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Spatiotemporal variations of climate warming in northern Northeast China as indicated by freezing and thawing indices
Quaternary International 349 (2014) 187e195
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Quaternary International journal homepage: www.elsevier.com/locate/quaint
Spatiotemporal variations of climate warming in northern Northeast China as indicated by freezing and thawing indices Dongliang Luo a, Huijun Jin a, *, Rui Jin a, Xingguo Yang b, Lanzhi Lü a a
State Key Laboratory of Frozen Soils Engineering, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, Gansu 730000, China b Meteorological Bureau of Ningxia Hui Autonomous Region, Yinchuan 750002, China
a r t i c l e i n f o
a b s t r a c t
Article history: Available online 2 August 2014
As the thermal state of the upper boundary conditions of the soil layer, ground surface and air temperatures sensitively indicate the heat transferring process between atmosphere and land surface. Due to the combined effects of high latitude and elevation, northern northeast (NNE) China is the second largest permafrost region in China. Based on the daily ground surface and air temperatures at 21 selected stations in NNE China, the ManneKendall test and Sen's slope estimate were used to detect changes in the mean annual ground surface temperature (MAGST), mean annual air temperature (MAAT), annual ground surface freezing index (GFI), annual air freezing index (AFI), annual ground surface thawing index (GTI), annual air thawing index (ATI), and surface offset of MAGSTeMAAT for the period between 1972 and 2005. The results show a significant warming in NNE China during the past three decades. The MAGST and MAAT averaged 0.72 and 0.50 C, with mean increasing rates of 0.61 and 0.72 C/10y, respectively. The lowest MAGST and MAAT were observed in the northernmost and middle parts of the Da Xing'anling Mountains. The multiyear average GFI is 2822.1 C /y with a range between 1827.6 and 3919.6 C $d. The multiyear average AFI is 2688.8 C /y with a range between 1729.5 and 3606.1 C $d. Over the same period, the multiyear average GTI ranged between 2451.8 and 3705.5 C $d, with an average of 2514.0 C /y, and the multiyear average of ATI ranged from 1902.7 to 2990.1 C $d, with an average of 2508.3 C . Trend analyses show a significant decline in annual GFI (13.5 C $d/y) and annual AFI (13.4 C $d/y), and a significant increase in annual GTI (9.96 C $d/y) and annual ATI (8.71 C $d/y). The most pronounced warming has occurred in sporadic permafrost regions of NNE China. However, in continuous permafrost, and discontinuous permafrost regions with extensive presence of taliks, such as at Ta'he and Xinlin stations, no significant trend is detected. Study of the variations of freezing and thawing indices may provide some implications of spatiotemporal changes in the thermal regimes of active layer and permafrost soils, and facilitate better understanding of cold environment changes in permafrost regions of Northeast China. © 2014 Elsevier Ltd and INQUA. All rights reserved.
Keywords: Climate Change Freezing and thawing indices Surface offset Permafrost Northern northeast (NNE) China
1. Introduction Northeast China is the second largest expanse of permafrost and the primary region of latitudinal permafrost in China, and the southernmost part of the Eurasian cryosphere (Wei et al., 2011). Latest statistics indicates that the areal extent of permafrost in Northeast China has shrunk to 0.24 106 km2, most of which is in northern northeast (NNE) China, the Da and Xiao Xing'anling Mountains (Ran et al., 2012). Driven by many programs and projects on engineering explorations, design, and construction, and * Corresponding author. E-mail addresses: [email protected] (D. Luo), [email protected] (H. Jin). http://dx.doi.org/10.1016/j.quaint.2014.06.064 1040-6182/© 2014 Elsevier Ltd and INQUA. All rights reserved.
ecological rehabilitation, research on permafrost in NNE China has received increasing attention from scientists, engineerers, and governmental administrators since the late 1950s (Jin et al., 2010; Wei et al., 2011). Among them, delineating the southern limit of permafrost with isotherms of mean annual air temperatures (MAAT) and zoning of permafrost regions (e.g., Guo and Li, 1981; Lu et al., 1993), is one of the most important. Due to its thin and warm nature of the permafrost, and its sensitivity to climate change and anthropogenic activities, permafrost degradation in the Xing'anling Mountains has been clearly observed during the past several decades (Jin et al., 2007; He et al., 2009; Chang et al., 2013). For example, the northward shifting of the southern limit of permafrost from the 1970s to the 2000s has been confirmed by on-site data
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along highways in the Da and Xiao Xing'anling Mountains and the ChinaeRussia Crude Oil Pipeline (CRCOP) route from Mo'he to Daqing (Jin et al., 2007). However, the lack of long-term observation data has made it difficult to quantitatively analyze the spatial and temporal variations of permafrost changes in NNE China. Moreover, these studies on the northward shifting of the southern limit of permafrost in NNE China were based on the analysis of isotherms of MAAT, but without support from adequate data on ground surface temperatures. The ground surface is the direct interface where energy and mass exchanges between earth and atmosphere take place. It is therefore of great importance for predicting thermal regime of permafrost soils and mapping permafrost distribution (Frauenfeld et al., 2007; Wu et al., 2013). Myriad local variations in vegetation, topography, and snow cover can produce differences with a range of several degrees between the MAGST and MAAT over a small region (Smith and Riseborough, 2002). Therefore, the ground surface temperature and related parameters, such as annual GFI and GTI, play important roles in dynamics of active layers and permafrost soils. Because air temperature data are more readily available, most previous studies in Northeast China focused on the spatiotemporal variations of annual, summer and winter air temperatures (e.g., Wei et al., 2008; He et al., 2013). Wei et al. (2008) reported an increase of approximately 1.0 C in MAAT during 1976e2000 compared with that of 1950e1975. He et al. (2013) reported that during 1961e2005, the increasing rate of MAAT is 0.38 C /10y, and the warming trend in winter is 0.53 C /10y, much higher than that in summer (0.24 C /10y). There is little work detailing changes in GST in permafrost regions in NNE China. The intense increase in ground
et al., 2001; Anisimov et al., 2007; Wu et al., 2013). This study will help better understanding changes in the thermal regimes of ground surface, active layer and permafrost soils, and further facilitates the understanding of the stability of cold region environments in Northeast China. 2. Data and methodologies Daily temperature datasets were obtained from the National Climate Center of China Meteorological Administration (http://cdc. cma.gov.cn/home.do). GST is measured on a standard yard of 2 4 m with sensors on the surface of snow cover in wintertime, and bare ground in summertime, while air temperatures are measured at 2 m height. The earliest systematic observations of GST in NNE China started in 1951 at Nenjiang and Keshan stations, and generally around or after the 1960se1970s at most other stations. Although the daily GST at Xiao'ergou, Xin'youqi and Arxaan stations have missing values for several years before the year of 1972, the time series of all the stations are complete after 1972 (Table 1). However, for some unknown reasons, the daily GST at most stations in NNE China suffered a serious absence of measurements during the winters (from November to the next February) after 2005. Therefore, considering continuity, uniformity, and long time series of datasets, 21 meteorological stations in or around permafrost regions with complete and continuous data series from 1972 to 2005 were selected to analyze the spatial and temporal changes in the MAGST, MAAT, and freezing and thawing indices. In addition, data quality control and homogeneity assessment of the ground surface and air temperatures were checked using the RClimDex software (http://etccdi.pacificclimate.org/software.shtml).
Table 1 List of metadata for the 21 selected meteorological stations in NNE China. WMO identification number 50136 50246 50439 50353 50425 50434 50442 50468 50514 50527 50548 50557 50564 50603 50618 50632 50639 50656 50658 50727 50774
Station name Mo'he Ta'he Xinlin Huma Erguna Tuli'he Jagdaqi Hei'he Machuria Hailar Xiaoergou Nenjiang Sunwu Xinyouqi Xinzuoqi Bûgt Zalantun Beian Keshan Arxaan Yichun
Latitude (N)
0
52 58 52 210 51 420 51 430 50 150 50 290 50 240 50 150 49 340 49 130 49 120 49 100 49 260 48 400 48 130 48 460 48 000 48 170 48 030 47 100 47 440
Longitude (E)
0
122 31 124 430 124 200 126 390 120 110 121 410 124 070 127 270 117 260 119 450 123 430 125 140 127 210 116 490 118 160 121 550 122 440 126 310 125 530 119 560 126 550
Elevation (m a.s.l.)
Land use (landscape)
Time series of available measurements
433.0 361.9 494.6 177.4 581.4 732.6 371.7 166.4 661.7 610.2 286.1 242.2 234.5 554.2 642.0 739.7 306.5 269.7 234.6 1027.4 240.9
forest forest high coverage grassland open forest dry land open forest forest forest open forest open forest forest dry land forest open forest open forest forest forest open forest dry land forest high coverage grassland
1958e2006 1972e2005 1972e2005 1956e2005 1958e2005 1957e2005 1966e2005 1959e2005 1958e2005 1956e2005 1960e2005 1951e2005 1957e2005 1961e2005 1960e2005 1957e2005 1952e2005 1958e2005 1951e2005 1952e2005 1958e2005
surface and air temperatures result in major variations of annual freezing and thawing indices, and the active layer thickness (ALT), and eventually extensive permafrost degradation (Wu et al., 2012, 2013). In this study, the spatiotemporal variations of MAAT and MAGST, surface offset between MAAT and MAGST, annual GFI, annual GTI, annual AFI, and annual ATI are analyzed on the basis of daily ground surface and air temperatures from 21 selected meterological stations. The freezing and thawing indices are important for assessing seasonal freeze and thaw depth, as well as the distribution of permafrost and seasonally frozen ground (Klene
There are a number of freezing and thawing indices in the literature. Frauenfeld et al. (2007) reviewed the definitions, principles and methods for calculating the freezing and thawing indices. Among the different methods of computing freezing and thawing indices, the criteria of summing all temperatures below or above 0 C during the freezing (thawing) periods are suitable and plausible (Wu et al., 2011, 2013). The annual freezing (thawing) indices in continuous cold (warm) seasons, the annual freezing index is calculated from July to next June, and the annual thawing index from January to December. The annual freezing and thawing
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Gaussian distribution data, and benefit in less sensitive to outliers in observation records, the ManneKendall test has been widely used in analyzing climate changes (e.g., Li et al., 2013; Wang et al., 2013; Chen et al., 2014). The statistical methods were previously introduced to detect the observed trends in surface freezing and thawing indices on the bordering eastern Mongolia and on the Interior Qinghai-Tibet Plateau (QTP) to the southwest (Wu et al., 2011, 2013).
indices are calculated using the following formulas (Frauenfeld et al., 2007):
FI ¼
DF X
jTn j; Tn < 0 C
(1)
DT X Tp ; Tp > 0 C
(2)
i¼1
TI ¼
3. Results and discussions
i¼1
where FI (TI) is the annual freezing (thawing) index, Tn (Tp) represents the daily GST with negative (positive) temperature during the freezing (thawing) period. The surface offset depends on the isolation and albedo effects of different ground conditions (such as vegetation covers in summer, snow cover in winter). The low thermal conductivity of snow restricts the loss of heat from the ground during the coldest part of the year, and the vegetation reduces the solar radiation reaching the ground surface in summer and the effects on the accumulation and persistence of snow cover. The surface offset that due to the complex processes within the surface layer could be calculated as follows (Smith and Riseborough, 2002):
Surface Offset ¼
189
FIð1 nFÞ TIð1 nTÞ e P P
3.1. Spatiotemporal variations in ground surface and air temperatures During 1972e2005, the average MAAT ranged from 4.25 C (Tuli'he station) to 3.41 C (Zalantun station), with an average of 0.50 C for all the selected 21 stations in NNE China. The lowest MAAT does not occur at the Mo'he Station (52 580 N, 122 310 E, 433.0 m a.s.l.), the northernmost in China, but at the Tuli'he station (50 290 N, 121410 E, 732.6 m a.s.l.) in the middle Da Xing'anling Mountains (Fig. 1). This phenomenon may be attributed to the higher elevation and smaller atmospheric temperature inversion in the central parts (e.g., Tuli'he station) than in the northern parts of the Da Xing'anling Mountains (e.g., Mo'he station), which could affect the latitudinal effects on temperature. The atmospheric temperature inversion in Mo'he is 10 C km1, which is higher than other places in the Da Xing'anling Mountains (Jin et al., 2007). The MAATs are lower than 2.0 C at Mo'he, Ta'he, Tuli'he, Xinlin, Erguna, and Arxaan stations, which are located in, or adjacent to, the regions of continuous permafrost and discontinuous permafrost with taliks (Table 1 and Fig. 1a). The stations in sporadic permafrost regions, including Ai'hui, Xin'youqi, Xin'zuoqi, and Yichun, have a positive average MAAT over the period 1972e2005. The MAGSTs are all warmer than the corresponding MAATs. Although with negative MAATs, the stations of Jagdaqi, Manchuria, Hailar, Xiao'ergou, Sunwu and Bûgt have positive MAGSTs. The average MAGST is less than 2 C at Mo'he and Tuli'he stations, and between 2.0 and 1.0 C at Ta'he, Xinlin, and Erguna stations (Table 2).
(3)
where nF (nT) is scaling factor between winter (summer) air and ground surface temperatures, P is annual period (365 days). Due to the availability of GST, the surface offset in this study could be simplified by subtracting the MAGST from MAAT:
Surface Offset ¼ MAATeMAGST
(4)
The changing rate and its significance level of annual GFI, GTI, AFI, ATI, and surface offset are obtained from the ManneKendall test and Sen's slope estimate (Sen, 1968; Kendall, 1975). The Sen's slope estimate is used to detect the changing rate, while the rank-based nonparametric ManneKendall test is used to obtain the significance level. Because of its robustness and suitability for analyzing non-
Table 2 MAAT, MAGST, surface offset, changing rate, and Z-value obtained from the ManneKendall trend test and Sen's slope estimate at the 21 selected meteorological stations in NNE China. Station
Mo'he Ta'he Xinlin Huma Erguna Tuli'he Jagdaqi Ai'hui Manchuria Hailar Xiao'ergou Nenjiang Sunwu Xin'youqi Xin'zuoqi Bûgt Zalantun Bei'an Keshan Arxaan Yichun Average
MAAT
MAGST
Surface offset
Avg ( C)
Sen's slope (C /10y)
Z-value
Avg ( C)
Sen's slope (C /10y)
Z-value
Avg ( C)
Sen's slope (C /10y)
Z-value
4.09 2.28 2.60 0.78 2.31 4.25 0.54 0.59 0.49 0.69 0.07 0.59 0.31 1.30 0.44 0.27 3.45 0.99 2.07 2.49 1.35 0.50
0.53 0.30 0.58 0.79 0.70 0.48 0.64 0.70 0.67 0.81 0.85 0.60 0.92 0.62 0.55 0.46 0.56 0.52 0.56 0.40 0.55 0.61
2.81 1.70 3.23 3.97 3.75 3.16 3.97 3.94 3.78 4.14 4.78 3.78 4.98 4.01 3.32 2.90 3.84 3.58 3.65 2.55 3.65 3.81
3.50 1.18 1.90 0.09 1.01 2.96 0.29 1.18 1.27 1.25 0.56 1.98 0.63 3.17 2.41 0.57 4.64 2.54 3.79 0.82 2.35 0.72
0.51 0.25 0.32 0.80 0.11 0.71 0.54 0.67 0.69 1.01 0.89 0.62 1.14 0.76 0.75 0.47 0.51 0.35 0.61 0.63 0.72 0.68
2.68 1.41 1.96 3.78 4.62 4.10 3.23 3.45 3.52 4.43 3.75 3.91 5.37 3.78 3.49 3.10 3.29 2.81 3.78 3.55 4.23 3.97
0.62 1.11 0.72 0.73 1.29 1.31 0.86 0.62 1.80 1.98 0.66 1.42 0.99 1.91 2.00 0.87 1.22 1.58 1.75 1.71 1.02 1.25
0.02 0.02 0.21 0.06 0.25 0.27 0.01 0.05 0.003 0.18 0.08 0.06 0.24 0.13 0.22 0.05 0.12 0.20 0.01 0.10 0.20 0.007
0.47 0.31 3.03 0.99 2.58 3.52 0.11 1.15 0.31 2.48 0.89 1.41 2.29 1.31 2.81 0.86 1.99 2.55 0.21 1.25 3.03 2.22
Notes: The Z-value is used to test the significance level (when the Z-value reaches 1.96 [2.58], it means the significance level of the changing rate is 95% [99%]).
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Fig. 1. Distribution of MAAT (a) and MAGST (b), and their increasing rates (c) in NNE China.
In summary, the average MAAT and MAGST during 1972e2005 were lower in the northern and middle Da Xing'anling Mountains, with rising trends in the eastern and southern parts in NNE China. However, the Arxaan station (47100 N, 119 560 E, 1027.4 m a.s.l.), the southernmost one among the 21 stations, has colder MAAT (2.52 C) and MAGST (0.82 C) due to its higher elevation. To a certain extent, this distribution pattern of MAGST and MAAT shows a vertical zonation of temperature in NNE China (Lu et al., 1993). The average time series of the MAAT and MAGST were generated for all the selected 21 stations. The MAAT ranged from 1.75 C in 1987 to 0.84 C in 1990, and with a multiyear average of 0.50 C for all 21 stations (Fig. 2). Over the same period, the MAGST varied from 0.64 C in 1987 to 2.10 C in 1995, and with a multiyear average of 0.72 C for 21 stations. The increasing rate of MAAT ranged from 0.30 (Ta'he) to 0.92 C/10y (Sunwu), with a 21-station average of 0.61 C/10y at a significance level of 0.05 as obtained by the ManneKendall test and Sen's slope estimate (Table 2). That of the MAGST varied from 0.25 (Ta'he) to 1.14 C/10y (Sunwu), with an average at 0.68 C/10y for all 21 stations at a significance level of 0.05.
The results in this study confirm that the most pronounced warming had occurred at Sunwu station in NNE China during the past several decades as indicated by He et al. (2013). However, there is a difference in the increasing rate of MAAT between this study and a previous work. He et al. (2013) reported an increasing rate of MAAT at 0.66 C /10y at Sunwu station during the period 1961e2005. In the present study, the increasing rate of MAAT at Sunwu station (0.92 C /10y) is much higher (Table 2). This may be attributed to different time spans of data (1972e2005). In general the most significant warming appeared in sporadic permafrost regions, e.g., Hailar, Xiao'ergou, and Sunwu stations with increasing rates higher than 0.80 C /10y (Fig. 1c). The increasing rates of MAAT in the central part of the Da Xing'anling Mountains and Yile'huli Mountains, e.g., Mo'he, Tuli'he, Bûgt, and Arxaan stations, were lower than 0.60 C /10y. Over the period 1972e2005, the increasing rates of MAGST were largely consistent with that of MAAT in NNE China. However, the increasing rate of MAGST (0.11 C/10y) is much lower than that of the MAAT (0.70 C/10y) at Erguna station. The significant positive trend for annual mean snow depth in the
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Fig. 2. MAAT and MAGST averaged for the 21 selected stations in NNE China during the period 1972e2005.
eastern Inner Mongolia (Ma and Qin, 2012), may be responsible for the lower increase of the MAGST at Erguna station. Except for the year of 2004 at Xinlin, the years of 1972e1975 at Erguna, the year of 1981 at Ai'hui station, the annual surface offset for most stations are positive, i.e., annual ground surface temperatures are warmer than corresponding annual air temperatures. There are 8 stations with a decreasing trend of surface offset (Table 2). Xinlin, Zalantun and Bei'an stations show significant decreasing trends at a significance level of 0.05. Annual surface offsets at the other 13 stations show increasing trends during 1972e2005. Erguna, Tuli'he, Hailar, Sunwu, Xinzuoqi, and Yichun show significant increasing trends of the annual surface offset at a significance level of 0.05. In total, there are 12 stations which show no statistically significant trends of change in surface offset (Table 2). The average annual surface offset of the 21 stations is 1.25 C , with a statistically significant linear increasing rate of 0.0069 C /y at a significance level of 0.05, similar to the trend as obtained from Sen's slope estimate (0.0071 C /y) (Table 2, Fig. 3a). The variations of annual surface offset may indicate changes in the snow cover, surface vegetation, land use, and even urbanization. The fact that MAGST is higher than MAAT may be related to the thermal effects of surface coverage, which influences the seasonal distribution patterns of ground surface and air temperatures. Previous studies at high latitudes demonstrated that the thermal effect of winter snow cover is generally greater than that of vegetation cover in summer, and the MAGST is likely to be warmer than the MAAT in most cases (Smith and Riseborough, 2002). In comparison with monthly average air temperatures, monthly average ground
surface temperatures are higher during the period MarcheOctober and lower in the wintertime (Fig. 3b). The monthly ground surface and air temperatures are lowest in January (24.3 C and 26.3 C, respectively), and highest in June (23.7 C and 19.7 C, respectively), which are lower than those on the QTP in January and higher than those in June as reported by Zhang et al. (2006). The difference between monthly ground surface and air temperature decreases from 2.0 C in January to 1.5 C in February, and then increases to 0.9 C in March, then reaches the highest value of 4.5 C in June (Fig. 3). After June, the difference between monthly ground surface and air temperatures decreases; until November and December, monthly ground surface temperatures are 0.6 C and 1.64 C lower than monthly air temperatures. The distribution features of surface offsets differ slightly from those on the QTP, where they are largest in July and smallest in November (Zhang et al., 2006). The snow season on the QTP continues from October to next May and is the longest duration in China (Ma and Qin, 2012). There is snow on the ground surface even in June and September. Thought the snow cover in summer is unstable due to the strong radiation, the melting of it consumes much energy for latent heat fusion; hence, the temperature rise on the ground surface will be dampened. Therefore, the largest difference of ground surface and air temperature on the QTP occurs later than in Northeast China. 3.2. Spatial variations of freezing/thawing index The mean annual GFI and AFI are larger in the northernmost and central areas of the Da Xing'anling Mountains, i.e., Mo'he and
Fig. 3. Trends of average annual surface offset (a), and difference of monthly air temperature and ground surface temperature in a year (b) in NNE China during the period 1972e2005.
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Fig. 4. Spatial distribution of mean annual GFI (a), mean annual AFI (b), mean annual GTI (c), and mean annual ATI (d) in NNE China.
Tuli'he stations in continuous permafrost regions, and smaller in regions of sporadic permafrost and seasonally frozen ground (Fig. 4). The mean annual GFI (1827.6 C $d) and AFI (1729.5 C $d) are smallest at Zalantun station, and largest at Mo'he station (3919.6 C $d and 3606.1 C $d). Averaged annual GFI of all the selected stations ranged from 2326.6 C $d (in 2001) to 3311.2 C $d (in 1976), averaged at 2822.1 C $d. Mean annual AFI varied from 2171.3 C $d (in 2001) to 3237.0 C $d (in 1976), averaging 2688.8 C $d, which is higher than on the QTP permafrost (2218 C $d), regions of seasonally frozen ground (SFG) in North America (400 C $d), SFG regions in Asia (889 C $d), and SFG regions in Russia (866 C $d), but far smaller than in the Arctic (3922 C $d), North American permafrost regions (4804 C $d), and Siberian permafrost regions (5651 C $d) as averaged from reanalysis air temperature product (CRU TS 2.1) as reported by Frauenfeld et al. (2007). Not all the mean annual GFI are larger than the corresponding mean annual AFI in NNE China, as those at Hailar, Xin'youqi, and Arxaan are 112.3, 103.5, and 9.0 C $d smaller than the corresponding mean annual AFI. The difference of mean annual GFI and AFI ranged from 112.3 (Hailar) to 516.8 C $d (Xiao'ergou), with an average value of 133.3 C $d for all the 21 stations. The mean annual GTI varied from 2451.8 (Tuli'he) to 3705.5 C $d (Keshan), with an average of 3101.2 C $d for all the 21 stations. The mean
annual ATI ranged from 1902.7 (Tuli'he) to 2990.1 C $d (Zalantun), with an average of 2514.0 C $d for all 21 stations. As revealed from ground boreholes, the lowest MAGT (ground temperature at depth of zero annual amplitude) in NNE China is 3.3 C in the central area of the Da Xing'anling Mountains (Borehole GH-9 in Gen'he, 50.94 N, 121.51 E, 819 m a.s.l.), but higher than 1.0 C in north central part (Borehole MG-1 in Man'gui, 52.04 N, 122.07 E, 633 m a.s.l.) (Chang et al., 2013). While the MAGT is lower than 2.0 C at Borehole CW09 (51.69 N, 124.39 E, 500 m a.s.l.), and lower than 1.0 C at Borehole CW10 (51.47 N, 124.28 E, 580 m a.s.l.) near Xin'lin station, but higher at Boreholes CW05 (52.54 N, 124.58 E, 439 m a.s.l.) and CW06 (52.43 N, 124.66 E, 435 m a.s.l.) near Ta'he station. This shows that the higher freezing indices agree well with lower permafrost temperature in NNE China, and GFI and AFI could be reliable for modeling the thermal regimes of permafrost and predicting permafrost distribution and dynamics. Unlike freezing indices, the mean annual GTI are all larger than the corresponding mean annual ATI. The mean annual ATI ranged from 1898.2 (Tuli'he) to 2981.9 C $d (Zalantun), with an average of 2508.3 C $d for all the selected stations. The mean annual ATI differs from the mean annual GTI by from 368.4 (Aihui) to 756.5 C $d (Xin'zuoqi), with an average difference of 587.2 C $d for all 21 stations. In comparison air thawing index in NNE China, the mean
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annual ATI are higher in Midlatitudes (5195 C $d), SFG regions in North America (4567 C $d), SFG regions in Asia (4132 C $d), SFG regions in Russia (3230 C $d), but lower in the Arctic (1232 C $d), QTP permafrost (682 C $d), and Siberian permafrost (968 C $d) as shown previously (Frauenfeld et al., 2007). The mean annual GFI, GTI, AFI, and ATI show strong latitudinal zonality in NNE China. In the Da Xing'anling Mountains, the mean annual GTI and ATI increase eastwards and southwards (Fig. 4c). On the basis of linear regression analysis, for every degree increase in northern latitude, the mean annual GFI and AFI increase by 238.0 C $d (R2 ¼ 0.60, p ¼ 0.000) and 192.2 C $d (R2 ¼ 0.49, p ¼ 0.000), respectively, while the mean annual GTI and ATI decrease by 119.1 C $d (R2 ¼ 0.29, p ¼ 0.012) and 101.6 C $d (R2 ¼ 0.26, p ¼ 0.019), respectively. 3.3. Temporal variations of freezing/thawing index
Fig. 5. Changing trends in annual GFI, AFI, GTI, and ATI in NNE China during 1972e2005.
The decreasing rate of annual GFI ranged from 6.0 (Ta'he) to 30.9 C $d/y (Sunwu). Except for Ta'he, Xinlin, Manchuria, Bügt, Zalantun, Bei'an, and Arxaan stations, the other 14 stations show statistically significant decreases in annual GFI at a significance level of 0.05 (Table 3). Except for Ta'he, the annual AFI at other 20 stations show statistically significant decreasing trends. Decrease of annual AFI ranged from 2.9 (Ta'he) to 21.9 C $d/y (Xiao'ergou). A large decrease in annual GFI and AFI occurred in sporadic
Fig. 6. Changes in annual GFI (a), annual GTI (b), annual AFI (c), annual ATI (d) for the selected 21 stations in NNE China during 1970e2005. The light gray bold line is the 5-year running average, and the straight line is the linear fit.
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and Xin'zuoqi stations, have increasing rates significantly higher than 14.0 C $d/y (Table 3). The increasing rates of annual ATI are higher than that of annual GTI at Ta'he, Xinlin, Huma, Jagdaqi, Ai'hui, Sunwu, Bûgt, and Bei'an stations, but lower than the corresponding annual GTI at the other15 stations. The increases in GTI and ATI at Mo'he and Ta'he stations are lower than 5.0 C $d/y, but without statistically significant trends. We averaged the GTI and ATI of all 21 stations. As shown in Fig. 5, the increasing rate of the mean annual GTI is 11.0 C $d/y, 2.1 C $d/y higher than that of the corresponding annual ATI. The slower decreasing of GFI and AFI, and smaller increasing of ATI and GTI at Mo'he, Ta'he, and Xinlin stations, may be attributed
permafrost regions of NNE China (Fig. 5). At Ta'he and Xinlin stations along the CRCOP route in the Yile'huli Mountains, the increasing rate of annual GFI is smallest among all the 21 stations. This may suggest that the reduction of seasonally frozen ground is minor compared with other sites in NNE China. The average time series for the annual GFI and AFI are shown in Fig. 6. The decreasing rates of annual GFI and AFI averaged for all 21 stations are both 13.3 C $d/y, but with respective Z-values of 2.74 and 2.48 as obtained from ManneKendall's test. The linear fit of annual GFI and AFI are 12.3 and 12.2 C $d/y, respectively, almost the same with the trend (13.5 and 13.4 C $d/y) as obtained from Sen's slope estimate.
Table 3 Mean values and change trends of freezing and thawing indices of the selected 21 stations in NNE China. Station
Mo'he Ta'he Xinlin Huma Erguna Tuli'he Jagdaqi Ai'hui Manchuria Hailar Xiao'ergou Nenjiang Sunwu Xin'youqi Xin'zuoqi Bûgt Zalantun Bei'an Keshan Arxaan Yichun Average
GFI
GTI
AFI
ATI
Avg (C $d)
Sen's slope (C $d/y)
Z-value
Avg (C $y)
Sen's slope (C $d/y)
Z-value
Avg (C $y)
Sen's slope (C $d/y)
Z-value
Avg (C $y)
Sen's slope (C $d/y)
Z-value
3919.6 3154.8 3300.0 3262.8 3358.2 3517.6 2856.6 2644.7 2689.4 2682.4 3086.6 2706.8 2794.0 2230.1 2600.2 2542.7 1827.6 2500.1 2308.6 2927.5 2358.9 2822.1
15.4 7.2 4.8 21.3 18.7 12.8 15.8 16.0 6.6 16.1 21.8 10.2 31.9 15.5 13.6 6.8 4.9 2.4 7.5 8.3 18.2 13.5
2.94 1.18 1.86 2.81 3.03 2.43 3.10 2.51 0.89 2.19 2.77 1.77 4.46 2.74 1.77 1.44 1.35 0.57 1.49 1.41 3.88 2.74
2667.3 2727.2 2616.3 3241.1 3007.5 2451.8 2968.8 3089.1 3170.2 3164.6 3297.1 3442.7 3050.7 3416.8 3493.7 2760.2 3538.2 3435.9 3705.5 2645.4 3234.8 3101.2
2.6 2.1 7.0 9.8 23.7 13.7 4.6 7.0 17.1 17.7 13.4 13.5 9.4 11.4 14.7 7.0 12.1 8.0 11.8 11.8 6.2 9.96
1.05 0.79 2.82 3.26 5.04 4.26 1.31 2.12 4.43 4.74 5.04 3.88 2.77 3.13 4.23 2.69 3.55 2.09 3.88 2.90 2.03 3.97
3606.1 3029.8 3054.8 2896.1 3197.6 3451.2 2615.2 2500.7 2656.9 2794.7 2569.8 2554.8 2669.1 2333.6 2574.9 2341.2 1729.5 2449.6 2230.5 2936.5 2272.9 2688.8
15.4 2.9 12.8 17.4 10.5 12.0 13.5 15.4 13.3 17.5 18.0 12.8 20.0 13.5 13.7 7.4 8.6 10.1 8.9 9.3 13.3 13.4
2.90 0.63 2.29 2.61 1.77 2.03 2.68 2.61 2.16 2.71 3.65 2.12 3.60 2.32 2.06 1.70 2.12 1.90 1.96 1.70 2.94 2.48
2121.4 2199.1 2119.7 2608.0 2362.4 1902.7 2420.7 2720.7 2482.1 2549.3 2592.0 2772.0 2563.5 2813.0 2737.2 2244.6 2990.1 2812.6 2988.8 2021.5 2772.1 2514.0
2.1 4.8 8.1 9.6 14.3 6.9 8.0 10.0 9.9 12.0 11.1 9.1 12.1 9.0 9.6 7.2 12.1 9.1 9.9 5.2 4.0 8.7
0.76 2.12 3.75 4.17 4.82 3.19 3.94 4.23 4.30 4.43 5.01 4.10 4.56 3.78 3.88 3.52 4.43 3.45 3.94 2.42 2.16 4.46
Notes: The Z-value is used to test the significance level (when Z-value reaches 1.96 [or 2.58], the significance level of the changing rate is 95% [or 99%]); GFI, GTI, AFI, and ATI slopes stands for the change rates obtained by the Sen's slope estimate.
The decline in annual GFI and AFI in NNE China is more pronounced than those in the adjacent regions such as Mongolia (Wu et al., 2011), the QTP (Wu et al., 2013), and high latitudes north of 50 N (Frauenfeld et al., 2007). Wu et al. (2011) reported an increasing rate of 7 C $d/y for annual GFI in Mongolia, but only 30% of the 20 studied stations displayed decreasing trends. As in high latitudes (north of 50 N), Frauenfeld et al. (2007) reported a decreasing rate of 8.6 C $d/y for air freezing index during 1967e2001. In addition, on the central QTP, a decreasing rate of 11.1 C $d/y in annual GFI occurred during 1980e2007 (Wu et al., 2013). This difference indicates the warming trend in the winter in Northeast China is similar to other regions in the northern hemisphere, but different from that in Mongolia, where the temperature in winter decreases. To compare the changing trends of freezing index for different regions, however, the same methodologies and data source with uniform time series should be adopted. The Sen's slope estimate gives increasing rates of annual GTI ranging from 2.1 (Ta'he) to 23.7 C $d/y (Erguna), with an average of 9.96 C $d/y. The annual ATI ranged from 2.1 (Mo'he) to 14.3 C $d/y (Erguna), with an average of 8.7 C $d/y (Table 3). The analysis shows that 90.5% (for GTI) and 95.2% (for ATI) stations with a statistically significant increasing trend at a significance level of 0.05. However, no significant changes were observed at Mo'he and Ta'he stations. Annual GTI and ATI on the western flank of the Da Xing'anling Mountains, as represented by Erguna, Manchuria, Haila
to the higher forest coverage in the Yile'huli and Xing'anling Mountains, and colder temperature of the permafrost. The dense forest coverage and the underlying moss layer reduce the direct incident radiation and dampen the rise of ground surface and air temperatures. Since there are high correlations between permafrost and GST (Frauenfeld et al., 2007; Wu et al., 2011), the spike in annual GTI corresponds to an intensive summer warming and increasing thawing degree days, and would cause the deepening of the seasonally thawed layer. Sen's slope estimate indicates statistically significant increases in annual GTI and ATI at a significance level of 0.05. The increasing rate of GTI in NNE China is less drastic than that in Mongolia (29 C $d/y) during 1987e2005 (e.g., Wu et al., 2011), and on central QTP (12.5 C $d/y) during 1980e2007 (Wu et al., 2013), but much higher than in the high north (4.4 C $d/y) during 1967e2001 (Frauenfeld et al., 2007). The difference between the increasing rates in ATI and GTI in the northern hemisphere may be related to varying degrees of summer warming, and imply different degrees of permafrost degradation. The change in the ALT in NNE China is less severe than that in Mongolia and on the QTP, but much sharper than in the high-latitude permafrost regions. Less drastic decreases of the GFI and AFI in permafrost regions indicates that the seasonally frozen ground regions are more susceptible to climate change (Frauenfeld et al., 2004, 2007; Jin et al., 2007; Wu et al., 2010). This is in agreement with that in Russia, where the
D. Luo et al. / Quaternary International 349 (2014) 187e195
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changes in seasonal thaw depth are greater than the seasonal freeze depth (Frauenfeld et al., 2004). The study on the QTP permafrost regions by Wu et al. (2010) shows that the ALT, related to thawing index, in warm permafrost is more than double that in cold permafrost, and is attributed to changes in unfrozen water content with temperature.
and 41301068), Hundred Talents Program of the Chinese Academy of Sciences (Grant No. 51Y251571), Excellent Youth Scholars Fund of Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences.
4. Conclusions
Anisimov, O.A., Lobanov, V.A., Reneva, S.A., Shiklomanov, N.I., Zhang, T.J., Nelson, F.E., 2007. Uncertainties in gridded air temperature fields and effects on predictive active layer modeling. Journal of Geophysical Research 112 (F2), F02S14. Chang, X.L., Jin, H.J., He, R.X., Jing, H.Y., Li, G.Y., Wang, Y.P., Luo, D.L., Yu, S.P., Sun, H.B., 2013. Review of permafrost monitoring in the northern Da Hinggan Mountains, Northeast China. Journal of Glaciology and Geocryology 35 (1), 93e100 (in Chinese). Chen, Y.N., Deng, H.J., Li, Z., Xu, C.C., 2014. Abrupt change of temperature and precipitation extremes in the arid regions of Northwest China. Quaternary International 336, 35e43. Frauenfeld, O.W., Zhang, T.J., Barry, R.G., 2004. Interdecadal changes in seasonal freeze and thaw depths in Russia. Journal of Geophysical Research 109, D05101. Frauenfeld, O.W., Zhang, T.J., McCreight, J.L., 2007. Northern hemisphere freezing/ thawing index variations over the twentieth century. International Journal of Climatology 27, 47e63. Guo, D.X., Li, Z.F., 1981. Preliminary approach to the history and age of permafrost in Northeast China. Journal of Glaciology and Geocryology 3, 1e16 (in Chinese). He, R.X., Jin, H.J., Chang, X.L., Lü, L.Z., Yu, S.P., Yang, S.Z., Wang, S.L., Sun, G.Y., 2009. Degradation of permafrost in the northern part of northeastern China: present state and causal analysis. Journal of Glaciology and Geocryology 31, 829e834 (in Chinese). He, W., Bu, R.C., Xiong, Z.P., Hu, Y.M., 2013. Characteristics of temperature and precipitation in Northeast China from 1961 to 2005. Acta Ecologica Sinica 33, 0519e0531 (in Chinese). Jin, H.J., Yu, Q.H., Lü, L.Z., Guo, D.X., He, R.X., Yu, S.P., Sun, G.Y., Li, Y.W., 2007. Degradation of permafrost in the Xing'anling Mountains, Northeast China. Permafrost and Periglacial Processes 18, 245e258. Jin, H.J., Hao, J.Q., Chang, X.L., Zhang, J.M., Yu, Q.H., Qi, J.L., Lü, L.Z., Wang, S.L., 2010. Zonation and assessment of frozen-ground conditions for engineering geology along the ChinaeRussia crude oil pipeline route from Mo'he to Daqing, Northeastern China. Cold Regions Science and Technology 64 (3), 213e225. Kendall, M.G., 1975. Rank Correlation Methods, fourth ed. Griffin, London, pp. 49e58. Klene, A.E., Nelson, F.E., Shiklomanov, N.I., Hinkel, K.M., 2001. The n-factor in natural landscapes: variability of air and soil-surface temperatures, Kuparuk River Basin, Alaska, U.S.A. Arctic, Antarctic and Alpine Research 33 (2), 140e148. Li, X.C., Gemmer, M., Zhai, J.Q., Liu, X.F., Su, B.D., Wang, Y.J., 2013. Spatio-temporal variation of actual evapotranspiration in the Haihe River Basin of the past 50 years. Quaternary International 304, 133e141. Lu, G.W., Wen, B.L., Guo, D.X., 1993. Geographical southern limit of permafrost in Northeastern China. Journal of Glaciology and Geocryology 15, 214e218 (in Chinese). Ma, L.J., Qin, D.H., 2012. Spatial-temporal characteristics of observed key parameters for snow cover in China during 1957e2009. Journal of Glaciology and Geocryology 34 (1), 1e11 (in Chinese). Ran, Y.H., Li, X., Cheng, G.D., Zhang, T.J., Wu, Q.B., Jin, H.J., Jin, R., 2012. Distribution of permafrost in China: an overview of existing permafrost maps. Permafrost and Periglacial Processes 23, 322e333. Sen, P., 1968. Estimates of the regression coefficient based on Kendall's tau. Journal of the American Statistical Association 63, 1379e1389. Smith, M.W., Riseborough, D.W., 2002. Climate and the limits of permafrost: a zonal analysis. Permafrost and Periglacial Processes 13, 1e15. Wang, B.L., Zhang, M.J., Wei, J.L., Wang, S.J., Li, X.F., Li, S.S., Zhao, A.F., Li, X.S., Fan, J.P., 2013. Changes in extreme precipitation over Northeast China, 1960e2011. Quaternary International 298, 177e186. Wei, Z., Jin, H.J., Luo, C.X., Zhang, J.M., Lü, L.Z., Yang, S.Z., Ji, Y.J., 2008. Characteristics of atmospheric environmental changes of permafrost in northeastern China in 50 years. Journal of Lanzhou University (Natural Sciences) 44, 39e43 (in Chinese). Wei, Z., Jin, H.J., Zhang, J.M., Yu, S.P., Han, X.J., Ji, Y.J., He, R.X., Chang, X.L., 2011. Prediction of permafrost changes in Northeastern China under a changing climate. Science China Earth Sciences 54 (6), 924e935. Wu, T.H., Wang, Q.X., Zhao, L., Batkhishig, O., Watanabe, M., 2011. Observed trends in surface freezing/thawing index over the period 1987e2005 in Mongolia. Cold Regions Science and Technology 69, 105e111. Wu, T.H., Zhao, L., Li, R., Wang, Q.X., Xie, C.W., Pang, Q.Q., 2013. Recent ground surface warming and its effects on permafrost on the central Qinghai-Tibet Plateau. International Journal of Climatology 33, 920e930. Wu, Q.B., Zhang, T.J., 2010. Changes in active layer thickness over the Qinghai-Tibetan Plateau from 1995 to 2007. Journal of Geophysical Research 115, D09107. Wu, Q.B., Zhang, T.J., Liu, Y.Z., 2012. Thermal state of the active layer and permafrost along the Qinghai-Xizang (Tibet) Railway from 2006 to 2010. The Cryosphere 6, 607e612. Zhang, W.G., Li, S.X., Wu, T.H., Pang, Q.Q., 2006. Changes of the difference between ground and air temperature over the Qinghai-Xizang Plateau. Acta Geographica Sinica 61, 899e910 (in Chinese).
Ground surface and air temperatures, freezing and thawing indices, and surface offsets during 1972e2005 at 21 selected stations in NNE China were analyzed in this paper. Both ground surface and air temperatures have showed significant warming trends, but vary spatially in NNE China. The detection techniques of Sen's Slope estimate and ManneKendall trend test have shown that the most pronounced warming occurred in sporadic permafrost regions of NNE China, where the permafrost temperatures are higher than 1 C. The spatial patterns of the freezing index are mostly consistent with the distribution of MAGST and MAGT, the larger the freezing index, the lower the MAGST and MAGT. The changing rates of the freezing and thawing index in the central area of Da Xing'anling (with lowest permafrost temperature at Borehole GH-9 in NNE China) and Yile'huli Mountains (with permafrost temperature lower than 1 C), are relatively moderate. This indicates that the increase of ALT and degradation of permafrost distribution are not noticeable as in other regions in NNE China. The changes in annual GFI and GTI in response to the respective winter and summer warming in NNE China differ from those in other parts of the northern hemisphere. Those in NNE China are less sensitive than those in Mongolia and on the QTP, but more noticeable than in high latitudes (>50 N). The spatial variations of ground surface freezing and thawing indices in NNE China show latitudinal zonality to a certain degree. This study therefore provides evidence supporting the findings that in NNE China permafrost temperature is lowest in the central area of Da Xing'anling Mountains and Yile'huli Mountains. The temporal variations in freezing and thawing indices will facilitate the mapping of permafrost distribution and seasonal freeze and thaw depths. However, the potential forces driving the increasing of thawing index and decreasing of freezing are not clear in NNE China. The variations of snow timing, duration, depth, density and structure could affect the ground thermal regimes on different time-scale basis (daily, monthly, seasonal, and annual) due to seasonal warming impacts. The terrestrial radiation and energy balances could be altered by long-term land use changes and deforestation, causing ground surface and air temperature to rise. Urbanization even in small villages and towns in NNE China could exhibit a strong urban heat island effect especially during the cold season, which would aggravate the warming trends. However, the thermal effects on the ground surface of vegetation cover in summer and snow cover in winter are still not clear, and need to be further studied in NNE China. In the future, the focus will be on the study of the spatiotemporal variations of seasonal freeze (thaw) depth, and the relationships with varying snow depth and freezing and thawing indices, which will help to better understanding the mechanisms of cold environment changes in NNE China. Acknowledgements We thank the reviewers for their constructive and insightful comments and suggestions. We also thank Prof. Geoffrey Gay for improving the English. This work was supported by Global Change Research Program of China (Grant No. 2010CB951402), National Natural Science Foundation (NSF) of China (Grant Nos. 41171055
References
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Quaternary International journal homepage: www.elsevier.com/locate/quaint
Spatiotemporal variations of climate warming in northern Northeast China as indicated by freezing and thawing indices Dongliang Luo a, Huijun Jin a, *, Rui Jin a, Xingguo Yang b, Lanzhi Lü a a
State Key Laboratory of Frozen Soils Engineering, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, Gansu 730000, China b Meteorological Bureau of Ningxia Hui Autonomous Region, Yinchuan 750002, China
a r t i c l e i n f o
a b s t r a c t
Article history: Available online 2 August 2014
As the thermal state of the upper boundary conditions of the soil layer, ground surface and air temperatures sensitively indicate the heat transferring process between atmosphere and land surface. Due to the combined effects of high latitude and elevation, northern northeast (NNE) China is the second largest permafrost region in China. Based on the daily ground surface and air temperatures at 21 selected stations in NNE China, the ManneKendall test and Sen's slope estimate were used to detect changes in the mean annual ground surface temperature (MAGST), mean annual air temperature (MAAT), annual ground surface freezing index (GFI), annual air freezing index (AFI), annual ground surface thawing index (GTI), annual air thawing index (ATI), and surface offset of MAGSTeMAAT for the period between 1972 and 2005. The results show a significant warming in NNE China during the past three decades. The MAGST and MAAT averaged 0.72 and 0.50 C, with mean increasing rates of 0.61 and 0.72 C/10y, respectively. The lowest MAGST and MAAT were observed in the northernmost and middle parts of the Da Xing'anling Mountains. The multiyear average GFI is 2822.1 C /y with a range between 1827.6 and 3919.6 C $d. The multiyear average AFI is 2688.8 C /y with a range between 1729.5 and 3606.1 C $d. Over the same period, the multiyear average GTI ranged between 2451.8 and 3705.5 C $d, with an average of 2514.0 C /y, and the multiyear average of ATI ranged from 1902.7 to 2990.1 C $d, with an average of 2508.3 C . Trend analyses show a significant decline in annual GFI (13.5 C $d/y) and annual AFI (13.4 C $d/y), and a significant increase in annual GTI (9.96 C $d/y) and annual ATI (8.71 C $d/y). The most pronounced warming has occurred in sporadic permafrost regions of NNE China. However, in continuous permafrost, and discontinuous permafrost regions with extensive presence of taliks, such as at Ta'he and Xinlin stations, no significant trend is detected. Study of the variations of freezing and thawing indices may provide some implications of spatiotemporal changes in the thermal regimes of active layer and permafrost soils, and facilitate better understanding of cold environment changes in permafrost regions of Northeast China. © 2014 Elsevier Ltd and INQUA. All rights reserved.
Keywords: Climate Change Freezing and thawing indices Surface offset Permafrost Northern northeast (NNE) China
1. Introduction Northeast China is the second largest expanse of permafrost and the primary region of latitudinal permafrost in China, and the southernmost part of the Eurasian cryosphere (Wei et al., 2011). Latest statistics indicates that the areal extent of permafrost in Northeast China has shrunk to 0.24 106 km2, most of which is in northern northeast (NNE) China, the Da and Xiao Xing'anling Mountains (Ran et al., 2012). Driven by many programs and projects on engineering explorations, design, and construction, and * Corresponding author. E-mail addresses: [email protected] (D. Luo), [email protected] (H. Jin). http://dx.doi.org/10.1016/j.quaint.2014.06.064 1040-6182/© 2014 Elsevier Ltd and INQUA. All rights reserved.
ecological rehabilitation, research on permafrost in NNE China has received increasing attention from scientists, engineerers, and governmental administrators since the late 1950s (Jin et al., 2010; Wei et al., 2011). Among them, delineating the southern limit of permafrost with isotherms of mean annual air temperatures (MAAT) and zoning of permafrost regions (e.g., Guo and Li, 1981; Lu et al., 1993), is one of the most important. Due to its thin and warm nature of the permafrost, and its sensitivity to climate change and anthropogenic activities, permafrost degradation in the Xing'anling Mountains has been clearly observed during the past several decades (Jin et al., 2007; He et al., 2009; Chang et al., 2013). For example, the northward shifting of the southern limit of permafrost from the 1970s to the 2000s has been confirmed by on-site data
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along highways in the Da and Xiao Xing'anling Mountains and the ChinaeRussia Crude Oil Pipeline (CRCOP) route from Mo'he to Daqing (Jin et al., 2007). However, the lack of long-term observation data has made it difficult to quantitatively analyze the spatial and temporal variations of permafrost changes in NNE China. Moreover, these studies on the northward shifting of the southern limit of permafrost in NNE China were based on the analysis of isotherms of MAAT, but without support from adequate data on ground surface temperatures. The ground surface is the direct interface where energy and mass exchanges between earth and atmosphere take place. It is therefore of great importance for predicting thermal regime of permafrost soils and mapping permafrost distribution (Frauenfeld et al., 2007; Wu et al., 2013). Myriad local variations in vegetation, topography, and snow cover can produce differences with a range of several degrees between the MAGST and MAAT over a small region (Smith and Riseborough, 2002). Therefore, the ground surface temperature and related parameters, such as annual GFI and GTI, play important roles in dynamics of active layers and permafrost soils. Because air temperature data are more readily available, most previous studies in Northeast China focused on the spatiotemporal variations of annual, summer and winter air temperatures (e.g., Wei et al., 2008; He et al., 2013). Wei et al. (2008) reported an increase of approximately 1.0 C in MAAT during 1976e2000 compared with that of 1950e1975. He et al. (2013) reported that during 1961e2005, the increasing rate of MAAT is 0.38 C /10y, and the warming trend in winter is 0.53 C /10y, much higher than that in summer (0.24 C /10y). There is little work detailing changes in GST in permafrost regions in NNE China. The intense increase in ground
et al., 2001; Anisimov et al., 2007; Wu et al., 2013). This study will help better understanding changes in the thermal regimes of ground surface, active layer and permafrost soils, and further facilitates the understanding of the stability of cold region environments in Northeast China. 2. Data and methodologies Daily temperature datasets were obtained from the National Climate Center of China Meteorological Administration (http://cdc. cma.gov.cn/home.do). GST is measured on a standard yard of 2 4 m with sensors on the surface of snow cover in wintertime, and bare ground in summertime, while air temperatures are measured at 2 m height. The earliest systematic observations of GST in NNE China started in 1951 at Nenjiang and Keshan stations, and generally around or after the 1960se1970s at most other stations. Although the daily GST at Xiao'ergou, Xin'youqi and Arxaan stations have missing values for several years before the year of 1972, the time series of all the stations are complete after 1972 (Table 1). However, for some unknown reasons, the daily GST at most stations in NNE China suffered a serious absence of measurements during the winters (from November to the next February) after 2005. Therefore, considering continuity, uniformity, and long time series of datasets, 21 meteorological stations in or around permafrost regions with complete and continuous data series from 1972 to 2005 were selected to analyze the spatial and temporal changes in the MAGST, MAAT, and freezing and thawing indices. In addition, data quality control and homogeneity assessment of the ground surface and air temperatures were checked using the RClimDex software (http://etccdi.pacificclimate.org/software.shtml).
Table 1 List of metadata for the 21 selected meteorological stations in NNE China. WMO identification number 50136 50246 50439 50353 50425 50434 50442 50468 50514 50527 50548 50557 50564 50603 50618 50632 50639 50656 50658 50727 50774
Station name Mo'he Ta'he Xinlin Huma Erguna Tuli'he Jagdaqi Hei'he Machuria Hailar Xiaoergou Nenjiang Sunwu Xinyouqi Xinzuoqi Bûgt Zalantun Beian Keshan Arxaan Yichun
Latitude (N)
0
52 58 52 210 51 420 51 430 50 150 50 290 50 240 50 150 49 340 49 130 49 120 49 100 49 260 48 400 48 130 48 460 48 000 48 170 48 030 47 100 47 440
Longitude (E)
0
122 31 124 430 124 200 126 390 120 110 121 410 124 070 127 270 117 260 119 450 123 430 125 140 127 210 116 490 118 160 121 550 122 440 126 310 125 530 119 560 126 550
Elevation (m a.s.l.)
Land use (landscape)
Time series of available measurements
433.0 361.9 494.6 177.4 581.4 732.6 371.7 166.4 661.7 610.2 286.1 242.2 234.5 554.2 642.0 739.7 306.5 269.7 234.6 1027.4 240.9
forest forest high coverage grassland open forest dry land open forest forest forest open forest open forest forest dry land forest open forest open forest forest forest open forest dry land forest high coverage grassland
1958e2006 1972e2005 1972e2005 1956e2005 1958e2005 1957e2005 1966e2005 1959e2005 1958e2005 1956e2005 1960e2005 1951e2005 1957e2005 1961e2005 1960e2005 1957e2005 1952e2005 1958e2005 1951e2005 1952e2005 1958e2005
surface and air temperatures result in major variations of annual freezing and thawing indices, and the active layer thickness (ALT), and eventually extensive permafrost degradation (Wu et al., 2012, 2013). In this study, the spatiotemporal variations of MAAT and MAGST, surface offset between MAAT and MAGST, annual GFI, annual GTI, annual AFI, and annual ATI are analyzed on the basis of daily ground surface and air temperatures from 21 selected meterological stations. The freezing and thawing indices are important for assessing seasonal freeze and thaw depth, as well as the distribution of permafrost and seasonally frozen ground (Klene
There are a number of freezing and thawing indices in the literature. Frauenfeld et al. (2007) reviewed the definitions, principles and methods for calculating the freezing and thawing indices. Among the different methods of computing freezing and thawing indices, the criteria of summing all temperatures below or above 0 C during the freezing (thawing) periods are suitable and plausible (Wu et al., 2011, 2013). The annual freezing (thawing) indices in continuous cold (warm) seasons, the annual freezing index is calculated from July to next June, and the annual thawing index from January to December. The annual freezing and thawing
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Gaussian distribution data, and benefit in less sensitive to outliers in observation records, the ManneKendall test has been widely used in analyzing climate changes (e.g., Li et al., 2013; Wang et al., 2013; Chen et al., 2014). The statistical methods were previously introduced to detect the observed trends in surface freezing and thawing indices on the bordering eastern Mongolia and on the Interior Qinghai-Tibet Plateau (QTP) to the southwest (Wu et al., 2011, 2013).
indices are calculated using the following formulas (Frauenfeld et al., 2007):
FI ¼
DF X
jTn j; Tn < 0 C
(1)
DT X Tp ; Tp > 0 C
(2)
i¼1
TI ¼
3. Results and discussions
i¼1
where FI (TI) is the annual freezing (thawing) index, Tn (Tp) represents the daily GST with negative (positive) temperature during the freezing (thawing) period. The surface offset depends on the isolation and albedo effects of different ground conditions (such as vegetation covers in summer, snow cover in winter). The low thermal conductivity of snow restricts the loss of heat from the ground during the coldest part of the year, and the vegetation reduces the solar radiation reaching the ground surface in summer and the effects on the accumulation and persistence of snow cover. The surface offset that due to the complex processes within the surface layer could be calculated as follows (Smith and Riseborough, 2002):
Surface Offset ¼
189
FIð1 nFÞ TIð1 nTÞ e P P
3.1. Spatiotemporal variations in ground surface and air temperatures During 1972e2005, the average MAAT ranged from 4.25 C (Tuli'he station) to 3.41 C (Zalantun station), with an average of 0.50 C for all the selected 21 stations in NNE China. The lowest MAAT does not occur at the Mo'he Station (52 580 N, 122 310 E, 433.0 m a.s.l.), the northernmost in China, but at the Tuli'he station (50 290 N, 121410 E, 732.6 m a.s.l.) in the middle Da Xing'anling Mountains (Fig. 1). This phenomenon may be attributed to the higher elevation and smaller atmospheric temperature inversion in the central parts (e.g., Tuli'he station) than in the northern parts of the Da Xing'anling Mountains (e.g., Mo'he station), which could affect the latitudinal effects on temperature. The atmospheric temperature inversion in Mo'he is 10 C km1, which is higher than other places in the Da Xing'anling Mountains (Jin et al., 2007). The MAATs are lower than 2.0 C at Mo'he, Ta'he, Tuli'he, Xinlin, Erguna, and Arxaan stations, which are located in, or adjacent to, the regions of continuous permafrost and discontinuous permafrost with taliks (Table 1 and Fig. 1a). The stations in sporadic permafrost regions, including Ai'hui, Xin'youqi, Xin'zuoqi, and Yichun, have a positive average MAAT over the period 1972e2005. The MAGSTs are all warmer than the corresponding MAATs. Although with negative MAATs, the stations of Jagdaqi, Manchuria, Hailar, Xiao'ergou, Sunwu and Bûgt have positive MAGSTs. The average MAGST is less than 2 C at Mo'he and Tuli'he stations, and between 2.0 and 1.0 C at Ta'he, Xinlin, and Erguna stations (Table 2).
(3)
where nF (nT) is scaling factor between winter (summer) air and ground surface temperatures, P is annual period (365 days). Due to the availability of GST, the surface offset in this study could be simplified by subtracting the MAGST from MAAT:
Surface Offset ¼ MAATeMAGST
(4)
The changing rate and its significance level of annual GFI, GTI, AFI, ATI, and surface offset are obtained from the ManneKendall test and Sen's slope estimate (Sen, 1968; Kendall, 1975). The Sen's slope estimate is used to detect the changing rate, while the rank-based nonparametric ManneKendall test is used to obtain the significance level. Because of its robustness and suitability for analyzing non-
Table 2 MAAT, MAGST, surface offset, changing rate, and Z-value obtained from the ManneKendall trend test and Sen's slope estimate at the 21 selected meteorological stations in NNE China. Station
Mo'he Ta'he Xinlin Huma Erguna Tuli'he Jagdaqi Ai'hui Manchuria Hailar Xiao'ergou Nenjiang Sunwu Xin'youqi Xin'zuoqi Bûgt Zalantun Bei'an Keshan Arxaan Yichun Average
MAAT
MAGST
Surface offset
Avg ( C)
Sen's slope (C /10y)
Z-value
Avg ( C)
Sen's slope (C /10y)
Z-value
Avg ( C)
Sen's slope (C /10y)
Z-value
4.09 2.28 2.60 0.78 2.31 4.25 0.54 0.59 0.49 0.69 0.07 0.59 0.31 1.30 0.44 0.27 3.45 0.99 2.07 2.49 1.35 0.50
0.53 0.30 0.58 0.79 0.70 0.48 0.64 0.70 0.67 0.81 0.85 0.60 0.92 0.62 0.55 0.46 0.56 0.52 0.56 0.40 0.55 0.61
2.81 1.70 3.23 3.97 3.75 3.16 3.97 3.94 3.78 4.14 4.78 3.78 4.98 4.01 3.32 2.90 3.84 3.58 3.65 2.55 3.65 3.81
3.50 1.18 1.90 0.09 1.01 2.96 0.29 1.18 1.27 1.25 0.56 1.98 0.63 3.17 2.41 0.57 4.64 2.54 3.79 0.82 2.35 0.72
0.51 0.25 0.32 0.80 0.11 0.71 0.54 0.67 0.69 1.01 0.89 0.62 1.14 0.76 0.75 0.47 0.51 0.35 0.61 0.63 0.72 0.68
2.68 1.41 1.96 3.78 4.62 4.10 3.23 3.45 3.52 4.43 3.75 3.91 5.37 3.78 3.49 3.10 3.29 2.81 3.78 3.55 4.23 3.97
0.62 1.11 0.72 0.73 1.29 1.31 0.86 0.62 1.80 1.98 0.66 1.42 0.99 1.91 2.00 0.87 1.22 1.58 1.75 1.71 1.02 1.25
0.02 0.02 0.21 0.06 0.25 0.27 0.01 0.05 0.003 0.18 0.08 0.06 0.24 0.13 0.22 0.05 0.12 0.20 0.01 0.10 0.20 0.007
0.47 0.31 3.03 0.99 2.58 3.52 0.11 1.15 0.31 2.48 0.89 1.41 2.29 1.31 2.81 0.86 1.99 2.55 0.21 1.25 3.03 2.22
Notes: The Z-value is used to test the significance level (when the Z-value reaches 1.96 [2.58], it means the significance level of the changing rate is 95% [99%]).
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Fig. 1. Distribution of MAAT (a) and MAGST (b), and their increasing rates (c) in NNE China.
In summary, the average MAAT and MAGST during 1972e2005 were lower in the northern and middle Da Xing'anling Mountains, with rising trends in the eastern and southern parts in NNE China. However, the Arxaan station (47100 N, 119 560 E, 1027.4 m a.s.l.), the southernmost one among the 21 stations, has colder MAAT (2.52 C) and MAGST (0.82 C) due to its higher elevation. To a certain extent, this distribution pattern of MAGST and MAAT shows a vertical zonation of temperature in NNE China (Lu et al., 1993). The average time series of the MAAT and MAGST were generated for all the selected 21 stations. The MAAT ranged from 1.75 C in 1987 to 0.84 C in 1990, and with a multiyear average of 0.50 C for all 21 stations (Fig. 2). Over the same period, the MAGST varied from 0.64 C in 1987 to 2.10 C in 1995, and with a multiyear average of 0.72 C for 21 stations. The increasing rate of MAAT ranged from 0.30 (Ta'he) to 0.92 C/10y (Sunwu), with a 21-station average of 0.61 C/10y at a significance level of 0.05 as obtained by the ManneKendall test and Sen's slope estimate (Table 2). That of the MAGST varied from 0.25 (Ta'he) to 1.14 C/10y (Sunwu), with an average at 0.68 C/10y for all 21 stations at a significance level of 0.05.
The results in this study confirm that the most pronounced warming had occurred at Sunwu station in NNE China during the past several decades as indicated by He et al. (2013). However, there is a difference in the increasing rate of MAAT between this study and a previous work. He et al. (2013) reported an increasing rate of MAAT at 0.66 C /10y at Sunwu station during the period 1961e2005. In the present study, the increasing rate of MAAT at Sunwu station (0.92 C /10y) is much higher (Table 2). This may be attributed to different time spans of data (1972e2005). In general the most significant warming appeared in sporadic permafrost regions, e.g., Hailar, Xiao'ergou, and Sunwu stations with increasing rates higher than 0.80 C /10y (Fig. 1c). The increasing rates of MAAT in the central part of the Da Xing'anling Mountains and Yile'huli Mountains, e.g., Mo'he, Tuli'he, Bûgt, and Arxaan stations, were lower than 0.60 C /10y. Over the period 1972e2005, the increasing rates of MAGST were largely consistent with that of MAAT in NNE China. However, the increasing rate of MAGST (0.11 C/10y) is much lower than that of the MAAT (0.70 C/10y) at Erguna station. The significant positive trend for annual mean snow depth in the
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Fig. 2. MAAT and MAGST averaged for the 21 selected stations in NNE China during the period 1972e2005.
eastern Inner Mongolia (Ma and Qin, 2012), may be responsible for the lower increase of the MAGST at Erguna station. Except for the year of 2004 at Xinlin, the years of 1972e1975 at Erguna, the year of 1981 at Ai'hui station, the annual surface offset for most stations are positive, i.e., annual ground surface temperatures are warmer than corresponding annual air temperatures. There are 8 stations with a decreasing trend of surface offset (Table 2). Xinlin, Zalantun and Bei'an stations show significant decreasing trends at a significance level of 0.05. Annual surface offsets at the other 13 stations show increasing trends during 1972e2005. Erguna, Tuli'he, Hailar, Sunwu, Xinzuoqi, and Yichun show significant increasing trends of the annual surface offset at a significance level of 0.05. In total, there are 12 stations which show no statistically significant trends of change in surface offset (Table 2). The average annual surface offset of the 21 stations is 1.25 C , with a statistically significant linear increasing rate of 0.0069 C /y at a significance level of 0.05, similar to the trend as obtained from Sen's slope estimate (0.0071 C /y) (Table 2, Fig. 3a). The variations of annual surface offset may indicate changes in the snow cover, surface vegetation, land use, and even urbanization. The fact that MAGST is higher than MAAT may be related to the thermal effects of surface coverage, which influences the seasonal distribution patterns of ground surface and air temperatures. Previous studies at high latitudes demonstrated that the thermal effect of winter snow cover is generally greater than that of vegetation cover in summer, and the MAGST is likely to be warmer than the MAAT in most cases (Smith and Riseborough, 2002). In comparison with monthly average air temperatures, monthly average ground
surface temperatures are higher during the period MarcheOctober and lower in the wintertime (Fig. 3b). The monthly ground surface and air temperatures are lowest in January (24.3 C and 26.3 C, respectively), and highest in June (23.7 C and 19.7 C, respectively), which are lower than those on the QTP in January and higher than those in June as reported by Zhang et al. (2006). The difference between monthly ground surface and air temperature decreases from 2.0 C in January to 1.5 C in February, and then increases to 0.9 C in March, then reaches the highest value of 4.5 C in June (Fig. 3). After June, the difference between monthly ground surface and air temperatures decreases; until November and December, monthly ground surface temperatures are 0.6 C and 1.64 C lower than monthly air temperatures. The distribution features of surface offsets differ slightly from those on the QTP, where they are largest in July and smallest in November (Zhang et al., 2006). The snow season on the QTP continues from October to next May and is the longest duration in China (Ma and Qin, 2012). There is snow on the ground surface even in June and September. Thought the snow cover in summer is unstable due to the strong radiation, the melting of it consumes much energy for latent heat fusion; hence, the temperature rise on the ground surface will be dampened. Therefore, the largest difference of ground surface and air temperature on the QTP occurs later than in Northeast China. 3.2. Spatial variations of freezing/thawing index The mean annual GFI and AFI are larger in the northernmost and central areas of the Da Xing'anling Mountains, i.e., Mo'he and
Fig. 3. Trends of average annual surface offset (a), and difference of monthly air temperature and ground surface temperature in a year (b) in NNE China during the period 1972e2005.
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Fig. 4. Spatial distribution of mean annual GFI (a), mean annual AFI (b), mean annual GTI (c), and mean annual ATI (d) in NNE China.
Tuli'he stations in continuous permafrost regions, and smaller in regions of sporadic permafrost and seasonally frozen ground (Fig. 4). The mean annual GFI (1827.6 C $d) and AFI (1729.5 C $d) are smallest at Zalantun station, and largest at Mo'he station (3919.6 C $d and 3606.1 C $d). Averaged annual GFI of all the selected stations ranged from 2326.6 C $d (in 2001) to 3311.2 C $d (in 1976), averaged at 2822.1 C $d. Mean annual AFI varied from 2171.3 C $d (in 2001) to 3237.0 C $d (in 1976), averaging 2688.8 C $d, which is higher than on the QTP permafrost (2218 C $d), regions of seasonally frozen ground (SFG) in North America (400 C $d), SFG regions in Asia (889 C $d), and SFG regions in Russia (866 C $d), but far smaller than in the Arctic (3922 C $d), North American permafrost regions (4804 C $d), and Siberian permafrost regions (5651 C $d) as averaged from reanalysis air temperature product (CRU TS 2.1) as reported by Frauenfeld et al. (2007). Not all the mean annual GFI are larger than the corresponding mean annual AFI in NNE China, as those at Hailar, Xin'youqi, and Arxaan are 112.3, 103.5, and 9.0 C $d smaller than the corresponding mean annual AFI. The difference of mean annual GFI and AFI ranged from 112.3 (Hailar) to 516.8 C $d (Xiao'ergou), with an average value of 133.3 C $d for all the 21 stations. The mean annual GTI varied from 2451.8 (Tuli'he) to 3705.5 C $d (Keshan), with an average of 3101.2 C $d for all the 21 stations. The mean
annual ATI ranged from 1902.7 (Tuli'he) to 2990.1 C $d (Zalantun), with an average of 2514.0 C $d for all 21 stations. As revealed from ground boreholes, the lowest MAGT (ground temperature at depth of zero annual amplitude) in NNE China is 3.3 C in the central area of the Da Xing'anling Mountains (Borehole GH-9 in Gen'he, 50.94 N, 121.51 E, 819 m a.s.l.), but higher than 1.0 C in north central part (Borehole MG-1 in Man'gui, 52.04 N, 122.07 E, 633 m a.s.l.) (Chang et al., 2013). While the MAGT is lower than 2.0 C at Borehole CW09 (51.69 N, 124.39 E, 500 m a.s.l.), and lower than 1.0 C at Borehole CW10 (51.47 N, 124.28 E, 580 m a.s.l.) near Xin'lin station, but higher at Boreholes CW05 (52.54 N, 124.58 E, 439 m a.s.l.) and CW06 (52.43 N, 124.66 E, 435 m a.s.l.) near Ta'he station. This shows that the higher freezing indices agree well with lower permafrost temperature in NNE China, and GFI and AFI could be reliable for modeling the thermal regimes of permafrost and predicting permafrost distribution and dynamics. Unlike freezing indices, the mean annual GTI are all larger than the corresponding mean annual ATI. The mean annual ATI ranged from 1898.2 (Tuli'he) to 2981.9 C $d (Zalantun), with an average of 2508.3 C $d for all the selected stations. The mean annual ATI differs from the mean annual GTI by from 368.4 (Aihui) to 756.5 C $d (Xin'zuoqi), with an average difference of 587.2 C $d for all 21 stations. In comparison air thawing index in NNE China, the mean
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annual ATI are higher in Midlatitudes (5195 C $d), SFG regions in North America (4567 C $d), SFG regions in Asia (4132 C $d), SFG regions in Russia (3230 C $d), but lower in the Arctic (1232 C $d), QTP permafrost (682 C $d), and Siberian permafrost (968 C $d) as shown previously (Frauenfeld et al., 2007). The mean annual GFI, GTI, AFI, and ATI show strong latitudinal zonality in NNE China. In the Da Xing'anling Mountains, the mean annual GTI and ATI increase eastwards and southwards (Fig. 4c). On the basis of linear regression analysis, for every degree increase in northern latitude, the mean annual GFI and AFI increase by 238.0 C $d (R2 ¼ 0.60, p ¼ 0.000) and 192.2 C $d (R2 ¼ 0.49, p ¼ 0.000), respectively, while the mean annual GTI and ATI decrease by 119.1 C $d (R2 ¼ 0.29, p ¼ 0.012) and 101.6 C $d (R2 ¼ 0.26, p ¼ 0.019), respectively. 3.3. Temporal variations of freezing/thawing index
Fig. 5. Changing trends in annual GFI, AFI, GTI, and ATI in NNE China during 1972e2005.
The decreasing rate of annual GFI ranged from 6.0 (Ta'he) to 30.9 C $d/y (Sunwu). Except for Ta'he, Xinlin, Manchuria, Bügt, Zalantun, Bei'an, and Arxaan stations, the other 14 stations show statistically significant decreases in annual GFI at a significance level of 0.05 (Table 3). Except for Ta'he, the annual AFI at other 20 stations show statistically significant decreasing trends. Decrease of annual AFI ranged from 2.9 (Ta'he) to 21.9 C $d/y (Xiao'ergou). A large decrease in annual GFI and AFI occurred in sporadic
Fig. 6. Changes in annual GFI (a), annual GTI (b), annual AFI (c), annual ATI (d) for the selected 21 stations in NNE China during 1970e2005. The light gray bold line is the 5-year running average, and the straight line is the linear fit.
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and Xin'zuoqi stations, have increasing rates significantly higher than 14.0 C $d/y (Table 3). The increasing rates of annual ATI are higher than that of annual GTI at Ta'he, Xinlin, Huma, Jagdaqi, Ai'hui, Sunwu, Bûgt, and Bei'an stations, but lower than the corresponding annual GTI at the other15 stations. The increases in GTI and ATI at Mo'he and Ta'he stations are lower than 5.0 C $d/y, but without statistically significant trends. We averaged the GTI and ATI of all 21 stations. As shown in Fig. 5, the increasing rate of the mean annual GTI is 11.0 C $d/y, 2.1 C $d/y higher than that of the corresponding annual ATI. The slower decreasing of GFI and AFI, and smaller increasing of ATI and GTI at Mo'he, Ta'he, and Xinlin stations, may be attributed
permafrost regions of NNE China (Fig. 5). At Ta'he and Xinlin stations along the CRCOP route in the Yile'huli Mountains, the increasing rate of annual GFI is smallest among all the 21 stations. This may suggest that the reduction of seasonally frozen ground is minor compared with other sites in NNE China. The average time series for the annual GFI and AFI are shown in Fig. 6. The decreasing rates of annual GFI and AFI averaged for all 21 stations are both 13.3 C $d/y, but with respective Z-values of 2.74 and 2.48 as obtained from ManneKendall's test. The linear fit of annual GFI and AFI are 12.3 and 12.2 C $d/y, respectively, almost the same with the trend (13.5 and 13.4 C $d/y) as obtained from Sen's slope estimate.
Table 3 Mean values and change trends of freezing and thawing indices of the selected 21 stations in NNE China. Station
Mo'he Ta'he Xinlin Huma Erguna Tuli'he Jagdaqi Ai'hui Manchuria Hailar Xiao'ergou Nenjiang Sunwu Xin'youqi Xin'zuoqi Bûgt Zalantun Bei'an Keshan Arxaan Yichun Average
GFI
GTI
AFI
ATI
Avg (C $d)
Sen's slope (C $d/y)
Z-value
Avg (C $y)
Sen's slope (C $d/y)
Z-value
Avg (C $y)
Sen's slope (C $d/y)
Z-value
Avg (C $y)
Sen's slope (C $d/y)
Z-value
3919.6 3154.8 3300.0 3262.8 3358.2 3517.6 2856.6 2644.7 2689.4 2682.4 3086.6 2706.8 2794.0 2230.1 2600.2 2542.7 1827.6 2500.1 2308.6 2927.5 2358.9 2822.1
15.4 7.2 4.8 21.3 18.7 12.8 15.8 16.0 6.6 16.1 21.8 10.2 31.9 15.5 13.6 6.8 4.9 2.4 7.5 8.3 18.2 13.5
2.94 1.18 1.86 2.81 3.03 2.43 3.10 2.51 0.89 2.19 2.77 1.77 4.46 2.74 1.77 1.44 1.35 0.57 1.49 1.41 3.88 2.74
2667.3 2727.2 2616.3 3241.1 3007.5 2451.8 2968.8 3089.1 3170.2 3164.6 3297.1 3442.7 3050.7 3416.8 3493.7 2760.2 3538.2 3435.9 3705.5 2645.4 3234.8 3101.2
2.6 2.1 7.0 9.8 23.7 13.7 4.6 7.0 17.1 17.7 13.4 13.5 9.4 11.4 14.7 7.0 12.1 8.0 11.8 11.8 6.2 9.96
1.05 0.79 2.82 3.26 5.04 4.26 1.31 2.12 4.43 4.74 5.04 3.88 2.77 3.13 4.23 2.69 3.55 2.09 3.88 2.90 2.03 3.97
3606.1 3029.8 3054.8 2896.1 3197.6 3451.2 2615.2 2500.7 2656.9 2794.7 2569.8 2554.8 2669.1 2333.6 2574.9 2341.2 1729.5 2449.6 2230.5 2936.5 2272.9 2688.8
15.4 2.9 12.8 17.4 10.5 12.0 13.5 15.4 13.3 17.5 18.0 12.8 20.0 13.5 13.7 7.4 8.6 10.1 8.9 9.3 13.3 13.4
2.90 0.63 2.29 2.61 1.77 2.03 2.68 2.61 2.16 2.71 3.65 2.12 3.60 2.32 2.06 1.70 2.12 1.90 1.96 1.70 2.94 2.48
2121.4 2199.1 2119.7 2608.0 2362.4 1902.7 2420.7 2720.7 2482.1 2549.3 2592.0 2772.0 2563.5 2813.0 2737.2 2244.6 2990.1 2812.6 2988.8 2021.5 2772.1 2514.0
2.1 4.8 8.1 9.6 14.3 6.9 8.0 10.0 9.9 12.0 11.1 9.1 12.1 9.0 9.6 7.2 12.1 9.1 9.9 5.2 4.0 8.7
0.76 2.12 3.75 4.17 4.82 3.19 3.94 4.23 4.30 4.43 5.01 4.10 4.56 3.78 3.88 3.52 4.43 3.45 3.94 2.42 2.16 4.46
Notes: The Z-value is used to test the significance level (when Z-value reaches 1.96 [or 2.58], the significance level of the changing rate is 95% [or 99%]); GFI, GTI, AFI, and ATI slopes stands for the change rates obtained by the Sen's slope estimate.
The decline in annual GFI and AFI in NNE China is more pronounced than those in the adjacent regions such as Mongolia (Wu et al., 2011), the QTP (Wu et al., 2013), and high latitudes north of 50 N (Frauenfeld et al., 2007). Wu et al. (2011) reported an increasing rate of 7 C $d/y for annual GFI in Mongolia, but only 30% of the 20 studied stations displayed decreasing trends. As in high latitudes (north of 50 N), Frauenfeld et al. (2007) reported a decreasing rate of 8.6 C $d/y for air freezing index during 1967e2001. In addition, on the central QTP, a decreasing rate of 11.1 C $d/y in annual GFI occurred during 1980e2007 (Wu et al., 2013). This difference indicates the warming trend in the winter in Northeast China is similar to other regions in the northern hemisphere, but different from that in Mongolia, where the temperature in winter decreases. To compare the changing trends of freezing index for different regions, however, the same methodologies and data source with uniform time series should be adopted. The Sen's slope estimate gives increasing rates of annual GTI ranging from 2.1 (Ta'he) to 23.7 C $d/y (Erguna), with an average of 9.96 C $d/y. The annual ATI ranged from 2.1 (Mo'he) to 14.3 C $d/y (Erguna), with an average of 8.7 C $d/y (Table 3). The analysis shows that 90.5% (for GTI) and 95.2% (for ATI) stations with a statistically significant increasing trend at a significance level of 0.05. However, no significant changes were observed at Mo'he and Ta'he stations. Annual GTI and ATI on the western flank of the Da Xing'anling Mountains, as represented by Erguna, Manchuria, Haila
to the higher forest coverage in the Yile'huli and Xing'anling Mountains, and colder temperature of the permafrost. The dense forest coverage and the underlying moss layer reduce the direct incident radiation and dampen the rise of ground surface and air temperatures. Since there are high correlations between permafrost and GST (Frauenfeld et al., 2007; Wu et al., 2011), the spike in annual GTI corresponds to an intensive summer warming and increasing thawing degree days, and would cause the deepening of the seasonally thawed layer. Sen's slope estimate indicates statistically significant increases in annual GTI and ATI at a significance level of 0.05. The increasing rate of GTI in NNE China is less drastic than that in Mongolia (29 C $d/y) during 1987e2005 (e.g., Wu et al., 2011), and on central QTP (12.5 C $d/y) during 1980e2007 (Wu et al., 2013), but much higher than in the high north (4.4 C $d/y) during 1967e2001 (Frauenfeld et al., 2007). The difference between the increasing rates in ATI and GTI in the northern hemisphere may be related to varying degrees of summer warming, and imply different degrees of permafrost degradation. The change in the ALT in NNE China is less severe than that in Mongolia and on the QTP, but much sharper than in the high-latitude permafrost regions. Less drastic decreases of the GFI and AFI in permafrost regions indicates that the seasonally frozen ground regions are more susceptible to climate change (Frauenfeld et al., 2004, 2007; Jin et al., 2007; Wu et al., 2010). This is in agreement with that in Russia, where the
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changes in seasonal thaw depth are greater than the seasonal freeze depth (Frauenfeld et al., 2004). The study on the QTP permafrost regions by Wu et al. (2010) shows that the ALT, related to thawing index, in warm permafrost is more than double that in cold permafrost, and is attributed to changes in unfrozen water content with temperature.
and 41301068), Hundred Talents Program of the Chinese Academy of Sciences (Grant No. 51Y251571), Excellent Youth Scholars Fund of Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences.
4. Conclusions
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Ground surface and air temperatures, freezing and thawing indices, and surface offsets during 1972e2005 at 21 selected stations in NNE China were analyzed in this paper. Both ground surface and air temperatures have showed significant warming trends, but vary spatially in NNE China. The detection techniques of Sen's Slope estimate and ManneKendall trend test have shown that the most pronounced warming occurred in sporadic permafrost regions of NNE China, where the permafrost temperatures are higher than 1 C. The spatial patterns of the freezing index are mostly consistent with the distribution of MAGST and MAGT, the larger the freezing index, the lower the MAGST and MAGT. The changing rates of the freezing and thawing index in the central area of Da Xing'anling (with lowest permafrost temperature at Borehole GH-9 in NNE China) and Yile'huli Mountains (with permafrost temperature lower than 1 C), are relatively moderate. This indicates that the increase of ALT and degradation of permafrost distribution are not noticeable as in other regions in NNE China. The changes in annual GFI and GTI in response to the respective winter and summer warming in NNE China differ from those in other parts of the northern hemisphere. Those in NNE China are less sensitive than those in Mongolia and on the QTP, but more noticeable than in high latitudes (>50 N). The spatial variations of ground surface freezing and thawing indices in NNE China show latitudinal zonality to a certain degree. This study therefore provides evidence supporting the findings that in NNE China permafrost temperature is lowest in the central area of Da Xing'anling Mountains and Yile'huli Mountains. The temporal variations in freezing and thawing indices will facilitate the mapping of permafrost distribution and seasonal freeze and thaw depths. However, the potential forces driving the increasing of thawing index and decreasing of freezing are not clear in NNE China. The variations of snow timing, duration, depth, density and structure could affect the ground thermal regimes on different time-scale basis (daily, monthly, seasonal, and annual) due to seasonal warming impacts. The terrestrial radiation and energy balances could be altered by long-term land use changes and deforestation, causing ground surface and air temperature to rise. Urbanization even in small villages and towns in NNE China could exhibit a strong urban heat island effect especially during the cold season, which would aggravate the warming trends. However, the thermal effects on the ground surface of vegetation cover in summer and snow cover in winter are still not clear, and need to be further studied in NNE China. In the future, the focus will be on the study of the spatiotemporal variations of seasonal freeze (thaw) depth, and the relationships with varying snow depth and freezing and thawing indices, which will help to better understanding the mechanisms of cold environment changes in NNE China. Acknowledgements We thank the reviewers for their constructive and insightful comments and suggestions. We also thank Prof. Geoffrey Gay for improving the English. This work was supported by Global Change Research Program of China (Grant No. 2010CB951402), National Natural Science Foundation (NSF) of China (Grant Nos. 41171055
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