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  • View in gallery
    Fig. 1.

    Linear trends of Z200 (shading; gpm decade−1) in (a) JRA-55 and (b) NCEP over the period 1958–2017. (c) Time series of mean Z200 averaged over the TP (75°–105°E, 20°–40°N; solid lines, left ordinate; gpm) and the NH (dotted line, right ordinate; gpm). In (a) and (b), black contours denote mean Z200 equal to 12 500 gpm indicating the SAH. Grid points with trends that are statistically significant at the 95% confidence level are denoted by small crosses.

  • View in gallery
    Fig. 2.

    Vertical profiles of zonal mean Z200 (dotted line, left ordinate; gpm) and linear trends of Z200 (solid lines, right ordinate; gpm decade−1) averaged over 75°–105°E in (a) JRA-55 and (b) NCEP.

  • View in gallery
    Fig. 3.

    Vertical cross section of linear trends of zonal winds (shading; m s−1 decade−1) and mean zonal winds (contour; m s−1) averaged over 75°–105°E in (a) JRA-55 and (b) NCEP. (c),(d) As in (a) and (b), but for zonal-mean air temperatures (contour; °C). Light green dots denote trends that are statistically significant at the 95% confidence level. Gray shading areas denote terrain altitudes averaged over 75°–105°E.

  • View in gallery
    Fig. 4.

    Linear trends of mean surface temperatures (°C decade−1) in (a) JRA-55 and (b) NCEP in 1958–2017. Grid points with trends that are statistically significant at the 95% confidence level are denoted by small crosses.

  • View in gallery
    Fig. 5.

    EOF1 of residual Z200 (gpm) in (a) JRA-55 and (b) NCEP with (c) corresponding PC1 over the period 1958–2017. In (a) and (b), the black contour denotes mean Z200 equal to 12 500 gpm indicating the SAH. The total variance explained by EOF1 is indicated in the parentheses. In (c), dotted lines are a 5-yr running mean of PC1 in the two reanalyses.

  • View in gallery
    Fig. 6.

    EOF1 of residual Z200 (gpm) in (a) ERA-20C and (b) 20CR with (c) corresponding PC1 over the period 1900–2010. Black contours denote mean Z200 equal to 12 410 gpm in (a) ERA-20C and 12 520 gpm in (b) 20CR indicating the SAH. The total variance explained by each EOF is indicated in the parentheses.

  • View in gallery
    Fig. 7.

    Linear trends of mean surface temperatures (°C decade−1) in (a) JRA-55 and (c) NCEP during the period of 1979–2017. Linear trends of surface temperature regression onto the PC1 time series in (b) JRA-55 and (d) NCEP in 1979–2017. Grid points with trends that are statistically significant at the 95% confidence level are denoted by small crosses.

  • View in gallery
    Fig. 8.

    (a) Time series of the Asian midlatitude dipole-like mode covariances between preindustrial simulations of CESM-LE and reanalysis data. Linear trend composites of (b) Z200 (gpm decade−1) and (c) surface temperatures (°C decade−1) averaged in the picked years (covariances larger than 12 gpm2 decade−2) in simulations. In (b), purple vectors (107 Pa m2 s−2; vectors less than 106 Pa m2 s−2 are omitted) denote the NH wave activity flux associated with the corresponding dipole-like pattern.

  • View in gallery
    Fig. 9.

    A schematic diagram of the linkage between the Asian midlatitude warming and the weakening of westerly winds. Gray shading denotes the terrain of the TP. Dark blue contours denote Z200 pressure surfaces. The Asian midlatitude warming is closely associated with an anomalous high north of the TP, partially driven by atmospheric internal variability. The anomalous high coincides with 1) an anomalous anticyclone (denoted as light blue circle), favoring a barotropic structure north of the TP. Anticyclonic winds cause downward movement of air, leading to 2) air adiabatically warming and increased surface temperatures (denoted as a red column). The tropospheric and surface warming in the Asian midlatitude is accompanied by 3) lifting pressure surfaces in this region and 4) weakening the meridional gradient of geopotential height. 5) The resulting reduction of the meridional gradient weakens westerly winds near the TP and thus sensible heat flux of the TP, further contributing to the weakening of TP thermal forcing and East Asian summer monsoon. The thermal forcing change could excite two wave trains including one propagating northward along subtropical westerly jet generating an anomalous anticyclone to the north of the TP providing a positive feedback of the Asian midlatitude warming.

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The Contribution of Internal Variability to Asian Midlatitude Warming

Xiaofang Feng Key Laboratory of Meteorological Disaster, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing, China

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Liguang Wu Department of Atmospheric and Oceanic Sciences and Institute of Atmospheric Sciences, Fudan University, Shanghai, China
Innovation Center of Ocean and Atmosphere System, Zhuhai Fudan Innovation Research Institute, Zhuhai, China

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Abstract

The tropospheric warming in the Northern Hemisphere (NH) midlatitudes has been an important factor in regulating weather and climate since the twentieth century. Apart from anthropogenic forcing leading to the midlatitude warming, this study investigates the possible contribution of internal variability to Asian midlatitude warming and its role in East Asian circulation changes in boreal summer, using four reanalysis datasets in the past century and a set of 1800-yr preindustrial control simulations of the Community Earth System Model version 1 large ensemble (CESM-LE). The surface and tropospheric warming in the Asian midlatitudes is associated with a strong upper-level geopotential height rise north of the Tibetan Plateau (TP). Linear trends of 200-hPa geopotential height (Z200) confirm a dipole of an anomalous high north of the TP and an anomalous low over the Iranian Plateau in 1958–2017. The leading internal circulation mode bears a striking resemblance to the Z200 trend in the past 60 and 111 years, indicating that the long-term trend may be partially of internal origin. The Asian midlatitude warming is also found in preindustrial simulations of CESM-LE, further suggesting that internal variability explains at least part of the temperature change in the Asian midlatitudes, which is in a chain of wave trains along the NH midlatitudes. The Asian warming decreases the meridional gradient of geopotential height, resulting in the weakening of westerly winds over the TP and the TP thermal forcing. Thus, it is essential to consider the role of internal variability in shaping East Asian surface temperature and East Asian summer monsoon changes in the past decades.

© 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: Liguang Wu, liguangwu@fudan.edu.cn

Abstract

The tropospheric warming in the Northern Hemisphere (NH) midlatitudes has been an important factor in regulating weather and climate since the twentieth century. Apart from anthropogenic forcing leading to the midlatitude warming, this study investigates the possible contribution of internal variability to Asian midlatitude warming and its role in East Asian circulation changes in boreal summer, using four reanalysis datasets in the past century and a set of 1800-yr preindustrial control simulations of the Community Earth System Model version 1 large ensemble (CESM-LE). The surface and tropospheric warming in the Asian midlatitudes is associated with a strong upper-level geopotential height rise north of the Tibetan Plateau (TP). Linear trends of 200-hPa geopotential height (Z200) confirm a dipole of an anomalous high north of the TP and an anomalous low over the Iranian Plateau in 1958–2017. The leading internal circulation mode bears a striking resemblance to the Z200 trend in the past 60 and 111 years, indicating that the long-term trend may be partially of internal origin. The Asian midlatitude warming is also found in preindustrial simulations of CESM-LE, further suggesting that internal variability explains at least part of the temperature change in the Asian midlatitudes, which is in a chain of wave trains along the NH midlatitudes. The Asian warming decreases the meridional gradient of geopotential height, resulting in the weakening of westerly winds over the TP and the TP thermal forcing. Thus, it is essential to consider the role of internal variability in shaping East Asian surface temperature and East Asian summer monsoon changes in the past decades.

© 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: Liguang Wu, liguangwu@fudan.edu.cn

1. Introduction

The Northern Hemisphere (NH) midlatitude troposphere has experienced enhanced warming over the satellite era (e.g., Fu et al. 2006; Hoerling et al. 2001). The warming air temperature indicates an upward bulging tendency of the upper-tropospheric pressure surfaces, which leads to a poleward shift of the subtropical westerly jet stream (Fu and Lin 2011). Since it is just south of the westerly jet stream, the South Asian high (SAH) is also affected by this lifting of pressure surfaces (Wu et al. 2017; Webster 2006; Mason and Anderson 1963). Corresponding to the midlatitude tropospheric warming, surface temperatures in central Asia have been characterized by a warming trend since the twentieth century (Chen et al. 2009; Zhang et al. 2007). The central Asia warming is commonly believed to be due to anthropogenic forcing, since Asia is identified as one of the regions hardest hit by the effects of anthropogenic forcing (Stips et al. 2016). Accelerated warming in the Arctic is also discussed as one of several factors amplifying blocking and stationary Rossby wave patterns along the midlatitudes (Wang et al. 2013; Hoskins and Woollings 2015; Coumou et al. 2018). Despite the effects of external forcing such as increasing greenhouse gases and anthropogenic aerosols, internal variability is a possible factor explaining atmospheric circulation and temperature changes on the global scale. Recent studies note that global atmospheric circulation driven by low-frequency sea surface temperature (SST) variability may be essential to explain changes in the midlatitudes in the past century (Ding et al. 2014; Trenberth et al. 2014; Zhang et al. 2007; Ding and Wang 2005). Thus, examining internal variability in a long-term context could help us understand the large-scale circulation and temperature changes in the Asian midlatitudes in recent decades.

The influence of climate change on the East Asian summer monsoon system has attracted substantial scientific interest since the mid-twentieth century (e.g., Huang and Yan 1999; Jiang and Wang 2005; Ding et al. 2008; Zhu et al. 2012). The local response of central Asia to anthropogenic forcing may be responsible for the decline of northern East Asian surface wind speed (Zhu et al. 2012; Xu et al. 2006). The reductions of sensible heat flux over the Tibetan Plateau (TP) also contribute to the weakening of the monsoon circulation and changes of land–sea thermal contrast in East Asia (Duan et al. 2013). On interannual and interdecadal scales, Pacific SST variability plays a role in weakening large-scale monsoon circulation (Yang and Lau 2004; Ding et al. 2008; Zhu et al. 2011; Xu et al. 2015). However, due to the limited time range of available datasets, whether the observed weakening surface winds are linked with the Asian midlatitude warming and how internal variability regulates large-scale circulation changes in this region remain unclear.

Thus, the purpose of this study is to improve our understanding of large-scale circulation changes in East Asia and its underlying mechanism. We will place recent circulation and temperature changes in the Asian midlatitudes into a long-term context to investigate the contribution of internal variability. Using a new set of fully coupled preindustrial control simulations of the Community Earth System Model version 1 large ensemble (CESM-LE), which provide a unique perspective on the role of internal variability without the effects of anthropogenic forcing, we further demonstrate the importance of internal variability to the recent atmospheric circulation and temperature trends.

2. Data and methods

a. Four modern reanalysis datasets

We used monthly geopotential height, air temperature, wind, and surface temperature from four reanalysis datasets, including the Japanese 55-year Reanalysis (JRA-55; Kobayashi et al. 2015), the National Centers for Environmental Prediction Reanalysis (NCEP; Kalnay et al. 1996), the ECMWF’s first atmospheric reanalysis of the twentieth century (ERA-20C; Stickler et al. 2014), and the National Oceanic and Atmospheric Administration (NOAA) Twentieth Century Reanalysis in the most recent version (20CR, version 3; Compo et al. 2011). Our study mainly focuses on boreal summer (July–September) covering the period from 1958 to 2017 overlapped by JRA-55 and NCEP. Considering internal variability in a long-term context, the period is extended from 1900 to 2010 overlapped by ERA-20C and 20CR. In addition, the Pacific decadal oscillation (PDO) index and the Atlantic multidecadal oscillation (AMO) index are used in this study, and more detailed information on these indices can be found through the websites https://www.esrl.noaa.gov/psd/data/timeseries/AMO/ and https://www.esrl.noaa.gov/psd/gcos_wgsp/Timeseries/PDO/.

b. CESM-LE preindustrial simulations

The CESM-LE simulations are performed using CESM1 (Hurrell et al. 2013) including an 1800-yr fully coupled preindustrial control run. The multicentury control run is under preindustrial (1850) radiative forcing conditions to simulate atmospheric variability with limited attribution of external forcing effects. The CESM-LE preindustrial control run successfully reproduce internal oscillations such as the interdecadal Pacific oscillation (IPO) and the AMO (e.g., Si and Hu 2017; Kim et al. 2020). A more detailed model description of CESM-LE preindustrial simulations is provided in Kay et al. (2015).

c. Running trend analysis

To find whether the observed 60-yr trend patterns of geopotential height and surface temperature exist as a part of internal variability, we use the running trend analysis to calculate 60-yr trends in a set of 1800-yr preindustrial simulations of CESM-LE. We define 1741 overlapping time windows each with 60 years and calculate the linear trend in each time window to obtain 1741 groups of trends. These trends reflect 60-yr changes of atmospheric circulation and surface temperature without anthropogenic forcing. By analyzing trend patterns that resemble to the trends obtained in reanalysis, we investigate the role of internal variability in the Asian midlatitude warming.

d. Pattern matching method

We use the pattern matching method to determine 1741 spatial patterns of geopotential height trends in CESM-LE preindustrial simulations that best match the trends in reanalysis. Based on the most commonly used Pearson correlation coefficient, spatial correlation between the two datasets is given by
Corr(Simulation,Reanalysis)= Cov(Simulation,Reanalysis)Div(Simulation) × Div(Reanalysis),
where Cov(Simulation,Reanalysis) is the covariance of geopotential height trends in CESM-LE preindustrial simulations and reanalysis data, and Div(Simulation) and Div(Reanalysis) are their standard deviations of geopotential height trends. Since we mainly focus on the distribution of the trend pattern regardless of relative strength in each dataset, we use the covariance as a metric to summarize the degree of structural resemblance between individual trends in CESM-LE preindustrial simulations and reanalysis data.

e. Wave activity analysis

Atmospheric wave activity analysis (Plumb 1985) is used to reveal wave energy propagation along the NH midlatitudes. The wave flux vector directly provides the direction and intensity on propagating large-scale quasi-stationary Rossby waves. This approach is a powerful tool to diagnose the propagation of stationary Rossby waves and their interactions with zonal-mean flows.

3. Dipole-like trends of Z200 in the Asian midlatitudes over the past 60 years

Linear trends of 200-hPa geopotential height (Z200) show a wide range of increasing geopotential height and a chain of intermittent trends along 40°N with an increasing trend north of the TP over the period 1958–2017 in JRA-55 and NCEP (Figs. 1a,b). These features likely reflect a combination of an atmospheric response to anthropogenic forcing and internal variability. The large-scale uniform height rise is considered as an atmospheric response to the increase of CO2 forcing and ozone depletion (Fu et al. 2011). The dipole of an anomalous low over the Iranian Plateau and an anomalous high north of the TP is a key factor regulating climate system changes, such as meridional shifts of the SAH center and the subtropical jet stream (Wu et al. 2017).

Fig. 1.
Fig. 1.

Linear trends of Z200 (shading; gpm decade−1) in (a) JRA-55 and (b) NCEP over the period 1958–2017. (c) Time series of mean Z200 averaged over the TP (75°–105°E, 20°–40°N; solid lines, left ordinate; gpm) and the NH (dotted line, right ordinate; gpm). In (a) and (b), black contours denote mean Z200 equal to 12 500 gpm indicating the SAH. Grid points with trends that are statistically significant at the 95% confidence level are denoted by small crosses.

Citation: Journal of Climate 34, 7; 10.1175/JCLI-D-20-0231.1

The dipole-like trends also influence SAH intensity over the TP. To measure the change of SAH intensity over the TP, we use the mean Z200 averaged in this region (75°–105°E, 20°–40°N). Considering the NH tropospheric warming since the twentieth century, we construct a NH warming index to measure the overall effect of external forcing using the mean Z200 averaged over the NH (0°–360°E, 0°–90°N). The SAH intensity over the TP presents different variations in the two reanalyses in the past 60 years (Fig. 1c). It shows an increasing trend in NCEP (7.3 gpm decade−1) and an insignificant trend in JRA-55 (2.4 gpm decade−1). The increasing rate over the TP in NCEP is close to the linear trend of the NH warming index (7.7 gpm decade−1 in NCEP, 6.8 gpm decade−1 in JRA-55), suggesting that the signal of SAH intensity increase might be a result of a pressure level rise due to the hemispheric warming effect. The different behaviors of SAH intensities between products suggests that we need another measurement to understand SAH changes and its inner mechanism. Additionally, we find that linear trends of the SAH intensity in the two reanalyses have large biases likely associated with different model setups and data assimilation. This difference reflects a temporal inhomogeneity issue in current reanalysis products, and we should carefully consider the limitation of using reanalyses to study long-term changes on regional scales.

Considering a spatially uniform increase of atmospheric response to anthropogenic forcing on the global scale, the meridional gradient of geopotential height may be a good parameter to reflect changes in SAH intensity. To better understand SAH intensity changes over the TP, we plot the vertical–latitude cross section of mean Z200 and its linear trends averaged over 75°–105°E (Fig. 2). The zonal mean geopotential height is lower at the higher latitudes with the maximum around 30°N indicating the center of SAH over the TP. Although the magnitude of linear trends is different in JRA-55 and NCEP, likely due to systematic biases, linear trends of Z200 exhibit a similar minimum at 30°N and maximum at 45°N in the two reanalyses. The enhanced increase of geopotential height in the Asian midlatitudes decreases the meridional gradient of geopotential height between 30° and 45°N, not efficiently increasing SAH intensity over the TP. This confirms the result of Wu et al. (2017) that SAH intensity over the TP is insensitive to the effects of anthropogenic forcing in recent decades. The increase of geopotential height north of the TP, being a part of the dipole-like trend in the Asian midlatitudes, is a key point to understanding large-scale circulation changes in this area.

Fig. 2.
Fig. 2.

Vertical profiles of zonal mean Z200 (dotted line, left ordinate; gpm) and linear trends of Z200 (solid lines, right ordinate; gpm decade−1) averaged over 75°–105°E in (a) JRA-55 and (b) NCEP.

Citation: Journal of Climate 34, 7; 10.1175/JCLI-D-20-0231.1

4. The Asian midlatitude warming related to the dipole-like pattern

The increase of geopotential height north of the TP is consistent with the existence of an anomalous anticyclone, based on geostrophic wind balance. Linear trends of zonal winds averaged over 75°–105°E show enhanced westerly winds between 45° and 80°N and weakening winds over the TP, representing an anomalous anticyclone north of the TP in JRA-55 and NCEP (Figs. 3a,b). The anomalous anticyclone is barotropic in structure, accompanied by air temperature warming in the troposphere. Air temperatures in the Asian midlatitudes are increasing from the surface to nearly 300 hPa with its maximum warming rate in the lower troposphere (~700 hPa; Figs. 3c,d). The larger warming rate makes the pressure level higher due to the hydrostatic balance. The maximum warming rate is between 45° and 50°N, where the anomalous anticyclone is located.

Fig. 3.
Fig. 3.

Vertical cross section of linear trends of zonal winds (shading; m s−1 decade−1) and mean zonal winds (contour; m s−1) averaged over 75°–105°E in (a) JRA-55 and (b) NCEP. (c),(d) As in (a) and (b), but for zonal-mean air temperatures (contour; °C). Light green dots denote trends that are statistically significant at the 95% confidence level. Gray shading areas denote terrain altitudes averaged over 75°–105°E.

Citation: Journal of Climate 34, 7; 10.1175/JCLI-D-20-0231.1

Corresponding to the Asian midlatitude tropospheric warming, linear trends of surface temperatures show conspicuous warming in the Asian midlatitudes over the period 1958–2017 (Fig. 4). The anticyclonic winds cause downward movement of air mass, leading to adiabatically warmed air and increased surface temperatures. The Asian midlatitude warming coincides with increasing geopotential height north of the TP, further suggesting that atmospheric large-scale circulation plays a prominent role in shaping the distribution of surface temperature changes.

Fig. 4.
Fig. 4.

Linear trends of mean surface temperatures (°C decade−1) in (a) JRA-55 and (b) NCEP in 1958–2017. Grid points with trends that are statistically significant at the 95% confidence level are denoted by small crosses.

Citation: Journal of Climate 34, 7; 10.1175/JCLI-D-20-0231.1

5. Asian midlatitude leading mode in the past century

To explore the physical mode of regional circulation variability tying to the dipole-like pattern in the Asian midlatitudes, we employ empirical orthogonal function (EOF) analysis to examine whether leading modes share similarities with the linear trend pattern. To focus on internal variability, we regress out the NH warming index from Z200 fields at each grid in JRA-55 and NCEP before EOF analysis. The first EOF mode (EOF1) of residual Z200 shows a dipole over north of the TP and the Iranian Plateau in the positive phase (Figs. 5a,b). The leading mode bears a striking resemblance to Z200 trends in the past 60 years, indicating that the linear trends may be partially of internal origin and thus share a similar underlying mechanism. The principal component of EOF1 (PC1) is primarily characterized by a low-magnitude multidecadal oscillation with a period of ~50 years (Fig. 5c).

Fig. 5.
Fig. 5.

EOF1 of residual Z200 (gpm) in (a) JRA-55 and (b) NCEP with (c) corresponding PC1 over the period 1958–2017. In (a) and (b), the black contour denotes mean Z200 equal to 12 500 gpm indicating the SAH. The total variance explained by EOF1 is indicated in the parentheses. In (c), dotted lines are a 5-yr running mean of PC1 in the two reanalyses.

Citation: Journal of Climate 34, 7; 10.1175/JCLI-D-20-0231.1

To understand whether this internal mode remains intact over longer periods, we examine the leading EOFs of Z200 from ERA-20C and 20CR over the period 1900–2010. We also use the regression method to remove the long-term trend on the hemispheric scale before EOF analysis. To reduce the influence of interannual variations, a 5-yr running mean is applied in the two century-long reanalyses. We find that a similar dipole-like mode stands out as EOF1 in both ERA-20C and 20CR (Figs. 6a,b). While uncertainty exists in long-term reanalysis data since there are systematic model biases and fewer observations constraining earlier periods, a general consistency of the Asian midlatitude structure obtained from all four reanalyses suggests that this dipole-like pattern is an important internal mode in the past century and it partially contributes to the trend pattern in recent decades.

Fig. 6.
Fig. 6.

EOF1 of residual Z200 (gpm) in (a) ERA-20C and (b) 20CR with (c) corresponding PC1 over the period 1900–2010. Black contours denote mean Z200 equal to 12 410 gpm in (a) ERA-20C and 12 520 gpm in (b) 20CR indicating the SAH. The total variance explained by each EOF is indicated in the parentheses.

Citation: Journal of Climate 34, 7; 10.1175/JCLI-D-20-0231.1

Further, to examine what portions of recent warming trends are ascribed to internal variability, we calculate the regression maps of surface temperature in the Asian midlatitudes against the PC1 time series over the satellite era, in which the data are more reliable. Compared with strong warming trends in the Asian midlatitudes over the period of 1979–2017, trends of the regressed surface temperature are characterized by a slightly weaker warming trend in north of the TP, although trend patterns have some subtle differences in west of 80°E and south of the TP between JRA-55 and NCEP (Fig. 7). We roughly quantify the contribution of internal variability by using the regressed surface temperature trends divided by the trends in 1979–2017. The consistent warming north of the TP from the regressed surface temperature could explain around 50%–70% of the total trends in the past 40 years. In other words, internal variability may have contributed to at least half of the recent 40-yr warming trend in the Asian midlatitudes by the enhancement of the internal mode via a phase transition. Thus, this emphasizes that internal variability plays an essential role in modulating Asian midlatitude climate.

Fig. 7.
Fig. 7.

Linear trends of mean surface temperatures (°C decade−1) in (a) JRA-55 and (c) NCEP during the period of 1979–2017. Linear trends of surface temperature regression onto the PC1 time series in (b) JRA-55 and (d) NCEP in 1979–2017. Grid points with trends that are statistically significant at the 95% confidence level are denoted by small crosses.

Citation: Journal of Climate 34, 7; 10.1175/JCLI-D-20-0231.1

Previous studies suggest that the dipole-like mode is connected with the PDO, the leading mode in the North Pacific (e.g., Zhu et al. 2011; Xu et al. 2015). PC1 is statistically significantly correlated with the PDO index (Zhang et al. 1997; Mantua et al. 1997) in the past 60 years (r = −0.41 in NCEP and −0.53 in JRA-55) and weaker in the past 111 years (r = −0.18 in ERA-20C and −0.31 in 20CR). The similarity of the dipole-like mode and related surface temperature anomalies over the Lake Baikal is also described in Zhu et al. (2011), and they argue that this mode could be driven by Pacific SST although the signal is weaker in their experiments. Here, we found that this internal dipole-like mode is also related to the AMO (Kerr 2000). The AMO index (Enfield et al. 2001) is statistically significantly correlated with PC1 in the past 60 years (r = 0.46 in NCEP and 0.30 in JRA-55) and weaker in the past 111 years (r = 0.35 in ERA-20C and 0.17 in 20CR), although it has uncertainty in early periods due to less observation assimilation. The tropical Atlantic SST could induce a teleconnection through Rossby wave propagating toward Eurasia modulating atmospheric circulation and precipitation in this area (Xu et al. 2015). The Atlantic SST variability may also affect Pacific SST by the delayed response in the North Pacific to the North Atlantic SST forcing via an atmospheric bridge and an oceanic bridge (Liu and Alexander 2007; Gong et al. 2020). Mechanisms of interbasin teleconnections remain understudied regarding origins of regional decadal climate variability. Nevertheless, the linkage between the dipole-like pattern and the two indices suggests that the large-scale circulation variability in the Asian midlatitudes is partially driven by internal SST variability associated with the PDO and the AMO on interdecadal and multidecadal scales.

6. Internal variability in the NH midlatitudes

To further investigate whether the dipole-like pattern exists as a part of internal variability without anthropogenic forcing, we use a set of 1800-yr preindustrial simulations of CESM-LE to obtain the dipole-like structure in the model. To compare with the trend in the past 60 years, we use the running trend analysis to make the 60-yr running trend of Z200 and surface temperature in simulations and obtain 1741 groups of linear trends. Then, we use the pattern matching method to determine the Z200 trend pattern in the simulations that best matches the dipole-like trend in reanalysis data by the highest covariance between simulations and the linear combination of trends in JRA-55 and NCEP in the Asian midlatitudes (in the domain 50°–110°E, 30°–60°N). Covariances of Z200 trends in model and reanalysis data oscillate during the 1800 years (Fig. 8a). Here, we make a trend composite that best matches the dipole-like pattern with the covariance higher than 12 gpm2 decade−2. The composite of Z200 trends shows a zonal wavenumber-3 pattern in the NH midlatitudes. The anomalous high north of the TP coincides with two anomalous lows over the Iranian Plateau and northeastern China (Fig. 8b). Atmospheric wave activity shows clear energy propagation along the midlatitudes of the NH, where circulation anomalies are generated to regulate surface temperature changes. Surface temperature trends associated with this internal mode show a warming trend in the Asian midlatitudes and its related SST pattern exhibits a strong resemblance to AMO and weaker signal of the PDO especially in the tropics (Fig. 8c). Thus, it appears that the model’s intrinsic variability presents a dipole-like structure in the Asian midlatitudes with the AMO and the PDO partially playing a role in shaping the pattern of extratropical surface temperature trends in the NH.

Fig. 8.
Fig. 8.

(a) Time series of the Asian midlatitude dipole-like mode covariances between preindustrial simulations of CESM-LE and reanalysis data. Linear trend composites of (b) Z200 (gpm decade−1) and (c) surface temperatures (°C decade−1) averaged in the picked years (covariances larger than 12 gpm2 decade−2) in simulations. In (b), purple vectors (107 Pa m2 s−2; vectors less than 106 Pa m2 s−2 are omitted) denote the NH wave activity flux associated with the corresponding dipole-like pattern.

Citation: Journal of Climate 34, 7; 10.1175/JCLI-D-20-0231.1

We know that reanalysis data contain considerable uncertainty, although the quality of reanalysis products has been improved in the satellite era. The variability and long-term trends derived from century-long reanalysis products contain temporal inhomogeneities caused by changes in the analysis system (including the model and the data assimilation scheme from different observational stations and satellites) and the density of the observational network (Krueger et al. 2013). Considering these limitations in modern reanalysis datasets, we additionally use the 1800-yr preindustrial simulations of the CESM-LE to investigate natural climate variability. The consistent leading EOFs from four reanalyses and the similarity in simulations suggest that the observed Asian midlatitude warming and its related dipole-like pattern have existed in the past century, and internal variability partially explains these changes with the AMO and the PDO for a portion modulating extratropical climate via atmospheric teleconnections on multidecadal scales. Besides, it is also essential to investigate cross-basin mechanisms of the Atlantic and the tropical eastern Pacific to better understand how oceanic internal variability drives atmospheric circulation in the NH high latitudes (Zhang and Delworth 2007).

7. Conclusions and discussion

In this study, we show that internal variability is partially responsible for Asian midlatitude surface temperature and circulation changes in recent decades, supported by four reanalysis datasets in the past century and the multicentury freely running simulations of CESM-LE. The Asian midlatitude warming is closely associated with an anomalous high north of the TP, partially driven by internal variability on multidecadal scales. Atmospheric circulation favors a zonal wavenumber-3 pattern in the NH midlatitudes with an anomalous high in the Asian midlatitudes. As shown in Fig. 9, the anomalous high coinciding with an anomalous anticyclone generates a tropospheric warming from the surface, further raising pressure surfaces in the surrounding area. The resulting reduction of the geopotential height meridional gradient weakens westerly winds near the TP and further weakens the sensible heat flux over the TP, and also contributes to the weakening of westerly winds over East Asia. The dipole associated with the Asian midlatitude warming can be consistently obtained as a leading circulation mode from four reanalyses in the past century. Using the CESM-LE multicentury preindustrial control run, we also find a similar pattern without the effects of anthropogenic forcing, further suggesting that internal variability plays a prominent role in dominating the recent large-scale circulation changes.

Fig. 9.
Fig. 9.

A schematic diagram of the linkage between the Asian midlatitude warming and the weakening of westerly winds. Gray shading denotes the terrain of the TP. Dark blue contours denote Z200 pressure surfaces. The Asian midlatitude warming is closely associated with an anomalous high north of the TP, partially driven by atmospheric internal variability. The anomalous high coincides with 1) an anomalous anticyclone (denoted as light blue circle), favoring a barotropic structure north of the TP. Anticyclonic winds cause downward movement of air, leading to 2) air adiabatically warming and increased surface temperatures (denoted as a red column). The tropospheric and surface warming in the Asian midlatitude is accompanied by 3) lifting pressure surfaces in this region and 4) weakening the meridional gradient of geopotential height. 5) The resulting reduction of the meridional gradient weakens westerly winds near the TP and thus sensible heat flux of the TP, further contributing to the weakening of TP thermal forcing and East Asian summer monsoon. The thermal forcing change could excite two wave trains including one propagating northward along subtropical westerly jet generating an anomalous anticyclone to the north of the TP providing a positive feedback of the Asian midlatitude warming.

Citation: Journal of Climate 34, 7; 10.1175/JCLI-D-20-0231.1

Many studies have focused on the TP amplified warming to understand its role in regulating weather and climate change in East Asia in the past 40 years. Although TP surface temperature is increasing dramatically due to climate change, the TP thermal forcing is weakening due to extremely reduced surface winds over the plateau (Yang et al. 2014; Duan and Wu 2008). The reduced surface winds may be partially explained by the resulting reduction of the meridional gradient associated with the Asian midlatitude warming. The thermal forcing change of the TP may be a part of the atmospheric response to internal variability to a certain extent. Interestingly, the thermal forcing change could excite two wave trains, including one propagating northward along the subtropical westerly jet generating an anomalous anticyclone to the north of the TP (Wang et al. 2008; Liu et al. 2012) that is similar to the dipole-like pattern linked with the Asian midlatitude warming, providing a positive feedback.

On the other hand, climate change seems to enhance waveguide teleconnections in the midlatitudes by amplifying their resonance (Teng and Branstator 2019; Wang et al. 2013). However, since the impacts of anthropogenic forcing and natural forcings including solar changes and volcanic aerosol emissions on climate internal variability might be nonlinear and feature regional differences, much research focuses on decomposing the observed climate changes into contributions of anthropogenic forcing and internal variability (Christidis and Stott 2015; Diffenbaugh et al. 2017). In this study, we roughly estimate the contribution of internal variability, finding it can explain at least half of the Asian midlatitude warming in the past 40 years. It remains an open question on how to quantify the contributions of external forcing and internal variability over longer periods. Future work is expected to quantitatively assess their impacts to better understand large-scale circulation variability in East Asia in recent decades.

Acknowledgments

This research was jointly supported by the National Natural Science Foundation of China (41730961 and 41675051), the Open Research Program of the State Key Laboratory of Severe Weather (2019LASW-A02). X. F. was jointly supported by the China Scholarship Council (CSC; 201808320280) and Postgraduate Research and Practice Innovation Program of Jiangsu Province (SJKY19_0926).

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