Role of the North Pacific sea surface temperature in the East Asian winter monsoon decadal variability
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In this study, a possible mechanism for the decadal variability in the East Asian winter monsoon (EAWM) is proposed. Specifically, the North Pacific sea surface temperature (SST) may play an important role. An analysis of the observations shows that the North Pacific SST has a remarkable decadal pattern whose phase shifted around the mid-1980s. This North Pacific SST decadal pattern can weaken the East Asian trough and enhance the North Pacific Oscillation through changing air–sea interactions over the North Pacific. The weak East Asian trough enhances the zonal circulation and weakens the meridional circulation over East Asia, consequently leading to a weaker southward cold surge and East Asia warming around the mid-1980s. The numerical experiment further confirms the pronounced physical processes. In addition, over the longer period of 1871–2012, the indices of the EAWM and North Pacific SST decadal pattern are also highly consistent on the decadal timescale, which further confirms the impact of the North Pacific SST decadal pattern on the EAWM decadal variability.
KeywordsEast Asian winter monsoon Sea surface temperature Decadal variability Atmospheric circulation East Asian trough North Pacific Oscillation
The East Asian monsoon is one of the most active climate systems in the Northern Hemisphere (e.g., Lau and Li 1984; Tao and Chen 1987; Matsumoto 1992; Ding 1994). The climate anomalies associated with the East Asian monsoon have a strongly variable intensity that can result in extreme events, such as droughts, floods, intense snowfall, and cold surges; these events have a profound impact on people’s livelihoods, society, and the natural environment in East Asia. In addition, the East Asian monsoon can drive the atmospheric general circulation and affect the climate variability in distant regions (e.g., Li and Mu 2000; Yang et al. 2002; Lau and Weng 2002; Chang et al. 2005; Zhou et al. 2007). Therefore, the variability in the East Asian monsoon and its causes have been greatly emphasised in the literature.
Observational analysis shows that the East Asian summer monsoon (EASM) significantly weakened around the late 1970s (e.g., Wang 2001; Wu and Wang 2002; Gong and Ho 2002; Hu et al. 2003; Han and Wang 2007; Ding et al. 2008). Studies on the EASM-related mechanisms indicated that this EASM decadal weakening is largely attributable to the variations in the sea surface temperature (SST). For example, the tropical Pacific and Indian Ocean SST decadal variability may play an important role (Chang et al. 2000; Gong and Ho 2002; Hu et al. 2003; Yang and Lau 2004; Li et al. 2008, 2010 Zhou et al. 2009). The extratropical SST interdecadal modes, i.e., the Pacific Decadal Oscillation (PDO) and Atlantic Multi-decadal Oscillation (AMO), are also contributors (Yang et al. 2005; Ma and Shao 2006; Lu et al. 2006; Wang et al. 2009a; Zhu et al. 2011). Recently, Wang et al. (2013) indicated that human activities were a prime driver of the shift in the EASM in the late 1970s, while the SST variability is still an important method of transferring the impact of human activities to the EASM.
In contrast to the EASM, which experienced a decadal shift around the late 1970s, the East Asian winter monsoon (EAWM) showed decadal weakening around the mid-1980s (e.g., Shi 1996; Xu et al. 1999; Jhun and Lee 2004; Wang et al. 2009b; Wang and He 2012; He and Wang 2012; Sun and Ao 2013; Ding et al. 2014). This decadal weakening of the EAWM resulted in an increase in the winter surface air temperature, a decrease in the frequency of cold waves, and abundant and extreme precipitation over East Asia in the last three decades.
Most studies have focused on the interannual time scale of the EAWM variability. It has been found that the EAWM interannual variability is closely related to the Siberian High (Ding and Krishnamurti 1987; Gong et al. 2001), the Aleutian Low (Overland et al. 1999), the East Asian trough (Sun and Li 1997; Wang et al. 2009b), the North Atlantic Oscillation (NAO)/Arctic Oscillation (AO) (Wu and Huang 1999; Gong et al. 2001), El Niño-Southern Oscillation (ENSO) (Li 1990; Zhang et al. 1996; Wang and He 2012), the East Asian jet stream (Yang et al. 2002), the stationary planetary wave activity (Chen et al. 2005), and the snow cover over Eurasia (Watanabe and Nitta 1999). Recent studies also showed that the EAWM is closely related to Arctic sea ice content (Liu et al. 2012; Li et al. 2014). Among these factors, some have an unstable impact on the EAWM. For example, Wang and He (2012) found that the connection between the EAWM and ENSO was significantly weaker after the late 1970s; thus, predicting the interannual variability in the EAWM became difficult.
Compared with the interannual variability, studies on the decadal variability in the EAWM are rare, and the cause of the decadal shift in the EAWM around the mid-1980s remains unclear. After diagnosing the atmospheric circulation associated with the decadal EAWM variability, Jhun and Lee (2004) deduced that the AO may contribute to the decadal variability in the EAWM. Under global warming, models have shown a weakening EAWM; thus, global warming is also considered a factor that impacts the EAWM’s decadal shift (Hori and Ueda 2006).
In climate systems, the decadal SST mode is generally considered a major source of the climate decadal shift. For example, the most common SST decadal modes (e.g., the PDO, AMO, tropical Atlantic decadal warming mode, etc.) greatly contributed to the climate shift around the late 1970s (e.g., Trenberth and Hurrell 1994; Zhang et al. 1997a; Kerr 2000; Delworth and Mann 2000; Dong et al. 2006; Sun et al. 2009). Some studies also indicated that the PDO may contribute to the EAWM decadal variability. However, the PDO phase shift over past half century occurred around the late 1970s, leading the decadal shift in the EAWM by approximately 10 years. Because the atmosphere quickly responds to external forcing, the PDO variability with a lead time of approximately 10 years may not easily explain the EAWM weakening around the mid-1980s. Therefore, a natural question arises: is there any other decadal SST mode that contributed to the decadal shift in the EAWM around the mid-1980s? This study attempts to answer this question.
The remainder of the paper is organised as follows. The datasets and methods used in the present study are described in Sect. 2. Section 3 introduces the observed EAWM-related atmospheric and SST patterns. The possible link between the North Pacific SST decadal pattern and the EAWM according to a numerical simulation is presented in Sect. 4. Section 5 provides a discussion and conclusions.
2 Datasets and methods
The atmospheric circulation dataset used in this study is the monthly mean reanalysis from the National Centers for Environmental Prediction-National Center for Atmospheric Research (Kalnay et al. 1996). The NCEP–NCAR reanalysis data are available after 1948 and are gridded at 2.5° × 2.5° resolution. Because the quality of the NCEP-NCAR reanalysis data on a decadal time scale is debatable, the reanalysis dataset (ERA-40) produced by the European Centre for Medium-Range Weather Forecasts (Uppala et al. 2005) is used to confirm the robustness of the results identified with the NCEP–NCAR reanalysis. The ERA-40 data are gridded at a 2.5° × 2.5° resolution over 1957–2002.
To obtain the long-term EAWM decadal variability, the Twentieth Century Reanalysis version 2 (20CR V2) over 1871–2012 (Compo et al. 2011) is used. In addition, the AO index data obtained at http://www.esrl.noaa.gov/psd/data/20thC_Rean/timeseries/monthly/AO/ (1871–2012) are employed to investigate the relationship between the AO and EAWM on a decadal time scale. To discuss the connection between global warming and EAWM decadal variability, the Northern Hemisphere warming index at http://www.cru.uea.ac.uk/cru/data/temperature/ (1871–2012) is used.
The SST data gridded at a 2° × 2° resolution are the Extended Reconstructed Sea Surface Temperature version 3b (ERSST V3b), which are from the National Oceanic and Atmospheric Administration (NOAA), Earth System Research Laboratory (ESRL) (Smith and Reynolds 2003). The SST dataset is available after 1854.
The EAWM index (EAWMI) is defined as the negative mean geopotential height at 500 hPa within 25°–45°N and 110°–145°E, where the East Asian trough is located; this area reflects the variations in the EAWM-related circulation (Sun and Li 1997; Wang et al. 2009b; Wang and He 2012). In this paper, the December-January–February mean represents the boreal winter. For example, the winter of 1949 refers to the average of December 1948, January 1949 and February 1949.
3 Observed EAWM-related atmospheric and SST patterns
It is well known that the East Asian trough is a dominant system over East Asia; the trough can steer cold air south-eastward from the high latitudes to East Asia (Zhang et al. 1997b). Figure 2a shows significantly positive geopotential heights over East Asia; thus, the East Asian trough weakened around the mid-1980s. A weaker East Asian trough will lead to a more zonal circulation in the mid-to-high latitudes, which weakens the southward invasion of the cold air from the high latitudes.
In addition to the East Asian trough, Jhun and Lee (2004) indicated that the changes in the East Asian upper level jet stream can also reflect the intensity of the EAWM. The authors further defined an EAWM index using the 300 hPa meridional zonal wind shear. Comparing Fig. 2b in this study and Fig. 2 in their paper, the enhanced zonal wind over the East Asian mid-to-high latitudes and weakened zonal wind over the mid-to-low latitudes in Fig. 2b indicates weakening of the EAWM.
Under such an atmospheric circulation, there are prevailing anomalous south-westerly winds over northern East Asia at the low levels (Fig. 2c). Compared with the climatology, the anomalous south-westerly winds can weaken the dominant north-westerly winds over East Asia and thus prohibit the southward invasion of cold air from the high latitudes to East Asia.
Over the cool SST region, the changes in the turbulent heat flux are not strong. In contrast to the warm SST over the southwestern North Pacific, the significant SST warming over the high latitude North Pacific along the continental margin corresponds to a downward turbulent heat flux, which indicates that the SST warming over the region could result from energy absorption from the overlying atmosphere. Thus, the warm SST over the high latitude North Pacific could be a response to the atmospheric variability. The distribution of the anomalous turbulent heat flux from NCEP-NCAR in Fig. 5 is further confirmed by the International Comprehensive Ocean–Atmosphere Data Set (figure not shown).
4 Results of the numerical simulation
Here, the sensitivity experiments were performed with the global Community Atmosphere Model (CAM5), which is the atmospheric component of the Community Earth System Model (CESM1_0_5). The “F_2000” component set was selected for CESM1_0_5, which used a prescribed climatology for SST and sea ice and an active land model (Community Land Model; CLM) coupled to CAM5. The atmospheric composition was constant in the year 2000, with a CO2 concentration of 367.0 ppm during the simulations. The simulations used a 1.9° × 2.5° finite volume grid, with 26 hybrid sigma pressure levels and a 30-min integration time step. Detailed information on the model can be found in Gent et al. (2011).
We performed two sets of model simulations. First, a 55-year run with the model’s climatological SST and sea ice boundary conditions was performed, and the average for the last 40 years was defined as the control run (EXP0). In the sensitivity experiment, an idealised SST is constructed by imposing the North Pacific SST decadal pattern in Fig. 4 on the monthly climatological SSTs; then, a 55-year run was performed with the idealised SST and sea ice boundary conditions. The average over the last 40 years was defined as the sensitivity experiment run (EXP1). The difference between EXP1 and EXP0 reflects the impact of the North Pacific SST decadal pattern on the change in the atmospheric circulation. The 40-year mean values were equivalent to the values from an ensemble of 40 sensitivity experiments with SST changes over the North Pacific by means of different initial atmospheric and land surface conditions, similar to previous studies (e.g., Zhao et al. 2012).
Compared with the observations in the last section, the North Pacific SST decadal pattern can reproduce the observed decadal feature of the atmospheric circulation over the North Pacific and East Asia. Nevertheless, the uncertainty in the sensitivity experiment should not be ignored. There are still visible differences in the intensity and position of the atmospheric circulation patterns between the simulations and observations, which could be attributed to the climate model’s uncertainty in the extratropical climate simulation. Additionally, the observed feature is the result of the air-sea interactions, although the SST could play a more active role. The experiment only allows for one-way interactions; thus, the feedback of the atmospheric to the SST is not considered here. Such shortages could result in biases in the atmospheric simulation as compared with the observations. However, the observed atmospheric features are generally reproduced by the numerical experiment, which confirms the contribution of the North Pacific SST decadal pattern to the EAWM decadal variability.
5 Conclusion and discussion
Compared with the interannual variability, the possible cause of the decadal variability in the EAWM is still unclear. In this study, we proposed a factor that could be responsible for the EAWM decadal changes. Along with the decadal change in the EAWM, a dominant SST pattern over the North Pacific exhibits consistent decadal variability. The observations and numerical simulations show that this North Pacific SST decadal pattern can impact the East Asian trough and NPO pattern via changing the air-sea interactions; as a result, the East Asian trough weakens, and a positive NPO pattern occurs. The weakened East Asian trough can lead to a more zonal atmospheric circulation, which can weaken the meridional circulation over East Asia and prohibit the southward invasion of cold air.
Support for the Twentieth Century Reanalysis Project data set is provided by the US Department of Energy, Office of Science Innovative and Novel Computational Impact on Theory and Experiment (DOE INCITE) program and Office of Biological and Environmental Research (BER), and by the National Oceanic and Atmospheric Administration Climate Program Office. We also thank the British Atmospheric Data Centre for providing ECMWF reanalysis data. This work was jointly supported by the Special Fund for Public Welfare Industry (meteorology) (GYHY201306026) and the National Natural Science Foundation of China (41522503 and 41421004).
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