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GEOPHYSICAL RESEARCH LETTERS, VOL. 34, L16504, doi:10.1029/2007GL030550, 2007
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Impacts of peat and vegetation on permafrost degradation under climate warming Shuhua Yi,1,2 Ming-ko Woo,1 and M. Altaf Arain1 Received 1 May 2007; revised 5 July 2007; accepted 2 August 2007; published 29 August 2007.
[1] Simulations of maximum annual thaw at a continuous and a discontinuous permafrost site in Canada were performed using Community Land Model version 3 (CLM3) and randomized historical climate records from these sites, superimposed with United Nations Intergovernmental Panel on Climate Change (IPCC), Report on Emission Scenarios (SRES) A2 scenario of climate change. A positive trend in permafrost degradation was simulated for the 2000 to 2100 period in response to climate warming. Surface cover condition and soil properties play a dominant role in affecting ground thaw. In particular, a thin peat layer or surface organic cover can significantly buffer the permafrost against severe degradation. The occurrence of vegetation and extensive presence of a peat and organic layer in the circumpolar areas will modulate the regional impact of climate warming on permafrost thaw. Citation: Yi, S., M. Woo, and M. A. Arain (2007), Impacts of peat and vegetation on permafrost degradation under climate warming, Geophys. Res. Lett., 34, L16504, doi:10.1029/2007GL030550.
1. Introduction [2] Global warming is expected to have serious consequences on cold region phenomena, including the degradation of permafrost, defined as ground (soil or rock) that remains at or below 0°C for at least two consecutive years. There is a general agreement that the thawing of permafrost can lead to widespread changes in the cold region landscape [Nelson et al., 2001; Smith et al., 2005]. However, the magnitude of permafrost thaw remains debatable. A recent modeling effort [Lawrence and Slater, 2005] led to an alarming conclusion that by the end of this century only 1 million km2 of the currently estimated 10.5 million km2 of near-surface (i.e. 3.43 m thick) permafrost would remain. This simulated result was questioned by Burn and Nelson [2006], who based on field and historical evidence deemed so large a change over such a short period excessive. Such scientific communications are essential to the improved projection of climate warming effects, and we wish to add our findings to this discussion. The objective of our study was to simulate maximum ground thaw (which defines the thickness of the active layer) at a continuous and a discontinuous permafrost site, using long-term climate station records superimposed by projected climate warming trends,
1 School of Geography and Earth Sciences, McMaster University, Hamilton, Ontario, Canada. 2 Now at Department of Biology and Wildlife, University of Alaska Fairbanks, Alaska, USA.
Copyright 2007 by the American Geophysical Union. 0094-8276/07/2007GL030550$05.00
and parameterized with soils typically found in the Arctic and subarctic environments.
2. Study Sites [3] Study sites are located in the Northwest Territories of Canada and represent environments sensitive to climate change. Inuvik (IVK, 68.18°N, 133.29°W, 68 m) is a continuous permafrost site at the North American tree-line and Norman Wells (NWS, 65.18°N, 126.44°W, 70 m) is a discontinuous permafrost site located in the taiga ecozone dominated by boreal forest [Burns, 1974]. Both sites offer long-term (since 1970s) climate records. The mean annual temperature (1970– 1999) was 8.5 and 5.3°C for IVK and NWS, respectively. Their respective average temperatures were 12 and 14°C for July and 30 and 29°C for January. Mean annual precipitation totals were about 300 mm at both stations. Precipitation was possibly underestimated due to poor gauge catch of snowfall [Goodison, 1978].
3. Methods 3.1. Model [4] The Community Land Model version 3 (CLM3) was developed by the US National Center for Atmospheric Research (NCAR) for coupling with Community Atmospheric Model and Community Climate System Model (CCSM) [Oleson et al., 2004]. We chose this model to provide methodological compatibility with the CCSM model used by Lawrence and Slater [2005], but we employed CLM3 in a stand-alone mode and with several critical modifications as described by Yi et al. [2006]. These modifications include (i) a canopy heat storage capacity term, (ii) a two-directional Stefan’s algorithm (described in detail by Woo et al. [2004]) to refine the resolution of the freeze-thaw front, using soil temperature and moisture forcing from the CLM3, (iii) peat or surface organic layers in the CLM3 soil profile following Letts et al. [2000] and (iv) presence of unfrozen water in the soil column. Yi et al. [2006] demonstrated that these adaptations to CLM3 allow correct simulation of the freezing and thawing fronts in a Canadian boreal forest, with seasonal frost. Using observed soil data from an Alaskan permafrost site, Nicolsky et al. [2007] subsequently demonstrated that inclusion of surface organic layer and unfrozen water dynamics along with increased (80 m) soil column depth in the CLM3 can reduce the simulated depth of thaw, though the thaw was still overestimated compared with the measured values. 3.2. Soil and Vegetation Parameters [5] Mineral soils in northern regions are diverse and range from boulders and till left by Pleistocene glaciations
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Table 1. Soil Profiles Used in the Simulationa Layer
1
Thickness, cm 1.75 P0 SC P10 FP P30 FP
2
3
4
5
6
7
8
9
10
2.8 SC HP FP
4.5 SC SP FP
7.4 SC SC HP
12.3 SC SC SP
20.3 SC SC SC
33.6 SC SC SC
55.4 SC SC SC
91.3 SC SC SC
113.7 SC SC SC
a
SC, silty clay; FP, fibric peat; HP, hemic peat; SP, sapric peat.
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[8] Figure 1 summarizes the changes in surface air temperatures (DTa) in January and July, and the relative change in precipitation (DP) compared to the 30-year averages for 1970 – 1999, for IVK and NWS areas. While the precipitation shows no obvious trend, annual mean temperature is projected to increase by about 5°C at the end of the century. Warming is especially significant between November and February.
4. Results to alluvial sand and clay sediments of former lakes. We used a generic mineral soil represented by silty clay, which is parameterized in the CLM3. Most permafrost landscape has a top organic cover comprising of living plants overlying peat that is more decomposed at depth, progressively termed fibric, hemic and sapric peat. For generality, we used the parameterization for the three types of peat provided by Letts et al. [2000]. Three types of ground cover were considered, viz. bare ground, shrub tundra and boreal forest. Bare soil is more prevalent in the Arctic Islands, but is included to represent an extreme exposure of the ground to atmospheric forcing. [6] We labeled model runs according to soil and surface cover conditions, with Px designating peat cover of x-cm thickness, and B, S or F for bare, shrub or forest covers (e.g. P10S indicates 10 cm peat over mineral soil, under a shrub vegetation). Simulations were performed using three soil profiles, including totally silty clay with no surface organic or peat layer (P0), thin peat of about 10 cm on top of silty clay (P10), and thick peat of about 30 cm overlying silty clay (P30). The thickness of the ten soil layers in CLM3, and their constituent materials, are given in Table 1. Vegetation parameters including monthly leaf/stem area index values were from Bonan [1996]. For the forest and the shrub, the height of canopy bottom was 8.5 and 0.1 m, and the canopy top was 17.0 and 0.5 m, respectively. 3.3. Generation of Climate Forcing Data [7] The Intergovernmental Panel on Climate Change (IPCC) Special Report on Emission Scenarios (SRES) proposed scenarios of climate warming due to human activities (http://cera-www.dkrz.de/IPCC_DDC/SRES/ index.html). We chose the A2 scenario to capture the more extreme degree of potential permafrost degradation. Outputs from the Canadian Centre for Climate Modelling and Analysis (CCCma) were used as we feel that the Canadian GCM can best portray the Canadian climate. To provide climate data for the simulation, we made use of historical records superimposed with the scenario trends of DTa and DP. To eliminate any possible trend or oscillation in the historical data, individual years were randomly sampled from the 1970 – 1999 datasets to construct artificial 100-year series for IVK and NWS. Then, for each simulation year between 2000 and 2100, the monthly changes in Ta and P were applied to the constructed halfhourly temperature and precipitation time series. Incident solar radiation, wind speed and relative humidity were assumed to be the same as those of the randomly selected year. Simulations were performed from 1970 to 2100. The actual historical data for 1970 – 1999 period (not randomized) were used to initiate the model simulation for IVK and NWS.
4.1. Snow Cover Comparison [9] The insulating effect of snow buffers the soil surface from winter coldness, but the presence of snow cover in the spring delays warming of the soil, thus affecting the penetration of the freezing and the thawing fronts. Nine model runs (various combinations of P0, P10 and P30 with F, S, and B) were made, using the 1970 – 1999 data to simulate snow depth (Figure 2). Simulated and observed maximum snow depths were broadly in agreement for these years (Figure 2). The root mean squared errors in simulated snow depth were 14.2 and 19.6 cm for IVK and NWS, respectively, compared with the mean annual maximum snow depths of 66 cm (IVK) and 47 cm (NWS). There was a small systematic over-estimation of observed snow
Figure 1. CCCma GCM A2 scenario output (a) change in surface air temperature in January DTa, (b) change in surface air temperature in July DTa, and (c) relative change in precipitation DP, compared to the monthly average air temperature and monthly total precipitation over the period of 1970 and 1999. (Solid lines are for Inuvik and dashed lines are for Norman Wells).
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degradation simulated by the model. The mean air temperatures for 30-year periods were 5.3 ( 8.5), 3.6 ( 6.4), and 1.8 ( 4.4)°C for 1970 – 1999, 2021 – 2050, and 2071– 2100, respectively, at NWS (IVK). Since the model used historical data superimposed with warming trends, the latitudinal (3°) climatic differences between stations were inherited in the inputs to the simulation. Overall, the continuous permafrost site of IVK was colder than the discontinuous permafrost location of NWS. This difference in air temperature was maintained throughout the century and was translated into regional differences in ground thaw.
Figure 2. Comparison between simulated and measured annual maximum snow depth at (a) Inuvik and (b) Norman Wells. The line represents average annual maximum snow depth and the shaded area shows the range of annual maximum snow depths from 9 simulations performed at each location. Open circles represent measured snow depths.
4.4. Maximum Annual Thaw [12] Our results show that a general warming will increase the length of snow-free season and the ground surface temperature, decrease the soil water content, and increase the active layer depth, irrespective of ground cover and soil type. Figures 3 and 4 illustrate the simulated annual maximum thaw depth at IVK and NWS, with bare ground, shrub and forest vegetation, for soil profiles with 0, 10 and 30 cm of top peat layer. Despite the inter-annual variability in the depth of the active layer, there is a clear trend of increasing thickness over the century, indicating a gradual degradation of the permafrost at IVK and NWS. Table 2 provides a summary for one of the cases to illustrate the trend in the degradation of the permafrost. In general, NWS will experience deeper thaw than IVK, but thawing at both sites will be affected by vegetation and soil properties, i.e. [13] (i) For the same soil profile, the absence of any surface cover produces the deepest annual thaw, whereas the thaw is shallower when a shrub cover is present, and is further reduced under a forest.
depth at NWS after 1980, which may be due to re-location of the weather station, though this effect cannot be confirmed. 4.2. Freeze-Thaw Fronts [10] Explicitly simulated fronts enable a better definition of the thaw depth than that derived directly by CLM3. The latter is subject to abrupt jumps, as freeze-thaw moves between model layers of discrete thickness (see figures in the work by Yi et al. [2006]). It is noted, however, that total soil profile depth in CLM3 is limited to 3.43 m and this causes uncertainty in deep thaw simulation. There are recent attempts by Alexeev et al. [2007] and by Nicolsky et al. [2007] to extend the profile depth in CLM3, but we kept the depth to 3.43 m to be compatible with the analysis of Lawrence and Slater [2005] so that our results can be compared directly. Without deep ground temperature from the model to provide an upward forcing, there is no mechanism to generate two-directional freeze-thaw. Thus, the front may remain flat throughout the winter. The uncertainty in deeper thaw simulations may not be a major concern for the present study which focused primarily on the maximum depth of thaw and not the freeze-back mechanism. 4.3. Temperature Difference Between Sites [11] The ability of the model to broadly replicate the snow cover and the improved refinement of the freeze-thaw front lent confidence to the interpretation of permafrost
Figure 3. Maximum simulated thaw depth for (a) forest covered ground, (b) deciduous shrub covered ground, and (c) bare ground at Inuvik with silty-clay soil and no peat layer (P0, solid line), 10 cm peat layer (P10, dotted line), and 30 cm peat layer (P30, dashed line).
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[19] (iii) Although evapotranspiration is larger for forest than for bare ground, their annual soil water content is similar. This is especially true at IVK. [20] (iv) During the warm season, forest intercepts rainfall, but most of the rain on bare ground becomes runoff. Thus, bare ground produces much larger surface runoff than forest. [21] In general, peat has higher porosity than mineral soils, allowing freer drainage, larger water and ice storage when saturated, but offers more effective insulation when dry. Regarding the soil influence, model results show that: [22] (i) Compared with mineral soil, peat retains more water and hence allows less runoff (e.g. mean annual runoff of 1970 – 1999 for P0B and P30B was 184 and 178 kg m 2 at NWS, and 192 and 184 kg m 2 at IVK, respectively). [23] (ii) When soil column is wet, the larger porosity of peat has a higher water content than saturated mineral soil. A large water content translates into more ice in peat layer which then requires much more latent heat to achieve the same depth of thaw compared to the mineral soil. [24] (iii) When soil column is dry, the large volume of air in porous peat greatly reduces its thermal conductivity resulting in retarded ground thaw depths in the summer. [25] The above modeled features provide a physical basis for interpretation of the simulated thaw. Our simulated permafrost degradation rates are far lower than those
Figure 4. Same as Figure 3, but for Norman Wells.
[14] (ii) Under the same surface cover conditions, the presence of a thin peat layer in the soil greatly retards ground thaw, with thicker peat yielding shallower thaw depth. [15] Thus, model runs showed that by 2100, a column with 30 cm of peat cover (P30) would have an increase in active layer depth of only 3°C higher surface temperature than P0F), and consequently shallower thaw depth.
Table 2. Summary of Simulated Variables for a Soil Profile With a 10 cm Peat Layer (P10), Under Cover Conditions of Boreal Forest (F), Shrub (S) and Bare Ground (B), Over Three Periods (1970 – 1999, 2021 – 2050 and 2071 – 2100) at a Continuous Permafrost (Inuvik) and Discontinuous Permafrost (Norman Wells) Sitea 1970 – 1999 F
S
2021 – 2050 B
F
S
SF TG DD IF RF DN TP EP SW MT
110 7.8 856 36 83 8 33 154 1340 48.4
102 8.5 870 8 178 6 10 82.8 1359 44.9
101 9.3 937 4 183 7 0 85.1 1368 48.1
Inuvik 121 111 8.7 9.5 1053 1060 41 7 83 181 13 5 31 10 143 75.2 1285 1321 71 60.7
SF TG DD IF RF DN TP EP SW MT
134 8.7 1168 50 69 11 45 162.3 1301 79.2
124 9 1114 13 168 10 13 93.4 1348 67.9
122 9.6 1173 2 177 12 0 95.7 1358 67.6
Norman Wells 139 129 9.9 10.3 1378 1325 63 29 70 165 15 21 51 17 160.5 93.6 1289 1333 98.2 88.9
2071 – 2100 B
F
S
B
111 10.2 1136 2 184 10 0 76.2 1345 63.5
134 9.9 1326 48 65 15 33 147.6 1264 91.5
125 10.7 1336 18 154 11 14 80.1 1314 83.6
124 11.5 1420 4 165 15 0 80.1 1341 83.9
127 10.9 1389 13 174 24 0 96.9 1342 88.7
152 10.6 1609 70 63 15 58 171.9 1237 121.4
139 11.3 1568 47 146 37 19 103.3 1308 110.5
136 12 1637 37 151 50 0 105.2 1324 110.3
a SF, length of snow-free period (days); TG, mean ground temperature at 1 cm depth during snow-free period (°C); DD, total degree-days during snow-free period (°C day); IF, annual total infiltration (mm); RF, annual total runoff (mm); DN, annual total drainage (mm); TP, annual total transpiration (mm); EP, annual total evaporation (mm); SW, annual mean soil water content (both liquid and ice content in the soil column) (kg m 2); MT, annual maximum thaw depth (cm).
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predicted by Lawrence and Slater [2005]. On the other hand, our results suggest that northern development should avoid stripping the ground of an insulating cover that protects the permafrost from deep thaw. Forest fire in permafrost regions, which may become more prevalent in the future [Flannigan et al., 2005], can reduce surface organic layer, and this can affect ground thaw [MacKay, 1995; Yoshikawa et al., 2003] on both local and regional scales.
6. Conclusions [26] Simulations of a continuous and a discontinuous permafrost location confirmed that regional climate warming will lead to deeper ground thaw in the 21st century. However, simulation results indicated that vegetation cover and soil properties can buffer the permafrost from severe degradation. Given that extensive areas in the circumpolar region have a peat or surface organic cover, it is surmised that the peat will enable the preservation of permafrost against projected warming in most northern areas. On the other hand, disturbance of the ground cover on a local scale or fires in the boreal forest and tundra can lead to accelerated permafrost thaw. From regional and global perspectives, findings of this study caution against generalization, when vegetation and soil factors play a strong role in modulating climate warming impacts on the loss of permafrost. [27] Acknowledgments. This study was supported by the NSERC of Canada through the Mackenzie GEWEX Study, and NSERC, CFCAS and BioCAP Canada Foundation funded Fluxnet-Canada Research Network and Canadian Carbon Program (CPP) as well as CFCAS funded Canadian Global Coupled Climate Carbon Model Network (CGC3M). Climate data were provided by Environment Canada and the CLM3 was made available from NCAR and computational resources by the SHARCNET.
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Bonan, G. B. (1996), A land surface model (LSM Version 1.0) for ecological, hydrological and atmospheric studies, technical description and user’s guide, Tech. Rep. NCAR/TN-417+STR, Natl. Cent. for Atmos. Res., Univ. Corp. for Atmos. Res., Boulder, Colo. Burn, C. R., and F. E. Nelson (2006), Comment on ‘‘A projection of severe near-surface permafrost degradation during the 21st century’’ by David M. Lawrence and Andrew G. Slater, Geophys. Res. Lett., 33, L21503, doi:10.1029/2006GL027077. Burns, B. M. (1974), The Climate of the Mackenzie Valley-Beaufort Sea, vol. I and II, Environ. Canada, Toronto, Ont., Canada. Flannigan, M. D., K. A. Logan, B. D. Amiro, W. R. Skinner, and B. J. Stocks (2005), Future area burned in Canada, Clim. Change, 72, 1 – 16. Goodison, B. E. (1978), Accuracy of Canadian snow gage measurements, J. Appl. Meteorol., 27, 1542 – 1548. Lawrence, D. M., and A. G. Slater (2005), A projection of severe nearsurface permafrost degradation during the 21st century, Geophys. Res. Lett., 32, L24401, doi:10.1029/2005GL025080. Letts, M., N. Roulet, N. Comer, M. Skarupa, and D. Verseghy (2000), Parameterization of peatland hydraulic properties for the Canadian Land Surface Scheme, Atmos. Ocean, 38(1), 141 – 160. MacKay, J. R. (1995), Active layer changes (1968 to 1993) following the forest-tundra fire near Inuvik, N.W.T., Canada, Arct. Alp. Res., 27(4), 323 – 336. Nelson, F. E., O. A. Anisimov, and N. I. Shiklomanov (2001), Subsidence risk from thawing permafrost, Nature, 410, 889 – 890. Nicolsky, D. J., V. E. Romanovsky, V. A. Alexeev, and D. M. Lawrence (2007), Improved modeling of permafrost dynamics in a GCM landsurface scheme, Geophys. Res. Lett., 34, L08501, doi:10.1029/ 2007GL029525. Oleson, W. K., et al. (2004), Technical description of the Community Land Model (CLM), NCAR Tech. Rep. NCAR/TN-461+STR, Natl. Cent. for Atmos. Res., Boulder, Colo. Smith, L. C., Y. Sheng, G. M. MacDonald, and L. D. Hinzman (2005), Disappearing Arctic lakes, 308, 1429. Woo, M. K., A. M. Arain, M. Mollinga, and S. Yi (2004), A two-directional freeze and thaw algorithm for hydrologic and land surface modelling, Geophys. Res. Lett., 31, L12501, doi:10.1029/2004GL019475. Yi, S., A. M. Arain, and M. K. Woo (2006), Modifications of a land surface scheme for improved simulation of ground freeze-thaw in northern environments, Geophys. Res. Lett., 33, L13501, doi:10.1029/2006GL026340. Yoshikawa, K., W. R. Bolton, V. Romanovsky, M. Fukuda, and L. D. Hinzman (2003), Impacts of wildfire on the permafrost in the boreal forests of Interior Alaska, J. Geophys. Res., 108(D1), 8148, doi:10.1029/2001JD000438.
References Alexeev, V. A., D. J. Nicolsky, V. E. Romanovsky, and D. M. Lawrence (2007), An evaluation of deep soil configurations in the CLM3 for improved representation of permafrost, Geophys. Res. Lett., 34, L09502, doi:10.1029/2007GL029536.
M. A. Arain and M. Woo, School of Geography and Earth Sciences, McMaster University, Hamilton, ON, Canada L8S4K1. (
[email protected]) S. Yi, Department of Biology and Wildlife, University of Alaska Fairbanks, AK 99775, USA.
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