Factors Responsible for the Increase of Winter Low Temperature Extremes from the Mid-1990s to the Early 2010s in Northern China

Zunya Wang aLaboratory for Climate Studies, National Climate Center, China Meteorological Administration, Beijing, China

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Yanju Liu aLaboratory for Climate Studies, National Climate Center, China Meteorological Administration, Beijing, China

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Guofu Wang aLaboratory for Climate Studies, National Climate Center, China Meteorological Administration, Beijing, China

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Qiang Zhang aLaboratory for Climate Studies, National Climate Center, China Meteorological Administration, Beijing, China

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Abstract

It is argued that the occurrence of cold events decreases under the background of global warming. However, from the mid-1990s to the early 2010s, northern China experienced a period of increasing occurrence of low temperature extremes (LTE). Factors responsible for this increase of LTE are investigated in this analysis. The results show that the interdecadal variation of the winter mean temperature over mid- and high-latitude Eurasia acts as an important thermal background. It is characterized by two dominant modes, the “consistent cooling” pattern and the “warm high-latitude Eurasia and cold midlatitude Eurasia” pattern, from the mid-1990s to the early 2010s. The two patterns jointly provide a cooling background for the increase of LTE in northern China. Meanwhile, though the interdecadal variation of the Arctic Oscillation (AO), Ural blocking (UB), and Siberian high (SH) are all highly correlated with the occurrence of LTE in northern China, the AO is found to play a dominant role. On one hand, the AO directly affects the occurrence of LTE because of its dynamic structure; on the other hand, it takes an indirect effect by affecting the intensity of UB and SH. Further analyses show that the winter temperature in mid- and high-latitude Eurasia and the AO are independent factors that influence the increase of LTE in northern China from the mid-1990s to the early 2010s.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Qiang Zhang, zhq62@cma.gov.cn

Abstract

It is argued that the occurrence of cold events decreases under the background of global warming. However, from the mid-1990s to the early 2010s, northern China experienced a period of increasing occurrence of low temperature extremes (LTE). Factors responsible for this increase of LTE are investigated in this analysis. The results show that the interdecadal variation of the winter mean temperature over mid- and high-latitude Eurasia acts as an important thermal background. It is characterized by two dominant modes, the “consistent cooling” pattern and the “warm high-latitude Eurasia and cold midlatitude Eurasia” pattern, from the mid-1990s to the early 2010s. The two patterns jointly provide a cooling background for the increase of LTE in northern China. Meanwhile, though the interdecadal variation of the Arctic Oscillation (AO), Ural blocking (UB), and Siberian high (SH) are all highly correlated with the occurrence of LTE in northern China, the AO is found to play a dominant role. On one hand, the AO directly affects the occurrence of LTE because of its dynamic structure; on the other hand, it takes an indirect effect by affecting the intensity of UB and SH. Further analyses show that the winter temperature in mid- and high-latitude Eurasia and the AO are independent factors that influence the increase of LTE in northern China from the mid-1990s to the early 2010s.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Qiang Zhang, zhq62@cma.gov.cn

1. Introduction

The Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC) reported that the global mean temperature increased 0.85°C (0.65°–1.06°C) during 1880–2012 (IPCC 2013). Under the background of global warming, the frequency and intensity of extreme events have changed correspondingly (IPCC 2012). General decreasing trends in low temperature extremes were reported over different regions worldwide but with a diversity of magnitude and frequency (Heino et al. 1999; Plummer et al. 1999; Easterling et al. 2000; Bonsal et al. 2001; Manton et al. 2001; Barbson and Palutikof 2002; Klein Tank and Können 2003; DeGaetano and Allen 2002; Peterson et al. 2002; Aguilar et al. 2005; Zhang et al. 2005; Nogaj et al. 2006; Vincent and Mekis 2006; El Kenawy et al. 2019; Sen 2019).

The society and economy in China are heavily affected by extremely low temperatures during wintertime. Significant decreasing trends in low temperature extremes were observed in China during recent decades, with greater magnitude in the northern part of China and during the wintertime (Zhai and Pan 2003; Qain and Lin 2004; Wang et al. 2012; Li 2014; Yu and Li 2015; Wang et al. 2018; Shi et al. 2018). However, obvious cold anomalies over the Euro-Asian continent during winter were reported in recent years under the background of global warming (Ding et al. 2008; Bao et al. 2010; Cohen et al. 2010; Wang et al. 2010; Petoukhov and Semenov 2010; Blunden et al. 2011; Guirguis et al. 2011; Peterson et al. 2012; Liu et al. 2012; Wallace et al. 2014; Zhou et al. 2018). For example, northern parts of the Northern Hemisphere experienced an extreme cold winter in 2005/06; unprecedented extreme low temperature, snowfall, and icing events hit China in early 2008; parts of Europe, Russia, and the United States suffered frigid temperatures during the winters of 2009/10 and 2010/11. Some researchers have noticed the increase of occurrence of the low temperature extremes (LTE) in China after the 1990s (Wang et al. 2012; Ma et al. 2018). However, is this increase statistically significant, is it an interdecadal variation or a stable changing trend, and what are the temporal and spatial characteristics? These questions will be first investigated in this study to learn the feature of the recent increase of LTE and lay the foundation for further analysis of the possible causes.

Some studies have pointed out that the frequent cold events in recent years are part of the “warm Arctic and cold continent” pattern, which is closely related to global warming (Petoukhov and Semenov 2010; Cohen et al. 2012, 2014; Screen and Simmonds 2014; Semenov and Latif 2015). In particular, the rapid Arctic warming plays an important role (Honda et al. 2009; Cohen et al. 2012; Liu et al. 2012; Zhang et al. 2012; Mori et al. 2014; Luo et al. 2017; Ma et al. 2018; Ma and Zhu 2019). The Arctic warming has resulted in a reduced meridional gradient of air temperature, and then a wavier jet stream and broader meridional meander in mid–high latitudes. This favors the occurrence of Ural blocking (UB) and intensification of Siberian high (SH). The UB enhances cold advection downstream (Wu and Wang 2002), while the strengthened SH characterizes a stronger-than-normal East Asian winter monsoon (Ding and Krishnamurti 1987; Ding 1990; Gong and Ho 2002). Both of the two circulations favor the southward outbreak of cold airs and then contribute to the occurrence of cold events over East Asia (Ding and Krishnamurti 1987; Zhang et al. 1997; Park et al. 2014; Nakamura et al. 2016). Besides, the Arctic Oscillation (AO) has long been regarded as one of the important large-scale factors affecting the winter weather and climate over East Asia (Gong and Wang 1999; Wu and Wang 2002; Jeong and Ho 2005; Liu et al. 2012; Ma et al. 2018). AO’s negative phase has higher-than-average air pressure over the Arctic region and lower-than-average pressure over mid–high latitudes (Thompson and Wallace 1998; Thompson et al. 2000). Then polar cold air easily breaks out southward and causes more cold events in mid–high latitudes. Moreover, the AO is also believed to have close relationship with the variation of UB and SH (Wu and Wang 2002; Wang et al. 2010; Park et al. 2011). On one hand, the negative AO phase, companying with great meridional meanders, is favorable for the occurrence of UB. On the other hand, the AO index is negatively correlated with the intensity of SH. It is obvious that previous research has revealed a lot of factors and possible mechanisms affecting the winter weather and climate in East Asia. However, the factors affecting the recent increase of LTE in China are not clear, and the related physical processes also need to be investigated further. Therefore, these issues will be discussed in this analysis.

The remainder of this paper is structured as follows: The data and methods will be introduced in section 2. Section 3 will reveal the spatial and temporal characteristics of the recent increase of LTE in China. In section 4, the relationship between the frequency of LTE in China and the winter temperature over mid–high-latitude Eurasia will be investigated. The impacts of general circulations will be discussed in section 5. Conclusions and discussion will be presented in section 6.

2. Data and methods

The daily minimum temperature data from 2419 observation stations in China during 1961–2019 were used in this study. The dataset includes measurements from 212 national reference stations, 632 national basic stations, and 1575 national observatories. The dataset was compiled by the China Meteorological Administration, with spatial consistency, temporal consistency, and internal consistency being checked and suspicious records being adjusted (Cao et al. 2016; Ren et al. 2017). Two more data processing steps were performed to obtain more reliable climatic statistics. First, the winters (December–February) with total missing records equal to or more than 20% were removed for a fixed station. Second, the stations with consecutive records of less than 30 yr were excluded. Then, the data from 2315 stations were adopted.

The monthly average daily minimum temperature of the gridded Climatic Research Unit (CRU) Time series (TS) data, version 4.04, from 1961 to 2019 was used to analyze the spatial–temporal characteristics of the temperatures over mid- and high-latitude Eurasia, with a resolution of 0.5° × 0.5° (University of East Anglia Climatic Research Unit et al. 2020).

According to the IPCC, extreme climate (extreme weather or climate event) is defined as the occurrence of a value of a weather or climate variable above (or below) a threshold value near the upper (or lower) ends of the range of observed values of the variable (IPCC 2012). To quantify climate extremes, the Expert Team on Climate Change Detection and Indices (ETCCDI) defined 27 extreme indices (IPCC 2007). In this analysis, the frequency of LTE was calculated following the definition of the ETCCDI. For a single station, the daily minimum temperature on a certain day as well as the previous and subsequent 5 days during 1981–2010 was arranged in ascending order, and then the value corresponding to the 10th percentile was taken as the threshold for this day. An LTE was identified when the daily minimum temperature was lower than the threshold.

Additionally, the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis dataset was used to provide the related circulation patterns (Kalnay et al. 1996). The spatial resolution consists of 2.5° × 2.5° grids. The daily AO index was also used (http://www.cpc.ncep.noaa.gov/products/precip/CWlink/daily_ao_index/ao.shtml).

In this research, Fourier harmonics analysis was performed to extract the interdecadal variations. For the winters from 1961/62 to 2018/19, the sum of the first–sixth harmonics was taken as the interdecadal component. Empirical orthogonal function (EOF) analysis and correlation analysis were adopted, and Student’s t test was used to assess the statistical significance. Note that the interdecadal components have very high autocorrelations, and the effective sample size for the significance test of correlation can be estimated as follows:
N*=Nτ=(N1)N1(1|τ|/N)ρx(τ)ρy(τ)
where N* is the effective sample size and ρx(τ) and ρy(τ) are the autocorrelation functions of the time series of x(t) and y(t), respectively (Davis 1976; Bretherton et al. 1999). Area-weighted average is adopted in this analysis.

3. Changes of LTE in China

Figure 1 shows the linear trend of winter occurrence of LTE in each station of China from 1961/62 to 2018/19. A general decreasing trend is observed for most of China, exceeding the confidence level of 95% in 86% of stations. The average occurrence of LTE in China also shows a significant decreasing trend, with the linear trend coefficient being −2.6 days decade−1 (−29.7% decade−1) and exceeding the confidence of 99% (Fig. 2a). The changing trend in LTE is generally consistent with previous studies (Zhai and Pan 2003; Qain and Lin 2004; Wang et al. 2012; Li 2014; Yu and Li 2015). However, a decreasing pause was noticed after the mid-1990s, without a linear trend being detected. In particular, a slightly increasing trend was observed from the mid-1990s to the early 2010s. But after the early 2010s, the occurrence of China-averaged LTE turned to decrease. Calculations show that the greatest increasing trend appeared in 1996/97 to 2012/13; this period is focused on in this analysis.

Fig. 1.
Fig. 1.

(a) Linear trends of the frequencies of LTE in winter from 1961/62 to 2018/19 for each station in China, with the black crosses indicating exceedance of the 95% confidence level. (b) Time series of the frequencies of LTE averaged over China in winter from 1961/62 to 2018/19. The red line indicates the interdecadal component, and the black line presents the linear trend.

Citation: Journal of Applied Meteorology and Climatology 60, 9; 10.1175/JAMC-D-20-0225.1

Fig. 2.
Fig. 2.

(a) Linear trends of the frequencies of LTE in winters from 1996/97 to 2012/13 for each station in northern China (to the north of 35°N), with the black crosses indicating exceedance of the 95% confidence level. (b) Time series of the frequencies of LTE averaged over northern China in winter from 1996/97 to 2012/13. The red line indicates the interdecadal component, and the black and blue lines present the linear trend from 1961/62 to 1995/96 and from 1996/97 to 2012/13, respectively.

Citation: Journal of Applied Meteorology and Climatology 60, 9; 10.1175/JAMC-D-20-0225.1

By calculating the linear trend coefficients of winter occurrence of LTE in each station of China from 1996/97 to 2012/13, the greatest increasing magnitude is observed in northern China (to the north of 35°N). As shown in Fig. 2a, the increasing trend is observed in 80.3% of total stations in northern China and exceeded the confidence level of 95% in 83.1% of them. Figure 2b shows the winter occurrence of LTE averaged over northern China. A significant decreasing trend is observed from 1961/62 to 1995/1996, with the linear trend coefficient being −4.9 days decade−1 (28.5% decade−1, relative to the average from 1961/62 to 2018/19). An interdecadal transition occurred in the mid-1990s, however, from a decreasing trend to an increasing trend. From 1996/97 to 2012/13, the winter frequency of LTE has increased at a speed of 3.5 days decade−1 (28.5% decade−1, relative to the average of 1961/62 to 2018/19), exceeded the confidence level of 95%. After 2012/13, the occurrence of LTE in northern China turned to decrease. The relatively cold period from the mid-1990s to the early 2010s constitutes an important part of the interdecadal variation of the LTE occurrence in northern China.

4. Relation with the temperature in mid–high-latitude Eurasia

Changes in mean climate affect directly the occurrence of weather and climate extremes. Generally, an increase in average temperature leads to a decrease in cold extremes. To understand the impacts of temperature background on the changes in the occurrence of LTE in northern China, the temporal and spatial variations in the winter average temperature over mid- and high-latitude Eurasia were discussed first.

From 1996/97 to 2012/13, the winter occurrence of LTE in northern China increased greatly. During this period, the average winter temperature shows a significant increasing trend over high-latitude Eurasia but a deceasing trend over midlatitude Eurasia (Fig. 3). This distribution of changing trend is consistent with the “warm Arctic and cold continent” pattern (Cohen et al. 2010, 2012, 2014; Petoukhov and Semenov 2010; Wallace et al. 2014; Screen and Simmonds 2014; Semenov and Latif 2015). It is obvious that the cooling over midlatitude Eurasia provided a favorable thermal background for the increase of occurrence of LTE in northern China.

Fig. 3.
Fig. 3.

Linear trends of the average winter temperature over the Northern Hemisphere from 1996/97 to 2012/13, with the black cross denoting exceedance of the 95% confidence level.

Citation: Journal of Applied Meteorology and Climatology 60, 9; 10.1175/JAMC-D-20-0225.1

Figure 4 shows the spatial–temporal variation of the winter temperature over mid–high-latitude Eurasia by EOF analysis. The first mode accounts for 63% of the total variance and is characterized by the “consistent variation” pattern across the region (Fig. 4a). In winters from 1961/62 to 2018/19, a significant increasing trend is observed in the first principal component (PC1), with obvious interdecadal variation (Fig. 4b). Then the first mode depicts the consistent warming over the whole of mid- and high-latitude Eurasia. The correlation of the PC1 and the global mean winter temperature reaches 0.80 on the interdecadal time scale and 0.68 on the interannual time scale, exceeding the confidence level of 99%. Therefore, it is reasonable to take the first mode of the temperature in mid- and high-latitude Eurasia as a regional manifestation of global warming. The meridional dipole pattern features the second mode, accounting for 16.8% of the total variance (Fig. 4c). The interannual and interdecadal variations dominate the second principal component (PC2) (Fig. 4d). It can be noticed that the “warm high-latitude Eurasia and cold midlatitude Eurasia” pattern occurred from the 1960s to the mid-1980s and again from the mid-1990s to the early 2010s, whereas the opposite pattern was maintained between the two periods.

Fig. 4.
Fig. 4.

The first two leading modes [(a) the first mode; (c) the second mode] and principal components [(b) the first principal component; (d) the second principal component] of the EOF analysis on average winter temperature over mid–high-latitude Eurasia. In (b) and (d), the red lines denote the interdecadal variations and the black lines denote the linear trend fittings.

Citation: Journal of Applied Meteorology and Climatology 60, 9; 10.1175/JAMC-D-20-0225.1

After the linear trend is removed, both minus PC1 and PC2 show highly similar interdecadal variations with the frequency of LTE in northern China (Fig. 5). An obvious interdecadal transition in the mid-1990s is noticed for the PC1. The general increase of temperature over mid- and high-latitude Eurasia shifted to decrease (Fig. 5a). And from the mid-1990s to the early 2010s, the “consistent cooling” pattern dominates the winter temperature over mid- and high-latitude Eurasia. This pattern just corresponds to the “global warming hiatus” (Kerr 2009; Easterling and Wehner 2009; Medhaug et al. 2017). It is the phenomenon that the surface of Earth seemed hardly to warm between about 1998 and 2012 (Medhaug et al. 2017). The high correlation between the minus PC1 and the frequency of the occurrence of LTE in northern China on the interdecadal time scale, being 0.77 (Table 1), presents that the “consistent cooling” pattern is the important background of more LTE during the mid-1990s to the early 2010s. Meanwhile, the correlation of interdecadal components between the PC2 and the frequency of LTE in northern China also reaches 0.62 (Table 1), exceeding the confidence level of 95% (Fig. 5b). An interdecadal transition is also evidently observed in the mid-1990s. As this transition, the “warm high-latitude Eurasia and cold midlatitude Eurasia” pattern dominates from the mid-1990s to the early 2010s. The cold midlatitude Eurasia is also favorable for the occurrence of LTE in northern China.

Fig. 5.
Fig. 5.

The interdecadal components of frequencies of the LTE averaged over northern China and the negative (a) PC1 and (b) PC2 of winter temperature over mid–high-latitude Eurasia from 1961 to 2019. The linear trend is removed, and the value is normalized.

Citation: Journal of Applied Meteorology and Climatology 60, 9; 10.1175/JAMC-D-20-0225.1

Table 1.

Correlations between the frequencies of LTE in northern China and different variables in winter from 1961/62 to 2018/19 on the interdecadal time scale (the linear trend is removed), and linear trend coefficients of each variable in winter from 1996/97 to 2012/13. An asterisk indicates statistical significance at the 95% confidence level.

Table 1.

Overall, the winter temperature over mid- and high-latitude Eurasia is closely related to the occurrence of LTE in northern China on the interdecadal time scale. The “consistent cooling” pattern and the “warm high-latitude Eurasia and cold midlatitude Eurasia” pattern jointly favor the increase of LTE in northern China from the mid-1990s to the early 2010s, as the important thermal background.

5. Related circulation anomalies

In this section, the atmospheric internal factors responsible for the increase of LTE in northern China from the mid-1990s to the early 2010s were investigated. The circulation anomalies at different layers were regressed against the normalized frequencies of LTE averaged over northern China on the interdecadal time scale. In the calculation, the linear trend has been removed. As shown in Fig. 6a, the negative phase of AO characterizes the mid–high-layer atmosphere, when the occurrence of LTE is more than normal. The positive height anomalies over the Arctic indicate the weakened Arctic vortex, and the cold air breaks out southward from the Arctic to the mid–high latitude along the pressure gradient. Meanwhile, the negative AO phase corresponds to the pattern with “ridge over Ural and trough over northeast Asia” at the 500-hPa level. This circulation pattern, with great meridional meander, also favors the southward intrusion of cold air, and then results in more LTE in northern China. At the 850-hPa level (Fig. 6b), the anticyclonic anomalies control the Ural, while the cyclonic circulation is over northeast Asia. The circulation anomalies match the “ridge over Ural and trough over northeast Asia” pattern at the mid–high level well. The northerly airflows prevail in most of northern China, leading to the intensification of the East Asian winter monsoon and frequent cold air activities. In the sea level pressure (SLP) regressing field, the strong Siberian high and deep Asian low can be observed clearly. This pattern can intensify the cold advection, and then induce the occurrence of chilly weather. The consistent spatial patterns at different layers present a barotropic vertical structure of atmosphere. Therefore, the deep and stable atmosphere provides an advantageous dynamical condition for the occurrence of LTE and the maintenance of the cold period from the mid-1990s to the early 2010s.

Fig. 6.
Fig. 6.

Regressions of (a) 500-hPa geopotential height (color shaded; black crosses indicate exceedance of the 95% confidence level), (b) 850-hPa wind (vectors; color shading indicates terrain heights greater than 1000 m, and blue dots indicate exceedance of the 95% confidence level), and (c) sea level pressure anomalies (color shading; black dots indicate exceedance of the 95% confidence level) against the frequencies of LTE averaged over northern China (to the north of 35°N) on the interdecadal time scale.

Citation: Journal of Applied Meteorology and Climatology 60, 9; 10.1175/JAMC-D-20-0225.1

The close relationship between the occurrence of LTE and the AO index can be observed more clearly in Fig. 7. The evolution of frequencies of LTE averaged over northern China is almost opposite to the winter AO index. Their correlation coefficient reaches −0.71, exceeding the confidence level of 95% (Table 1). That is, the smaller or greater the AO index is, the higher or lower the frequency of LTE in northern China is, respectively. From the mid-1990s to early 2010s, the decreasing AO index just corresponds to the significantly increasing LTE in northern China. Circulation anomalies regressed on the negative AO index are shown in Fig. 8. By comparison, the circulation patterns are found highly similar to those favorable for the occurrence of LTE as shown in Fig. 6. This high similarity further indicates the close relationship between the AO and the occurrence of LTE in northern China.

Fig. 7.
Fig. 7.

The interdecadal components of the frequency of LTE in northern China (red line) and the AO index (green dashed line) in winter from 1961 to 2019. The linear trend is removed, and the value is normalized.

Citation: Journal of Applied Meteorology and Climatology 60, 9; 10.1175/JAMC-D-20-0225.1

Fig. 8.
Fig. 8.

As in Fig. 6, but for the regressions on the negative AO index in winter.

Citation: Journal of Applied Meteorology and Climatology 60, 9; 10.1175/JAMC-D-20-0225.1

Except for the negative AO phase, the stronger-than-normal SH and the UB accompany the increase of LTE in northern China, as shown in Fig. 6 and Fig. 8. For quantitative analysis, the Ural blocking index (UBI) is defined as the mean geopotential height at the 500-hPa level averaged over 45°–75°E and 40°–60°N, and the Siberian high index (SHI) is defined as the mean SLP averaged over 80°–120°E and 40°–60°N (Wu and Wang 2002). The correlation between the UBI and the occurrence of LTE in northern China on the interdecadal time scale is 0.50, exceeding the confidence level of 95% (Table 1). The high correlation indicates that the development of the Ural blocking favors the occurrence of LTE. However, the Ural blocking is closely related to the AO (Li et al. 2012; Peings 2019). Then is the AO or the Ural blocking the dominant influential factor of the occurrence of LTE in northern China? To answer this question, the partial correlation analysis is further conducted between the UBI, AO, and occurrence of LTE. The result shows that the occurrence of LTE is correlated at −0.60 with the AO on the interdecadal time scale, without the impacts of the Ural blocking. The correlation between the occurrence of LTE and the UBI is only −0.17, however, taking away the impacts of AO. Obviously, the AO plays a dominant role. The same analysis has been performed on the SH, AO, and occurrence of LTE. And similar results are obtained. The SHI is correlated with the occurrence of LTE at 0.34 and is correlated with the AO at −0.60 on the interdecadal time scale, which are both statistically significant. The partial correlation coefficient between the occurrence of LTE and AO reaches −0.66 without the impact of SH, and the occurrence of LTE is partially correlated with SHI at only −0.12 without the impact of AO. The dominance of AO is confirmed again. The AO affects the occurrence of LTE directly on one hand and has indirect impacts through the UB and SH on the other hand.

The winter temperature in mid- and high-latitude Eurasia and the AO have been identified as the major factors responsible for the increase of LTE from the mid-1990s to the early 2010s in the above analyses. Note that the two factors are highly correlated. The correlation coefficient between the PC1 of the winter temperature over mid- and high-latitude Eurasia and AO reaches −0.57 on the interdecadal time scale, with the linear trend removed. It reaches −0.69 on the interdecadal time scales with the linear trend kept. However, the PC2 has a low correlation with the AO. The partial correlation analysis shows that both the PC1 and AO are independently and significantly correlated with the occurrence of LTE in northern China on the interdecadal time scale, with the partial correlation coefficients being −0.55 and 0.59, respectively. Therefore, the winter temperature over mid- and high-latitude Eurasia and AO act as two independent factors to affect the increase of LTE in northern China from the mid-1990s to early 2010s.

6. Conclusions and discussion

From daily temperature data from 2419 observatories, the winter occurrence of low temperature extreme shows general decreasing trends across China during the recent six decades. However, a significant increasing trend has been detected in northern China from the mid-1990s to the early 2010s, with the linear trend coefficient being the greatest from 1996/97 to 2012/13.

The interdecadal variation of winter temperature in mid- and high-latitude Eurasia ranks as one of the important thermal factors responsible for the changes in LTE in northern China. The “general cooling” pattern and the “warm high-latitude Eurasia and cold midlatitude Eurasia” pattern dominate the winter temperature in mid- and high-latitude Eurasia from the mid-1990s to the early 2010s. They jointly provide a cooling background for the increase of LTE in northern China.

The Arctic Oscillation, Ural blocking, and Siberian high are all significantly correlated with the occurrence of LTE in northern China on the interdecadal time scale. However, the partial correlation analysis indicates that the AO plays a dominant role. The negative AO phase has higher-than-average air pressure over the Arctic region and lower-than-average pressure in the mid–high latitudes. Then polar air tends to break out southward to cause the occurrence of LTE in northern China. Also, in the negative AO phase, the Ural blocking develops and the Siberian high intensifies. They also favor polar air to intrude southward and result in cold events. Although the winter temperature over mid- and high-latitude Eurasia and the AO are significantly correlated, it is found that the two factors affect the increase of LTE in northern China from the mid-1990s to the early 2010s independently.

Cohen et al. (2014) and Ma et al. (2018; Ma and Zhu 2019) have pointed out that the Arctic amplification (AA) helps to enhance the intrusion of cold air and cause extreme midlatitude weather. Following their definition, the winter surface temperature averaged over all longitudes and 60°–90°N is taken to represent the intensity of AA. It is found that the AA is also significantly correlated with the occurrence of LTE in northern China on the interdecadal time scales, but the correlation coefficient is much lower than that between the temperature in mid- and high-latitude Eurasia and the occurrence of LTE in northern China. Then the close relationship between temperature background and midlatitude extremes is confirmed again. Moreover, the interdecadal variation of temperature in mid- and high-latitude Eurasia is highlighted.

In this analysis, the thermal background and atmospheric internal dynamic factors responsible for the increase of LTE in northern China from the mid-1990s to the early 2010s are discussed. In addition, the external forcing is also important. It has been revealed that the decrease of autumn Arctic sea ice favors the occurrence of winter cold events in the mid–high-latitude Northern Hemisphere (Honda et al. 2009; Liu et al. 2012; Tang et al. 2013). Also, the development of La Niña status provides a favorable condition for a stronger-than-normal East Asian winter monsoon and cold weather and climate in East Asia (Zhang et al. 1997; Ding et al. 2008; Li et al. 2010). However, the impacts of external forcing on the occurrence of LTE in northern China and the related physical processes are still unknown. Therefore, the contribution of external factors to the increase of LTE in northern China from the mid-1990s to the early 2010s needs to be discussed further.

Acknowledgments

This work is financially supported by the National Key R&D Program of China (2018YFC15050600) and the National Nature Science Foundation of China (41790471 and 41730964).

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