mid-century where the mean summer temperatures

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over land may increase moderately (by 1–4 K), a changed temperature variability affects the maximum/minimum values of thaw depth. Even if by the end of the century the warming will be dominant (3–6 K), changes in summer air temperature variability affect ALT interannual oscillations. The inspection of the change in the interannual air temperature variability in summer (Fig. 3) indicates an increased variability (by up to 1 K) over most parts of Siberia and Alaska/Northern Canada for the middle of the century. A decreased variability over Northern Europe and West Russian Arctic (up to − 2 K) for the same period is found, and also at the end of the century, but there with a smaller magnitude. At the end of the 21st century all the present-day areas of continuous permafrost show an increased interannual variability of summer air temperature, which may be favourable for a higher variability in thaw depth, especially over Northern Canada, Northern Alaska and the Laptev Sea coastal area. Increase in ALT variability may increase the probability of extreme thaw depths in some particular summers increasing the probability for involving the upper permafrost into seasonal thaw. If this upper permafrost is ice-rich, which is often the case, the increase in probability of thermokarst initiation and increase in intensity of thermo-erosion, landslides and other slope processes should be expected even in the regions with relatively cold permafrost. This probability will increase even more with time because of the predicted general long-term positive trend in ALT in response to climate warming. Generally, our high-resolution maps highlight the distinct spatial variation of the changes in interannual summer air temperature variability. As a result, a regionally strongly divergent change in the interannual variability of thaw depth can be expected. It is difficult to attribute these considerable regional-scale differences in the change of air temperature variability ultimately to a specific physical process or changes of the land surface. Over Europe and globally, it has been discussed that increased temperature variability over land may be attributed to reduced soil moisture so that reduced evaporative cooling allow more extreme warm events (e.g., Kharin and Zwiers, 2005; Rowell, 2005). This is what is seen here over Northern Canada and parts of Siberia (e.g. Central Siberian Upland) and oppositely (increased soil moisture, decreased temperature variability) over Northern Europe and West Russian Arctic (see Fig. 3). Further and more generally, complex feedbacks between land surface and atmosphere have been identified to influence the climate change signal (Seneviratne et al., 2006). 3.1.4.2. Maximum and minimum summer temperatures. The extreme (maximum/minimum) thaw depth corresponds to the extreme (warmest/coldest) summer air temperature. Thus, a warming of

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Fig. 3. Simulated changes of interannual variability of summer air temperature (K); “2046–65 minus CTRL” and “2080–99 minus CTRL.” The present-day (CTRL) values are shown as black isolines. Grid points where soil moisture decreases (increases) by more than 20 mm are marked with black (white) dots.

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extreme air temperature would potentially lead to increased extreme thaw depths affecting the transitional and upper permafrost layers, and permafrost may start to thaw. These considerations are particularly important for the relatively warmer discontinuous permafrost zones. The calculated future change in the maximum summer air temperature indicates both increase and decrease (Fig. 4), which conforms with its strong interannual variability in the considered time slices (not shown). At the mid-century, an increase of maximum summer temperature by 3–6 K is calculated over parts of Alaska, the Central Canadian Arctic and the eastern and western Central Siberian Plateau, while a decrease by up to − 2 K is found over the West Russian Arctic. These positive/negative temperature changes are associated with increase/decrease of interannual temperature variability (Fig. 3). At the end of the 21st century, the increase of maximum summer temperature is more widespread. Its increase is stronger in the East Russian Arctic, compared to the mid-century changes. The changes are very moderate over the West Russian Arctic. The minimum summer temperature is generally projected to increase in the circum-Arctic area, whereby the magnitude accelerates towards the end of the century (Fig. 4). Then, the strongest increase of 4–6 K is calculated over the eastern and western Central Siberian Plateau, Mackenzie, Brooks and Alaska mountains. The underlying reason is the decrease of snow cover and associated albedo decrease in these mountains. For some areas of permafrost like the region of the East Siberian river plains, both maximum and minimum temperatures are projected to slightly increase, creating moderately favourable

conditions for a more extensive thaw depth. Over the Mackenzie Mountains and the Brooks Ranges, both maximum and minimum summer temperatures are projected to increase rather strongly, implying conditions favourable for an increase in extreme thaw depth at the end of the century. 3.1.4.3. Occurrence of warm and cold summers. Warm summers are characterized by an intensified thaw season, larger than normal thawing degree-days and are often accompanied by an early spring snow melt. Among others, the response in the frozen ground includes the warming of the surface and the deepening of the active layer. For a cold summer opposite effects are expected. Further, changes in the frequency of occurrence of warm and cold summers could affect oscillations or trends of ALT and may affect the timing of initiation of longterm permafrost thaw and talik formation. Fig. 5 shows that in CTRL climate, 30-50% of all summers are warm in most parts of Alaska and parts of Siberia (northern Taimyr Peninsula, Lena delta, Yano-Indigirka plain) (see also CTRL-plot in Fig. 7 which has a finer scale). Further, the results indicate the strong increase of occurrence of warm summers in the future. The spatial patterns of change are closely connected with those of the maximum summer temperature changes (Fig. 4). In almost all Arctic regions, all summers are considered to be warm at the end of the century. The only exception is northern Europe and West Russian Arctic, where about half of the years are warm, associated with the small changes in maximum summer temperatures (Fig. 4). Cold summers

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Fig. 5. Simulated frequency of occurrence (%) of warm summers, for CTRL, 2046–65, and 2080–99. Threshold to define warm summers is from CTRL (see Section 2.2. for definition).

do not appear anymore in the future time slices (not shown), because the future summer minimum temperature is above the coldest mean summer temperature of CTRL everywhere in the domain.

Consecutive warm years are most important if they are also wet (in summer), because such events could trigger potential permafrost collapse. Fig. 6 clearly demonstrates that all future summers are projected to be wet.

3.1.5. Warm and cold spells

3.1.5.2. Warm spells in the thaw period. For the active layer, warm spells in the thaw period (March–September) rather than in the year or season are additionally considered (see Section 2.2.4). In CTRL climate, maximum occurrence of spells (10–40 days) is found over the lowlands, particularly over the Mackenzie and Lena Basins and the West Russian Arctic (Fig. 6). In the mid-century time period, the spells are significantly increased by up to 30 days over the present-day maximumspell regions and by up to 10 days over the other areas. At the end of the century, the total account of these long-lasting warm spells are projected to significantly increase (by more than 40 days in selected regions) almost everywhere in the circum-Arctic area, and the mean length of individual events increases by 5–25 days. Especially along the Mackenzie River, over the West Russian Arctic and in Central Siberia, areas with discontinuous permafrost are projected to show an increase in these long-lasting warm conditions and therefore ground temperature and ALT are expected to further increase there.

3.1.5.1. Warm and cold spells on a yearly scale. Of interest here are warm and cold spells on a yearly scale. Their connection to frozen ground changes is that consecutive warm years could steadily increase permafrost temperature and thus trigger permafrost degradation, while consecutive cold years could decrease permafrost temperature and thus stabilize permafrost, which is probably most important for areas of relatively warm, more discontinuous permafrost. In CTRL climate, extreme events of warm and cold spells are found infrequently (Figs. 6 and 9). Warm spells are found over the West Siberian Plain, Central Siberian Plateau, and east of the Lena River. They are characterized by a total of 3–10 years, which occur in a maximum of 3 events, and have an average length of 2–5 years. Interestingly, the regions of warm spell occurrence agree with the regions of high continentality (difference between July and January temperature >45 K; Fig. 1). The cold spells occur over different regions (maritime-influenced regions), namely over northern Europe, parts of Alaska, West Russian Arctic and south-east Siberia, but their characteristics (total number of 3–8 years, 1–3 events, length of 3–4 years) are quite similar as for the warm spells. Fig. 6 shows significant changes of warm spells in the future. Due to the pronounced general warming (see Figs. 1, 2, 4), the year-maximum temperatures of all the years in the future time slices are already in the mid century above the warmest year-mean temperature of the CTRL period. Therefore, all the 20 years in the future time slices compose the warm spell. The most notable exception is Alaska in the mid century; there the warm spells increase by 6–15 years. This may be due to the fact that this region exhibits the highest variability of air temperature in the mid-century time slice. At the end of the century the threshold (the warmest year-mean temperature of the CTRL period) is also exceeded in this area. No further cold spells have been calculated in future (not shown), i.e. there are no more events of at least 3 consecutive cold years where the actual year-minimum air temperature is below the coldest year-mean temperature of the CTRL period. This is in agreement with the earlier finding that the warming of the minimum temperature is higher than that of the maximum temperature (Rinke and Dethloff, 2008).

3.2. Regional amplification processes in future While the previous Section 3.1 describes the distinct mean future warming aspects expected to be linked with significant frozen ground changes, this section investigates such conditions which contribute to amplify (or dampen) increase in ALT due to this future warmer climate state. The strong warming effect initiates a mean climate shift (see Section 3.1), and here in Section 3.2 we consider such effects which could further trigger or amplify the warming of the ground. Therefore, here the changes in the occurrence of warm/cold summers and warm/cold spells are discussed differently to Section 3.1. Here, their definitions/thresholds in the future time slices are based on the mean climate conditions for each of these future time slices (and not on CTRL like in Section 3.1.) to cover the new climate state (e.g. a summer is “warm” in relation to other summers occurring in the same time period). As in general the threshold for e.g. warm summer is higher in future time slices than in CTRL, positive changes “future minus CTRL” in the following figures indicate those areas which are particularly vulnerable. Thus, by applying the appropriate changed thresholds for the future climate indices, their regional-scale future changes on top of the massive climate shift (with respect to the CTRL threshold)

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become resolved. For example, all years in Siberia are classified as warm (with respect to the CTRL threshold) in the future time slices, so that all spatial variability in the climate change signal of warm spells is solely attributed to their spatial variability in the CTRL period (Fig. 6). But the following figures emphasize the most vulnerable regions in future. 3.2.1. Summer air temperature 3.2.1.1. Occurrence of warm and cold summers. The future projections calculate for some of the places with maximum occurrence of warm summers in CTRL (Alaska, parts of Siberia like northern Taimyr Peninsula, Lena delta, Yano-Indigirka plain) a drastic reduction of their occurrence by 20–30% (Fig. 7). The figure further shows pronounced future changes in the frequency of occurrence of warm summers for areas like northern Europe, West Russian Arctic, Mackenzie and Yukon delta, and parts of East Siberia characterized by a maximum of 1–3 warm summers in 20 years (5–15%); here the projections calculate an increase of occurrence of up to 30%. The frequency of cold summers is projected to change by the range from − 30% to +30%, whereby again spatially non-uniform responses become obvious

(Fig. 7). The climate change signal is clearly non-linear: Considering the changes in the mid-century time slice, there are areas (e.g. central Alaska) characterized by increase/decrease of occurrence of cold/ warm summers, while other areas (e.g. Indigirka plain, West Russian Arctic) show an increase of occurrence of both warm and cold summers. While it is therefore difficult to assign definitive areas of favourable conditions for amplifying the active layer deepening, it is obvious that the projected changes exhibit a high spatial variability. 3.2.1.2. Occurrence of warm summers following a snowy winter. A warm summer is particularly of relevance for the frozen ground state if it follows a snowy winter because the latter establishes a precondition for faster and deeper ground warming and thawing especially in the warm permafrost. The insulating snow effect prevents strong cooling of ground temperature and constrains the freeze depth in nonpermafrost regions. Furthermore, in the areas with fine-grained soils, by the end of such snowy winter, frozen active layer still contains a significant amount of unfrozen water (up to 15–20% in discontinuous permafrost regions) and is much more susceptible to thaw during the following summer (Romanovsky and Osterkamp, 2000).

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As expected, the comparison of Figs. 7 and 8 shows that the occurrence of such coincident extreme events (warm summer following a snowy winter) are again much more rare than the occurrence of only warm summers. In CTRL climate, this happens in only 4 of 20 years (20%) in parts of Siberia, the Canadian Arctic and Alaska. Compared to the future changes of warm summer occurrence, the changes here are more moderate (mostly within ±20%). At the end of the century, there are more “snowy winters”–“warm summers” combinations in northern Alaska and Canada, and East Siberia which points to an amplification of ground warming and thawing there. 3.2.2. Warm and cold spells Fig. 9 shows significant changes in spells for the future. At the end of the century, both the warm and cold spells are reduced (by 2–8 years) or even disappeared over those regions where presently the maximum spells are found. Spells are projected to establish over different regions. Warm spells increase (by 2–4 years) over the West Siberian Plain, along the Laptev Sea coast, and Canadian Archipelago, while cold spells (2–6 years, 1–2 events, length of 2–4 years) occur over the Central Siberian Plateau and north-west

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Canadian Arctic, at the end of the century. In the mid century, warm spells are mainly projected to move from lowlands to mountain ranges. The comparison of the two future time slices emphasizes the highly non-linear behaviour of such extreme event changes. As already pointed out (Section 2.2.5.), consecutive warm years are most important for permafrost changes if they are also wet (in summer), and if consecutive cold years go along with a dry summer. Fig. 9 demonstrates that the areas with future increased or newly established warm spells are wetter in summer in the future. This can be seen in both future periods, and describes a potential increased risk of frozen ground changes over West Siberian Plain, along the Laptev Sea coast, and Canadian Archipelago, whereby these areas are presently characterized by a relatively shallow active layer that usually does not exceed 1 m (CALM network, http://www.udel.edu/ Geography/calm/data/north.html). The areas with future increased or newly established cold spells are drier in summer in the future. Thus, no amplifying effects for increasing ALT on the top of the general warming are projected to occur in the Central Siberian Plateau. The analysis of the warm/cold spells on the seasonal scale indicates most pronounced changes in spring and summer (not shown).

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Fig. 8. Simulated frequency of occurrence (%) of warm summers following a snowy winter; for CTRL, and changes “2046–65 minus CTRL” and “2080–99 minus CTRL.” Threshold to define warm summers is different for each time slice (see Section 2.2. for definitions).

At the end of the century, summer warm spells are projected to increase by 2–4 years over northern Europe, southern Alaska, and Northern Canada, and spring warm spells are calculated to increase by 2–8 years over East Siberia (territory east of the Lena River). The significant changes in the cold spells show an increase by 1–2 years over southern Alaska in summer and by 1–3 years over the Central Siberian Plateau in spring. 4. Summary and conclusions In using the RCM HIRHAM, we have focussed on the controlling role of changing air temperature, key temperature-related measures and coactive temperature-precipitation factors (warm summer following snowy winter; consecutive warm/cold years if they are also wet/dry) in conditioning future changes in permafrost conditions. Again, we underline that we have not investigated specifically how these drivers of change impact permafrost in the model, simply because we do not think the HIRHAM parameterization justify any conclusions based directly on the modelled soil developments. Therefore, our conclusions about potential frozen ground changes should be considered with some care, because other factors (e.g., snow depth and timing, vegetation, hydrology, etc.) are equally important. Recently it has also been discussed that potential permafrost changes are subject to varying lag times with depth (e.g. Burn and Nelson, 2006; Lawrence et al., 2008), and ice-rich cold permafrost may be quite resilient to thaw (Froese et al., 2008). Further, we refer to the fact that the global warming patterns vary greatly between different GCMs and that the discussed regional manifestations are based on one GCM and RCM run only. Our results highlight the spatially non-uniform responses of atmospheric drivers relevant for frozen ground conditions to climate change in the Arctic. While it is well known that global warming with the associated Arctic amplification pose a certain threat towards degrading and even complete or partial thaw of permafrost in many regions, the regional manifestations of global warming are difficult to assess using global models. The presented horizontally highresolution circum-Arctic future climate change simulations indicate pronounced and geographically varying changes in temperature and precipitation related indices. The annual air temperature-driven ground warming is modulated by the net insulating effect of snow on ground temperature. Positive and negative changes in SCI over different regions have been calculated, promoting or dampening permafrost degradation. The former

case is calculated over most of the present-day continuous permafrost areas, particularly over Northern and Central Siberia (over 200 cmday SCI increase at the end of the century), while the other occurs over Northern Europe, West Russian Arctic, Southern Alaska and Southern Siberia. The changes in FDD and TDD reflect the changes in temperature. The changes in FDD are in many areas double those for TDD because winter temperature changes are roughly double the summer changes. However, the change in winter air temperatures does not solely control the conditions of the soils due to the effects of snow cover, hence tying the changes in the summer temperatures to the simple ALT indicators. A strong increase (5–8 K) in MAAT is accompanied by a decrease in continentality (3–9 K) over today's areas of discontinuous and continuous permafrost at the end of the century. Changes in MAAT and degree-days in the order of those that have been calculated in this study can be expected to significantly affect frozen ground conditions. Particularly the areas of relatively warm (close to 0 °C) discontinuous permafrost are expected to be sensitive to those simulated climate changes. However, the highest annual temperature increase is calculated for coastal and inland continuous permafrost areas like Taimyr Peninsula, Victoria Island and northern Alaska and Siberia. These areas are underlain by cold and continuous permafrost and hence this strong warming is not likely to be as great a threat to the integrity of permafrost as it would have been if occurring further southwards. Lower FDD and higher TDD can both be interpreted as drivers of a decrease in seasonal freeze depth and increase in ALT. For ALT, future changes in summer air temperature are also quantified by means of different measures (interannual variability, maximum/minimum temperatures, warm/cold summers). We have seen that positive/negative maximum summer temperature changes are associated with increase/decrease of interannual temperature variability in summer. While changes in the maximum temperature are projected to vary geographically, related to its strong interannual variability, the minimum summer temperature is projected to increase in the entire circum-Arctic area. The latter favours an increase in thaw depth everywhere, once the permafrost is warmed, while the former locally will be a buffer against widespread thaw depth increase if maximum temperature is decreasing. An increase in extreme thaw depth is favoured locally there where both the minimum and the maximum temperature increase. We have also demonstrated that pronounced changes in both frequency of occurrence of warm/cold summers and consecutive warm/cold years (spells) using the modelled present-day is controlling permafrost conditions. All summers are

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Fig. 9. Simulated warm and cold spells (years) on yearly scale; for CTRL, and changes “2046–65 minus CTRL” and “2080–99 minus CTRL.” White/black dots mark those areas where summers are wetter/drier in future. Threshold to define warm/cold spells is different for each time slice (see Section 2.2. for definitions).

considered as warm at the end of the century, except for northern Europe and West Russian Arctic associated with the small changes in maximum summer temperatures there. Cold summers do not appear in any of the future time slices. Further, the thresholds for warm and cold spells are exceeded at the end of the century, so that warm spells are composed by all years and cold spells do not appear anymore. Besides these general warming trend aspects that would promote an increase in ALT and a northward shift of the southern permafrost boundary, the additional analysis of future changes using the mean conditions for the warmer climate (i.e. using the future criteria to define warm/cold years and spells) highlights some particularly vulnerable regions (West Siberian Plain, Laptev Sea coast, Canadian Archipelago) which are projected to be warmer, to experience increased warm spells and to be wetter in summer; all this contributes to amplify the permafrost degradation initiated by the general warming trend. Other regions show no such combined effects. For example over the Mackenzie Mountains, while both minimum and maximum summer air temperatures increase strongly, pointing to increased thawing depths, the competing decrease in warm summers concurring with an increase in cold summers would dampen the thawing.

In conclusion we note that the detailed geographical setting of a region is preconditioning the potential changes in permafrost conditions towards a fast or slow response to a global warming signal. We have identified regions, where competing drivers based on air temperature will prevent a fast degradation of permafrost (e.g. the Mackenzie Mountains) and similarly there are regions where all drivers pull in the same direction (e.g. the West Siberian Plain). Therefore, we propose that simulations of future change in permafrost conditions based on either direct climate model output or from an offline permafrost model should qualify the projected change in the context of understanding the likely future variability in the light of past changes and variability. The different temperature and precipitation 'indicators' analyzed here can assist the monitoring changes in permafrost conditions. In principle, the analysis could be repeated with observations, satellite-based or from stations, and then permafrost responses can be investigated. So we propose that the results from this work may be used to design experiments or data analysis based on new or existing drilling sites with subsurface temperature information made available.

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