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Southwest Pacific nations are among some of the worst impacted and most vulnerable globally in terms of tropical cyclone (TC)-induced flooding and accompanying risks. This study objectively quantifies the fractional contribution of TCs to extreme rainfall (hereafter, TC contributions) in the context of climate variability and change. We show that TC contributions to extreme rainfall are substantially enhanced during active phases of the Madden–Julian Oscillation and by El Niño conditions (particularly over the eastern southwest Pacific region); this enhancement is primarily attributed to increased TC activity during these event periods. There are also indications of increasing intensities of TC-induced extreme rainfall events over the past few decades. A key part of this work involves development of sophisticated Bayesian regression models for individual island nations in order to better understand the synergistic relationships between TC-induced extreme rainfall and combinations of various climatic drivers that modulate the relationship. Such models are found to be very useful for not only assessing probabilities of TC- and non-TC induced extreme rainfall events but also evaluating probabilities of extreme rainfall for cases with different underlying climatic conditions. For example, TC-induced extreme rainfall probability over Samoa can vary from ~ 95 to ~ 75% during a La Niña period, if it coincides with an active or inactive phase of the MJO, and can be reduced to ~ 30% during a combination of El Niño period and inactive phase of the MJO. Several other such cases have been assessed for different island nations, providing information that have potentially important implications for planning and preparing for TC risks in vulnerable Pacific Island nations.

Simulations and projections of the El Nino Southern Oscillation’s (ENSO’s) influence on TC track variability was analysed globally using Coupled Model Intercomparison project Phase 5 (CMIP5) models. The ability of these models to simulate the historical (1970–2000) ENSO–TC track relationship and inform us of the likely projected changes resulting from high carbon emissions (RCP8.5) in a climate projection (2070–2100) was determined through cluster analysis. The number of seasonal TC occurrences during traditional ENSO events (“El Nino” and “La Nina”) in each cluster were used to determine whether each cluster was “El Nino dominant”, “La Nina dominant” or “neither”. Only seven out of a combined total of 28 clusters across all basins were found to disagree in terms of “ENSO dominance” between the observed records and historical model simulations. This suggests that models can simulate the ENSO and TC track relationship reasonably well. Under sustained high carbon emissions, La Nina TCs were projected to become dominant over El Nino TCs in the central South Indian Ocean (~ 60–100°E), the southern Bay of Bengal and over straight-moving TCs in the South China Sea. El Nino TCs were projected to increase and become dominant over La Nina TCs in a larger area of the western South Pacific (~ 160°E–165°W) and central North Pacific (~ 160°E–145°W) Oceans. Projections of track directions and lifetimes, while less robust, indicated that El Nino TCs would track westward more often in the Coral Sea (150–165°E), while El Nino TCs that took an eastward track here would have longer lifetimes (~ 3 days).

The sensitivity of tropical cyclone (TC) projection results to different models and the detection and tracking scheme used is well established in the literature. Here, future climate projections of TC activity in the Eastern North Pacific basin (ENP, defined from 0° to 40°N and 180° to ~ 75°W) are assessed with a model- and basin-independent detection and tracking scheme that was trained in reanalysis data. The scheme is applied to models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) experiments forced under the historical and Representative Concentration Pathway 8.5 (RCP8.5) conditions. TC tracks from the observed records and models are analysed simultaneously with a curve-clustering algorithm, allowing observed and model tracks to be projected onto the same set of clusters. The ENP is divided into three clusters, one in the Central North Pacific (CNP) and two off the Mexican coast, as in prior studies. After accounting for model biases and auto-correlation, projection results under RCP8.5 indicated TC genesis to be significantly suppressed east of 125°W, and significantly enhanced west of 145°W by the end of the twenty-first century. Regional TC track exposure was found to significantly increase around Hawaii (~ 86%), as shown in earlier studies, owing to increased TC genesis, particularly to the south-east of the island nation. TC exposure to Southern Mexico was shown to decrease (~ 4%), owing to a south-westward displacement of TCs and overall suppression of genesis near the Mexican coastline. The large-scale environmental conditions most consistent with these projected changes were vertical wind shear and relative humidity.

Reliable projections of future changes in tropical cyclone (TC) characteristics are highly dependent on the ability of global climate models (GCMs) to simulate the observed characteristics of TCs (i.e., their frequency, genesis locations, movement, and intensity). Here, we investigate the performance of a suite of GCMs from the U.S. CLIVAR Working Group on Hurricanes in simulating observed climatological features of TCs in the Southern Hemisphere. A subset of these GCMs is also explored under three idealized warming scenarios. Two types of simulated TC tracks are evaluated on the basis of a commonly applied cluster analysis: 1) explicitly simulated tracks, and 2) downscaled tracks, derived from a statistical–dynamical technique that depends on the models’ large-scale environmental fields. Climatological TC properties such as genesis locations, annual frequency, lifetime maximum intensity (LMI), and seasonality are evaluated for both track types. Future changes to annual frequency, LMI, and the latitude of LMI are evaluated using the downscaled tracks where large sample sizes allow for statistically robust results. An ensemble approach is used to assess future changes of explicit tracks owing to their small number of realizations. We show that the downscaled tracks generally outperform the explicit tracks in relation to many of the climatological features of Southern Hemisphere TCs, despite a few notable biases. Future changes to the frequency and intensity of TCs in the downscaled simulations are found to be highly dependent on the warming scenario and model, with the most robust result being an increase in the LMI under a uniform 2°C surface warming.

The Okubo–Weiss–Zeta (OWZ) tropical cyclone (TC) detection scheme, which has been used to detect TCs in climate, seasonal prediction, and weather forecast models, is assessed on its ability to produce a realistic TC track climatology in the ERA-Interim product over the 25-yr period 1989 to 2013. The analysis focuses on TCs that achieve gale-force (17 m s−1) sustained winds. Objective criteria were established to define TC tracks once they reach gale force for both observed and detected TCs. A lack of consistency between storm tracks preceding this level of intensity led these track segments to be removed from the analysis. A subtropical jet (STJ) diagnostic is used to terminate transitioning TCs and is found to be preferable to a fixed latitude cutoff point. TC tracks were analyzed across seven TC basins, using a probabilistic clustering technique that is based on regression mixture models. The technique grouped TC tracks together based on their geographical location and shape of trajectory in five separate “cluster regions” around the globe. A mean trajectory was then regressed for each cluster that showed good agreement between the detected and observed tracks. Other track measures such as interannual TC days and translational speeds were also replicated to a satisfactory level, with TC days showing limited sensitivity to different latitude cutoff points. Successful validation in reanalysis data allows this model- and grid-resolution-independent TC tracking scheme to be applied to climate models with confidence in its ability to identify TC tracks in coarse-resolution climate models.

Impacts of tropical cyclones in the South Pacific Island countries are of great significance. Now with the growing threats from human-induced climate change, the need for effective disaster risk management and adaptation strategies for these island countries is more important than before. In order to implement appropriate strategies, a comprehensive understanding of South Pacific tropical cyclone activity—and how it is likely to change as a result of human-induced climate change—is essential. While a number of past studies have examined various aspects of tropical cyclone activity in the South Pacific basin, a review that consolidates those studies with new information is essential. In this chapter, we first examine tropical cyclone data quality for the South Pacific basin and then review the robustness of the relationship between South Pacific tropical cyclones and drivers of natural climate variability. Note that an understanding of the limitations of the data quality is important to determine the extent of natural climate variability and signatures—if any—of human-induced climate change on tropical cyclones. We then examine the influence of climate change on tropical cyclones using up-to-date historical observations and climate model projections.

Tropical cyclones (TCs) can have severe impacts on Australia. These include extreme rainfall and winds, and coastal hazards such as destructive waves, storm surges, estuarine flooding, and coastal erosion. Various aspects of TCs in the Australian region have been documented over the past several decades. In recent years, increasing emphasis has been placed on human-induced climate change effects on TCs in the Australian region and elsewhere around the globe. However, large natural variability and the lack of consistent long-term TC observations have often complicated the detection and attribution of TC trends. Efforts have been made to improve TC records for Australia over the past decades, but it is still unclear whether such records are sufficient to provide better understanding of the impacts of natural climate variability and climate change. It is important to note that the damage costs associated with tropical cyclones in Australia have increased in recent decades and will continue to increase due to growing coastal settlement and infrastructure development. Therefore, it is critical that any coastal infrastructure planning and engineering decisions, as well as disaster management decisions, strongly consider future risks from tropical cyclones. A better understanding of tropical cyclones in a changing climate will provide key insights that can help mitigate impacts of tropical cyclones on vulnerable communities. An objective assessment of the Australian TCs at regional scale and its link with climate variability and change using improved and up-to-date data records is more imperative now than before.

The El Nino/Southern Oscillation influences tropical cyclone variability. Under climate change, cyclones around Pacific island nations are projected to increase in frequency during El Nino events and decrease during La Nina events. The El Nino/Southern Oscillation (ENSO) drives substantial variability in tropical cyclone (TC) activity around the world1,2,3. However, it remains uncertain how the projected future changes in ENSO under greenhouse warming4,5,6,7,8 will affect TC activity, apart from an expectation that the overall frequency of TCs is likely to decrease for most ocean basins9,10,11. Here we show robust changes in ENSO-driven variability in TC occurrence by the late twenty-first century. In particular, we show that TCs become more frequent (∼20–40%) during future-climate El Nino events compared with present-climate El Nino events—and less frequent during future-climate La Nina events—around a group of small island nations (for example, Fiji, Vanuatu, Marshall Islands and Hawaii) in the Pacific. We examine TCs across 20 models from the Coupled Model Intercomparison Project phase 5 database12, forced under historical and greenhouse warming conditions. The 12 most realistic models identified show a strong consensus on El Nino-driven changes in future-climate large-scale environmental conditions that modulate development of TCs over the off-equatorial western Pacific and the central North Pacific regions. These results have important implications for climate change and adaptation pathways for the vulnerable Pacific island nations.

Past studies have shown that tropical cyclone (TC) projection results can be sensitive to different types of TC tracking schemes, and that the relative adjustments of detection criteria to accommodate different models may not necessarily provide a consistent platform for comparison of projection results. Here, future climate projections of TC activity in the western North Pacific basin (WNP, defined from 0°–50°N and 100°E–180°) are assessed with a model-independent detection and tracking scheme. This scheme is applied to models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) forced under the historical and representative concentration pathway 8.5 (RCP8.5) conditions. TC tracks from the observed records and independent models are analyzed simultaneously with a curve-clustering algorithm, allowing observed and model tracks to be projected onto the same set of clusters (k = 9). Four of the nine clusters were projected to undergo significant changes in TC frequency. Straight-moving TCs in the South China Sea were projected to significantly decrease. Projected increases in TC frequency were found poleward of 20°N and east of 160°E, consistent with changes in ascending motion, as well as vertical wind shear and relative humidity respectively. Projections of TC track exposure indicated significant reductions for southern China and the Philippines and significant increases for the Korean peninsula and Japan, although very few model TCs reached the latter subtropical regions in comparison to the observations. The use of a fundamentally different detection methodology that overcomes the detector/tracker bias gives increased certainty to projections as best as low-resolution simulations can offer.

The relationships between tropical cyclones in the South Pacific Ocean basin and the two major modes of natural climate variability (i.e., El Nino–Southern Oscillation and the Madden–Julian Oscillation) are reviewed. Main focus is on how tropical cyclone genesis location, frequency, track, and intensity are influenced by these modes of natural variability. The impact of climate change on tropical cyclone characteristic in the South Pacific is also reviewed with particular emphasis on climate model projections.

Changes in tropical cyclone (TC) frequency under anthropogenic climate change are examined for 13 global models from phase 5 of the Coupled Model Intercomparison Project (CMIP5), using the Okubo–Weiss–Zeta parameter (OWZP) TC-detection method developed by the authors in earlier papers. The method detects large-scale conditions within which TCs form. It was developed and tuned in atmospheric reanalysis data and then applied without change to the climate models to ensure model and detector independence. Changes in TC frequency are determined by comparing TC detections in the CMIP5 historical runs (1970–2000) with high emission scenario (representative concentration pathway 8.5) future runs (2070–2100). A number of the models project increases in frequency of higher-latitude tropical cyclones in the late twenty-first century. Inspection reveals that these high-latitude systems were subtropical in origin and are thus eliminated from the analysis using an objective classification technique. TC detections in 8 of the 13 models reproduce observed TC formation numbers and geographic distributions reasonably well, with annual numbers within ±50% of observations. TC detections in the remaining five models are particularly low in number (10%–28% of observed). The eight models with a reasonable TC climatology all project decreases in global TC frequency varying between 7% and 28%. Large intermodel and interbasin variations in magnitude and sign are present, with the greatest variations in the Northern Hemisphere basins. These results are consistent with results from earlier-generation climate models and thus confirm the robustness of coupled model projections of globally reduced TC frequency.

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.

A novel approach to tropical cyclone (TC) detection in coarse-resolution numerical model data is introduced and assessed. This approach differs from traditional detectors in two main ways. First, it was developed and tuned using 20 yr of ECMWF Interim Re-Analysis (ERA-Interim) data, rather than using climate model data. This ensures that the detector is independent of any climate models to which it will later be applied. Second, only relatively large-scale parameters resolvable in climate models are included, in order to minimize any grid-resolution dependence on parameter thresholds. This approach is taken in an attempt to construct a unified TC detection procedure applicable to all climate models without the need for any further tuning or adjustment. Unlike traditional detectors that seek to identify TCs directly, the authors' method seeks to identify conditions favorable for TC formation. Favorable TC formation regions at the center of closed circulations in the lower troposphere to the midtroposphere are identified using a low-deformation vorticity parameter. Additional relative and specific humidity thresholds are applied to ensure the thermodynamic environment is favorable, and a vertical wind shear threshold is applied to eliminate storms in a destructive shear environment. A further requirement is that thresholds for all parameters must be satisfied for at least 48 h before a TC is deemed to have developed. A thorough assessment of the detector performance is provided. It is demonstrated that the method reproduces realistic TC genesis frequency and spatial distributions in the ERA-Interim data. Application of the detector to four climate models is presented in a companion paper.

The influence of different types of ENSO on tropical cyclone (TC) interannual variability in the central southwest Pacific region (5°–25°S, 170°E–170°W) is investigated. Using empirical orthogonal function analysis and an agglomerative hierarchical clustering of early tropical cyclone season Pacific sea surface temperature, years are classified into four separate regimes (i.e., canonical El Niño, canonical La Niña, positive-neutral, and negative-neutral) for the period between 1970 and 2009. These regimes are found to have a large impact on TC genesis over the central southwest Pacific region. Both the canonical El Niño and the positive-neutral years have increased numbers of cyclones, with an average of 4.3 yr−1 for positive-neutral and 4 yr−1 for canonical El Niño. In contrast, during a La Niña and negative-neutral events, substantially fewer TCs (averages of ~2.2 and 2.4 yr−1, respectively) are observed in the central southwest Pacific. The enhancement of TC numbers in both canonical El Niño and positive-neutral years is associated with the extension of favorable low-level cyclonic relative vorticity, and low vertical wind shear eastward across the date line. Relative humidity and SST are also very conducive for genesis in this region during canonical El Niño and positive-neutral events. The patterns are quite different, however, with the favorable conditions concentrated in the date line region for the positive-neutral, as compared with conditions farther eastward for the canonical El Niño regime. A significant result of the study is the demonstration that ENSO-neutral events can be objectively clustered into two separate regimes, each with very different impacts on TC genesis.

This study presents a binary classification model for the prediction of tropical cyclone (TC) activity in the Fiji, Samoa, and Tonga regions (the FST region) using the accumulated cyclone energy (ACE) as a proxy of TC activity. A probit regression model, which is a suitable probability model for describing binary response data, is developed to determine at least a few months in advance (by July in this case) the probability that an upcoming TC season may have for high or low TC activity. Years of “high TC activity” are defined as those years when ACE values exceeded the sample climatology (i.e., the 1985–2008 mean value). Model parameters are determined using the Bayesian method. Various combinations of the El Niño–Southern Oscillation (ENSO) indices and large-scale environmental conditions that are known to affect TCs in the FST region are examined as potential predictors. It was found that a set of predictors comprising low-level relative vorticity, upper-level divergence, and midtropspheric relative humidity provided the best skill in terms of minimum hindcast error. Results based on hindcast verification clearly suggest that the model predicts TC activity in the FST region with substantial skill up to the May–July preseason for all years considered in the analysis, in particular for ENSO-neutral years when TC activity is known to show large variations.

This study examines the variation in tropical cyclone (TC) intensity for different phases of the El Niño–Southern Oscillation (ENSO) phenomenon in the Fiji, Samoa, and Tonga (FST) region. The variation in TC intensity is inferred from the accumulated cyclone energy (ACE), which is constructed from the 6-hourly Joint Typhoon Warning Center best-track data for the period 1985–2006. Overall, results suggest that ACE in the FST region is considerably influenced by the ENSO signal. A substantial contribution to this ENSO signal in ACE comes from the region equatorward of 15°S where TC numbers, lifetime, and intensity all play a significant role. However, the ACE–ENSO relationship weakens substantially poleward of 15°S where large-scale environmental variables affecting TC intensity are found to be less favorable during El Niño years than during La Niña years; in the region equatorward of 15°S, the reverse is true. Therefore, TCs entering this region poleward of 15°S are able to sustain their intensity for a longer period of time during La Niña years as opposed to TCs entering the region during El Niño years, when they decay more rapidly.

An objective methodology for forecasting the probability of tropical cyclone (TC) formation in the Fiji, Samoa, and Tonga regions (collectively the FST region) using antecedent large-scale environmental conditions is investigated. Three separate probabilistic forecast schemes are developed using a probit regression approach where model parameters are determined via Bayesian fitting. These schemes provide forecasts of TC formation from an existing system (i) within the next 24 h (W24h), (ii) within the next 48 h (W48h), and (iii) within the next 72 h (W72h). To assess the performance of the three forecast schemes in practice, verification methods such as the posterior expected error, Brier skill scores, and relative operating characteristic skill scores are applied. Results suggest that the W24h scheme, which is formulated using large-scale environmental parameters, on average, performs better than that formulated using climatology and persistence (CLIPER) variables. In contrast, the W48h (W72h) scheme formulated using large-scale environmental parameters performs similar to (poorer than) that formulated using CLIPER variables. Therefore, large-scale environmental parameters (CLIPER variables) are preferred as predictors when forecasting TC formation in the FST region within 24 h (at least 48 h) using models formulated in the present investigation.

This study presents seasonal prediction schemes for tropical cyclones (TCs) affecting the Fiji, Samoa, and Tonga (FST) region. Two separate Bayesian regression models are developed: (i) for cyclones forming within the FST region (FORM) and (ii) for cyclones entering the FST region (ENT). Predictors examined include various El Niño–Southern Oscillation (ENSO) indices and large-scale environmental parameters. Only those predictors that showed significant correlations with FORM and ENT are retained. Significant preseason correlations are found as early as May–July (approximately three months in advance). Therefore, May–July predictors are used to make initial predictions, and updated predictions are issued later using October–December early-cyclone-season predictors. A number of predictor combinations are evaluated through a cross-validation technique. Results suggest that a model based on relative vorticity and the Niño-4 index is optimal to predict the annual number of TCs associated with FORM, as it has the smallest RMSE associated with its hindcasts (RMSE = 1.63). Similarly, the all-parameter-combined model, which includes the Niño-4 index and some large-scale environmental fields over the East China Sea, appears appropriate to predict the annual number of TCs associated with ENT (RMSE = 0.98). While the all-parameter-combined ENT model appears to have good skill over all years, the May–July prediction of the annual number of TCs associated with FORM has two limitations. First, it underestimates (overestimates) the formation for years where the onset of El Niño (La Niña) events is after the May–July preseason or where a previous La Niña (El Niño) event continued through May–July during its decay phase. Second, its performance in neutral conditions is quite variable. Overall, no significant skill can be achieved for neutral conditions even after an October–December update. This is contrary to the performance during El Niño or La Niña events, where model performance is improved substantially after an October–December early-cyclone-season update.

This study examines the modulation of tropical cyclone (TC) activity by the Madden–Julian oscillation (MJO) in the Fiji, Samoa, and Tonga regions (FST region), using Joint Typhoon Warning Center best-track cyclone data and the MJO index developed by Wheeler and Hendon. Results suggest strong MJO–TC relationships in the FST region. The TC genesis patterns are significantly altered over the FST region with approximately 5 times more cyclones forming in the active phase than in the inactive phase of the MJO. This modulation is further strengthened during El Niño periods. The large-scale environmental conditions (i.e., low-level relative vorticity, upper-level divergence, and vertical wind shear) associated with TC genesis show a distinct patterns of variability for the active and inactive MJO phases. The MJO also has a significant effect on hurricane category and combined gale and storm category cyclones in the FST region. The occurrences of both these cyclone categories are increased in the active phase of the MJO, which is associated with enhanced convective activity. The TCs in the other MJO phases where convective activity is relatively low, however, show a consistent pattern of increase in hurricane category cyclones and a concomitant decrease in gale and storm category cyclones. Finally, TC tracks in different MJO phases are also objectively described using a cluster analysis technique. Patterns seen in the clustered track regimes are well explained here in terms of 700–500-hPa mean steering flow.

This study examines the variations in tropical cyclone (TC) genesis positions and their subsequent tracks for different phases of the El Niño–Southern Oscillation (ENSO) phenomenon in the Fiji, Samoa, and Tonga region (FST region) using Joint Typhoon Warning Center best-track data. Over the 36-yr period from 1970/71 to 2005/06, 122 cyclones are observed in the FST region. A large spread in the genesis positions is noted. During El Niño years, genesis is enhanced east of the date line, extending from north of Fiji to over Samoa, with the highest density centered around 10°S, 180°. During neutral years, maximum genesis occurs immediately north of Fiji with enhanced genesis south of Samoa. In La Niña years, there are fewer cyclones forming in the region than during El Niño and neutral years. During La Niña years, the genesis positions are displaced poleward of 12°S, with maximum density centered around 15°S, 170°E and south of Fiji. The cyclone tracks over the FST region are also investigated using cluster analysis. Tracks during the period 1970/71–2005/06 are conveniently described using three separate clusters, with distinct characteristics associated with different ENSO phases. Finally, the role of large-scale environmental factors affecting interannual variability of TC genesis positions and their subsequent tracks in the FST region are investigated. Favorable genesis positions are observed where large-scale environments have the following seasonal average thresholds: (i) 850-hPa cyclonic relative vorticity between −16 and −4 (×10−6 s−1), (ii) 200-hPa divergence between 2 and 8 (×10−6 s−1), and (iii) environmental vertical wind shear between 0 and 8 m s−1. The subsequent TC tracks are observed to be steered by mean 700–500-hPa winds.

Studies of tropical cyclone (TC) formation from tropical waves have shown that TC formation requires a wave-relative quasi-closed circulation: the "marsupial pouch" concept. This results in a layerwise nearly contained region of atmosphere in which the modification of moisture, temperature and vorticity profiles by convective and boundary layer processes occurs undisturbed. The pouch concept is further developed in this paper. TCs develop near the centre of the pouch where the flow is in near solid body rotation. A reference-frame independent parameter is introduced that effectively measures the level of solid-body rotation in the lower troposphere. The parameter is the product of a normalized Okubo-Weiss parameter and absolute vorticity (OWZ). Using 20 yr of ERA-interim reanalysis data and the IBTrACS global TC database, it is shown 95% of TCs including, but not limited to, those forming in tropical waves are associated with enhanced levels of OWZ on both the 850 and 500 hPa pressure levels at the time of TC declaration, while 90% show enhanced OWZ for at least 24 h prior to declaration. This result prompts the question of whether the pouch concept extends beyond wave-type formation to all TC formations world-wide. Combining the OWZ with a low vertical shear requirement and lower troposphere relative humidity thresholds, an imminent genesis parameter is defined. The parameter includes only relatively large-scale fluid properties that are resolved by coarse grid model data (>150 km), which means it can be used as a TC detector for climate model applications. It is also useful as a cyclogenesis diagnostic in higher resolution models such as real-time global forecast models.