Respective impacts of the East Asian winter monsoon and ENSO on winter rainfall in China

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1 Click Here for Full Article JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 115,, doi: /2009jd012502, 2010 Respective impacts of the East Asian winter monsoon and ENSO on winter rainfall in China Lian-Tong Zhou 1 and Renguang Wu 2 Received 17 May 2009; accepted 22 September 2009; published 26 January [1] Using station rainfall observations and the ERA-40 reanalysis, this study investigates respective impacts of the East Asian winter monsoon (EAWM) and El Niño-Southern Oscillation (ENSO) on winter (November March) rainfall in China by removing the interdependence between the EAWM and ENSO using a linear regression. It is found that circulation and temperature anomalies over the tropics and midlatitude North Pacific are mainly induced by ENSO, and those over the midlatitude Asia are closely linked to the EAWM. The warm ENSO induced lower-level southwesterly winds deflect from the southeast coast of China, and thus, the influence of ENSO on winter rainfall is mainly in southern China. The lower-level southerly winds associated with a weak EAWM penetrate northward over eastern China, and thus, the EAWM influences winter rainfall in eastern China. Citation: Zhou, L.-T., and R. Wu (2010), Respective impacts of the East Asian winter monsoon and ENSO on winter rainfall in China, J. Geophys. Res., 115,, doi: /2009jd Introduction [2] The East Asian monsoon and the El Niño-Southern Oscillation (ENSO) are two important factors for climate variability over East Asia. Many studies have shown the impacts of ENSO-related tropical Pacific sea surface temperature (SST) anomalies on the interannual variations of the East Asian rainfall [e.g., Fu and Teng, 1988; Huang and Wu, 1989; Nitta and Hu, 1996; Yang and Lau, 1998; Zhang et al., 1999; Chang et al., 2000; Wang et al., 2000; Huang and Zhou, 2002; Wu and Wang, 2002; Zhou and Huang, 2003; Huang et al., 2003; Wu et al., 2003; Chan and Zhou, 2005; Lin and Lu, 2009]. During El Niño years, abovenormal winter rainfall is often observed in southern China in association with anomalous lower-level southwesterly winds to the northwest flank of an anomalous anticyclone over the western North Pacific [Wang et al., 2000; Zhang and Sumi, 2002; Wu et al., 2003; Zhou et al., 2010]. [3] The East Asian winter monsoon (EAWM) is one of the strongest winter monsoons on the earth. Climatologically, the EAWM displays a clear baroclinic vertical structure, with a northerly wind component at lower troposphere and a southerly wind component at middle and upper troposphere. Associated are ascents at lower latitudes and descents over mid- and high-latitude Asian land. The anomalous EAWM can induce circulation changes over East Asia [Chang et al., 1979; Lau and Chang, 1987; Sun and Sun, 1994; Ji et al., 1997; Zhang et al., 1997; Chen and Sun, 1999; Compo et al., 1999; Chen et al., 1 Center for Monsoon System Research, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China. 2 Center for Ocean-Land-Atmosphere Studies, Calverton, Maryland, USA. Copyright 2010 by the American Geophysical Union /10/2009JD012502$ ; Nakamura et al., 2002; Chan and Li, 2004; Chou et al., 2009]. However, the impact of the EAWM on winter rainfall in China is rarely studied. A recent study (L. T. Zhou, Impact of East Asian Winter Monsoon on winter rainfall over South China and its dynamical process, submitted to International Journal of Climatology, 2009) indicates that the EAWM can have a large impact on winter rainfall in South China. A weak EAWM corresponds to anomalous southwesterly winds over the South China Sea, which induces anomalous moisture convergence and upward motion and thus enhanced rainfall over southern China. [4] There is evidence that the EAWM and ENSO are not independent. On one hand, ENSO can induce large wind anomalies along the East Asian coast [e.g., Wang et al., 2000; Yang et al., 2002; Wu et al., 2003], and thus affect the EAWM variability. On the other hand, the EAWM activity can influence the atmosphere-ocean coupled system in the equatorial Pacific [e.g., Yamagata and Mausumoto, 1989; Yasunari and Seki, 1992]. Li [1988, 1990] suggested that a strong EAWM may play a role for triggering the El Niño events. Li et al. [2005] indicated that a strong EAWM can lead to anomalous westerly winds over the equatorial western Pacific. Because of the interdependence between the EAWM and ENSO, the results obtained in previous analyses based on a single index for the EAWM or ENSO without considering their interdependence may include impacts of both factors. The objective of this study is to investigate the respective impacts of the EAWM and ENSO on circulation and temperature over the western Pacific-East Asia and rainfall in China. We are interested in how the anomalies change when the interdependence between the EAWM and ENSO are removed from a single index. [5] The organization of the rest of the text is as follows. In section 2, we describe the data sets and methods used in 1of11

2 Figure 1. Time series of normalized (a) EAWMI (solid curves) and EAWMI res (dashed curves) and (b) NDJFM NINO3.4 SST (solid curves) and NINO3.4 SST res (dashed curves). this study. In section 3, the relationship of rainfall, circulation, and temperature variations with the EAWM and the ENSO is analyzed without considering their interdependence. In section 4, we examine respective impacts of the EAWM and the ENSO by removing the EAWM-related variability from ENSO and the ENSO-related variability from the EAWM. Summary and discussions are provided in section Data Sets and Methods [6] This study uses monthly station rainfall data at 160 stations in China during , which are provided by the Chinese Meteorological Data Center. The monthly mean temperature and winds are from the ERA- 40 reanalysis on a grid of the European Centre for Medium-Range Weather Forecasts (ECMWF) [Uppala, 2002], which covers the period The monthly mean SST data on a 1 1 grid are from the Met Office Hadley Center, which covers the period [Rayner et al., 2003]. [7] The NINO3.4 SST anomaly averaged over the region of 5 S 5 N, W is taken as an index to represent ENSO. This study uses an East Asian winter monsoon index (EAWMI) defined by Chen et al. [2000]. This index is calculated by averaging meridional winds at 10 m over the East China Sea (25 40 N, E) and the South China Sea (10 25 N, E), and over the period from November to March (NDJFM). Note that the positive values of the EAWMI indicate a weak EAWM, while the negative values indicate a strong EAWM. The values for the normalized EAWMI and the NDJFM NINO3.4 SST anomalies are shown in Figures 1a and 1b (solid curves), respectively. Our analysis focuses on seasonal mean of NDJFM because of notable correlation between the EAWM and monthly mean rainfall in China during November through March. 2of11

3 Figure 2. Anomalies of (a) NDJFM rainfall (mm), (c) 700 hpa vertical p-velocity (Pa s 1 ), and (e) moisture convergence (integration hpa) (g m 2 s 1 ) obtained by regression with respect to the EAWMI. (b, d, and f) Same as Figures 2a, 2c, and 2e except for NDJFM NINO3.4 SST. The contour interval is 20 mm in Figures 2a and 2b, 0.01 Pa s 1 in Figures 2c and 2d, and 0.01 g m 2 s 1 in Figures 2e and 2f. The shading denotes regions with correlation significant at the 95% confidence level. [8] From Figure 1, the EAWMI and the NINO3.4 SST index show coherent year-to-year variations. The correlation coefficient between the EAWMI and the NDJFM NINO3.4 SST is 0.75 for the period This suggests that the EAWM and ENSO are closely related. This result is in agreement with previous studies. For example, Li [1990] and Chen et al. [2000] indicate that a strong (weak) EAWM could trigger the occurrence of El Niño (La Niña), and El Niño (La Niña) could weaken (strengthen) the EAWM. Wang et al. [2000] showed that a warm ENSO induces an anomalous anticyclone over the western North Pacific with southwesterly winds to its northwest flank at lower troposphere. Similar results are obtained in Wu et al. [2003]. These southwesterly winds presumably weaken the EAWM. [9] In order to analyze the respective influences of the EAWM and ENSO on the circulation, temperature, and rainfall anomalies, we remove the EAWM from the ENSOrelated variability to obtain an ENSO-independent EAWMI (EAWMI res ) and the ENSO from the EAWM-related variability to obtain an EAWM-independent NINO3.4 SST (NINO3.4 SST res ). This is done by means of a linear regression as follows: EAWMI res ¼ EAWMI r 1 ðeawmi; NINO3:4 SSTÞNINO3:4 SST; NINO3:4 SST res ¼ NINO3:4 SST r 2 ðnino3:4 SST; EAWMIÞEAWMI; where r 1 (r 2 ) is the regression coefficient of the NINO3.4 SST (EAWMI) with respect to the EAWMI (NINO3.4). The obtained EAWMI res and NINO3.4 SST res are shown in Figures 1a and 1b (dashed curves), respectively. The correlation coefficient between the EAWMI and EAWMI res 3of11

4 Figure 3. Anomalies of (a) NDJFM surface (10 m), (c) 700 hpa, and (e) 300 hpa wind (m s 1 ) obtained by regression with respect to the EAWMI. (b, d, and f) Same as Figures 3a, 3c, and 3e except for NDJFM NINO3.4 SST. The wind scale is shown at the bottom of the respective plots. The shading denotes regions with correlation significant at the 95% confidence level. The significance in Figures 3a 3d is based on the correlation with v wind and that in Figures 3e 3f is based on the correlation with u wind. is 0.39, and that between the NDJFM NINO3.4 SST and NINO3.4 SST res is 0.82, for the period The above two correlation coefficients suggest that the influence of ENSO on the EAWM is larger than the influence of the EAWM on ENSO. 3. Observed Climate Features Associated With the EAWM and ENSO [10] In this section, we analyze the relationship of rainfall, circulation, and temperature with the EAWM and ENSO without considering their interdependence. The results of this section provide a basis for comparison with the results of the next section that removes the interdependence from the EAWM and ENSO. [11] Figure 2 shows the regression of rainfall, 700 hpa vertical p-velocity, and column-integrated moisture convergence from 1000 to 100 hpa with respect to the EAWMI and the NDJFM NINO3.4 SST, respectively. All the regressions are calculated for NDJFM mean. The EAWMI and NDJFM NINO3.4 SST display a significant positive correlation with rainfall in southern and eastern China (Figures 2a and 2b). This indicates that the winter rainfall increases during El Niño years and weak EAWM years and decrease during La Niña years and strong EAWM years. The obtained relationship with ENSO is consistent with previous studies [Zhang and Sumi, 2002; Wu et al., 2003]. A significant enhancement of ascent motion (Figures 2c and 2d) and tropospheric moisture convergence (Figures 2e and 2f) is seen over southern and eastern China corresponding to El Niño and weak EAWM years, which is consistent with 4of11

5 Figure 4. Anomalies of (a) NDJFM surface (2 m), (c) 700 hpa, and (e) 300 hpa temperature ( C) obtained by regression with respect to the EAWMI. (b, d, and f) Same as Figures 4a, 4c, and 4e except for NDJFM NINO3.4 SST. The contour interval is 0.2 C. The shading denotes regions with correlation significant at the 95% confidence level. the rainfall increase. In comparison, the rainfall, vertical motion, and moisture convergence anomalies extend somewhat more northward for the EAWM than for the ENSO. [12] Figure 3 shows NDJFM wind anomalies at surface (10 m), 700 hpa, and 300 hpa obtained by regression with respect to the EAWMI and NDJFM NINO3.4 SST, respectively. In the tropics, the wind anomalies corresponding to a weak EAWM and a warm ENSO are very similar. At surface and 700 hpa, the main features are an anomalous anticyclone over the western North Pacific, southwesterlies along the southeast coast of China, anomalous cyclones to the north and south of the equatorial western-central Pacific and westerlies over the equator, easterlies over the Maritime Continent and the equatorial Indian Ocean (Figures 3a, 3b, 3c, and 3d). At 300 hpa, there are anomalous anticyclones to the north and south of the equatorial central Pacific and easterlies over the equator, cyclonic winds over South Asiawestern North Pacific (Figures 3e and 3f). The wind anomalies over the midlatitude North Pacific display similarity for a weak EAWM and a warm ENSO, featuring a barotropic anticyclone, but tilting westward with altitude. One difference is that the wind anomalies are more zonal corresponding to the weak EAWM, but there are large northerly components corresponding to the warm ENSO. Over midlatitude Asian land, notable differences are seen in the mid- and upper-level winds. The EAWM corresponds to large wind anomalies (Figures 3c and 3e), whereas ENSO is accompanied by very weak wind anomalies (Figures 3d and 3f). The large westerly winds over midlatitudes at middle and upper troposphere suggest a connection between the EAWM and the East Asian jet stream [Yang et al., 2002]. Another difference to note is that the lower-level southerlies along the east coast of China extends more northward for the EAWM than for the ENSO (Figures 3a and 3b). [13] The above wind anomalies are consistent with previous studies of the influence of ENSO [e.g., Chang et al., 2000; Wang et al., 2000; Wu et al., 2003]. A key feature to note is the anomalous lower-level anticyclone over the western North Pacific and associated southwesterly winds to its northwest flank. The southwesterly winds along the 5of11

6 Figure 5. Same as Figure 2 but with respect to the (a, c, and e) EAWMI res and (b, d, and f) NDJFM NINO3.4 SST res. coast of China supply the moisture and contribute to the rainfall increase over southern and eastern China. The differences seen over the midlatitude Asian land indicate that the EAWM has a closer relationship with the circulation changes over midlatitude Asia. Such relationship is also evident in the winter mean circulation field (not shown). The similarities seen in the tropics cannot tell whether both the EAWM and ENSO contribute to circulation anomalies or one of them is more important than the other. [14] Figure 4 shows NDJFM temperature anomalies at surface, 700 hpa, and 300 hpa corresponding to a weak EAWM and a warm ENSO, respectively. The temperature anomalies display similar distributions for the EAWM and ENSO. There are, however, pronounced differences in the magnitude and vertical structure in the subtropics and midlatitudes. At surface and 700 hpa, a weak EAWM corresponds to large and positive temperature anomalies extending from western China to western North Pacific (Figures 4a and 4c), whereas a warm ENSO corresponds to small temperature anomalies, in particular, over the land (Figures 4b and 4d). At 300 hpa, negative temperature anomalies extend from southern China to midlatitude North Pacific (Figures 4e and 4f). In comparison, the magnitude is larger for the ENSO than for the EAWM. [15] Consistent with the differences seen in wind anomalies, the EAWM has a closer relationship with the temperature changes over midlatitude Asia. Again, the similarities in the tropics invite a further investigation in order to determine whether both the EAWM and ENSO are important, or one of them plays a more important role than the other. 4. Respective Impacts of the EAWM and ENSO [16] In this section, we analyze the results obtained by regression with respect to the EAWMI res and NINO3.4 SST res, that is, the part dependent on ENSO or EAWM has been removed from the EAWM or ENSO. Comparison will be made with the results of the previous section to help 6of11

7 Figure 6. Same as Figure 3 but with respect to the (a, c, and e) EAWMI res and (b, d, and f) NDJFM NINO3.4 SST res. understand how the interdependence between the EAWM and ENSO affect the analysis. [17] Figure 5 shows NDJFM rainfall, 700 hpa vertical p-velocity, and tropospheric moisture convergence obtained by regression with respect to the EAWMI res and NDJFM NINO3.4 SST res, respectively. In comparison, the EAWMI res - related rainfall anomalies are more significant and located at higher latitudes, whereas the NINO3.4 SST res -related rainfall anomalies are larger in southern China (Figures 5a and 5b). For both cases, the significant area and the magnitude of rainfall anomalies are smaller compared to those seen in Figure 2. This difference is because Figure 2 includes effects of both ENSO and EAWM, and Figure 5 considers impacts of only one of them. In particular, the rainfall anomalies in southern China are much smaller in Figure 5a than in Figure 2a, suggesting that ENSO plays a more important role for southern China rainfall variability. Differences consistent with the rainfall anomalies are seen in the vertical velocity and moisture convergence. For ENSO, both the ascent and moisture convergence are limited to southeast coast of China (Figures 5d and 5f). For the EAWM, the ascent and moisture convergence cover a much broad area in southern and eastern China (Figures 5c and 5e). These results indicate that the independent ENSO influence on winter rainfall is mainly over southern China, and the EAWM has a larger independent influence on winter rainfall in eastern China. In the tropics, the vertical motion and moisture convergence for ENSO display a spatial distribution very similar to that in Figure 2, whereas opposite anomalies tend to occur corresponding to the EAWM. The significance of these anomalies in the tropics is much lower for the EAWM than for ENSO. [18] Figure 6 shows NDJFM wind anomalies at different levels. Nearly opposite wind anomalies are seen for the EAWMI res and the NDJFM NINO3.4 SST res except for lower tropospheric winds along the southeast coast of China. The wind anomalies in the tropics and midlatitude North Pacific for ENSO are similar, and those for EAWM are opposite to those seen in Figure 3. The wind anomalies in the tropics are larger and more significant for ENSO than for the EAWM. This suggests that the tropical circulation anomalies before removing the interdependence are mostly due to ENSO. In contrast, the wind anomalies over the midlatitude Asian land for the EAWM are similar, and those for the ENSO are opposite to those seen in Figure 3. Further, the magnitude of wind anomalies is larger for the EAWM than for ENSO. This indicates that the EAWM has a larger impact on circulation changes over midlatitude Asia. Along the southeast coast of China, the surface and 700 hpa winds are southwesterly in Figures 6b and 6d, but southeasterly in Figures 6a and 6c. Both types of winds contribute to above-normal rainfall in southern and eastern China. The wind anomalies in Figure 6a indicate a weakening of the anticyclonic winter monsoon circulation and those in Figures 6c and 6e indicate a northward retreat of the winter monsoon trough. All of these are consistent with a typical weak EAWM. [19] When the ENSO-related part is removed, the temperature anomalies at surface and 700 hpa associated with the EAWM become weaker and less significant in the tropical Indo-western Pacific, but do not show much change over the East Asian land and western North Pacific (Figures 7a and 7c). At 300 hpa, positive temperature anomalies appear over East Asia (Figure 7e), in sharp contrast to negative temperature anomalies seen in Figure 4e. Over the tropical Indian Ocean, the change in temperature anomalies is less obvious. After removing the EAWM-related part, the temperature anomalies in the tropical Pacific and midlatitude North Pacific associated with ENSO become larger, so do the negative temperature anomalies at 300 hpa over East Asia (Figures 7b, 7d, and 7f). The temperature anomalies in the tropical Indian Ocean become weaker and less significant. The temperature anomalies at surface and 700 hpa display a prominent change over East Asia with negative temperature anomalies over most of China (Figures 7b and 7d), which is in sharp contrast to positive (albeit weak) temperature anomalies seen in Figures 4b and 4d. The above results suggest that ENSO has a dominant contribution to temperature anomalies over the Pacific Ocean, and the temperature changes associated with the EAWM and ENSO are very different over East Asia. [20] To further compare the anomalies over East Asia, we show in Figures 8 and 9 the latitude-pressure section for geopotential height and temperature anomalies along E. Corresponding to the EAWMI res, the geopotential 7of11

8 Figure 7. Same as Figure 4 but with respect to the (a, c, and e) EAWMI res and (b, d, f) NDJFM NINO3.4 SST res. Figure 8. Anomalies of geopotential height (gpm) along E obtained by regression with respect to the (a) EAWMI res and (b) NDJFM NINO3.4 SST res. The contour interval is 50 gpm. The shading denotes correlation significant at the 95% confidence level. 8of11

9 Figure 9. Same as Figure 8 but for temperature ( C) with contour interval of 0.2 C. height anomalies over East Asia (20 40 N) change from negative at surface to positive at mid- and uppertroposphere (Figure 8a). This vertical structure is consistent with positive temperature anomalies through the troposphere (Figure 9a). The magnitude of temperature anomalies decreases with height. In contrast, corresponding to the NINO3.4 SST res, the geopotential height anomalies are positive at the lower troposphere and negative at mid- and upper-troposphere (Figure 8b). This is accompanied by negative temperature anomalies through the troposphere with the magnitude increasing with the height (Figure 9b). [21] The temperature increase over East Asia corresponding to a weak EAWM is related to anomalous southerly winds (Figures 6a and 6c) that transport more warm air from the tropics. This is confirmed by regressed temperature advection. A region of large positive temperature advection appears over East Asia along E corresponding to a positive EAWMI res (figure not shown). The large temperature decrease over East Asia at upper level corresponding to positive NDJFM NINO3.4 SST res is associated with anomalous westerly winds (Figure 6f) that are against the mean zonal temperature gradient along N over East Asiawestern North Pacific (figure not shown). 5. Summary and Discussions [22] This study analyzes the relationship of the rainfall in China, circulation and temperature over East Asia and western Pacific in winter with the EAWM and ENSO using station rainfall observations and the ERA-40 reanalysis. The analysis has been performed for both without considering the interdependence between the EAWM and ENSO and removing their interdependence using a linear regression. [23] Without removing the interdependence between the EAWM and ENSO, the circulation and temperature anomalies associated with a weak EAWM and a warm ENSO are similar over the tropics. A weak EAWM or a warm ENSO features an anomalous anticyclone over the western North Pacific and southwesterly along the southeast coast of China at lower troposphere, an anomalous cyclone over South Asia-subtropical western Pacific and an anomalous anticyclone over midlatitude East Asia at upper level, anomalous ascent over southern and eastern China, and warm temperature anomalies over the tropical Indo-western Pacific. The anomalous southwesterly winds along the southeast coast of China substantially enhance the moisture supply, contributing to the increase in rainfall in southern and eastern China. The circulation anomalies over the midlatitude Asia and temperature anomalies over China and subtropical western Pacific are very different for the EAWM and ENSO. Large and positive temperature anomalies are seen at lower troposphere for a weak EAWM, but not for a warm ENSO. Correspondingly, upper-level westerly wind anomalies over midlatitude Asian continent are seen for a weak EAWM, but wind anomalies are weak for a warm ENSO. This suggests a closer link of the EAWM than ENSO to the midlatitude Asian dynamic and thermodynamic changes. [24] Further analyses removing the interdependence from the EAWM and the ENSO reveal very different circulation and temperature anomalies both in the tropics and midlatitudes. The results indicate that the circulation anomalies over the tropics as identified without removing the interdependence are mainly induced by ENSO, and those over the midlatitude Asia are closely linked to the EAWM. The results also suggest that temperature anomalies over the Pacific Ocean are largely due to ENSO. The temperature anomalies over East Asia are very different corresponding to the EAWM and ENSO. [25] This study indicates that the influence of ENSO on the winter rainfall is mainly in southern China, whereas the EAWM influences eastern China winter rainfall. This difference is related to different lower-level wind anomalies. Corresponding to a weak EAWM, southerlies penetrate northward over eastern China, whereas corresponding to a warm ENSO, southwesterlies deflect from the southeast coast of China. [26] Previous studies on the impacts of ENSO and the EAWM are based on a single index. There is evidence that the EAWM and ENSO are not independent. As such, the anomalies obtained based on a single index without considering the interdependence may include impacts of both the EAWM and ENSO. This study indicates that the results could be very different when the interdependence is removed. This suggests the necessity of considering the 9of11

10 interdependence when studying the respective influence of different factors in climate variability. [27] Previous studies have used different indices for the EAWM [e.g., Ji et al., 1997; Chen and Sun, 1999; Yang et al., 2002; Chan and Li, 2004]. This study only considered the index defined by Chen et al. [2000]. Because the relationship of the EAWM with ENSO and the atmospheric circulation may vary with the EAWM index [Wang and Chen, 2009], the results obtained in this study may subject to some quantitative changes when a different EAWM index is used. Nevertheless, we believe that the general conclusion will remain unchanged. [28] There are other factors, such as the North Atlantic Oscillation (NAO), the location of blocking high, and the pathway of winter monsoon surges [e.g., Zhang et al., 1997; Watanabe, 2004; Yu and Zhou, 2004; Xin et al., 2006], that may affect the atmospheric circulation over East Asia and thus the winter rainfall distribution in China. In view of the possible relation of these factors with ENSO, it may be necessary to remove their dependence on ENSO to assess their respective impacts on China rainfall. [29] In this study, the interdependence of ENSO and EAWM is removed using a linear regression. While this is a common approach in many previous studies, the linear regression cannot fully separate the independent influences of the two factors. The simultaneous regression also cannot account for the delayed effect of, e.g., EAWM on ENSO. Thus, the results of this study should be applied with the limitations of linear regression in mind. [30] Acknowledgments. The authors appreciate comments of three anonymous reviewers that have greatly improved this work. 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