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Savin S. Chand and Kevin J. E. Walsh

Abstract

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.

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Savin S. Chand and Kevin J. E. Walsh

Abstract

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.

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Savin S. Chand and Kevin J. E. Walsh

Abstract

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.

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Savin S. Chand and Kevin J. E. Walsh

Abstract

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.

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Savin S. Chand and Kevin J. E. Walsh

Abstract

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.

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Hamish A. Ramsay, Savin S. Chand, and Suzana J. Camargo

Abstract

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.

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Samuel S. Bell, Savin S. Chand, Suzana J. Camargo, Kevin J. Tory, Chris Turville, and Harvey Ye

Abstract

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.

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Samuel S. Bell, Savin S. Chand, Kevin J. Tory, and Christopher Turville

Abstract

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.

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Savin S. Chand, John L. McBride, Kevin J. Tory, Matthew C. Wheeler, and Kevin J. E. Walsh

Abstract

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.

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Savin S. Chand, Kevin J. E. Walsh, and Johnny C. L. Chan

Abstract

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.

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