The role of terrestrial snow cover in the climate system
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- Vavrus, S. Clim Dyn (2007) 29: 73. doi:10.1007/s00382-007-0226-0
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Snow cover is known to exert a strong influence on climate, but quantifying its impact is difficult. This study investigates the global impact of terrestrial snow cover through a pair of GCM simulations run with prognostic snow cover and with all snow cover on land eliminated (NOSNOWCOVER). In this experiment all snowfall over land was converted into its liquid–water equivalent upon reaching the surface. Compared with the control run, NOSNOWCOVER produces mean-annual surface air temperatures up to 5 K higher over northern North America and Eurasia and 8–10 K greater during winter. The globally averaged warming of 0.8 K is one-third as large as the model’s response to 2 × CO2 forcing. The pronounced surface heating propagates throughout the troposphere, causing changes in surface and upper-air circulation patterns. Despite the large atmospheric warming, the absence of an insulating snow pack causes soil temperatures in NOSNOWCOVER to fall throughout northern Asia and Canada, including extreme wintertime cooling of over 20 K in Siberia and a 70% increase in permafrost area. The absence of snow melt water also affects extratropical surface hydrology, causing significantly drier upper-layer soils and dramatic changes in the annual cycle of runoff. Removing snow cover also drastically affects extreme weather. Extreme cold-air outbreaks (CAOs)—defined relative to the control climatology—essentially disappear in NOSNOWCOVER. The loss of CAOs appears to stem from both the local effects of eliminating snow cover in mid-latitudes and a remote effect over source regions in the Arctic, where −40°C air masses are no longer able to form.
The most extensive component of the cryosphere, terrestrial snow cover is also the most rapidly and seasonally changing cryospheric variable (ACIA 2005). A snow pack strongly influences the overlying air, the underlying ground, and the atmosphere downstream. Many of these first-order effects are described by Cohen and Rind (1991), who emphasize the major thermodynamic influences of snow cover: high albedo, high emissivity, low thermal conductivity, and latent heat sink. The effect of snow cover on the atmospheric circulation has been investigated for purposes of seasonal forecasting (Cohen and Entekhabi 1999, 2001). In addition, the ecological and hydrological impacts of snow cover are important for environmental and water-resource issues (Campbell et al. 2005; Mote et al. 2005). Furthermore, recent and anticipated reductions in snow cover due to future greenhouse warming are an important topic for the global change community (IPCC 2001).
Many prior studies have investigated the physical basis for snow cover effects on climate. Early observational work found that snow cover can decrease the lower-tropospheric temperature locally by several degrees over days to months (Namias 1962; Wagner 1973; Dewey 1977). Subsequent modeling studies by Walsh et al. (1982) and Walsh and Ross (1988) demonstrated that excessive snow cover is associated with near-surface cooling of 5–10 K confined to the lower troposphere (up to 500 hPa), related to large-scale atmospheric circulation modes such as the Pacific-North American (PNA) pattern, and more influential to the planetary circulation over Eurasia than North America. Similar conclusions regarding the especially strong influence of Eurasian snow cover were reported by Foster et al. (1983), Walland and Simmonds (1997), and Yasunari et al. (1991). Idealized simulations by Barnett et al. (1988) corroborated the empirical evidence of Blanford (1884) that the Asian summer monsoon is affected by antecedent continental snow cover and also showed that Eurasian snow cover induces a downstream pressure response over North America. The dynamical influence of modeled Eurasian snow cover anomalies was later examined by Watanabe and Nitta (1998) and Clark and Serreze (2000), who found that the largest upper-air height response occurs downstream over the North Pacific Ocean.
These linkages between snow cover and atmospheric circulation have motivated efforts to forecast seasonal climate on the basis of snow cover anomalies. Cohen and Entekhabi (1999) reported that excessive summer–autumn snow coverage over Eurasia favors unusually cold winters over Western Europe and the eastern US, due to forcing of the negative phase of the Arctic Oscillation (AO). Subsequent studies by Cohen and Entekhabi (2001), Saito et al. (2001), Gong et al. (2003a, b), and Cohen and Saito (2003) refined the physical basis of this relationship: early-season snow cover anomalies trigger vertically propagating planetary waves that quickly alter the stratospheric polar vortex, whose anomalous strength then propagates downward to affect the surface annular mode during the course of the winter.
In addition to its possible role as a climate predictor, the ecological and societal impacts of snow cover are of considerable interest because of how a snow pack affects wintertime herbivores, the temperature of the underlying soil, and the magnitude and timing of river runoff. Rain falling on snow cover can cause large ungulate mortality due to surface icing, which animals cannot penetrate, and these rain-on-snow events are projected to become much more common in a warming climate (Putkonen and Roe 2003). Deer mortality also tends to increase during years of heavy snow, due to the similar foraging difficulties it poses (Tatatsuki et al. 1994). The low thermal conductivity of snow makes it an excellent insulator of the ground, resulting in soil temperatures up to 15 K warmer below a snow pack (Mölders and Walsh 2004). Ground temperatures beneath snow cover can be influenced as much by the snow as the overlying air temperature, as demonstrated by Stieglitz et al. (2003), who attribute half of the rise in the 20-m soil temperature at Barrow, AK to locally increasing snow cover since the 1970s. The insulating ability of a snow pack allows a surprising amount of ecological activity to occur during winter, much of which happens in the soil, where temperatures can remain high enough to support a wide range of biotic activities (Campbell et al. 2005). Warmer winters may actually result in colder soils because of snow cover reductions, based on field studies in which snow is manually removed from test plots. Such experiments have been conducted in New England over several winters by Groffman et al. (2001) and Decker et al. (2003), who observed lower soil temperatures and increases in soil freezing where snow cover is absent. The associated consequences were reported to be greater root mortality, more nutrient losses, and decreased productivity of certain tree species. Water resources in snowy climates are directly affected by both the presence and timing of snow cover. Mote et al. (2005) report declining mountain snow packs in western North America since 1950 and warn that projected reductions in future snow cover “will have profound consequences for water use”. Similarly, Barnett et al. (2005) conclude that future water supplies may be hindered by a warmer climate producing less snowfall and earlier seasonal melting. Both of these changes would thwart efforts to capture runoff, because most the early meltwater would exceed reservoir storage capacities and would no longer be available during the higher-demand periods in summer–autumn.
Terrestrial snow cover is expected to decrease in concert with greenhouse warming, and there are signs that such trends have already begun. Groisman et al. (1994) noted a retreat of North American springtime snow cover associated with strong warming during the previous decades, consistent with subsequent observations of earlier springtime snow melt over western North America (Stewart et al. 2005) and longer-term declines in Northern Hemisphere snow cover extent since the early twentieth century (Brown 2000). The extent of boreal snow during spring and summer was lower during the 1990s than at any time in the past 100 years (IPCC 2001). Climate models project continued decreases during this century, ranging from 5 to 15% over North America during the twenty-first century (Frei and Gong 2005) and up to 26% over the entire Northern Hemisphere (Dery and Wood 2006).
The purpose of this paper is to estimate the climatic impact of terrestrial snow cover on a global scale. This effort assesses the role of snow cover in the present climate and provides insight into how altered snow cover patterns may affect future climate. Thus, the snow-removal experiment described here is not intended merely as a “what if” pursuit, but rather as a means to quantify the influence of an important component of the climate system. This approach is similar to the numerous sea-ice removal simulations intended to evaluate the impact of ice cover on climate (Fletcher et al. 1973; Royer et al. 1990; Simmonds and Budd 1991; Bromwich et al. 1998) and a forest-removal experiment to quantify the climatic role of trees (Renssen et al. 2003). Prior studies of snow cover have also attempted to quantify its role, using the empirical and modeling approaches described above, as well as through statistical methods (Klein 1983, 1985; Klein and Walsh 1983; Walsh et al. 1985). While useful in shedding light on the role of snow cover, this earlier work has been limited in spatial and temporal extent. Model simulations of prescribed enhancements or reductions of snow cover have been done over specified regions based on observed fluctuations and over short (monthly-seasonal) time periods (Walsh and Ross 1988; Barnett et al. 1988; Cohen and Rind 1991; Walland and Simmonds 1997; Watanabe and Nitta 1998; Gong et al. 2004). The present study is unique in its radical approach of suppressing terrestrial snow cover at all locations and all times, so that the total climatological impact of snow cover can be evaluated. While obviously idealized, this tack is useful for assessing the global and time-mean influence, rather than the smaller-scale and shorter-term effects of snow cover anomalies examined in previous studies. This study also provides an upper-bound estimate of the impact of snow cover reductions to occur from anthropogenic warming, in which the positive snow-albedo feedback has been identified as a key process in amplifying the warming signal (ACIA 2005; Hall 2004).
A description of the model and experimental design is given in the following section. Section 3 includes an evaluation of the simulated snow cover in the control run and the major climatic changes that ensue from the removal of snow cover in the experiment. An interpretation of the results is presented in Sect. 4, along with caveats and implications for climate change. Conclusions are found in Sect. 5, which summarizes what the experiment implies for the role of snow cover in the present-day climate system.
2 Model description and simulations
NCAR’s Community Climate System Model, version 3 (CCSM3) is a fully coupled global climate model with components representing the atmosphere, dynamical ocean and sea ice, and land surface (Collins et al. 2005). The configuration used here employs a T42 atmospheric and land grid (approximately 2.8°× 2.8°), with approximately 1° resolution for the ocean and sea ice. The atmospheric component contains 26 levels in a hybrid-sigma pressure coordinate system. The land model, which contains ten sub-surface soil layers, exchanges energy, mass, and momentum with the atmosphere but does not allow changes in vegetation composition [although an optional dynamical global vegetation model does exist (Bonan and Levis 2005)].
This paper describes two parallel simulations to assess the global impact of terrestrial snow cover, using recent (1990) concentrations of greenhouse gases. The control run uses model-predicted snow cover over land and sea ice, whereas terrestrial snow cover is suppressed except on glaciers and ice sheets in the experiment (NOSNOWCOVER). Because this study is focused on the role of terrestrial snow cover, sea ice regions are not subjected to snow cover suppression. The climatic impact of snow cover on sea ice is probably quite different and more complex than that over land, because of competing thermodynamic influences of snow albedo and insulation on snow-covered ice packs (Maykut and Untersteiner 1971).
In NOSNOWCOVER, the snowfall generated within the atmospheric model was not altered, but all frozen precipitation was immediately converted into liquid–water equivalent upon reaching the land surface. This procedure avoids artificial latent heat effects in the atmosphere, compared with the alternative method of converting snowfall into rainfall before it reaches the ground, and ensures conservation of water. After the liquid–water-equivalent snowfall is applied to the land surface, the model predicts whether the water runs off, percolates into the soil, or ponds on the surface (details of the model’s land hydrology are found in Oleson et al. 2004). The model does not keep track of the temperature of melt water, but rather assigns the temperature of soil water to be that of the surrounding soil layer. Thus, melt water can percolate into the ground and refreeze, releasing latent heat as it does so. This process warms the soil, introducing an artificial heating term in NOSNOWCOVER, but the alternative treatment of warming snowfall to the melting point upon reaching the surface also fails to conserve energy. Fortunately, the effect of this artificial latent heating appears to be small, for it will be shown that soils cool dramatically in the absence of overlying snow cover (Sect. 3.2). The only other coding change in NOSNOWCOVER was to override part of the model’s canopy radiation module, which assumes that any standing water on leaves is snow when the canopy temperature is below freezing. In this experiment, such standing water is assumed to be liquid regardless of the temperature of the canopy.
The NOSNOWCOVER simulation was run 35 years, the first 15 of which were a transition to a new equilibrium and the final 20 were used for calculating the new climate state. The rapid adjustment time of the atmosphere and upper ocean is attributable to the (snow cover) forcing occurring only during certain times of the year and over a relatively small fraction of the globe that has a low heat capacity. A corresponding 20-year interval from the end of a long (1,000 year) control simulation was used for comparison to quantify the differences caused by the absence of snow cover.
3.1 CCSM3 snow coverage in control simulation
3.2 Results of NOSNOWCOVER simulation
Global and hemispheric statistics for the control and NOSNOWCOVER simulations. CAO days are defined relative to the control run’s climatology
Global surface air temperature annual (K)
NH extratropical land surface air temperature DJF (K)
NH extratropical upper-layer soil temperature DJF (K)
NH extratropical land surface air temperature JJA (K)
NH extratropical upper-layer soil temperature JJA (K)
NH sea ice cover (106 km2)
SH sea ice cover (106 km2)
NH extratropical permafrost fractional coverage
NH extratropical upper-layer soil moisture (m3/m3)
CAO days/year (Asia)
CAO days/year (Europe)
CAO days/year (N. America)
Monthly surface air temperature change averaged over the Northern Hemisphere in NOSNOWCOVER
Air temperature change (K)
In addition to this local thermodynamic role in accentuating Arctic air mass migrations, snow cover also seems to affect CAOs by altering the general circulation. In NOSNOWCOVER the anomalous upper-air flow over the western half of North America during winter becomes decidedly southerly (Fig. 10). By contrast, the equatorward migration of Arctic air masses into the continental US is known to be most likely when the upper-air circulation is precisely the opposite: a northerly flow pattern formed by a ridge (trough) over western (eastern) North America, such as the positive PNA pattern (Konrad 1998). In addition, the large reduction of average surface pressure during winter in NOSNOWCOVER over the Arctic air mass source region of North America (Alaska and the Yukon) (Fig. 9) is not conducive to the powerful polar anticyclones that drive extremely cold air into the contiguous US during CAOs (Dallavalle and Bosart 1975). The same kind of argument holds for Eurasia, where lower mean surface pressure suggests a reduction in very strong polar anticyclones that would drive Arctic air into Europe. Indeed, the frequency of the most powerful anticyclones that form over northern Siberia (>1,040 hPa) decreases by about 40%, while 40–80% declines occur over the favored source regions of North America (not shown).
The results demonstrate that in addition to its very strong local influence, snow cover has far-reaching impacts in space and time from its direct terrestrial forcing during the cold months of the year. Polar climate is strongly affected by the snow cover removal, both by virtue of the region’s in situ snow cover and through polar amplification from sea ice feedbacks. In NOSNOWCOVER, the oceanic areas of the Arctic experience significant changes in sea ice cover (26% decrease), precipitation (>10% increase), and surface pressure (up to 4 hPa lower), even though the snow cover forcing is confined to land areas. In fact, 72% of the global ocean area shows significant temperature increases, including 63% of the tropical oceans (30°S–30°N). This widespread warming is not merely surface-trapped but extends throughout the troposphere virtually everywhere in the world (Fig. 3). The associated large changes in upper-air circulation (Fig. 10) are remarkable both in their planetary extent and extreme remote response that generates the largest geopotential height increase nearly as far away as possible from any continent. This PNA wave train is probably forced from Eurasia, based on similar behavior found in previous prescribed snow cover simulations (Barnett et al. 1988; Yasunari et al. 1991), and may have very important implications for past and future global climate change. Yasunari et al. (1991) simulated reduced pressure aloft over eastern North America during anomalously high Eurasian snow cover and suggested that this troughing would help initiate ice sheets over the presumed nucleation region of northeastern Canada (this pattern is analogous to the anomalous ridge formed over eastern North America due to snow cover removal in Eurasia in NOSNOWCOVER). Likewise, Lamb (1977) proposed a remote-forcing mechanism in which glaciation in Scandinavia is triggered by a North American ice sheet triggering downstream adjustment of stationary planetary waves. Conceivably, a similar kind of dynamical forcing could become important for glacial ablation in a warming future climate, if terrestrial snow packs retreat as expected.
Another point about future climate change and the large-scale impact of snow cover is the magnitude of snow cover forcing in this experiment relative to that of greenhouse gases. As noted earlier, the global surface air temperature increase (0.84 K) in NOSNOWCOVER is one-third as large as the model’s sensitivity to 2 × CO2, thus indicating that snow cover is an important component of the global climate system. On a per area basis, however, the response of global temperature is much more sensitive to snow cover than to the CO2 increase, given that greenhouse forcing occurs continuously over the entire surface area of the earth, whereas the snow cover removal only applies to ice-free land during the snow-covered portion of the year. In NOSNOWCOVER the elimination of snow cover across 3.7% of earth’s area producing a 0.84 K global warming represents a normalized temperature response 9 times larger than that from a doubling of CO2, in which the 2.47 K warming was driven by forcing across all of earth’s surface. Alternatively, the traditional definition of climate sensitivity—the global mean temperature change relative to the global top-of-atmosphere (TOA) radiative perturbation—also indicates a much stronger influence from snow cover. The 0.84 K warming from a 0.57 W m−2 TOA perturbation caused by snow cover removal (estimated using the method of Gregory et al. (2004)) represents a sensitivity twice as large as the model’s 2 × CO2 case of a 2.47 K warming from a 3.6 W m−2 TOA perturbation [as reported by Kiehl et al. (2006)].
Several caveats apply to the results of this study. First, the reader is reminded that the snow cover generated by CCSM3 is smaller than observed (Fig. 1) and thus the estimated impact of snow cover is probably underestimated compared with a more realistic model. Second, because terrestrial snow cover was suppressed globally, this experiment is not able to assess the influence of snow cover by region (likewise, the relative contributions of remote forcing vs. the local role of sea ice reductions in shaping the large Arctic Ocean response cannot be determined from the existing experimental design but would require supplemental simulations with fixed sea ice). However, follow-up sensitivity tests using regional snow cover masking are being conducted to evaluate the relative influence of snow cover in Eurasian versus North American snow cover and in high-latitudes versus middle-latitudes. The results of these experiments will be presented in a future paper. Third, the simulated changes in soil temperature and permafrost expansion probably are exaggerated due to the shallowness of the model’s soil depth (3 m). Such a thin layer of soil may respond too sensitively compared with a deeper soil module that has greater thermal inertia. Fourth, the simulated expansion of permafrost area through idealized snow cover removal may not be directly applicable to the effects of snow pack retreat under greenhouse forcing. Future changes will be driven by atmospheric radiative heating that will simultaneously favor both snow melt and warmer soils. In addition, future snow cover retreat will probably be concentrated along the margins of the snow pack, where permafrost is uncommon. Fifth, this study has not considered any superimposed influence of vegetation changes, even though these undoubtedly would occur under such extreme terrestrial-based climate changes as those induced by snow cover removal. Primarily through their effect on surface albedo, extratropical shifts in vegetation cover can strongly influence climate change, through such positive feedbacks as those triggered by the conversion of tundra to boreal forest (Foley et al. 1994; Levis et al. 1999) and vice versa (Gallimore and Kutzbach 1996). Given the competing effects on vegetation of the climate changes caused by snow cover suppression—atmospheric warming but large wintertime cooling of the ground, and drying of the upper soil but not deeper layers—it is not clear how vegetation would respond to and influence the climate. A follow-up CCSM3 simulation incorporating the optional dynamical global vegetation model will allow vegetation to interact with the atmosphere and thus address this potentially important aspect of the influence of snow cover on climate.
Snow cover significantly cools the air throughout the troposphere at most locations, causing near-surface air temperatures to decrease annually by up to 6 K over high-latitude land and as much as 10 K during winter.
The global cooling effect of snow cover on surface air temperature is one-third the magnitude of 2 × CO2 forcing and nine times as large on a per area basis (twice as large using the traditional definition of climate sensitivity).
The insulating effect of snow cover is dominant during winter, causing much warmer soils over the climatological snow pack. The insulating impact is large enough to counteract the effect of overlying air temperature changes on the ground temperature. This suggests that an interesting interplay could develop in the future between a warming climate acting to shrink permafrost extent but waning snow cover favoring permafrost expansion.
The existence of snow cover greatly reduces the amount of permanently frozen soil at present, resulting in permafrost margins being about 5–10° further poleward.
Near-surface soils are much wetter as a result of overlying snow packs, which moisten the near-surface soil by about 25% across the boreal extratropics.
Snow cover dramatically affects the annual cycle of surface runoff, which peaks due to snow melt during spring-early summer in the extratropics and would instead follow the annual cycle of P − E in polar regions in the absence of snow cover.
Polar sea ice is much more extensive due to terrestrial snow cover, expanding by 26 and 10% in the Arctic and Antarctic regions, respectively.
The resulting colder, icier conditions in high latitudes affect the hydrological cycle: annual precipitation over the Arctic Ocean is significantly reduced (>10%) by the existence of adjacent snow cover on land.
Snow cover strongly affects atmospheric circulation in mid-high latitudes. The presence of snow cover causes Arctic surface pressure to be higher and to favor a more negative NAO pattern. Snow cover also shapes the flow pattern aloft, resulting in local and downstream height changes throughout the Northern Hemisphere.
Extreme temperatures during winter are strongly regulated by snow cover. Snow packs depress the coldest wintertime daily mean temperature by up to 20 K and are essential for the formation of bitterly cold Arctic air masses (below −40°C).
Extreme cold air outbreaks are highly dependent on snow cover. Over most of Eurasia and North America, the chilling effect provided by the underlying snow pack is required for CAOs to occur. Without this reinforcing boundary condition, bitterly cold air masses tend to remain more confined to high latitudes.
This project is supported by collaborative National Science Foundation grants ATM-0332099, ATM-0332081, and OPP-0327664. Constructive input from and collaboration with John Walsh, Diane Portis, and Bill Chapman on extreme cold air outbreaks were valuable in strengthening the manuscript. Suggestions by Michael Notaro on the overall content were also very helpful in improving the paper. Sam Levis was instrumental in assisting on the coding changes within the CCSM land component model.