J. Meteor. Res.  2018, Vol. 32 Issue (2): 191-202   PDF    
http://dx.doi.org/10.1007/s13351-018-7104-z
The Chinese Meteorological Society
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Article Information

Luo, B. H., and Y. Yao, 2018.
Recent Rapid Decline of the Arctic Winter Sea Ice in the Barents–Kara Seas Owing to Combined Effects of the Ural Blocking and SST. 2018.
J. Meteor. Res., 32(2): 191-202
http://dx.doi.org/10.1007/s13351-018-7104-z

Article History

Received July 6, 2017
in final form November 7, 2017
Recent Rapid Decline of the Arctic Winter Sea Ice in the Barents–Kara Seas Owing to Combined Effects of the Ural Blocking and SST
Binhe LUO1,2, Yao YAO2     
1. Physical Oceanography Laboratory, Qingdao Collaborative Innovation Center of Marine Science and Technology, College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266100;
2. Key Laboratory of Regional Climate–Environment for Temperate East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029
ABSTRACT: This study investigates why the Arctic winter sea ice loss over the Barents–Kara Seas (BKS) is accelerated in the recent decade. We first divide 1979–2013 into two time periods: 1979–2000 (P1) and 2001–13 (P2), with a focus on P2 and the difference between P1 and P2. The results show that during P2, the rapid decline of the sea ice over the BKS is related not only to the high sea surface temperature (SST) over the BKS, but also to the increased frequency, duration, and quasi-stationarity of the Ural blocking (UB) events. Observational analysis reveals that during P2, the UB tends to become quasi stationary and its frequency tends to increase due to the weakening (strengthening) of zo-nal winds over the Eurasia (North Atlantic) when the surface air temperature (SAT) anomaly over the BKS is posi-tive probably because of the high SST. Strong downward infrared (IR) radiation is seen to occur together with the quasi-stationary and persistent UB because of the accumulation of more water vapor over the BKS. Such downward IR favors the sea ice decline over the BKS, although the high SST over the BKS plays a major role. But for P1, the UB becomes westward traveling due to the opposite distribution of zonal winds relative to P2, resulting in weak downward IR over the BKS. This may lead to a weak decline of the sea ice over the BKS. Thus, it is likely that the rapid decline of the sea ice over the BKS during P2 is attributed to the joint effects of the high SST over the BKS and the quasi-stationary and long-lived UB events.
Key words: Arctic sea ice     rapid decline     Ural blocking     quasi stationary     sea surface temperature (SST)    
1 Introduction

The decline in the Arctic winter sea ice is dramatic during the recent decades (Comiso, 2006; Francis and Hunter, 2007; Comiso et al., 2008). The Arctic sea ice loss may affect the Northern Hemisphere midlatitude weather and climate through changing storm tracks, jet streams, planetary waves, and monsoons, according to previous studies (Wu et al., 2002; Cohen et al., 2014; Gao et al., 2015; Luo et al., 2016a, b). Some studies indicated that the Arctic amplification is associated with extreme weather in midlatitudes (Francis and Vavrus, 2012; Cohen et al., 2014; Screen and Simmonds, 2014). The Arctic sea ice reduction in winter has been recognized to be related to the enhanced warm Atlantic water flowing into the Arctic region (Spielhagen et al., 2011), the increased downward infrared (IR) radiation associated with tropospheric moisture and heat fluxes from midlatitudes to the Arctic (Stramler et al., 2011; Park et al., 2015), and other factors. The early autumn Arctic sea ice exhibits prominent interannual variability and may affect the winter sea ice cover to some extent (Zhang and Li, 2017). Many previous studies attributed the reduction of the Arctic winter sea ice to changes in the large-scale atmospheric circulations (Fang and Wallace, 1994; Sorteberg and Kvingedal, 2006; Park et al., 2015). Gong and Luo (2017) found that the Ural blocking (UB) can act as an amplifier for the Arctic sea ice decline in winter. Recent studies indicated that atmospheric blocking in different regions may play different roles in regional sea ice declines (Chen and Luo, 2017; Luo et al., 2017). However, it is difficult to use these results to explain why there is such an abrupt decline of winter sea ice observed in the recent decade (after 2000), given that the Arctic winter sea ice variability is also modulated by the phase of the Atlantic multidecadal oscillation (AMO) (Miles et al., 2014), and by the high surface sea temperature (SST) and meridional wind anomalies over the Barents Sea (Francis and Hunter, 2007).

More recently, Luo et al. (2016a, b) examined the role of Ural blocking in the winter warm Arctic–cold Eura-sian (WACE) pattern, and found that persistent UB events can further amplify the WACE pattern. However, they did not examine why the decline of the Arctic winter sea ice is accelerated after 2000. In this paper, we propose a mechanism to account for the abrupt decline of the Arctic winter sea ice over the Barents–Kara Seas (BKS) after 2000. This mechanism is based on the joint role played by the SST anomaly (SSTA) over the BKS and the Ural blocking-related warming. To test this hypothesis, we choose 1979–2000 (P1) and 2001–13 (P2) winters as the two time periods of our study because they just correspond to the periods of the slowly and rapidly declining (sudden change) periods of the Arctic winter sea ice to be detailed in Section 3. By comparing the differences in surface air temperature (SAT), SST, downward infrared radiation (IR), and water vapor anomalies associated with the UB events between P1 and P2, we may conclude whether the UB or SSTAs or their combination can act as more important contributors to the accelerated Arctic winter sea ice loss during P2 than during P1. Such a study will help improve our understanding of the physical cause of the abrupt decline of Arctic winter sea ice in the recent decade (after 2000).

This paper is organized as follows. In Section 2, we describe the data and method. In Section 3, we present the analysis results. The possible cause of the UB affecting the sea ice variability is given in Section 4. The main conclusions and discussion are given finally in Section 5.

2 Data and method

The sea ice data in winter (December–February: DJF) used here were actually the monthly mean satellite-observed sea ice extent (SIE) data taken from the National Snow–Ice Data Center of NOAA (NSIDC) from December 1979 to February 2013 (1979–2013) (Cavalieri et al., 1996). Based on this dataset, we derived the spatial pattern of the SIE trend and its time series. For the same time interval, we analyzed the daily atmospheric data, on a 2.5° × 2.5° horizontal resolution, of 500-hPa geopotential height, SAT, downward IR, and precipitable water from the NCEP/NCAR reanalysis dataset (Kalnay et al., 1996). The monthly SST data from 1979 to 2013 were taken from the Hadley Centre Sea Ice and Sea Surface Temperature dataset (Rayner et al., 2003) on a 1° × 1° grid. The AMO index (Enfield et al., 2001) was derived from the Physical Science Division of the NOAA Earth System Research Laboratory (https://www.esrl. noaa.gov/psd/data/timeseries/AMO/).

We define the anomalies of all variables at each grid point during 1979–2013 as the deviation from their long-term (1979–2013) mean for each day of the winter. The method used to identify the Ural blocking events over the region (30°–90°E) is the one-dimensional blocking index proposed by Tibaldi and Molteni (1990), which is also referred to as the TM index. Although many studies have developed modified two-dimensional blocking indices (Diao et al., 2006; Davini et al., 2012), the one-dimensional TM index provides a more efficient way to identifying the single blocking events. The definition and calculation method of the TM index can be found in Tibaldi and Molteni (1990) and Luo et al. (2016a, b). The blocking events in this study are identified based on the daily NCEP/NCAR reanalysis data. Here, the number of days of all UB events in a winter is counted as the UB frequency in that winter.

3 Results 3.1 Linear downward trend of the Arctic sea ice

To understand the cause for the rapid decline of the winter Arctic sea ice, it is useful to show the time series of the DJF-mean Arctic SIE (unit: %) averaged over the BKS (70°–80°N, 10°–80°E; the black box in Figs. 1b, c) during 1979–2013. Figure 1a shows that the SIE had a drastic change around 2000. Thus, the period 1979–2013 can be divided into two sub-periods: 1979–2000 (P1) and 2001–13 (P2). Of course, in some studies the period 1979–2013 was divided into 1979–99 (P1) and 2000–13 (P2) (Luo et al., 2016a). However, the results are basically similar between the slightly different division years (2000 vs. 1999; figure omitted).

It is clear in Fig. 1 that over the BKS, the SIE anomaly has a decline rate of –0.033 yr–1 during P1 and that of –0.158 yr–1 during P2 (linear trend above the 99% confidence level). Thus, the declining rate in P2 is nearly four times larger than that in P1 (black dashed line in Fig. 1a). This suggests that the BKS winter sea ice shows a rapid decline during P2. This can also be seen from the spatial distributions of the linear trend of the Arctic SIE anomaly in Figs. 1c, d. The heavy blue shadings in the black box in Fig. 1d indicate that the most significant decline of the SIE occurred over the BKS during P2. As indicated below, the linear decreasing trend of the SIE anomaly in Fig. 1c is likely related to the SSTA. To explore the cause of the rapid decline of the BKS winter sea ice during P2 in Fig. 1d, it is necessary to examine the time series of the anomalies of SAT and SST averaged over the BKS, the AMO index (Fig. 2a), and the UB frequency time series (Fig. 2b).

Figure 1 (a) Time series of the DJF-mean SIE anomaly during the winters of 1979–2013, in which the black dashed line represents a linear trend. (b, c) Horizontal distributions of the SIE linear trend for (b) 1979–2000 (P1) and (c) 2001–13 (P2), in which stippled regions indicate the linear trend above the 95% confidence level based on a two-sided Student’st-test.

It is seen that while the AMO index is negative during 1979–95, it is mostly positive during 1996–2013 (grey line in Fig. 2a). Thus, the AMO index shows a transition from the negative to positive phase during 1979–2013. The phase transition of this AMO index can be clearly seen from a 9-yr moving curve (bold grey line in Fig. 2a). Moreover, we see that the SST and SAT anomalies over the BKS region tend to be mostly positive during 2001–13. It reflects that the Atlantic warm water flows into the Arctic after 2000 (Spielhagen et al., 2011; Alexeev et al., 2013). The SST and SAT anomalies lag the AMO index about 3 yr, as revealed by the correlation calculation here. The further calculation also reveals that although the AMO index and the SSTA over the BKS have a positive (negative) correlation (significant at the 90% confidence level) of 0.31 (–0.28) for a non-detrended (detrended) case, but their correlation coefficient can reach 0.6 for a 5-yr moving average. However, it must be noted that over the BKS, the SAT anomaly has a very high positive correlation of 0.86 with the SST for a detrended case. This correlation coefficient can become 0.81 once the UB events are removed. This reflects that the presence of UB pattern can increase the positive correlation coefficient between the SAT and SST anomalies. Our calculation also reveals that during 1979–2013, the UB frequency and the BKS SIE anomaly have a negative correlation of –0.19 that is not statistically significant at the 90% confidence level, while the correlation between the SIE and SAT anomalies over the BKS is very high (–0.9). This reflects that the UB can have a certain contribution to the SIE variability. Thus, the Arctic sea ice decline over the BKS is also related to the UB, although the BKS SIE anomaly is mainly related to the SSTA (Francis and Hunter, 2007). Below we will demonstrate that the SSTA plays a major role in the Arctic sea ice decline.

Figure 2 Time series of (a) normalized DJF-mean SSTA (blue), SAT anomaly (red), and the AMO index (grey) averaged over the BKS, and (b) the UB frequency (number of days) during 1979–2013. Thick lines represent nine-point soomthed time series.
3.2 Different roles of the SSTA and UB

To understand the contributions of the BKS SSTA and UB frequency to the SIE decline, we show the regressed fields of the DJF-mean SIE anomaly against the detrended BKS SSTA and UB frequency time series in Fig. 3 for P1 and P2. It is clear that during P1, the negative SIE anomaly is weak in the BKS region (Fig. 1b) because the SST is relatively low (negative SSTA, see the blue line in Fig. 2a), but the negative SIE anomaly turns markedly strong during P2 (Fig. 1c, statistically significant) because the SST is relatively high (positive SSTA, see the blue line in Fig. 2a). This means that the high SST can explain largely the SIE decline over the BKS as there is a close correspondence between the SST-related SIE distribution (Figs. 1b, c) and the linear trend of SST (Fig. 2a). Thus, the high SST over the BKS plays a major role in the BKS sea ice decline. Moreover, as shown in Figs. 3a, b, the SSTA in P1 seems to contribute more to the changes in SIE (Fig. 3a) than that in P2 (Fig. 3b). Meanwhile, as noted in Fig. 3d, a portion of the SIE decline (with a statistically significant signal) is also related to the UB frequency during P2, while the contribution of the UB to the SIE decrease is ignorable during P1 (Fig. 3c). This means that the UB may play a more important role in the decline of BKS SIE during P2.

Figure 3 Regression fields of the DJF-mean SIE anomaly against the DJF-mean (a, b) SSTA over the BKS and (c, d) UB frequency for (a, c) P1 and (b, d) P2. Stippled regions indicate the regression fields above the 95% confidence level for a two-sided Student’s t-test.
3.3 Correlation between UB frequency and SSTA

Our calculation shows that the number of UB events is 2.6 (2.2) events per winter during P2 (P1), whereas the UB duration is 7.21 (6.35) days per winter during P2 (P1). Because P2 (P1) corresponds to a high (low) SST over the BKS (Figs. 2a, 4a, with a statistically significant signal), the high SST over the BKS favors increased UB frequency during P2; in contrast, the UB frequency is decreased during P1 because of low SST over the BKS. The main reason of why the UB duration is prolonged during P2 has been explained in Luo et al. (2016a), who noted that the reduction of mid–high latitude mean westerly wind over Eurasia favored the long persistence of UB events. As mentioned byLuo (2005) and Luo et al. (2014) based on a nonlinear multiscale interaction model of atmospheric blocking, the weak zonal wind in the blocking region favors the long lifetime of a blocking event. Thus, during P2 the enhanced BKS warming due to high SST is likely to favor more persistent UB events through reducing the Eurasian mid–high latitude westerly wind, as seen inFig. 8 below.

It is also found in Fig. 4b that the UB frequency exhi-bits a positive correlation with the SSTA over the BKS with a statistically significant signal. Thus, it is not difficult to conclude that the high (low) SST over the BKS during P2 (P1) favors (suppresses) the UB. As a result, the UB is able to result in a stronger SIE decline over the BKS during P2 than during P1 because of more persistent UB-induced warming in the north side of the UB anticyclone. In the next section, we will present an explanation for why the UB during P2 can produce a strong positive SAT anomaly over the BKS that favors the SIE decline.

Figure 4 (a) The P2 minus P1 difference of the SSTA and (b) correlation pattern of the SSTA with the UB frequency. Stippled regions indicate the fields above the 95% confidence level, based on a two-sided Student’s t-test.
4 The UB and the SAT anomaly over the BKS 4.1 Effect of the UB on water vapor and downward IR

To understand the possibility of the UB affecting the SAT anomaly over the BKS, we first show the daily composite of the life cycle of the SAT and 500-hPa geopotential height anomalies for the UB events during P1 and P2 (Fig. 5). It is interesting to find that during P1 (Fig. 5a), the blocking pattern is associated with the positive North Atlantic Oscillation (NAO+) and mainly established in the European continent due to the retrogression of intensified blocking anticyclone (Luo et al., 2011) through the energy dispersion of Rossby waves (Luo et al., 2007). But the growth of the UB during P2 is so slow and strong (Fig. 5b) that the UB is more persistent, while it is related to the upstream NAO+. Moreover, we also see that the NAO+ is located more eastward during P2 than during P1. This may be due to the stronger North Atlantic westerly wind as observed during P2 (Luo and Gong, 2006). The intensified North Atlantic westerly wind during P2 also tends to enhance the energy dispersion of the NAO+ anomaly to favor the establishment of the UB and lengthen its lifetime. According to previous studies (Luo, 2005; Luo et al., 2007, 2011, 2014), the NAO or blocking circulation is driven by synoptic-scale eddies, and the synoptic–planetary-scale interaction contributes significantly to the downstream development of pre-existing synoptic-scale eddies. However, the intensified upstream or weakened local westerly background wind induced by the BKS warming (sea ice decline) can feed back to the development of the blocking, despite that the blocking itself can influence the westerly jet.

We also see that a positive SAT anomaly center appears over the BKS in the north side of the blocking anticyclone region and is intensified (weakened) as the UB strengthens (decays). The UB-related positive SAT anomaly can amplify the SAT anomaly prior to the UB onset and then favors the further decline of the SIE over the BKS. Based on this inference, it is thought that the UB can cause a large decline of the sea ice if strong positive SAT anomaly appears over the BKS. Thus, it is necessary to examine whether the UB during P2 can result in a strong positive SAT anomaly over the BKS. It can be summarized in Fig. 5 that the positive SAT anomaly over the BKS is more persistent and intense during P2 (statistically significant color shading in Fig. 5b) than during P1 (color shading in Fig. 5a) because the life cycle of UB is more long-lived during P2 (contours in Fig. 5b) than during P1 (contours in Fig. 5a). In addition, Gong and Luo (2017) have examined the lead–lag relationship between UB and the BKS sea ice on the weekly timescale and found that the BKS sea ice decline lags about 4 days of the UB life cycle. The UB can enhance downward IR associated with moisture flux and water vapor over the BKS and then accelerates the melting of sea ice. Their study gives a possible physical mechanism on the interaction between UB and sea ice decline over the BKS. However, our result here emphasized the decadal variability of UB and its link with sea ice variation.

Figure 5a Time evolution of composite daily 500-hPa geopotential height (contours) and SAT anomalies (shadings) for UB events during P1. Stippled regions indicate the SAT anomalies above the 95% confidence level, based on a two-sided Student’s t-test. The contour interval is 30 gpm drawn from 30 gpm.
Figure 5b As in Fig. 5a, but during P2.

To further understand the difference of the UB-related SAT anomaly between P1 and P2, we show the time-mean of the daily evolution of the SAT and 500-hPa geopotential height anomalies during the UB life cycle (Averaging from lag –5 to 5 days, lag 0 day denotes the peak of UB event) in Fig. 6 for P1 and P2. We see that the UB pattern is located more eastward and has a larger anticyclonic area during P2 (Fig. 6b) than during P1 (Fig. 6a). Correspondingly, the positive SAT anomaly during P2 is stronger than during P1. Maybe, the strong positive SAT anomaly is related to the long persistence and strong quasi-stationarity of UB during P2. This point can also be seen from Fig. 5b. As revealed in Figs. 6e, f, the UB brings more water vapor into the BKS during P2 (Fig. 6f) than during P1 (Fig. 6e) because the UB is more persistent and quasi-stationary as shown below. The physical mechanism of the UB associated with more poleward water vapor has been indicated in Gong and Luo (2017). The intensified southerly wind upstream of the UB anticyclone can bring more warm water vapor in midlatitude Atlantic to the BKS region, especially during the persistent and quasi-stationary UB events. It is shown in Fig. 6d that stronger downward IR can be seen over the BKS region during P2 because the BKS has more water vapor. The stronger downward IR (Fig. 6d) leads to a stronger positive SAT anomaly during P2, thus favoring the decline of the BKS sea ice. To some extent, this can explain why the UB corresponds to a larger SIE decline during P2 than during P1 (Figs. 3a, c). It needs to be pointed out that because the traveling UB cannot generate a persistent warming and such a traveling blocking is more easily seen during P1, a weaker positive SAT anomaly over the BKS is only seen during P1. To indicate this point, we need to calculate the zonal movement of the UB during P1 and P2. We show the time–longitude evolution of the composite daily 500-hPa geopotential height anomalies averaged over 60°–85°N inFig. 7 for P1 and P2. It is obvious that the westward movement of the composite UB is dominant during P1 (Fig. 7a), while it shows a weak retrogression only during the UB decay stage for P2 (Fig. 7b). This indicates that the weak (strong) positive SAT anomaly over the BKS is related to the westward movement (quasi stationarity) of the UB during P1 (P2).

Figure 6 Time mean fields of (a, b) 500-hPa geopotential height and SAT anomalies, (c, d) downward IR, and (e, f) vertically intergrated water vapor content anomalies during (a, c, e) P1 and (b, d, f) P2. Stippled regions indicate the fields above the 95% confidence level, based on a two-sided Student’s t-test. The contour interval is 20 gpm drawn from 20 gpm in (a) and (b).
Figure 7 Longitudinal movement of the composite daily 500-hPa geopotential height anomalies averaged over 60º‒85ºN for (a) P1 and (b) P2. The red arrow denotes the movement direction.
4.2 Impact of the Arctic warming over the BKS on the UB movement

To examine the cause of the westward movement (quasi stationarity) of the UB during P1 (P2), we show the regressed 300-hPa zonal winds against the time series of the SAT anomaly averaged over the BKS (red lines in Fig. 2a) during P1 and P2 in Fig. 8. As seen from Fig. 2a, because the SAT anomaly is negative over the BKS during P1, the high-latitude westerly wind over the North Atlantic is weakened (Fig. 8a) so that it favors the westward movement of the UB. But during P2, the high-latitude North Atlantic westerly wind is intensified (Fig. 8b with a statistically significant signal), as a response of the BKS warming that is related to high SST (Fig. 3a), to inhibit the retrogression of the UB because the BKS SAT anomaly is positive during P2. For this case, a quasi-stationary UB is easily seen during P2. Thus, in the Arctic warming–blocking coupled system, there is a positive feedback between the BKS sea ice decline (warming) and the UB via the long persistence and quasi stationarity of the UB. This speculation needs to be quantified from a daily perspective, and deserves further study.

Figure 8 Regressed fields of DJF-mean 300-hPa zonal winds against the BKS SAT anomaly time series for (a) P1 and (b) P2. Stippled regions indicate the fields above the 95% confidence level, based on a two-sided Student’s t-test.
5 Conclusions and discussion

In this paper, we have examined the different roles of the positive SSTA over the BKS and the UB pattern in the observed abrupt loss of the Arctic winter sea ice in the recent decade. It is found that while the high SST during 2001–13 (P2) plays a major role in the sea ice decline over the BKS, the UB pattern during P2 also acts as a certain contribution to the sea ice decrease over the BKS. This is because the UB has a wider area and is more persistent and quasi stationary during P2 than during P1. The long-lived and quasi-stationary UB can bring more water vapor into the BKS region to generate a strong positive SAT anomaly over the BKS through enhanced downward IR. The strong positive SAT anomaly tends to strengthen the BKS sea ice decline. Thus, during P2, the combined role of the SSTA in the BKS and the UB pattern is to accelerate the declining of the Arctic winter sea ice over the BKS.

A physical explanation of why the UB becomes quasi stationary (westward traveling) during P2 (P1) is also presented in this paper. It is found that the westward movement (quasi stationarity) of the UB during P1 (P2) is related to the BKS cooling (warming) because of low (high) SST over the BKS (Fig. 8). Thus, the BKS warming related to high SST is able to produce a positive feedback between the Arctic sea ice decline and the UB. The increased westerly wind over North Atlantic can suppress the retrogression of the UB and the weak westerly wind over the Ural region may favor the maintenance of the UB. The motion and maintenance of blocking circulation are mainly forced by driven eddies; however, the regulating effect of background westerly wind on blocking development, especially the duration and zonal movement is also important (Luo et al., 2006, 2016a). Although Francis and Hunter (2007) emphasized the role of the SST and meridional wind anomalies in the winter Arctic sea ice loss and attributed the high SST to the increased greenhouse gas concentrations, they did not examine the role of the large-scale circulations. Here, we have noted that the long-lived and quasi-stationary UB pattern is likely important for the Arctic sea ice decline because the UB has increased the water vapor over the BKS. On the other hand, from P1 to P2, the AMO changes its phase resulting in SSTAs over the BKS being transformed from negative into positive (Peings and Magnusdottir, 2014); therefore, it is likely that the phase of the AMO can significantly modulate the Arctic SIE and UB variability. This question remains to be further investigated.

Acknowldgments. The authors thank the three anony-mous reviewers for their helpful comments in improving this paper.

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