Contrasting Impacts of South and North Tropical Indian Ocean Sea Surface Temperature Anomalies on East Asian Summer Climate

HU Kai-Ming

State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics & Center for Monsoon System Research, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100080, China

Contrasting Impacts of South and North Tropical Indian Ocean Sea Surface Temperature Anomalies on East Asian Summer Climate

HU Kai-Ming

State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics & Center for Monsoon System Research, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100080, China

Using observational data and model simulations, the author find that the North Indian Ocean (NIO) sea surface temperature (SST) anomalies can trigger an eastward atmospheric Kelvin wave propagating into the equatorial western Pacific, inducing an anomalous anticyclone over the subtropical Northwest Pacific (NWP) and resulting in prominent summer climate anomalies in the East Asia-Northwest Pacific (EANWP) region. However, the response of tropospheric temperatures and atmospheric Kelvin waves to the South Indian Ocean (SIO) SST anomalies is weak; as a result, the impact of the SIO SST anomalies on the EANWP summer climate is weak. The contrasting impacts of NIO and SIO SST anomalies on the EANWP summer climate is possibly due to the different mean state of SSTs in the two regions. In summer, the climatological SSTs in the NIO are higher than in the SIO, leading to a stronger response of atmospheric convection to the NIO SST anomalies than to the SIO SST anomalies. Thus, compared with the SIO SST anomalies, the NIO SST anomalies can lead to stronger tropospheric air temperature anomalies and atmospheric Kelvin waves to affect the EANWP summer climate.

Indian Ocean, Northwest Pacific anticyclone, East Asian climate

1　Introduction

The dominant mode of sea surface temperature (SST) interannual variability in the tropical Indian Ocean (TIO) features basin warming or cooling (Klein et al., 1999), known as the Indian Ocean basin mode (IOBM). The internal variations of the IOBM are closely related to El Ni?o-Southern Oscillation (ENSO). During the El Ni?o decaying phase, the TIO often experiences basin warming from spring to summer. On the one hand, the El Ni?o can lead to the TIO basin warming through changing atmospheric circulations to reduce sea surface evaporation and increase shortwave radiation (Klein et al., 1999). On the other hand, the El Ni?o can lead to subtropical southwest Indian Ocean warming by triggering downwelling oceanic Rossby waves in spring (Xie et al., 2002). The subtropicalsouthwest Indian Ocean warming can lead to equatorially anti-symmetric wind anomalies over the TIO in spring and early summer, helping the TIO warming persist into the following summer by reducing sea surface evaporation (Wu et al., 2008; Du et al., 2009).

The IOBM SST anomalies can exert a great influence on summer climate in the East Asia-Northwest Pacific (EANWP) region. In response to IOBM SST warming, there are Matsuno-Gill pattern (Matsuno, 1966; Gill, 1980) atmospheric circulation anomalies over the TIO and a warm tropospheric Kelvin wave trough extending into the equatorial western Pacific, inducing Ekman divergence in the subtropical NWP to suppress convection and develop a low-level anomalous anticyclone over the subtropical NWP (Xie et al., 2009). Besides via the exertion of a Kelvin wave, the IOBM SST warming could contribute to the NWP anomalous anticyclone by changing the local Walker circulation (Yuan et al., 2008; Wu et al., 2010; Chen et al., 2014; He and Wu, 2014). The NWP anomalous anticyclone in turn could lead to above-normal rainfall in the regions of the Yangtze River and Japan (Wang and Zhang, 2002), hot summers in South China, and cool summers in Northeast China (Hu et al., 2011, 2012). In addition, the IOBM SST anomalies could affect East Asian climate through modulating the location and strength of the South Asian high (Huang et al., 2011) and East Asian jet (Qu and Huang, 2012).

However, the impacts of the south and north parts of the IOBM SST anomalies on EANWP summer climate are different. Using numerical simulations, Huang and Hu (2008) reported that the impact of the NIO SST anomalies on East Asian summer climate is more significant than that of the south Indian Ocean (SIO) SST anomalies. Huang et al. (2011) demonstrated that the effect of NIO and SIO SST anomalies on the South Asian high is reversed: the NIO warming strengthens the South Asian high, but the SIO warming weakens it. In addition, the distribution of summer TIO SST anomalies during the El Ni?o decaying phase is not constant. For example, Hu et al. (2013) showed that the summer TIO SST anomalies during the El Ni?o decaying phase were mainly distributed along the equator and in the SIO during 1966-86, but were mainly distributed in the NIO during 1988-2008. Therefore, understanding the different impacts of the NIO and SIO SST anomalies on the EANWP summer climate is important to improve the prediction skill of summertime East Asian climate. However, why the impact of theNIO and SIO SST anomalies on EANWP summer climate is different is still unknown.

The aim of this paper is to investigate the different influences of NIO and SIO SST anomalies on the EANWP summer climate. The remainder of the paper is organized as follows. The data and numerical model are described in section 2. The evidence and reasons for the different effects of NIO and SIO SST anomalies on EANWP summer climate are presented in section 3. A brief summary is given in section 4.

2　Data and model

The monthly mean global SST dataset used in this study is the Hadley Centre Sea Ice and Sea Surface Temperature data set (HadISST1; Rayner et al., 2003), provided by the Hadley Center. The global precipitation dataset used in this study is the Center for Climate Prediction (CPC) Merged Analysis of Precipitation (CMAP; Xie and Arkin, 1997), which combines observations and satellite precipitation data into 2.5° × 2.5° global grids. The monthly mean winds and air temperatures are derived from the National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEPNCAR) atmospheric reanalysis with a resolution of 2.5° × 2.5°, which is available from 1948 to present (Kalnay et al., 1996).

An NIO and an SIO SST index are defined to denote the summertime SST variation in the NIO and the SIO, respectively. The NIO SST index is calculated by averaging the SST over the NIO (5-25°N, 40-100°E) in boreal summer (from June to August), and the SIO SST index is calculated by averaging the SST over the SIO (25-5°S, 40-100°E). For consistency with the GPCP precipitation data, this study focuses mainly on the period 1979-2012. For a 34-year time series, correlations of 0.29 and 0.34 reach the 90% and 95% confidence levels based on the Student's t-test, respectively.

The atmospheric general circulation model used in this study is ECHAM5, the fifth generation of the Hamburg version of the European Centre for Medium-Range Weather Forecasts model. In this study, a version with triangular truncation at zonal wavenumber 63 (T63; equivalent to 1.9° horizontal resolution) and 19 levels in the vertical direction is used. A detailed description of ECHAM5 is given in Roeckner et al. (2003).

3　Role of SIO and NIO SST anomalies in NWPEA summer climate variability

3.1 Relationship between NIO and SIO SST variations in summer

Figure 1 is a scatter diagram of the SIO and NIO indexes from 1979 to 2012. In general, the NIO and SIO indexes shows a significant positive linear relationship: the larger the SIO index, the larger the NIO index. This is consistent with previous study (Klein et al., 1999) showing that the SSTs often change uniformly in the TIO. However, it is also found that the SIO and NIO indexes do not obey a positive linear relationship in some years. For example, in 1991 and 2012, the SSTs are significantly above normal (above 1 standard deviation) in the SIO, but are normal (below 0.5 standard deviation) in the NIO. In 1994, by contrast, the SSTs are significantly below normal in the NIO, but normal in the SIO. In these years, the NIO and SIO SST anomalies do not occur concurrently. Thus, to better understand the impact of TIO SST variations on NWPEA summer climate, it is necessary to identify the different effects of NIO and SIO SST anomalies on NWPEA summer climate.

3.2 Observational analyses

Figure 2a shows the correlations of June-July-August (JJA) mean precipitation and tropospheric temperature (vertical average from 850 to 200 hPa) with the NIO SST index, and the regressions of 850 hPa winds onto the index. The correlations of tropospheric temperature feature a Matsuno-Gill pattern over the TIO, with the maximum correlation above 0.8 in the western TIO. Over the western Indian Ocean and Africa, there are two tails of tropospheric temperature anomalies denoting westward propagation of Rossby waves. Over the equatorial western Pacific, there is a wedge extending from the Indian Ocean, indicating the eastward propagation of Kelvin waves. Associated with the Matsuno-Gill pattern temperature anomalies, there are significant positive correlations of precipitation over the two sides of the equator in the western Indian Ocean and dipole precipitation anomalies over the EANWP. At 850 hPa there is an anomalous anticyclone over the subtropical NWP. Outside the Indian Ocean, the most prominent circulation and rainfall anomalies are distributed in the EANWP. The results suggest that the NIO SST anomalies could affect EANWP summer climate through triggering an atmospheric Kelvin wave, which is consistent with previous studies (Xie et al., 2009; Huang et al., 2010).

Figure 2b is the same as Fig. 2a except that the results are based on the SIO SST index. There are still positive correlations of tropospheric air temperature over the TIO, but the values are much weaker than in Fig. 2a. Over the equatorial western Pacific, the tropospheric air temperature anomalies are very weak, suggesting that the SIO warming cannot trigger warm Kelvin waves propagating into the western Pacific. As a result, the 850-hPa wind and the rainfall anomalies are weak in the EANWP. The results suggest that the impact of NIO SST anomalies on the EANWP summer climate is much stronger than the impact of SIO SST anomalies. In addition, since the NIO and SIO SST variations have a close relationship, it is hard to totally distinguish between their impacts on EANWP summer climate. Thus, the NWPEA climate anomalies associated with the SIO SST index possibly arise from the influence of NIO SST anomalies.

3.3 Model simulations

In this subsection, the results of model simulations are used to confirm the different effects of the NIO and SIO SST anomalies on EANWP summer climate. Three experiments using the ECHAM5 model were conducted: a control experiment (CTL_EXP), NIO experiment (NIO_ EXP), and SIO experiment (SIO_EXP). In the CTL_EXP, the model was forced by the observed monthly climatology of SST. In the NIO_EXP, 1°C SST anomalies were added over the NIO (5-25°N, 40-100°E). In the SIO_EXP, 1°C SST anomalies were added over the SIO (25-5°S, 40-100°E). In all experiments, the SST anomalies were kept constant in time and the model was integrated for 20 years. Thus, the experiments were equivalent to 20-member ensemble runs.

Figure 3a shows the difference of summer precipitation, tropospheric temperature, and 850 hPa winds between the NIO_EXP and the CTL_EXP. In response to the NIO warming, there are significant positive rainfall anomalies in the NIO and weak negative rainfall anomalies in the tropical SIO. According to the theory of Gill et al. (1980), the positive rainfall anomalies in the NIO can provide the heating to develop Matsuno-Gill pattern-like circulation anomalies. Indeed, in Fig. 3a the tropospheric temperature anomalies display a Matsuno-Gill pattern, with two Rossby wave tails in the western Indian Ocean and a Kelvin wave trough over the equatorial western Pacific. Along the Kelvin wave trough, there are positive rainfall anomalies extending from the TIO to the central Pacific. On the two sides of the Kelvin wave trough, there are negative rainfall anomalies, possibly caused by surface divergence through Ekman friction. Corresponding to Matsuno-Gill pattern-like tropospheric temperature anomalies, there are easterly anomalies in the western Pacific and westerly anomalies in the western Indian Ocean at 850 hPa. In the NWP, there is an anomalous anticyclone. Compared with observations (Fig. 2a), the simulated NWP anomalous anticyclone shifts a little westward, and the rainfall anomalies on the north flank of the NWP anticyclone are weak. In general, the simulated rainfall, tropospheric temperature, and 850 hPa wind anomalies are consistent with observations, suggestingthat the NIO SST anomalies do indeed exert a significant effect on EANWP climate in summer.

Figure 3b shows the difference between the SIO_EXP and the CTL_EXP. The rainfall anomalies display a north-south dipole structure over the TIO, with positive anomalies in the SIO and negative anomalies in the NIO, and their amplitudes are comparable. Compared with Fig. 3a, there are no obvious tropospheric temperature anomalies and Kelvin wave trough above the TIO in Fig. 3b. As a result, the circulation and rainfall anomalies over the NWP are very weak. The result proves that the SIO SST anomalies cannot exert a significant influence on EANWP climate in summer.

Both the observed and simulated results indicate that the response of tropospheric temperature to the NIO SST anomalies is larger than that to the SIO SST anomalies. Therefore, the NIO SST anomalies can impact EANWP summer climate through triggering Kelvin waves to affect EANWP summer climate, while the SIO SST anomalies cannot trigger the Kelvin wave into the western Pacific. As a result, the impact of NIO SST anomalies on the EANWP summer climate is much stronger than the impact of SIO SST anomalies. But why are the tropospheric air temperature anomalies induced by the NIO SST anomalies stronger than those induced by the SIO SST anomalies?

3.4 Possible reasons for the contrasting impacts of NIO and SIO SST anomalies on EANWP summer climate

Figure 4 shows the air temperature anomalies in the NIO_EXP and SIO_EXP at 200 hPa, 500 hPa, and 850 hPa. It is found that the response of air temperature to the NIO and SIO SST anomalies is very different. At 200 hPa, the air temperature anomalies in the NIO_EXP show a significant Matsuno-Gill pattern with maximum anomalies above 1°C, but are very weak in the SIO_EXP. At 500 hPa, the air temperature anomalies in the NIO_EXP still show a Matsuno-Gill Pattern with maximum temperature on the two sides of the equator, but are still weak in the SIO_EXP. At 850 hPa, there are positive tropospheric temperature anomalies over the NIO in the NIO_EXP and over the SIO in the SIO_EXP. The results show that the NIO SST anomalies could affect TIO air temperature from the surface to the upper level of the troposphere, but the SIO SST anomalies only affect lower-level air temperatures.

If the tropospheric air temperature obeys moist adiabatic adjustment, the upper tropospheric air temperature change in response to an SST change (T') is T＇+ (L/Cp)RH(dq/dT) T＇,where L is the latent heat of vaporization, Cpdenotes the specific heat at constant pressure, RH is relative humidity, and q is specific humidity (Hu et al., 2014). As shown in Fig. 4, the relationship exists in the NIO_EXP but does not exist in the SIO_EXP, suggesting that the atmosphere over the NIO obeys the moist adiabatic adjustment, but not over the SIO.

Whether the atmospheric air temperature obeys the moist adiabatic adjustment partly depends on the strength of the atmospheric convective activity there (Su et al., 2003). Generally, the atmospheric air temperature obeys the moist adiabatic adjustment in strong convective regions and not in weak convective regions. Moreover, the strength of atmospheric convection is related to the distribution of climatological SST. Lau et al. (1997) suggested that there is an SST threshold for convection. Above such a threshold, the atmospheric convection is closely related to SST anomalies; below it, the relationship between SST anomalies and atmospheric convection is weak. As shown in Fig. 5, the climatological SSTs in the NIO are higher than in the SIO. The summer SSTs in the NIO are above 28°C except for the regions in the west of the Arabian Sea, while the SSTs are below 27°C in the SIO to the south of 10°S. Thus, the NIO SST anomalies may trigger atmospheric convection more easily than the SIO SST anomalies, leading to a stronger response of tropospheric temperature anomalies to the NIO SST anomalies than to the SIO SST anomalies.

4　Summary

In observations, it is found that the effect of the NIO SST anomalies on EANWP summer climate is stronger than the effect of the SIO. The NIO SST anomalies could trigger atmospheric Kelvin waves propagating into the equatorial western Pacific to induce an anomalous anticyclone over the NWP, which results in summer climate anomalies in the EANWP. However, the response of tropospheric temperature to the SIO SST anomalies is weak, which leads to weak EANWP summer climate anomalies. The model simulations capture the different effects of the SIO and NIO SST anomalies on EANWP summer climate.

Using simulations, it is found that the NIO SST anomalies could affect air temperature from the surface to the upper troposphere, but the air temperature anomalies induced by the SIO SST anomalies are only confined to the lower levels of the troposphere. As a result, the response of tropospheric temperature anomalies to the NIO SST anomalies is larger than to the SIO SST anomalies. The difference is likely because of the different climatological SSTs in the NIO and the SIO. In summer, the climatological SSTs in the NIO are above 28°C except for the regions in the west of the Arabian Sea, while the SSTs are below 27°C in the SIO to the south of 10°S. Thus, the NIO SST anomalies may exert stronger atmospheric convective activity than the SIO SST anomalies, leading to larger EANWP climate anomalies over the EANWP in summer.

Acknowledgements. This study was supported by the National Basic Research Program of China (Grant Nos. 2012CB955604) and the National Natural Science Foundation of China (Grant Nos. 41205049 and 41275081).

References

Chen, J., Z. Wen, R. Wu, et al., 2014: Interdecadal changes in the relationship between Southern China winter-spring precipitation and ENSO, Climate Dyn., 43, 1327-1338.

Du, Y., S.-P. Xie, G. Huang, et al., 2009: Role of air-sea interaction in the long persistence of El Ni?o-induced North Indian Ocean warming, J. Climate, 22, 2023-2038.

Gill, A. E., 1980: Some simple solutions for heat-induced tropical circulation, Quart. J. Roy. Meteor. Soc., 106, 447-462.

He, Z., and R. Wu, 2014: Indo-Pacific remote forcing in summer rainfall variability over the South China Sea, Climate Dyn., 42, 2323-2337.

Hu, K., G. Huang, and R. Huang, 2011: The impact of tropical Indian Ocean variability on summer surface air temperature in China, J. Climate, 24, 5365-5377.

Hu, K., G. Huang, X. Qu, et al., 2012: The impact of Indian Ocean variability on high temperature extremes across south of Yangtze River Valley in late summer, Adv. Atmos. Sci., 29, 91-100.

Hu, K., G. Huang, and R. Wu, 2013: A strengthened influence of ENSO on august high temperature extremes over the southern Yangtze River Valley since the late 1980s, J. Climate, 26, 2205-2221.

Hu, K., G. Huang, X.-T. Zheng, et al., 2014: Interdecadal variations in ENSO influences on Northwest Pacific-East Asian early summertime climate simulated in CMIP5 models, J. Climate, 27, 5982-5998.

Huang, G., and K. Hu, 2008: Impact of North Indian Ocean SSTA on Northwest Pacific lower layer anomalous anticyclone in summer, J. Nanjing Inst. Meteor. (in Chinese), 31, 749-757.

Huang, G., K. Hu, and S.-P. Xie, 2010: Strengthening of tropical Indian Ocean teleconnection to the Northwest Pacific since the mid-1970s: An atmospheric GCM study, J. Climate, 23, 5294-5304.

Huang, G., X. Qu, and K. Hu, 2011: The impact of the tropical Indian Ocean on South Asian High in boreal summer, Adv. Atmos. Sci., 28, 421-432.

Kalnay, E., M. Kanamitsu, R. Kistler, et al., 1996: The NCEP/NCAR 40-year reanalysis project, Bull. Amer. Meteor.Soc., 77, 437-471.

Klein, S. A., B. J. Soden, and N. C. Lau, 1999: Remote sea surface temperature variations during ENSO: Evidence for a tropical atmospheric bridge, J. Climate, 12, 917-932.

Lau, K., H. Wu, and S. Bony, 1997: The role of large-scale atmospheric circulation in the relationship between tropical convection and sea surface temperature, J. Climate, 10, 381-392.

Matsuno, T., 1966: Quasi-geostrophic motions in the equatorial area, J. Meteor. Soc. Japan, 44, 25-43.

Qu, X., and G. Huang, 2012: Impacts of tropical Indian Ocean SST on the meridional displacement of East Asian jet in boreal summer, Int. J. Climatol., 32, 2073-2080, doi:10.1002/joc.2378.

Rayner, N. A., D. E. Parker, E. B. Horton, et al., 2003: Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century, J. Geophys. Res., 108, 4407, doi:10.1029/2002JD002670.

Roeckner, E., G. B?uml, L. Bonaventura, et al., 2003: The Atmospheric General Circulation Model ECHAM5: Part I. Model Description, Report No. 349, Max-Planck-Institut für Meteorlogie, 140pp.

Su, H., J. D. Neelin, and J. E. Meyerson, 2003: Sensitivity of tropical tropospheric temperature to sea surface temperature forcing, J. Climate, 16, 1283-1301.

Wang, B., and Q. Zhang, 2002: Pacific-east Asian teleconnection. Part II: How the Philippine Sea anomalous anticyclone is established during El Ni?o development, J. Climate, 15, 3252-3265.

Wu, R., B. P. Kirtman, and V. Krishnamurthy, 2008: An asymmetric mode of tropical Indian Ocean rainfall variability in boreal spring, J. Geophys. Res., 113, D05104, doi:10.1029/ 2007JD009316.

Wu, R., Z. Wen, S. Yang, et al., 2010: An interdecadal change in southern China summer rainfall around 1992/93, J. Climate, 23, 2389-2403.

Xie, P., and P. A. Arkin, 1997: Global Precipitation: A 17-year monthly analysis based on gauge observations, satellite estimates, and numerical model outputs, Bull. Amer. Meteor. Soc., 78, 2539-2558.

Xie, S. P., H. Annamalai, F. A. Schott, et al., 2002: Structure and mechanisms of South Indian Ocean climate variability, J. Climate, 15, 864-878.

Xie, S. P., K. M. Hu, J. Hafner, et al., 2009: Indian Ocean capacitor effect on Indo-Western Pacific climate during the summer following El Ni?o, J. Climate, 22, 730-747.

Yuan, Y., W. Zhou, J. C. Chan, et al., 2008: Impacts of the basinwide Indian Ocean SSTA on the South China Sea summer monsoon onset, Int. J. Climatol., 28, 1579-1587.

Hu, K.-M., 2015: Contrasting impacts of south and north tropical Indian Ocean sea surface temperature anomalies on East Asian summer climate, Atmos. Oceanic Sci. Lett., 8, 327-332,

10.3878/ AOSL20150026.

27 March 2015; revised 27 April 2015; accepted 28 April 2015; published 16 November 2015

HU Kai-Ming, hkm@mail.iap.ac.cn