Solar cycle modulation of the ENSO impact on the winter climate of East Asia

Authors


Abstract

[1] This study examines how the East Asian winter climate response to the El Niño-Southern Oscillation (ENSO) varies with the 11-year solar cycle. The results indicate that the ENSO and East Asian climate relationship is robust and significant during winters with low solar (LS) activity, with evident warming in the lower troposphere over East Asia, which can be closely linked to the decreased pressure gradient between the cold Eurasian continent and the warm Pacific. Moreover, during the LS and El Niño winters, there is a typical rainfall response in Southeast Asia, with wet conditions over South China and dry conditions over the Philippines, Borneo, Celebes, and Sulawesi, which can be explained by the anticyclone over the western North Pacific (WNP). However, during high solar activity winters, both the surface temperature and rainfall anomalies are much less closely associated with the ENSO. The possible mechanism for this solar modulation of the ENSO-related East Asian climate anomalies may be the change in the tropospheric circulation with the ENSO in both tropical and extratropical regions. Particularly, in the LS cases, an anomalous WNP anticyclone is intensified and a noticeable cyclone occupies northern Northeast Asia, resulting from the changing location and strength of the large-scale Walker circulation induced by the more pronounced sea surface temperature anomalies associated with the ENSO. Further investigation with long historic data confirms that the relationship between the ENSO and the East Asian winter climate anomalies depends on the phases of 11 year solar cycle, with enhanced East Asian climate variation during the LS winters.

1 Introduction

[2] Located in a strong monsoon region, East Asia has aperiodic and large-amplitude climate variability [Huang et al., 2003]. During winter, the climate of East Asia is dominated by the East Asian winter monsoon (EAWM). The EAWM is an important component of the global climate system and exerts a large social and economic impact on many East Asian countries during the wintertime. A strong EAWM can bring frequent and severe cold surges and/or snowstorms to China, Japan, and Korea [e.g., Ding, 1994; Chang et al., 2006]. The most prominent surface feature of the EAWM is the strong northwesterlies along the east flank of the Siberian high. At 500 hPa, there is a broad and deep East Asian trough (EAT) centered along the longitude of Japan. Previous studies have shown that the EAWM is anomalously strong when the EAT is deepened [Qiu and Wang, 1984; Wang et al., 2009]. For many Southeast Asian regions, winter is a wet monsoon season, but it is dry in Indochina and the Philippines [Cheang, 1987; Chang et al., 2005]. In addition to its local impacts, the effects of Southeast Asian rainfall can also extend to remote regions due to convective activities and diabatic cooling [Neale and Slingo, 2003]. Therefore, it is important to understand the mechanisms of wintertime climate change in East Asia.

[3] Many previous studies have examined winter climate fluctuations and tried to predict the variations in wintertime circulation in East Asia [e.g., Chang and Lau, 1982; Zhang et al., 1997; Chan and Li, 2004; Huang et al., 2004; Kang et al., 2006; Chen and Li, 2007; Wang and Chen, 2010]. Among the factors influencing the EAWM and Southeast Asian rainfall, the El Niño-Southern Oscillation (ENSO) plays a large role. As a coupled ocean-atmosphere phenomenon in the tropical Pacific, the ENSO has a significant impact on interannual global climate variations. As previous studies have shown, the EAWM is weaker during an El Niño event, and the climate is warmer and wetter than normal [e.g., Chen et al., 2000; Wang et al., 2000; Chen, 2002; Zhou et al., 2007b], while Southeast Asia tends to experience less rainfall [McBride et al., 2003; Zhou et al., 2009]. In contrast, during a La Niña winter, the aforementioned situations are generally reversed. Such differences can be regarded as being led by an anomalous Walker circulation and the related anomalous anticyclone over the subtropical western North Pacific (WNP), which is a key system that carries the impacts of ENSO to East Asia [Zhang et al., 1996; Wang et al., 2000; Wu et al., 2003; Chang et al., 2004; Feng et al., 2010]. However, the relationship between the ENSO and wintertime climate change in East Asia is not static and may be influenced by other factors [Zhou et al., 2007a; Wang et al., 2008; Wei et al., 2011; Chen et al., 2013].

[4] On the other hand, many studies have documented the role of the solar cycle on global climate variations [e.g., Rind, 2002; Kuroda, 2007; Rind et al., 2008; Chen and Zhou, 2012], and a possible mechanism for the coupled ocean-atmosphere dynamical response to solar forcing was first demonstrated by Meehl et al. [2003]. Subsequently, a number of other empirical and modeling studies also showed that the responses of the climate system to peak solar years resemble La Niña events [e.g., van Loon et al., 2004, 2007; Meehl et al., 2008, 2009]. Recent work has indicated that the impact of ENSO on the global climate could be modulated by the solar cycle. For example, during high solar (HS) activity phases, the ENSO signal in the polar stratosphere is insignificant, whereas the ENSO impacts in the lower polar stratosphere are strong during low solar activity (LS) phases [Kryjov and Park, 2007; Calvo and Marsh, 2011]. At the lower level, high sea surface temperature (SST) anomalies appeared in the Indian Ocean in an ENSO-developing year only when the LS occurred [Kodera, 2005], followed by a stronger anomalous anticyclone in the WNP due to changing Walker circulation anomalies and thus enhanced rainfall anomalies over the south of China in an ENSO-developing autumn [Zhou and Chen, 2012]. However, it is still not clear whether the ENSO-EAWM relationship also changes with the 11 year solar cycle. Therefore, the purpose of this study is to investigate the role of solar activity in determining the climate characteristics in East Asia that are related to the ENSO in boreal winter.

[5] The data sets and methods used in this study are described in section 2. The overall ENSO-East Asian winter climate relationship during the boreal winter is presented in section 3. In section 4, the modulation of the relationship by the 11 year solar cycle is examined, and the possible mechanism responsible for this modulation is discussed in section 5. Finally, a summary of the results is given in section 6.

2 Data and Methods

[6] The meteorological variables are from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis [Kalnay et al., 1996] for the period 1952–2011. We also use monthly temperature and rainfall data from 160 Chinese land stations (obtained from the China Meteorological Administration). Additionally, the rainfall data used in this study include the monthly global land precipitation data set known as Precipitation Reconstruction Over Land (PREC-L), which was produced by the Climate Prediction Center of the National Oceanic and Atmospheric Administration (NOAA) and constructed on a 1° × 1° grid. The SST data adopted here are from the HadISST data set compiled by the Hadley Centre in the United Kingdom. This is a unique combination of monthly globally complete fields of SST and sea ice concentration on a 1° latitude-longitude grid from 1870 to the present [Rayner et al., 2003]. The Climate Research Unit land air temperature data set version 3 (CRUTEM3) and the Kaplan sea level pressure (SLP) data available on the websites provided by the Earth System Research Laboratory, NOAA, both residing on a 5° × 5° grid, are used in this study for extended analysis [Kaplan et al., 2000; Brohan et al., 2006].

[7] Winter means are calculated by averaging the monthly means of December, January, and February (DJF). The winter mean SST anomaly averaged over the Niño 3 region (5°N–5°S, 150°W–90°W) is taken as an index because boreal winter is usually the mature phase of the ENSO [Rasmusson and Carpenter, 1982]. Currently, there are different choices for measuring the solar variation as discussed in Gray et al. [2010]. Here, we use the monthly sunspot numbers for the period of 1899–2011 (obtained from the National Geophysical Data Center, NOAA) to denote the 11 year solar cycle. The standardized time series of the November to March (NDJFM) mean sunspot numbers are shown in Figure 1. Actually, we also compared this series to the solar total irradiance reconstructed based on variations of solar magnetic field as indicated in Krivova et al. [2007]. They are correlated well and the results obtained in this study are almost the same with any of these two time series. The highest (lowest) 4 years in each solar cycle are categorized as HS (LS) phases as did in Chen and Li [2007]. In addition, during the second half of the twentieth century, observed El Niño events coincided with three significant volcanic activities that affected the waveguide for the vertically propagating planetary wave [Graf et al., 2007]; therefore, the 2 years following each volcanic eruption year are excluded. Based on this criterion, 39 (19) winters are selected as HS phases of the longer (shorter) period from 1900–2005 (1952–2011), and 38 (22) winters as LS phases. We first examined the direct impact of the solar activity on the EAWM by calculation of the air temperature differences at 850 hPa with the HS minus LS winters. The result displays very weak and insignificant signals over East Asia (figure not shown). This is also true for SLP field. Hence, we will focus on indirect impact of the solar forcing via the ENSO. Correlation and regression analysis are performed in each solar category throughout this paper. Student's two-sided t-tests are used to check the statistical significance.

Figure 1.

Standardized time series of the November–March (NDJFM) mean sunspot numbers for the period of 1899–2011.

3 Relationship Between the ENSO and East Asian Winter Climate

[8] The most prominent feature of the 850 hPa air temperature anomalies associated with El Niño is the apparent warming throughout East Asia south of 50°N, with the maximum >0.6°C in Mongolia (Figure 2a). Cooling in northern Northeast Asia has also been noted in the figure, with shading where it exceeds the 95% and 99% confidence levels. This cooling is closely associated with the deepened Aleutian low as shown in Figure 2b. Figure 2b further presents the weakened Siberian high and the enhanced WNP anticyclone. Hence, the pressure gradient between the cold Eurasian land and the warm ocean decreases significantly during the warm phase of the tropical eastern Pacific. It is well known that climatologically the wintertime low-level winds over East Asia feature strong northwesterlies along the east flank of the Siberian high. Therefore, the weaker pressure gradient favors southerly wind anomalies along the east coast of the Eurasian continent as shown in Figure 2d, which is believed to induce the warming in the lower troposphere. Figure 2c exhibits the relationship between the Niño 3 index and land precipitation in boreal winter based on the PREC-L data set. There are negative regions over the Philippines, Borneo, Celebes, and Sulawesi, and a positive center in South China, which is consistent with previous results [Zhang et al., 1996; Feng et al., 2010]. The responses of rainfall in Southeast Asia to El Niño are usually associated with an anomalous WNP anticyclone [Wang et al., 2000; Chang et al., 2004; Feng et al., 2010]. Hence, Figure 2d presents the spatial distributions of the regressions of the 850 hPa wind fields upon the Niño 3 index. The WNP anticyclone is located around the southern Philippines, which corresponds well with the below-normal rainfall anomalies due to the descending motions within its domain (Figure 2d). However, along the northwestern flank of this anticyclone are southwesterly winds, which can bring substantial water vapor to the areas extending from southern China to the south of Japan and result in more precipitation in South China. Again, it is worth noting that the strong Aleutian low lies in the higher latitudes of North Pacific, and the anomalous northerly winds on its west flank can lead to the evident cooling in the lower troposphere over northern Northeast Asia (Figure 2a).

Figure 2.

Regression patterns of the (a) 850 hPa air temperature, (b) sea level pressure (SLP), (c) rainfall based on the Precipitation Reconstruction over Land (PRE-L) data set, and (d) 850 hPa wind (unit: m/s) with respect to the winter mean (DJF) Niño 3 index from 1952 to 2011. Contour interval is 0.3°C in Figure 2a, 0.5 hPa in Figure 2b, and 0.3 mm/day in Figure 2c. Zero contour lines are omitted and dashed lines indicate negative values. Heavy and light shading in Figures 2a, 2b, and 2d denotes the regions at the 99% and 95% confidence levels, respectively. In Figure 2c, heavy and light shading denotes the areas with positive and negative values at the 95% confidence level, respectively.

4 Modulation of the ENSO-EAWM Relationship by the 11 Year Solar Cycle

[9] Figure 3 presents the correlation patterns of the winter mean (DJF) 850 hPa air temperature and the Niño 3 index for the two solar activity conditions. The El Niño-related warming in East Asia becomes weak in the HS phase (Figure 3a), while during the LS years, low-level air temperature anomalies are large and significant (Figure 3b). During warm ENSO events in the LS phases, a large positive area extends from the Indian Ocean across Indochina northeastward to the south of Japan in the mid- and low-latitude areas, with a western reach to near 40°N and 60°E. Moreover, negative correlation areas cover northern Northeast Asian regions in the higher latitudes (Figure 3b). These lower troposphere temperature anomalies in the reanalysis data are supported by calculation results from the surface temperatures at 160 Chinese stations. Surface temperature anomaly signals related to the ENSO are almost non-existent except for regions in the upper-middle reaches of the Yangtze River in the HS years (Figure 4a). In comparison, the warming becomes strong and significant over China in LS years, as shown in the shading in Figure 4b. Hence, the ENSO-EAWM relationship appears to change with the solar cycle.

Figure 3.

Correlations between the winter mean (DJF) Niño 3 index and the 850 hPa air temperature during the (a) HS and (b) LS phases, respectively. Contour interval is 0.3, with zero contour lines omitted. The dashed lines indicate negative values. Heavy and light shading denotes the regions at the 99% and 95% confidence levels, respectively.

Figure 4.

As in Figure 3, but showing the observed surface air temperature from 160 stations in China. Contour interval is 0.2.

[10] The influence of solar activity on the relationship among the ENSO, SLP, and EAT is further examined in Figure 5. The results suggest that the ENSO exhibits a distinguishable impact on the SLP in the LS category, with the entire tropical and subtropical region being positive but the Kamchatka region negative (Figure 5b). However, in the HS category, evident SLP signals induced by the ENSO are dramatically reduced, with the positive correlation center mainly confined to the tropical eastern Pacific and the negative correlation center lying over the eastern North Pacific (Figure 5a). These features can be reflected in the ENSO-related 500 hPa geopotential height fields as well (Figures 5c and 5d). In contrast to Figure 5d, the positive responses to the ENSO tend to occupy a smaller region in the lower latitudes south of 20°N (Figure 5c). On the contrary, during the LS winters, a large positive correlation area covers the whole area south of 40°N, including central and southern China as well as east of Japan. In addition, the below-normal center in the high latitudes shows pronounced differences, for the domain is enlarged during the LS and El Niño winters (Figure 5d). These results suggest that the EAT tends be more closely linked to the ENSO, and the pressure gradient between the cold continent and the warm ocean is less in the LS winters than in the HS winters. Therefore, cold wave intrusion into East Asia becomes relatively inactive in the warm ENSO and LS cases and results in remarkable warming in the lower troposphere, as shown in Figures 3b and 4b.

Figure 5.

As in Figure 3, but showing the SLP in Figures 5a and 5b, and the 500 hPa geopotential height in Figures 5c and 5d. Contour interval is 0.4.

[11] To highlight the distinct effects of ENSO according to the solar cycle, we also performed correlation analysis of wintertime Southeast Asian rainfall in the HS and LS years based on the Niño 3 index shown in Figure 6. Similar to the air temperature analysis results, the ENSO exerts a more significant influence in the LS phases, as the wet areas in South China and the dry areas in the southern part of Southeast Asia appear to be much larger (Figure 6b). In contrast, in the HS phases, the negative rainfall signals are weaker and located in southeastern Indochina and the Philippines, while the positive rainfall signals are rarely observed in South China but are instead found in southwestern Indonesia and central Sumatra (Figure 6a). Rainfall data from 160 Chinese observation stations confirm the previous results. In El Niño events, winter mean rainfall in southern China is increased during the LS years (Figure 7b).The patterns during the HS years denote no apparent rainfall response throughout China except for a dry center in the upper reaches of the Yangtze River (Figure 7a). All these results seem to reveal that the wintertime climate variations associated with the ENSO tend to be strongly dependent on the phase of solar cycle, since a more robust ENSO-EAWM relationship is established during the LS cases.

Figure 6.

Same as Figure 3, but showing the rainfall based on the Precipitation Reconstruction over Land (PRE-L) data set. Light and dark shading indicates the areas with negative and positive values at the 95% confidence level, respectively.

Figure 7.

As in Figure 6, but showing the rainfall of 160 Chinese stations.

5 Further Discussion

[12] It has been documented that an anomalous WNP anticyclone in the lower troposphere plays a dominant role in linking the ENSO to East Asia [Wang et al., 2000; Wang and Zhang, 2002; Wu et al., 2003]. Consequently, it is worth investigating the anomalous WNP anticyclone under different solar activity conditions. Figures 8a and 8b depict the regressions of the 850 hPa wind fields on the Niño 3 index for the HS and LS years, respectively. Under the LS conditions, both the intensity and domain of the ENSO-related WNP anticyclone are larger and thus significant southwesterly winds along its northwestern flank are intensified and can reach a latitude as high as the south of Japan (Figure 8b). This can explain the intensified wintertime climate anomalies in East Asia that are associated with the ENSO in these cases. However, during the HS and El Niño winters, the WNP anticyclone occupies a smaller domain (Figure 8a), which corresponds well with the relatively weaker rainfall anomalies over Southeast Asia in boreal winter. In addition, during the LS and El Niño winters, in the higher latitudes, the anomalous cyclone in the North Pacific is stronger, inducing enhanced northerly wind anomalies over the North Pacific (Figure 8b) and thus leading to the evident cooling in the lower troposphere in these areas (Figure 3b).

Figure 8.

As in Figure 2d, except showing the regressions during (a) HS and (b) LS winters, respectively.

[13] Previously, Wang and Zhang [2002] indicated that the development of the WNP anticyclone can be attributed to the combined effects of remote ENSO forcing, tropical-extratropical interaction, and monsoon-ocean interaction. Among many studies that have demonstrated the role of anomalous Walker circulations induced by the ENSO in this process, Wu et al. [2003] emphasized anomalous heating over the Bay of Bengal, while Feng et al. [2010] found diabatic cooling over the maritime continent to be the main cause. As a result, we examined the ENSO-related SSTs and large-scale Walker circulation anomalies during boreal winter to understand the different impacts of the two different solar activity levels. The correlations of winter mean SSTs with the Niño 3 index in the HS and LS phases are presented in Figure 9. The correlation patterns in these two categories are similar to those found in earlier studies [Kodera, 2005; Zhou and Chen, 2012]. In the HS years, there is no strong warm SST in the Indian Ocean, and the domain of positive correlation over the tropical eastern Pacific is smaller (Figure 9a). However, in the LS years, the positive SST signals in the Indian Ocean as well as the WNP are significant, and a clearer tri-pole pattern in the Pacific can be seen (Figure 9b). The possible mechanism for the solar modulation of the ENSO-related SST involves the increased solar forcing on the surface of the subtropical Pacific [e.g., Meehl et al., 2008]. The increased evaporation in the subtropical Pacific results in the enhanced moisture in these regions and further the strengthened trades since the moisture is carried to the tropical convergence zones by the trades. There is larger upwelling of colder water associated with stronger trades in the equatorial Pacific and the negative SST anomalies develop there. Additionally, the intensified rainfall anomalies and associated convective heating in the convergence zones further amplify the coupled feedbacks similar to those in La Niña events. Therefore, such a coupled air-sea mechanism is consistent with our SST analysis results that a La Niña-like SST pattern in the Pacific tends to be forced in the HS years.

Figure 9.

As in Figure 3, but showing the sea surface temperature (SST). Contour interval is 0.4.

[14] The influences of the solar activity on the tropical SST may further contribute to different circulation responses. Figure 10 depicts the regressions of the 850 hPa divergent winds and velocity potential upon the Niño 3 index, reflecting the anomalous Walker circulation and associated large-scale divergent motion. In the LS and El Niño cases, the anomalous Walker circulation is characterized by a significant descending (ascending) motion in the tropical western (eastern) Pacific (Figure 10b); while in the HS and El Niño cases, the sinking branch is limited to south of 30°N and the low-level divergent (convergent) motion over the tropical western (eastern) Pacific is much weaker (Figure 10a). These distinct Walker circulation responses can explain the enhanced tropospheric circulation anomalies associated with the ENSO in both tropical and extratropical regions and are consistent with the significant ENSO-related SST patterns in the LS phase. Hence, we speculate that in the LS and El Niño winters convective activity associated with the anomalous heating may be strengthened over the Indian Ocean as well as the equatorial eastern Pacific and may induce a more pronounced anticyclone in the WNP and cyclone in the North Pacific. This fits particularly well with the robust relationship between the ENSO and the East Asian winter climate found in the LS category. Therefore, our results confirm those of the previous studies mentioned above, that climate variations forced by the ENSO in East Asia result from atmospheric processes that are associated with the ENSO-related SST anomalies.

Figure 10.

Regressions of the winter mean (DJF) 850 hPa velocity potential (contour; interval: 2 × 105 m2/s) and the divergent wind field (vectors; unit: m/s) upon the Niño 3 index for (a) HS years and (b) LS years. Zero contour lines are suppressed. Light and dark shading indicates areas with negative and positive values at the 95% confidence level using a two-tailed student's t-test, respectively.

[15] It should be noted that the number of cases selected for the correlations in each solar activity phase is somewhat small for the period from 1952 to 2011. Therefore, we investigate the historical record to see whether the modulation of the solar cycle on the relationship between ENSO and winter climate still exists. Using the HadISST and Kaplan SLP data sets, an extended period beginning in 1900 can be examined. Figures 11a and 11b show the regression patterns of the CRUTEM3 data with respect to the Niño 3 index in the HS and LS phases, respectively. Clearly, El Niño-related warming in East Asia during the wintertime occurs mostly in the LS case, consistent with the results in section 4 (Figures 3 and 4).

Figure 11.

Regression maps for the observed winter mean (DJF) surface air temperature from CRUTEM3 on the Niño 3 index in (a) HS and (b) LS phases from 1900 to 2005. Contour interval is 0.5°C, with zero contour lines omitted and negative values dashed. Shading indicates the correlations exceeding the 95% confidence level.

[16] The relationship of ENSO and SST is analyzed for a longer period. As can be seen in Figure 12c, the SST anomaly pattern in relation to the ENSO becomes more pronounced during the LS cases, especially the positive SST anomalies over the Indian Ocean and the maritime continent stretching to the WNP, which is significantly weakened during the HS cases as shown in Figure 12a. Similarly, in comparison with the HS winters, the anomalous SLP responses are more distinguishable during the LS winters and may suggest a weaker land-ocean pressure gradient and stronger low-level anticyclonic anomalies over the WNP region (Figure 12d). The results of this extended period analysis are consistent with our above explanations of the effects of solar activity. As a consequence, the 11 year solar cycle variation should be taken into consideration when the ENSO is used to predict winter climate anomalies in East Asia.

Figure 12.

Correlations between the Niño 3 index and the winter mean (DJF) SST in (a) HS and (c) LS phases from 1900 to 2005; SLP in (b) HS and (d) LS phases from 1900 to 1998. Contour interval is 0.4, with zero contour lines omitted and the negative values dashed. Shading indicates the correlations exceeding the 99% confidence level.

6 Summary

[17] This study has documented the modulation of the 11 year solar cycle on winter climate anomalies in East Asia that are associated with the ENSO. Generally, a warm ENSO weakens the EAWM with low-level troposphere warming and favors below-normal rainfall across the Philippines, Borneo, Celebes, and Sulawesi, and above-normal rainfall over South China. This is physically consistent with the decreased pressure gradient between the cold Eurasian continent and the warm ocean as well as the anomalous WNP anticyclone associated with the ENSO. The reverse situation occurs during the cold ENSO winters. After the data are divided according to the phase of the solar cycle, the ENSO-EAWM relationship is shown to be robust (weak) when solar activity is low (high). In the LS cases, more remarkable warming induced by the ENSO in the lower troposphere is observed, and concurrently much wetter (drier) conditions appear over South China (southern Southeast Asia). Similar to the apparently weakened EAT at 500 hPa, the SLP anomalies associated with the ENSO are shown to be more pronounced, indicating a weaker pressure gradient and thus fewer cold air outbreaks in the LS winters compared to the HS winters.

[18] The issue of why the ENSO impacts on the East Asian winter climate depend on the solar cycle is also investigated here. Our findings reveal that for the El Niño events in the LS (HS) phases, the anomalous WNP anticyclone and the anomalous cyclone lying in North Pacific are stronger (weaker). The result suggests that these two anomalous tropospheric circulation systems can be attributed to changes in the large-scale Walker circulation anomalies related to the ENSO. It is found that in the LS and warm ENSO cases, a larger domain of an anomalous WNP anticyclone exists due to the intensified rising (sinking) branch over the eastern Pacific (eastern maritime continent). Furthermore, the differences in the location and strength of the large-scale Walker circulation induced by the ENSO between the two solar activity categories may be caused by different spatial patterns in tropical SSTs. During the HS years, the El Niño-related warming in the Indian Ocean and the western tropical Pacific is not prominent and the intensity and domain of the positive SST in the equatorial eastern Pacific is smaller, whereas during the LS years a clear tri-pole pattern in the Pacific concurs with an apparent warming in the Indian Ocean stretching eastward to the maritime continent. Consequently, our analysis shows that the tendency of the LS (HS) category to coincide with enhanced (weakened) climate variations associated with the ENSO during boreal winter can be well explained by the distinct SST patterns and related atmospheric processes.

[19] Further examination, using a longer record beginning in 1900, also suggests the modulation of solar activity on the ENSO-EAWM relationship. The surface air temperature and sea level pressure over East Asia are closely related to the variability of the Niño 3 index during the LS winters, but not during the HS winters. Corresponding to the robust warming in the LS cases, positive signals in the western Indian Ocean and maritime continent appear in the SST field, and these support our explanation of solar activity influence. Therefore, our results imply that solar cycle variation should be taken into account when predicting the ENSO-based winter climate in East Asia.

Acknowledgments

[20] The comments of three reviewers have led to a significant improvement of this paper. This work was supported jointly by the National Basic Research Program of China Grant 2010CB428603 and the National Natural Science Foundation of China Grants 41230527 and 41025017.

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