The number of tropical cyclones (TCs) in the Australian region exhibits a large variation between different ENSO regimes. While the difference in TC numbers and spatial distribution of genesis locations between the canonical El Niño and La Niña regimes is well known, the authors demonstrate that a statistically significant difference in TC numbers also exists between the recently identified negative-neutral and positive-neutral regimes. Compared to the negative-neutral and La Niña regimes, significantly fewer TCs form in the Australian region during the positive-neutral regime, particularly in the eastern subregion. This difference is attributed to concomitant changes in various large-scale environmental conditions such as sea level pressure, relative vorticity, vertical motion, and sea surface temperature.
The relationship between the number of Australian tropical cyclones (TCs) and the El Niño–Southern Oscillation (ENSO) has been extensively studied over the past few decades (McBride 1995; Chu 2004; Camargo et al. 2010). Nicholls (1979) was the first to explore this relationship, demonstrating the potential for seasonal prediction of Australian TC numbers. Subsequent studies (e.g., Nicholls 1984, 1985, 1992; Solow and Nicholls 1990; Evans and Allan 1992; McDonnell and Holbrook 2004; Kuleshov et al. 2008; Ramsay et al. 2008; Werner and Holbrook 2011) showed that more TCs form in the Australian region during La Niña than El Niño events. A systematic shift in the mean genesis location has been documented between these opposite phases of ENSO in the Australian–southwest Pacific region. For example, during El Niño events more TCs form near the date line and extend farther to the east, with low activity in the Coral Sea and Australian regions (e.g., Basher and Zheng 1995; Ramsay et al. 2008; Chand and Walsh 2009; Liu and Chan 2012; Vincent et al. 2011). The reverse occurs during La Niña events, when the TC formation is displaced southwestward into the Coral Sea and Australian regions, with relatively low activity east of the date line.
While the variability in TC activity between contrasting El Niño and La Niña regimes is well known, little is known of the variability that may occur within ENSO-neutral events (i.e., the events that are left once the El Niño and La Niña events are removed). Recently, Chand et al. (2013, hereafter C13) demonstrated for the Southern Hemisphere summer that ENSO-neutral events can be objectively separated into two distinct regimes (positive neutral and negative neutral). During positive-neutral events, more TCs form in the southwest Pacific with genesis locations similar to those during El Niño events. However, substantially fewer TCs are observed for the negative-neutral regime, with genesis locations somewhat resembling those in La Niña. This difference was attributed to the more favorable large-scale environmental conditions that occur during the positive-neutral regime (such as low-level cyclonic relative vorticity, vertical wind shear, sea surface temperatures, and relative humidity).
Note that positive- and negative-neutral regimes of C13 somewhat resemble a previously identified nontraditional type of El Niño (referred to as the El Niño Modoki or central Pacific El Niño) by various authors (e.g., Trenberth and Stepaniak 2001; Larkin and Harrison 2005; Ashok et al. 2007; Kug et al. 2009; Kao and Yu 2009). Such events have also been shown to impact TCs elsewhere in the world. Kim et al. (2009), for example, found that, unlike canonical El Niño, El Niño Modoki events are associated with greater-than-average TC frequency in the North Atlantic basin, with increasing landfall potential along the Gulf of Mexico coast and Central America. Similarly, El Niño Modoki is found to substantially modulate TC frequency (Chen and Tam 2010), genesis distribution (Kim et al. 2011), and tracks (Hong et al. 2011) in the western North Pacific basin. Above-normal TCs are also observed in the South China Sea during the June–August months of the El Niño Modoki years (Chen 2011).
The present investigation is motivated by these studies, but it follows the method of C13 to determine impacts of different ENSO regimes, particularly positive-neutral and negative-neutral regimes, on TCs that form in the Australian region (0–30°S, 90°–170°E). In section 2, datasets are described and a brief explanation of the different ENSO regimes obtained from C13 is given. Results are presented in section 3. Finally, a summary is given in section 4.
2. Data and methods
TC data used here were obtained from the National Climate Centre, Australian Bureau of Meteorology (e.g., Kuleshov et al. 2008). Only data for the Southern Hemisphere TC season (i.e., November–April) for the period beginning November 1970 and ending April 2009 are considered. This time period encompasses the era after which routine satellite observations became available. Consistent with earlier investigations (e.g., Werner and Holbrook 2011), we have included all TCs that formed in the Australian region. For the purpose of this investigation, TC genesis location is defined objectively as the first track point of each TC in the database. Atmospheric variables are extracted from the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) Reanalysis 1 products (Kalnay et al. 1996). The SST data are from the Met Office Hadley Centre Sea Ice and Sea Surface Temperature (HadISST) database (Rayner et al. 2003).
b. The ENSO regimes
C13 derived four distinct ENSO regimes by applying an agglomerative hierarchical clustering (AHC) technique (e.g., Kao and Yu 2009) and empirical orthogonal function (EOF) analysis (e.g., McBride et al. 2003; Ashok et al. 2007) to sea surface temperature (SST) anomaly data for the early (November–January) Southern Hemisphere TC season over the tropical Pacific (30°S–30°N, 120°E–60°W) for the period 1970–2009. The four identified regimes were the El Niño, La Niña, positive neutral, and negative neutral.
The El Niño regime includes the events of 1972/73, 1976/77, 1977/78, 1982/83, 1986/87, 1987/88, 1991/92, 1994/95, 1997/98, 2002/03, and 2006/07. Events corresponding to the La Niña regime are 1970/71, 1971/72, 1973/74, 1974/75, 1975/76, 1984/85, 1988/89, 1998/99, 1999/2000, 2000/01, 2005/06, 2007/08, and 2008/09. These events are in broad agreement with the classical El Niño and La Niña events defined by the National Oceanic and Atmospheric Administration (NOAA)'s Climate Prediction Center. Events corresponding to the positive-neutral regime are 1978/79, 1979/80, 1980/81, 1990/91, 1992/93, 1993/94, 2003/04, and 2004/05 while those corresponding to the negative-neutral regime are 1981/82, 1983/84, 1985/86, 1989/90, 1995/96, 1996/97, and 2001/02.
We note that the years identified here as El Niño Modoki do not bear a one-to-one correspondence with those of earlier authors such as Ashok et al. (2007). Inspection of the time series indicates the primary reason for this is that the current analysis is based on the structure during the Southern Hemisphere early austral summer season November–January, whereas the earlier studies focused more on the first half of the ENSO year, namely, June–December.
a. TC frequency and the ENSO regimes
The annual TC numbers for the entire Australian region and three subregions, as defined in Fig. 1a, are binned into their corresponding ENSO regimes. A bootstrap resampling method is applied to construct the 95% confidence intervals of the mean TC frequency for each regime (Figs. 1c–f). Following the procedure described in Chu and Wang (1997), the two-sample permutation method and a U-statistic test are applied to compare the mean TC frequency in each ENSO regime (see appendix for details of the method).
Climatologically, about 13 TCs form in the Australian region annually. However, individual seasons can exhibit a large variation of TC numbers ranging from, for example, 22 TCs in 1973/74 to as low as four TCs in 1987/88 season (Fig. 1b). As has been documented in past studies, this large variation is primarily due to the ENSO phenomenon. On average, significantly fewer TCs (at the 95% significance level) are observed during El Niño than La Niña (averages of 8.8 and 15.2 yr−1, respectively, as shown in Fig. 1c). Consistent with earlier investigations (e.g., Liu and Chan 2012), the largest contribution to this difference occurs in the western subregion (Fig. 1d) and, to a slightly lesser extent, in the eastern subregion (Fig. 1f). However, no significant difference in TC numbers exists between El Niño and La Niña events for the northern subregion (Fig. 1e). Further insight into these subregional differences of TC numbers in terms of their large-scale environmental controls is given in the following subsection.
The main result of the present work is the demonstration of the different impacts of the negative-neutral and positive-neutral regimes on Australian TC numbers and genesis locations. Past studies in the Australian region have binned TCs using, for example, the Trenberth (1997) classification of ENSO. An advantage of the present work is the consideration of two neutral regimes: negative neutral and positive neutral. Indeed, as shown in Fig. 1c, these two regimes modulate Australian TCs rather differently. The mean annual number of TCs that form in the Australian region is greater during negative-neutral than positive-neutral events (averages of 14.4 and 11 yr −1, respectively). This difference is significant at the 95% significance level. It is more robust in the eastern subregion than in the western and northern subregions. This is demonstrated by comparing the mean TC numbers for negative-neutral and positive-neutral regimes in Fig. 1f with those in Figs. 1d and 1e. Note here that the reverse is true for the southwest Pacific basin (i.e., east of 170°E), where significantly more TCs form during positive-neutral than during negative-neutral events, as noted by C13. This systematic oscillation in TC numbers between the Australian and the southwest Pacific basins during positive-neutral and negative-neutral regimes is similar to that observed for the two basins during El Niño and La Niña regimes, respectively.
b. TC genesis distribution and their large-scale environmental controls
As in C13, probability density functions (PDFs) are used here to describe the spatial distribution of TC genesis in each ENSO regime. The PDFs are computed from the anisotropic Gaussian functions using a 2.5° × 2.5° smoothing window over the entire Australian domain. Large-scale environmental conditions such as low-level relative vorticity, vertical wind shear, and vertical wind velocity, as well as some widely used remote signatures of ENSO such as SST and sea level pressure (SLP), are examined to understand the TC genesis variability in each ENSO regime.
Consistent with earlier investigations (e.g., Dare and Davidson 2004; Ramsay et al. 2008; Kuleshov et al. 2008), a large spread in TC genesis locations is noted over the entire Australian region (Fig. 2a). Overall, there appear to be four preferred areas of genesis: the western subregion between 90° and 105°E, the western Australian coastal region between 120° and 125°E, the Gulf of Carpentaria (135°–140°E), and the northeastern coastal region between 145° and 152°E extending eastward to the Coral Sea. However, genesis in these climatologically preferred areas can vary substantially between each ENSO regime (Figs. 2b–e).
During El Niño (La Niña) events, TC genesis can be substantially suppressed (enhanced), particularly in the western and eastern subregions, as shown in Fig. 2b (Fig. 2c). As reported in past investigations (e.g., Ramsay et al. 2008), these changes are largely controlled remotely by changes in equatorial SST anomalies due to ENSO and the corresponding changes in atmospheric circulation and conditions (such as wind shear, lower troposphere relative vorticity, and humidity). During El Niño, for example, the anomalously warm SSTs associated with Pacific warm pool extend farther eastward in the Pacific and westward in the Indian Ocean [see Fig. 3a and also Kim et al. (2012) for details on warm pool displacements in different ENSO conditions]. Favorable atmospheric conditions affecting TC genesis also shift eastward in the Pacific and farther westward in the Indian Ocean, leaving the Australian region relatively less conducive to TC genesis. Relative vorticity, for example, is anomalously less cyclonic over the entire Australian domain during El Niño events (Fig. 4a). This less conducive environment substantially reduces TC numbers, particularly in the western and eastern Australian domain. On the other hand, anomalously warm SSTs and large-scale environmental conditions (particularly relative vorticity, Fig. 4b) move westward during La Niña events (Fig. 3b), consequently creating more favorable conditions for TC genesis in the western and eastern Australian region. It appears that relative vorticity has a larger influence on TC genesis in the Australian region than environmental vertical wind shear, which does not show substantial variations between El Niño and La Niña events (not shown).
Interestingly, as noted in section 3a, TC genesis in the northern subregion does not show any significant variation between El Niño and La Niña events as was also shown in Ramsay et al. (2012). Statistical seasonal prediction models for TCs are also noted to have poor skill in this region because of the poor ENSO–TC relationship (Werner and Holbrook 2011). Similarly, Hendon et al. (2011) have noted a substantial weakening of the relationship between ENSO and summer rainfall in this monsoonal region, attributing this to seasonally varying air–sea interaction. Here we also use this air–sea interaction argument to understand the lack of ENSO–TC relationship in the northern subregion. During the summer monsoon, mean winds in the northern region are westerly. El Niño's anomalous easterly winds weaken the mean westerly wind (Fig. 4a), reducing fluxes of latent and sensible heat, leading to anomalously higher SSTs. The reverse occurs during La Niña, where enhanced westerlies lead to SST cooling, shown by anomalies in Fig. 4b. Note that during El Niño, the SSTs around northern Australia start off being cool at the beginning of the summer season, so the SST warming that occurs when the basic state winds become more easterly acts to dampen or even reverse the existing SST anomaly. Similarly, the initially warm SSTs during La Niña are damped or reversed once the summer monsoon season begins. This reversal of the local SST anomalies is hypothesized to locally nullify the impact of ENSO on TCs in the northern subregion.
As with the El Niño versus La Niña relationship, anomalously warm SSTs associated with Pacific warm pool extend farther eastward in the Pacific during positive-neutral events than during negative-neutral events (Figs. 3c,d). This displacement occurs in association with anomalously large cyclonic relative vorticity over Australia near 16°S, 120°–150°E during positive-neutral events (Fig. 4c), consequently triggering anomalous lifting near this location and the subsidence on the western and eastern flanks (Fig. 5a). This behavior is also evident in the SLP pattern, which is anomalously low near 16°S, 120°–150°E but high on the two flanks. The subsidence anomaly east of 150°E is relatively strong, thereby reducing TC formation east of about 150°E for the positive-neutral regime (Fig. 2d). However, the reverse occurs during the negative-neutral regime. Here the cyclonic relative vorticity is anomalously low in the region between 120° and 150°E where the SLP is anomalously high (Fig. 4d) and there is a net subsidence (Fig. 5b). On the two flanks the SLP is anomalously low, the relative vorticity is anomalously cyclonic, and there is a net lifting. As a result, TC genesis in the eastern subregion, and to a slightly lesser extent in the western subregion, is enhanced for the negative-neutral regime, as shown in Fig. 2e.
A recent study by C13 objectively identified four different ENSO regimes (i.e., El Niño, La Niña, positive neutral, and negative neutral). These regimes were shown to have different impacts on southwest Pacific TC numbers. The present paper extends the work of C13, with an emphasis on TCs that form in the Australian region (0°–30°S, 90°–170°E).
Consistent with earlier studies, results indicate a marked modulation of TC genesis between the different ENSO phases. TC genesis during El Niño (La Niña) events can be substantially suppressed (enhanced) in the Australian domain, particularly in the western and eastern subregions because of changes in the large-scale environmental conditions such as SSTs and relative vorticity. However, TC genesis in the northern subregion does not show any significant variation between El Niño and La Niña events. This lack of an ENSO–TC relationship is attributed to the air–sea interaction argument of Hendon et al. (2011), whereby the change in the basic-state winds during the monsoon results in a local dampening and sometimes reversal of the ENSO-related SST anomalies that exist at the beginning of the monsoon season.
The main result of this study is the demonstration that there exists a statistically significant difference in TC numbers between positive-neutral and negative-neutral regimes (averages of 11 and 14.4 yr−1, respectively), as also found between El Niño and La Niña (averages of 8.8 and 15.2 yr−1, respectively). The two regimes have distinct signatures in various environmental variables that control TCs in the Australian region. For example, the cyclonic relative vorticity during the negative-neutral regime is anomalously low in the region between 120° and 150°E, where the SLP is anomalously high and there is a net subsidence. On the two flanks the SLP is anomalously low, the relative vorticity is anomalously cyclonic and there is a net lifting. SSTs are also anomalously higher along the eastern Australian coast in negative-neutral regimes than in positive-neutral regimes. As a result, TC genesis in the eastern subregion and, to a slightly lesser extent, in the western subregion is enhanced for the negative-neutral regime. However, the reverse occurs during the positive-neutral regime.
In summary, we have shown here the impact of different ENSO regimes on TCs in the Australian region. In particular, we have demonstrated that positive-neutral and negative-neutral regimes, which were traditionally considered as a single ENSO-neutral class, can have a distinct and significant impact on the number and distribution of Australian TCs.
We acknowledge the Pacific-Australia Climate Change Science and Adaptation Planning (PACCSAP) project for supporting this work. PACCSAP is funded by AusAID, in collaboration with the Department of Climate Change and Energy Efficiency, and delivered by the Bureau of Meteorology and the Commonwealth Scientific and Industrial Research Organisation (CSIRO). We also acknowledge Drs. Andrew Dowdy and Kay Shelton for their comments on our manuscript.
Statistical Significance Test
Statistical significance tests for evaluating the difference between the mean values of TCs in different ENSO regimes are conducted using the two-sample permutation procedure described in Chu and Wang (1997). This procedure has a close connection with the bootstrap resampling method (e.g., Efron and Tibshirani 1991), but it is applied when two or more samples are compared simultaneously. The two samples to be compared here are combined to form a single, larger batch. The combined batch is then resampled using the Monte Carlo simulation method to form a pair of new batches, and the test statistics for each new batch are computed. In our case, we have computed mean and variance for each new pair of batches for 10 000 times, yielding 10 000 samples of means and variances. Because resampling destroys time ordering of data, it is necessary that our original data are not serially dependent. In our case, original TC data do not show any significant autocorrelation, suggesting that underlying data to be resampled are nearly independent. The U statistic is calculated for each pair of simulated sample using the formula of Chu and Wang (1997), such that
where n is the sample size, x is the mean, and var is the variance. In our case, we have altogether 10 000 samples of U statistics. From these 10 000 samples, we extracted the 95% confidence intervals of U using the percentile method. The U statistic associated with the two original data to be compared is also obtained. If the U statistic of the original data falls outside the 95% confidence intervals from the simulated samples, then the mean of the two are considered statistically different at the 5% significance level.
Current affiliation: School of Science, Information Technology and Engineering, University of Ballarat, Ballarat, Victoria, Australia.