The Chinese Meteorological Society
Article Information
- HU Zeng-Zhen, KUMAR Arun, HUANG Bohua, ZHU Jieshun, REN Hong-Li . 2017.
- Interdecadal Variations of ENSO around 1999/2000. 2017.
- J. Meteor. Res., 31(1): 73-81
- http://dx.doi.org/10.1007/s13351-017-6074-x
Article History
- Received May 16, 2016
- in final form September 20, 2016
2. Department of Atmospheric,Oceanic and Earth Sciences and Center for Ocean–Land–Atmosphere Studies,George Mason University, 4400University Drive,Fairfax,VA 22030,USA;
3. Laboratory for Climate Studies & CMA–NJU Joint Laboratory for Climate Prediction Studies,National Climate Center,China Meteorological Administration,Beijing 100081,China
Climate variability and prediction have attracted considerable attention in recent decades, due to its global impact on economy and society, as well as people's lives. Among the various physical modes or phenomena associated with climate variability and prediction, the El Niño–Southern Oscillation (ENSO) plays a dominant role in tropical Pacific climate variability on seasonal–interannual timescales (Wang et al., 2003). Furthermore, it is also the largest source of predictability of global climate variability (National Research Council, 2010;Wang et al., 2010). Correctly forecasting the evolution of ENSO is crucial for skillful seasonal climate forecasts over some land regions and in other ocean basins (National Research Council, 2010). Considering its importance, the forecasting of ENSO has become operational at national or regional centers (Graham et al., 2011;Barnston et al., 2012).
Although tremendous progress has been made in understanding and monitoring ENSO, our capability in predicting ENSO (i.e., the ENSO prediction skill) has not shown a steady increase with time during the past few decades (Kirtman and Pirani, 2009). Rather, there are indications of a decrease in ENSO prediction skill after 1999/2000 (Wang et al., 2010;Barnston et al., 2012). Given the improvements in prediction tools and the observing system (serving as the initial conditions of model forecasts), understanding the decline in ENSO prediction skill is an interesting issue.
In the last decade, a particularly remarkable change with respect to the characteristics of ENSO is a reduction in ENSO variability (McPhaden, 2012;Hu et al., 2013), linked to a decline in the subsurface ocean temperature variability and/or the air–sea coupling in the whole tropical climate system (Kumar and Hu, 2014;Hu et al., 2016a). Contrasting to evolution beforehand, another interesting phenomenon during 2000−2015 is that although subsurface warming developed well during spring or early summer but dismissed rapidly, such as in the years 2012 (Su et al., 2014) and 2014 (McPhaden, 2015), leading to climate models failing to predict a warm event. The decline in ENSO prediction skill may therefore be associated with the weakening of the climate variability in the tropical Pacific, including ENSO. The specific reasons for such a decline in skill may also be linked with a breakdown in the relationship between warm water volume (WWV), integrated across the equatorial Pacific, and ENSO SST anomalies. For example,Horii et al. (2012),McPhaden (2012), and Kumar and Hu (2014) all noted that, while the WWV led ENSO SST anomalies by 7–8 months during 1979–1999, WWV variations decreased and their lead time to ENSO reduced to only 3 months after 2000, showing a significant interdecadal variation.
In this paper, we use updated observational data to review the interdecadal change in tropical Pacific climate variability around 1999/2000, with a focus on ENSO. The analysis covers the interdecadal changes of ENSO variability and frequency, changes in the mean state of the tropical Pacific, and the possible connection between the changes in ENSO variability and frequency with changes in the mean state. The data and methods used in the analysis are briefly described in Section 2, and then the ENSO variability and frequency changes are presented in Section 3. The mean state changes in the tropical Pacific are examined, and the connection with the interdecadal changes in ENSO variability and frequency is discussed in Section 4. A summary and some further discussion are provided in Section 5.
2 Data and methodsThe monthly mean ocean temperature data are from the Global Ocean Data Assimilation System (GODAS) (Behringer and Xue, 2004). By using the ocean temperature and depth of the 20°C isotherm (D20) from GODAS, a WWV index is defined as the average of D20 over the region (5°S–5°N, 120°E–80°W) (Meinen and McPhaden, 2000). The SST data used in this work are from the ERSST v4 (Extended Reconstructed SST version 4) dataset, at a resolution of 2°×2° (Huang et al., 2015). The Niño3.4 index is defined as the averaged ERSST v4 SST anomaly over (5°N–5°S, 170°–120°W).
Both the surface wind stress and zonal wind at 1000 hPa from the NCEP–DOE reanalysis dataset (1°×1° grid) are used in this study (Kanamitsu et al., 2002). The precipitation data are from the Climate Anomaly Monitoring System and Outgoing Longwave Radiation (OLR) Precipitation Index (CAMS-OPI) dataset (Janowiak and Xie, 1999), and the OLR data are from Liebmann and Smith (1996), both on a 2.5°×2.5° grid. All the data are for the period January 1979 to December 2015, and the anomalies are calculated with respect to the climatological mean from January 1981 to December 2010.
To reveal the timescale dependence of the variability of the Niño3.4 index, as well as its frequency change, wavelet analysis is adopted (Meyers et al., 1993;Hu and Nitta, 1996). Firstly, wavelet analysis is conducted for the Niño3.4 index for the period January 1979 to December 2015, and then the variances corresponding to the different timescales from January 1979 to December 1999 and from January 2000 to December 2015 are separately calculated.
3 Variability and frequency changes 3.1 Variability changeThe decline in ENSO prediction skill since 2000 (Wang et al., 2010;Barnston et al., 2012) is associated with an overall suppression of climate variability in the tropical Pacific (McPhaden, 2012;Hu et al., 2013,2016a). As seen in Fig. 1, although an extremely strong El Niño occurred in 2015–2016, the mean standard deviation of the Niño3.4 index is smaller for January 2000 to December 2015 (green shading) than that for January 1979 to December 1999 (yellow shading), suggesting a reduction in ENSO variability since 2000 (Hu et al., 2013).
In fact, the variability of the whole tropical air–sea coupling system was suppressed after 2000 (Hu et al., 2013,2016a). For instance, SST variability decreased in the central and eastern tropical Pacific, especially along the coasts (Fig. 2a), although the variability increased slightly in the central tropical Pacific. This may have been the result of the more frequent occurrence of so-called central Pacific ENSO events after 2000 (Kao and Yu, 2009;Yeh et al., 2009;Ren and Jin, 2011;Hu et al., 2012a). Consistent with the reduction in SST variability in the central and eastern tropical Pacific, the variabilities of deep convection (represented by precipitation and OLR) and zonal wind at 1000 hPa also decreased after 2000, especially in the central and eastern tropical Pacific (Fig. 2).
Recently, through analysis of the variabilities in various dynamical and thermodynamical terms of the mixed-layer ocean heat budget across the equatorial Pacific,Hu et al. (2016a) pointed out that, after 1999/2000, the ocean–atmosphere coupling has weakened overall on the ENSO timescales during the ENSO mature phase, whereas it has not changed in the ENSO developing phase. That conclusion is consistent with the change in the variability shown in Figs. 1 and 2, as well as for the subsurface ocean temperature across the equatorial Pacific (Fig. 3a). The decrease in variability is mainly along the thermocline, but slightly above the thermocline in the central Pacific, and below the thermocline in the eastern Pacific. Therefore, the whole tropical Pacific climate system, including both the ocean and atmosphere, has shifted to a lower variability regime since 2000.
3.2 ENSO frequency changeIn addition to the reduction in ENSO variability (as well as the tropical Pacific climate system) since 2000, the frequency of ENSO has also experienced an interdecadal variation. Wavelet analysis (Meyers et al., 1993;Hu and Nitta, 1996) of the Niño3.4 index shows that the maximum variability was mainly confined to a periodicity of 1.5 to 4 years in January 1979 to December 1999 (bars in Fig. 4), whereas the variance distribution was flatter, with a relatively smaller major peak around 2 years and a secondary peak around 5 years, during January 2000 to December 2015 [shading in Fig. 4, as well as Fig. 8 in Hu et al. (2016a)]. This suggests that, compared with that in 1979–1999, the frequency of ENSO was less regular and closer to a white noise process (equal variance for all frequencies) in 2000–2015. Meanwhile, the frequency of the WWV index (figure omitted) also experienced a similar change to that of the Niño3.4 index.
As a consequence of the frequency changes to the Niño3.4 and WWV indices, as well as the variability change of ENSO, the lead–lag correlations between the two indices were different between the early and late periods, for both amplitude and the pattern of evolution (Fig. 5). The WWV led the ENSO SST anomalies by 7–8 months during 1979–1999 (shading in Fig. 5), whereas the lead time reduced remarkably to only 3 months during 2000–2015, in addition to an obvious decrease in the maximum correlation (bars in Fig. 5), which is consistent with previous results reported by McPhaden (2012),Horii et al. (2012), and Kumar and Hu (2014).Bunge and Clarke (2014) pointed out that the decreased WWV lead time is related to a marked increase in the variance of the tilt (east–west dipole) mode of thermocline variation, and a marked decrease in its second (one sign across the Pacific—also called WWV) mode (amplitude and its contribution). Such a change is probably associated with the “mean” La Niña-like condition (Xiang et al., 2013), including a westward displacement of the anomalous wind forcing. Furthermore, the change in ENSO variability coincided with the fact that the zonal advection feedback seems to have enhanced, while the thermocline feedback has suppressed, after 2000 (Lübbecke and McPhaden, 2014).
The subsurface ocean heat condition, or WWV, is a critical indicator and key predictor for ENSO evolution (Jin, 1997a,b;Clarke and Van Gorder, 2001;Kug et al., 2005;Ren and Jin, 2013;Tseng et al., 2016). The weakening of the correlation and shortening of the lead time of the WWV index relative to ENSO imply a reduction in ENSO's potential predictability, thus making ENSO prediction more challenging. The reduced ENSO predictability may also be the physical cause behind the decline in ENSO prediction skill since 2000 (Wang et al., 2010;Barnston et al., 2012;Kumar et al., 2015). However, we should point out that the data period (1979–2015) is clearly too short for studying interdecadal variation, which may to a certain extent affect the robustness of the results reported in the present paper.
4 Mean state changes and possible impactCollectively, the variability of the coupled system in the tropical Pacific, including ENSO, decreased and shifted to a relatively higher frequency regime associated with a flatter spectral distribution, and was closer to a white noise process, after 2000, as compared with that in 1979–1999. As documented in previous studies (e.g.,An and Wang, 2000;McPhaden et al., 2011;Zhu et al., 2011;Hu et al., 2013), both ENSO variability and frequency are connected with the climatological mean state. Next, we examine the mean state change in the tropical Pacific and discuss its possible connection with ENSO's variability and frequency changes.
The difference in subsurface ocean temperature between 2000–2015 and 1979–1999 (shading in Fig. 3b) shows pronounced warming anomalies around/above the thermocline in the western–central Pacific, and cooling anomalies around/below the thermocline in the eastern Pacific [also see Fig. 3 in Hu et al. (2013)]. As indicated in Hu et al. (2013), such changes in subsurface ocean temperature suggest a sharpening of the vertical gradient of the ocean temperature along the thermocline and a tendency towards a steeper thermocline tilt during 2000–2015. These changes indicate that the thermocline slope shifted from below- to above-normal around 1999/2000.
Consistent with the change in subsurface ocean temperature or the thermocline across the equatorial Pacific, the trade wind strengthened in the central and eastern tropical Pacific (Fig. 6d). Meanwhile, warm (cold) SST anomalies (Fig. 6a), enhanced (suppressed) deep convection (Fig. 6b), and increased (decreased) precipitation (Fig. 6c) are apparent in the western (central and eastern) tropical Pacific. Such changes in the mean state were associated with an enhancement of the zonal SST gradient (Fig. 6a) and strengthening of the Walker circulation [see Fig. 5 in Hu et al. (2013), and L'Heureux et al. (2013a,b)]. The change in the Walker circulation coincided spatially with the changes in surface wind stress divergence; that is, divergence mainly in the central and eastern Pacific (climatologically, the downward branch of the Walker circulation) and convergence in the western Pacific (climatologically, the upward branch of the Walker circulation; see shading in Fig. 6d).
The interdecadal changes in the mean state of the atmospheric and oceanic components over the tropical Pacific display a physically coherent picture, i.e., the warm SST anomaly in the west and cold anomaly in the east, the enlarged zonal SST gradient and the enhancement of surface wind stress and Walker circulation, as well as the increase in the slope of the thermocline, consistent with the increase (decrease) in precipitation and enhancement (suppression) of the deep convection in the western (eastern) equatorial Pacific. Such interdecadal changes in the mean state may be linked to the suppression of the climate variability in the tropical Pacific, including ENSO. For example,Hu et al. (2013) proposed that stronger surface trade winds, combined with a steeper thermocline slope, may hamper the movement of warm water across the equatorial Pacific. With the decrease in the variability of the WWV, the amplitude of ENSO may reduce. Through model sensitivity experiments,Hu et al. (2013) confirmed the linkages among wind stress, thermocline slope, and ENSO amplitude. They argued that either overly strong or overly weak wind stress (and an overly large or small thermocline slope) along the equator is unfavorable for ENSO growth (An and Wang, 2000;Hu et al., 2013). Too small a slope means too small a zonal gradient, which is unfavorable for strong air–sea coupling and thus a strong ENSO. In contrast, too large a slope may hinder warm water zonal migration, which is also unfavorable for ENSO growth. It is clear that, in addition to the ocean, the change in the atmospheric mean state may also play an active and important role in the interdecadal change of ENSO (Xiang et al., 2013,Hu et al., 2016b). The connection between mean state changes and ENSO frequency should be examined further in future work.
5 Summary and discussionThis paper discusses the interdecadal changes in the interannual climate variability in the tropical Pacific, with a focus on ENSO. Compared with 1979–1999, the whole tropical Pacific climate system, including both the ocean and atmosphere, shifted to a lower variability regime around 2000. Meanwhile, the frequency of ENSO became less regular and was closer to a white noise process. As a consequence of the changes in frequency and variability of the tropical Pacific climate variability, the lead time of the subsurface ocean heat condition (i.e., WWV) to ENSO (e.g., Niño3.4 index) decreased remarkably, in addition to an obvious reduction in the maximum correlation between them—a result that is consistent with previous studies (e.g.,Horii et al., 2012;McPhaden, 2012;Kumar and Hu, 2014). The weakening of the correlation and shortening of the lead time of the WWV index to ENSO probably reduced the potential predictability of ENSO and increased the challenge involved in its prediction. This may also be the physical reasoning behind the decline in ENSO prediction skill since 2000 (Wang et al., 2010;Barnston et al., 2012;Kumar et al., 2015).
Coincident with the tropical Pacific climate variability and frequency changes, the mean state of the atmospheric and oceanic components also experienced a physically coherent change associated with a basin-wide enhancement of the Pacific trade winds and colder mean eastern equatorial SST, which may also have caused the hiatus in the global warming trend [e.g.,England et al. (2014)]. Warm SST anomalies in the western Pacific and cold anomalies in the eastern Pacific led to an increase in the zonal SST gradient, which is linked to the enhancement of surface wind stress and Walker circulation, as well as an increase in the thermocline slope, and is consistent with an increase (decrease) in precipitation and an enhancement (suppression) of the deep convection in the western (eastern) equatorial Pacific.
The relationship between ENSO property changes and the mean state, however, is still not fully understood. Some studies suggest that mean state changes determine changes in ENSO variability. For example,Hu et al. (2013) argue that interdecadal variations of the mean state (vertical and zonal gradients of subsurface ocean temperature and the zonal contrast in zonal wind stress) may control the change in ENSO amplitude. On the other hand,McPhaden et al. (2011) suggest that the character variations of El Niño during 1980–2010 were mainly intrinsic. These natural ENSO variations were projected onto the background state and modified its structure because of the asymmetric spatial structures of central Pacific and eastern Pacific El Niño events.Ren et al. (2013) also argue that the two types of ENSO mode played an evident role in generating the interdecadal change of the ENSO regime around the late 1970s, which indicates the possibility that change in the stability of the ENSO mode may lead to such an interdecadal change in ENSO's properties.
Furthermore,An and Wang (2000) suggested that ENSO frequency change is accompanied by a significant change in the structure of the coupled ENSO mode. In comparison with the high-frequency regime of 1962–1975, they found that the structure of the coupled mode in the low-frequency regime of 1980–1993 featured an eastward shift of the westerly anomalies during the warm phase of ENSO. The altered ENSO characteristics since the 2000s seem to be associated with another shift in the air–sea coupling regime, different to those in either the 1960s–1970s or 1980s–1990s. However, its physical linkage with the change in the background state has yet to be fully understood from a theoretical perspective. Meanwhile, the impact of interdecadal variation of the tropical Pacific on the different types of ENSO remains unclear.
Moreover, the causes of interdecadal changes in the mean state of the tropical Pacific is still a controversial topic. In addition to the impact from the extratropical Pacific, such as the Pacific Decadal Oscillation or Interdecadal Pacific Oscillation, the Indian Ocean (e.g.,Luo et al., 2012) and Atlantic Ocean (e.g.,Li et al., 2016) may contribute to the interdecadal variation of the mean state of the tropical Pacific. Furthermore,McPhaden et al. (2011) noted that changes in the background conditions are opposite to those expected from greenhouse gas (GHG) forcing in climate models, and opposite to what is expected if changes in the background state are mediating a more frequent occurrence of central Pacific El Niño.Wittenberg (2009) identified strong interdecadal and intercentennial modulations of ENSO in a 2000-yr coupled model run with atmospheric composition, solar irradiance, and land cover fixed at 1860 values, in which ENSO variance could change 100% from period to period. This implies that internal processes of the air–sea coupled system can generate remarkable modulation of the tropical Pacific climate, including its mean state and variability—a suggestion consistent with the findings of Wang et al. (2003).
Nevertheless, an impact of increased GHG concentrations on the tropical Pacific climate and ENSO cannot be fully ruled out. A considerable amount of work has documented a robust response of the tropical Pacific climate and ENSO to increased GHG concentrations in different climate models. For instance, under the influence of increased GHG concentrations, the tropical easterly trade wind weakens, the equatorial thermocline shoals, and the oceanic temperature vertical gradients across the thermocline increase (Collins et al., 2011). Obviously, such changes will ultimately affect ENSO variability (Meehl et al., 1996;Timmermann et al., 1999;Hu et al., 2000,2012b;Cai et al., 2014).
Acknowledgements . We appreciate the constructive comments and suggestions from the two reviewers. The scientific results and conclusions, as well as any view or opinions expressed herein, are those of the authors and do not necessarily reflect the views of NWS, NOAA, or the Department of Commerce.
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