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The mid-Pliocene warm period (mPWP, 3.264-3.025 Ma, 1 Ma = 1 million years) was 1.84°C-3.60°C warmer than the pre-industrial period (Haywood et al., 2013b), with warming both in the ocean and on land. The causes of this warming included the increased atmospheric CO2 concentrations, a reduced ice sheet in the polar regions, and changed orography and vegetation (Salzmann et al., 2008; Dowsett et al., 2010). Since the mPWP is the most recent geological period in Earth's history that featured long-term warming, it has long been a focus for palaeoclimate modeling (e.g., Chandler et al., 1994; Sloan et al., 1996; Haywood and Valdes, 2004; Jiang et al., 2005; Yan et al., 2011; Jiang, 2013; Sun et al., 2013; Zhang et al., 2013b; Zhang and Jiang, 2014). Recently, the first phase of the Pliocene Model Intercomparison Project (PlioMIP) was initiated, with standardized designs for simulations (Haywood et al., 2010), to facilitate further model-model intercomparison.
The East Asian monsoon climate in the mPWP has also been widely studied (Jiang et al., 2005; Yan et al., 2012). In particular, since the initiation of PlioMIP, further understanding of the East Asian monsoon climate in the mPWP can be gained through model-model and model-data comparisons. For example, (Zhang et al., 2013a) used the PlioMIP simulations to investigate the regional climate in East Asia; and their model results showed that, in the mPWP compared to the pre-industrial period, the multi-model ensemble mean (MMM) indicates that the East Asian summer winds (EASWs) strengthened in monsoonal China, and the East Asian winter winds (EAWWs) weakened in northern monsoonal China. These model results are generally consistent with geological reconstructions (Ding et al., 2001; Xiong et al., 2001; Wan et al., 2007; Sun et al., 2008; Jiang and Ding, 2010).
However, the mechanisms responsible for these changed features of the monsoon climate remain unclear. Previous studies indicate that the uplift of the Tibetan Plateau (TP) and global cooling have both had a significant impact on the change of the monsoon climate in East Asia since the mPWP (An et al., 2001; Zhang et al., 2001; Lu et al., 2010; Ge et al., 2013). Theoretically, the global cooling is closely related to changes in sea surface temperatures (SSTs), atmospheric CO2 concentration and ice sheet extent, and affects vegetation. Whereas, the uplift of the TP also favors global cooling. Thus, the changes in these boundary conditions are potentially related to one another. However, we emphasize more the climate effects on a regional scale from the uplift of the TP, versus the effects on a large scale from global cooling. Seen in this way and based on mid-Pliocene palaeoenvironmental reconstructed boundary conditions including SSTs, atmospheric CO2 concentrations, ice sheet extent, vegetation and orography, we determine the boundary conditions responsible for the mid-Pliocene stronger EASWs and weaker EAWWs and investigate whether the crucial factors are the same. It is hoped that the findings will aid understanding of the climate effects of the uplift of the TP and global cooling in the East Asian monsoon climate since the mPWP.
To analyze the climate effects of reconstructed SSTs, an atmosphere-only general circulation model (GCM) was used in this study. The simulated SSTs from a coupled atmosphere-ocean GCM can over- or underestimate the reconstructed SSTs in certain regions (Dowsett et al., 2013; Salzmann et al., 2013), potentially affecting their role in the East Asian monsoon climate. Moreover, considering the changes of boundary conditions on a large scale, we treated the changes of SSTs, atmospheric CO2 concentration, and ice sheet together (collectively abbreviated as SCIS) as large-scale changes. Previous studies show that the simulated climatic responses arising from the change in ice sheet extent are strong at high latitudes but relatively weak in East Asia (Jiang et al., 2005). Thus, the effects of the combined changes of SCIS in East Asia possibly derive more from the changes of SSTs and atmospheric CO2 concentration. For comparison, we treated the changes of orography and vegetation separately to emphasize the effects on a regional scale in the East Asian continent. Although the changes of orography and vegetation also occur in other regions, the relevant changes in East Asia should have direct impacts in this region. In this way, the climate effects of the boundary conditions between the large and regional scale can be distinguished to a certain degree.
Previous simulations focusing on the East Asian monsoon climate in the mid-Pliocene have not investigated the effect of changes in orbital parameters. The question of how changes in orbital parameters affect the East Asian monsoon climate in the mid-Pliocene therefore required further examination, and we address this aspect in the present paper.
The remainder of the paper is organized as follows. In section 2, we describe the model and experimental design. In section 3, the model results, including surface air temperature (SAT) and monsoon circulation, are presented. Section 4 presents the implications for paleoclimate evolution in East Asia and discusses the related uncertainties. Section 5 summarizes the study.
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The GCM used in this study is version 4 of the Community Atmosphere Model (CAM4) (Neale et al., 2013), developed at the National Center for Atmospheric Research (NCAR). The resolution of CAM4 used here is T31 in the horizontal direction, with approximately 3.75° in both latitude and longitude, and 26 layers in the vertical direction. Moreover, version 4 of the Community Land Model (CLM4) is also included (Lawrence et al., 2011), and CLM4 uses the same horizontal resolution as in CAM4. More information and validation results regarding CAM4 and CLM4 can be found in (Shields et al., 2012) and (Neale et al., 2013).
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Ten numerical experiments were performed, as listed in Table 1. The first two experiments were the standard experiments for the pre-industrial (PI) and mPWP (MP), respectively. The boundary conditions were set following the PlioMIP experiment guidelines (Haywood et al., 2010), and the boundary conditions used were from the latest version of the PRISM (Pliocene Research Interpretation and Synoptic Mapping) palaeoenvironmental reconstruction, PRISM3 (Dowsett et al., 2010). The PI experiment used the default modern land/sea configuration, orography, ice sheet distribution, modern SSTs and sea ice fraction, and the modern vegetation provided by PRISM3. Atmospheric greenhouse gases were set to the pre-industrial values of 280 ppm for CO2, 270 ppb for N2O, 760 ppb for CH4, and zero for CFCs. The solar constant was set to 1365 W m-2. Orbital eccentricity, obliquity and precession were set to 0.016724, 23.446° and 102.04° (perihelion minus 180°), respectively. By comparison, in the MP experiment, the "alternate" boundary conditions from the PlioMIP, with unchanged land/sea configuration, were used. In the MP experiment compared to PI, the changed boundary conditions included the topography (Sohl et al., 2009), land cover (Salzmann et al., 2008), an increase of atmospheric CO2 concentration (to 405 ppm), SSTs, and sea ice fraction (Dowsett and Robinson, 2009) (Fig. 1). The sea ice fraction in the MP experiment was based on the rebuilt SSTs, and the sea ice fraction where the SSTs were higher than -1.8°C was set to zero. The other boundary conditions were kept the same as in the PI experiment.
Figure 1. The differences of (a) topography (units: m), (b) annual mean surface albedo, (c) summer SSTs (units: °C), and (d) winter SSTs (units: °C) between the MP and PI experiments.
To distinguish the individual effects of different boundary conditions on the mid-Pliocene East Asian monsoon climate (Table 1), six more experiments were designed to perform a full factor separation (Lunt et al., 2012). We use subscripts to indicate the different boundary conditions ("c" for combined changes of SCIS, "o" for orography, and "v" for vegetation). Thus, the factorization is as follows, using Taylor expansions (Lunt et al., 2012): \begin{eqnarray*} dT_{\rm SCIS}&\!\!=\!\!&\dfrac{1}{4}[(T_{\rm c}\!-\!T)\!+\!(T_{\rm co}\!-\!T_{\rm o})\!+\!(T_{\rm cv}\!-\!T_{\rm v})\!+\!(T_{\rm cov}\!-\!T_{\rm ov})]\\ dT_{\rm Orography}&\!\!=\!\!&\dfrac{1}{4}[(T_{\rm o}\!-\!T)\!+\!(T_{\rm co}\!-\!T_{\rm c})\!+\!(T_{\rm ov}\!-\!T_{\rm v})\!+\!(T_{\rm cov}\!-\!T_{\rm cv})]\\ dT_{\rm Vegetation}&\!\!=\!\!&\dfrac{1}{4}[(T_{\rm v}\!-\!T)\!+\!(T_{\rm cv}\!-\!T_{\rm c})\!+\!(T_{\rm ov}\!-\!T_{\rm o})\!+\!(T_{\rm cov}\!-\!T_{\rm co})] . \end{eqnarray*} Moreover, based on the MP experiment, two further experiments were designed to explore the sensitivity of the East Asian monsoon climate to orbital extremes during the mPWP (Dolan et al., 2011). The orbital parameters in the MP_NHmax experiment represented the point in time when the Northern Hemisphere's summer (July) insolation at 65°N was at a maximum (at 3.037 Ma), and the orbital parameters in the MP_NHmin represented the point in time when the Northern Hemisphere's summer insolation at 65°N was at a minimum (at 3.049 Ma). All experiments were integrated for 50 years, and all reached a quasi-equilibrium state within the first 30 years. The climatological means from the last 20 years in each experiment were analyzed below.
2.1. Model description
2.2. Experimental design and boundary conditions
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The climate was generally warmer and wetter in the mPWP in East Asia. In the MP experiment, compared to PI, the annual mean SAT generally increased in East Asia, with more warming in central-western China. In contrast, little cooling appeared at the southern margin of the Tibetan Plateau (Fig. 2a). These results agree well with the MMM of model results from the PlioMIP (Zhang et al., 2013a).
Figure 2. The differences of annual mean SAT (units: °C) between experiments and the contribution of the combined changes of SCIS, orographic change, and vegetational change in the MP experiment compared to the PI. In panels (a, e, f), only changes that are significant at the 95% confidence level (using the Student's t-test) are dotted.
After comparison, the combined changes of SCIS increased the annual mean SAT substantially, but the change of orography and vegetation only increased the annual mean SAT locally. The contribution of the combined changes of SCIS increased the SAT significantly across East Asia, with an almost zonal distribution and larger warming occurring in the north (Fig. 2b). In comparison, because of the nonuniform change of orography (Fig. 1a) and the effect of the temperature lapse rate, the SAT change was not uniform (Fig. 2c). More warming appeared in central-western China, and cooling existed around this region (Fig. 2c), due to the decreased orography in central-western China and the increased orography around this region in the mPWP compared to the pre-industrial period (Fig. 1a). Furthermore, for the contribution of vegetational change, due to the large increase of surface albedo around Northeast China (Fig. 1b), the SAT markedly decreased in this region (Fig. 2d). On the whole, the combined changes of SCIS had substantial effects on the warming in East Asia, while the change of orography and vegetation only exerted local warming effects.
The changes in orbital parameters significantly modulated the climate in East Asia. Due to the changed insolation (figure not shown), the change of orbital parameters from modern values to the values during 3.037 Ma and 3.049 Ma resulted in markedly different climate effects on the annual mean SAT in East Asia (Figs. 2e and f, Table 2). Although the SAT in boreal summer (June, July and August; JJA) generally increased in the MP_NHmax experiment and decreased in the MP_NHmin experiment, compared to PI in East Asia (Table 2), the changes in annual mean SAT manifested in a different way (Fig. 2e vs. Fig. 2f).
Figure 3. The differences of boreal summer 850 hPa winds (units: m s-1) between experiments and the contribution of the combined changes of SCIS, orographic change and vegetational change in the MP experiment compared to the PI experiment. In panels (a, e, f), only changes that are significant at the 95% confidence level for 850 hPa meridional winds (using the Student's t-test) are shaded. Regions with an elevation above 1500 m are left blank.
Figure 4. The same as in Fig. 3, but for the differences of boreal winter 850 hPa winds (units: m s-1).
Figure 7. The differences of boreal summer SAT (top, units: °C) and winter SAT (bottom, units: °C) between experiments and the contribution of the combined changes of SCIS, orographic change, and vegetational change in the MP experiment compared to the PI experiment. The SAT changes in the left column are zonally averaged within 105°-135°E. The SAT changes in the right column are meridionally averaged within 20°-50°N.
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The monsoon circulation was also greatly affected by the changes in boundary conditions. In the MP experiment compared to the PI experiment, in JJA, southwesterly winds largely strengthened in monsoonal China (Fig. 3a); while in boreal winter (December, January and February; DJF), the conditions were more complex. Northeasterly wind anomalies appeared in southern monsoonal China, while southeasterly wind anomalies occurred in northern monsoonal China, and northwesterly wind anomalies appeared in Northeast China (Fig. 4a). These results indicate that the mid-Pliocene EASWs largely strengthened in monsoonal China, and the EAWWs slightly weakened in northern monsoonal China. Like the changes in SAT, these characteristics also generally agree with the MMM of the PlioMIP models (Zhang et al., 2013a).
The combined changes of SCIS exerted the greatest effect on strengthening the EASWs in monsoonal China, but the change of orography had the greatest effect on weakening of the EAWWs in northern monsoonal China in the mPWP. In detail, the contributions of the orographic and vegetational changes were relatively weak for the mid-Pliocene strengthened EASWs in monsoonal China (Figs. 3c and d; Table 2), while the combined changes of SCIS exerted the greatest effect (Fig. 3b; Table 2). Whereas for EAWWs, the combined changes of SCIS weakened EAWWs mainly in and around Northeast China (Fig. 4b), and the vegetational change had a large effect on the strengthened EAWWs in Northeast China (Fig. 4d). In contrast, the change of orography had the greatest effect on weakening of EAWWs in northern monsoonal China (Fig. 4c; Table 2). Thus, the combined changes of SCIS and orographic change both played important roles in the change of East Asian monsoon winds.
Moreover, the changes in orbital parameters also further modulated the change of monsoon winds. Stronger southwesterly wind anomalies occurred in monsoonal China in JJA (Fig. 3e vs. Fig. 3a), and weaker southeasterly wind anomalies appeared in northern monsoonal China in DJF (Fig. 4e vs. Fig. 4a). By comparison, the changes in orbital parameters represented in Figs. 3f and 4f had an opposite effect, due to the opposite change in insolation, with weaker southwesterly wind anomalies in monsoonal China in JJA (Fig. 3f vs. Fig. 3a) but stronger southeasterly wind anomalies in northern monsoonal China in DJF (Fig. 4f vs. Fig. 4a). Thus, changes in orbital parameters could have markedly affected the monsoon winds in the mid-Pliocene.
Further investigations showed that the changed monsoon winds could be explained by a reorganization of the meridional temperature gradient and the zonal land-sea thermal contrast (Figs. 5 and 6). In JJA in the MP and MP_NHmax experiments, compared to PI, and also the contribution of the combined changes of SCIS (Figs. 5a, b and e), the SAT generally increased more in the middle latitudes than the low latitudes (Fig. 7a). This induced a decreased meridional temperature gradient, and also the anomalous southerly winds in East Asia (Figs. 3a, b and e), to compensate for the warming-induced loss of atmospheric mass. Meanwhile, the SAT changes were not evenly distributed between the land and ocean, and the SAT increased more over the East Asian continent than the adjacent oceans (Fig. 7b), especially in the MP_NHmax experiment compared to the PI experiment. As a result, the zonal land-sea thermal contrast was enhanced and the corresponding land-sea air pressure gradient was also increased (figure not shown), strengthening the southerly winds in East Asia. By comparison, the increased meridional temperature gradient and weakened land-sea thermal contrast, in particular in the MP_NHmin experiment compared to the PI experiment (Figs. 7a and b; Table 2), hindered the strengthening of EASWs.
As for JJA, the change of monsoon winds in DJF was also related to the change of the meridional temperature gradient and the zonal thermal contrast. In the MP and MP_NHmin experiments, compared to the PI experiment, the decreased monsoon winds in northern monsoonal China were more closely related to the increased SAT (Figs. 6a and f) and the corresponding weakened surface air pressure in northwestern China (figure not shown). This led to a decrease in the meridional temperature gradient and also a weakening of the zonal thermal contrast in East Asia (Figs. 7c and d). For the contribution of orographic change, the change of meridional temperature gradient was weak (Fig. 7c), and thus the southeasterly wind anomalies in northern monsoonal China were more related to the increased SAT in northwestern China and the resultant weakened zonal thermal contrast (Figs. 7d and 6c). In addition, this warming was further enhanced in the MP and MP_NHmin experiments (Fig. 7d).
3.1. Annual mean SAT
3.2. Boreal summer and winter monsoon circulation
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The combined changes of SCIS and orographic change from the mPWP to the present have clearly had different effects on the evolution of East Asian monsoon climate. The model results show that, in the mPWP compared to the pre-industrial, the EASWs strengthened in monsoonal China and the EAWWs weakened in northern monsoonal China (Zhang et al., 2013a). These results are consistent with existing geological evidence (Ding et al., 2001; Xiong et al., 2001; Wan et al., 2007; Sun et al., 2008; Jiang and Ding, 2010). Our analysis indicates that the reason for the strengthened EASWs and weakened EAWWs was the changes in different boundary conditions. That is, the combined changes of SCIS largely contributed to the strengthened EASWs in the mid-Pliocene through a decreased meridional temperature gradient and a strengthened zonal land-sea thermal contrast; while the orographic change had an important role in the decreased EAWWs in northern monsoonal China, which derived more from the increased SAT in northwestern China and the resultant weakened zonal thermal contrast. It should be noted that the simulated increased SAT in northwestern China was likely attributable more to the lowered orography of the TP in the mPWP compared to the pre-industrial period (Fig. 1a). The lowered orography of the TP is consistent with geological evidence, which indicates that several accelerated rises of the northern TP have occurred since the mid-Pliocene (Zheng et al., 2000; Fang et al., 2005; Li et al., 2014). Thus, in turn, from the mPWP to the present, we can see that the EASWs have weakened in monsoonal China and the EAWWs have strengthened in northern monsoonal China. Furthermore, the combined changes of SCIS, mainly representing global cooling on a large scale, are more likely to have been responsible for the weakened EASWs, while regional tectonic activity (including the uplift of the northern TP) has played an important role in the strengthening of the EAWWs (Zhang et al., 2015). Our results indicate that the two factors could both have important but different climate effects for East Asian climate evolution on the geological time scale, in contrast to the notion of excessive emphasis on one aspect in this process.
The mPWP was very long (∼0.24 Ma) and contained several orbital-scale cycles (Willeit et al., 2013). The model results in the present study show that changes in orbital-scale cycles may significantly modulate the evolution of East Asian monsoon climate. Changes in orbital parameters could markedly affect SAT, precipitation, and also East Asian monsoon winds. Thus, it is understandable that different proxy data, indicating different climate information, coexist together. Moreover, orbital-scale cycles could further modulate the impact of orographic change and the combined changes of SCIS on the evolution of East Asian monsoon climate.
The uncertainties in boundary conditions could have affected the model results. For example, a large discrepancy was found in the simulated East Asian monsoon climate between the model results based on reconstructed SSTs and those based on simulated SSTs (Zhang et al., 2013a). The reasons might derive both from the simulated and reconstructed SSTs. Even so, the inconsistency between the simulated and reconstructed SSTs (Dowsett et al., 2013; Salzmann et al., 2013) is more likely related to the time slab nature of the proxy data, representative of an average of multiple warm climates, while the model results only reflect a climate state based on constant external forcing (Haywood et al., 2013a). Further effort is needed to reduce the uncertainties in boundary conditions.
More experiments are needed. All the simulations in this study were performed using an atmosphere-only model, and hence fixed SSTs. Even so, along with changes in orbital parameters, if using a coupled atmosphere-ocean GCM, the simulated SSTs may also change, further affecting the land-sea thermal contrast, and in turn, the East Asian monsoon climate. Thus, more experiments are required to further understand the climate effects of changed orbital parameters. Besides, because of the different physical processes and parameterizations (Zhang et al., 2013a), the relative effects of orographic change compared to other forcings may be different in other GCMs, and thus more experiments with other GCMs are needed.
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Based on the PRISM3 palaeoenvironmental reconstruction, the causes of the changes in the mid-Pliocene East Asian monsoon climate are analyzed in this paper. The model results show that the combined changes of SCIS exerted the greatest effect on the strengthening of EASWs in monsoonal China, and the changes of orography had the greatest effect on the weakening of EAWWs in northern monsoonal China, in the mPWP, as compared to the pre-industrial period. The reorganization of the meridional temperature gradient and zonal thermal contrast are revealed as the underlying mechanisms for the changed monsoon winds. Moreover, changes in orbital parameters could further markedly modulate the East Asian monsoon climate.