Annual Tropical Cyclone Research Articles

Forced and Internal Variability of Tropical Cyclone Track Density in the Western North Pacific*

Abstract Forced interannual-to-decadal variability of annual tropical cyclone (TC) track density in the western North Pacific between 1979 and 2008 is studied using TC tracks from observations and simulations by a 25-km-resolution version of the GFDL High-Resolution Atmospheric Model (HiRAM) that is forced by observed sea surface temperatures (SSTs). Two modes dominate the decadal variability: a nearly basinwide mode, and a dipole mode between the subtropics and lower latitudes. The former mode links to variations in TC number and is forced by SST variations over the off-equatorial tropical central North Pacific, whereas the latter might be associated with the Atlantic multidecadal oscillation. The interannual variability is also controlled by two modes: a basinwide mode driven by SST anomalies of opposite signs located in the tropical central Pacific and eastern Indian Ocean, and a southeast–northwest dipole mode connected to the conventional eastern Pacific ENSO. The seasonal evolution of the ENSO effect on TC activity is further explored via a joint empirical orthogonal function analysis using TC track density of consecutive seasons, and the analysis reveals that two types of ENSO are at work. Internal variability in TC track density is then examined using ensemble simulations from both HiRAM and a regional atmospheric model. It exhibits prominent spatial and seasonal patterns, and it is particularly strong in the South China Sea and along the coast of East Asia. This makes an accurate prediction and projection of TC landfall extremely challenging in these regions. In contrast, basin-integrated metrics (e.g., total TC counts and TC days) are more predictable.

An ENSO-Forecast Independent Statistical Model for the Prediction of Annual Atlantic Tropical Cyclone Frequency in April

Statistical models for preseason prediction of annual Atlantic tropical cyclone (TC) and hurricane counts generally include El Niño/Southern Oscillation (ENSO) forecasts as a predictor. As a result, the predictions from such models are often contaminated by the errors in ENSO forecasts. In this study, it is found that the latent heat flux (LHF) over Eastern Tropical Pacific (ETP, defined as the region 0°–5°N, 115°–125°W) in spring is negatively correlated with the annual Atlantic TC and hurricane counts. By using stepwise backward elimination regression, it is further shown that the March value of ETP LHF is a better predictor than the spring or summer ENSO index for Atlantic TC counts. Leave-one-out cross validation indicates that the annual Atlantic TC counts predicted by this ENSO-independent statistical model show a remarkable correlation with the actual TC counts (R=0.72;Pvalue<0.01). For Atlantic hurricanes, the predictions using March ETP LHF and summer (July–September) ENSO indices show only minor differences except in moderate to strong El Niño years. Thus, March ETP LHF is an excellent predictor for seasonal Atlantic TC prediction and a viable alternative to using ENSO index for Atlantic hurricane prediction.

A dynamical‐statistical forecast model for the annual frequency of western Pacific tropical cyclones based on the NCEP Climate Forecast System version 2

A dynamical‐statistical forecast model for the annual tropical cyclones over the western North Pacific is developed based on the empirical relationship between the actual annual number of tropical cyclones (ANTCs) and the dynamical predictions of large‐scale variables by the Climate Forecast System version 2 of the National Centers for Environmental Prediction (NCEP). On interannual time scales, the ANTCs are significantly and negatively correlated with the July–October tropical North Atlantic sea surface temperature, tropical western Pacific vertical zonal wind shear (WPVZWS), and subtropical Pacific geopotential height at 500 hPa (HGT500). They are also positively correlated with the zonal wind at 850 hPa over the tropical Pacific Ocean. Skillful forecasts of the above four potential predictors are made with the 24‐member ensemble predictions by the NCEP model. The two‐predictor model with the HGT500 and the WPVZWS shows the most skillful hindcasts at 0–2 month leads assessed by the leave‐one‐out cross validation for the ANTCs over the 31 year record between 1982 and 2012. The corresponding correlation coefficients and the root‐mean‐square errors (RMSEs) between the observed and hindcast ANTCs are in the ranges from 0.73 to 0.79 and from 3.11 to 2.75, respectively. Observed ANTCs during El Niño–Southern Oscillation events are generally well captured with RMSEs ranging from 3.12 to 3.04 during El Niño years and from 3.62 to 2.44 during La Niña years. The forecast skill of the model for the past 10 years (2003–2012) is competitive with the current forecast schemes. The forecast model initialized in March, May, and June 2013 suggests an inactive season for 2013, with about 22 tropical cyclones.

Is there any long-term memory effect in the tropical cyclones?

The investigation of the intrinsic properties of the annual tropical cyclone count over Atlantic, during 1870–2006, is herewith attempted. The motivation behind this exploration is to contribute to the current understanding about the dynamics of these disastrous events, as tropical cyclones create destructive impacts for people living around tropical areas. The analytical tool used is the detrended fluctuation analysis, and the exponent obtained reveals that the time series of the annual tropical cyclone count over Atlantic obeys the classical random walk (white noise). In other words, the number of tropical cyclones seems to exhibit neither persistent nor antipersistent behavior. The reliability of the lack of scaling dependence in the time series of the annual tropical cyclone count is confirmed, by applying error bounds statistics and studying the decay of the autocorrelation function (i.e., not rejected exponential decay) and the variability of local slopes (i.e., lack of constancy in a sufficient range). In addition, the fact that the series used is fractional Gaussian noise depicts that the results obtained are reliable, despite the fact that the available data set is still limited. The indication of a nearly white noise signal in the tropical cyclone count fluctuations does not suggest that the climate change phenomenon does not exist.

Variability of tropical cyclone occurrence date in the South China Sea and its relationship with SST warming

Analyses of tropical cyclone (TC) occurrence dates in the South China Sea (SCS) for the past 60 yrs indicate a trend toward an earlier occurrence of the first annual TC in the SCS. On the other hand, a significant increasing trend in sea surface temperature (SST) in early summer (May–June) has been observed in the SCS. The negative correlation between the first annual TC occurrence date and SST in early summer during the period 1945–2009 suggests that the earlier occurrence of the first annual TC is related not only to the increasing of SST in the SCS, but also to the variability of SST in the Niño3.4 region. Quantitative analysis of the SCS TC occurrence date and SST by quantile regression also reveals such a relationship and confirms that the SCS early-season TCs tend to occur earlier when SSTs in the SCS and Niño3.4 region are increasing. Since the SCS SST anomalies are influenced by the El Niño-Southern Oscillation (ENSO), the relationship between the first annual TC occurrence date and ENSO-related large-scale atmospheric circulation including 850-hPa relative vorticity (RV), vertical wind shear (VWS), and moist static energy (MSE) in early summer are also investigated. It is found that variations of VWS and MSE have influences on first annual SCS TC occurrence dates, although there is not a statistically significant relationship between 850-hPa RV and first annual SCS TC occurrence date. These results suggest that the earlier occurrence of the first annual TC in the SCS is influenced not only by local SST, but also by ENSO through the alternation of early summer VWS and MSE in the SCS.

Variations in mean annual tropical cyclone size in the Atlantic

[1] Previous research has focused on predicting tropical cyclone (TC) size in near real time for individual storms. The purpose of this study is to develop models to explain interannual variations in mean Atlantic TC size, as measured by radius of maximum winds (RMAX) and radial extent of 34 knot winds (17 m s−1; R34), and to identify the nature of the relationship between various environmental and storm-related characteristics and TC size. Our analysis demonstrates that mean annual TC size varies systematically among the subbasins in the Atlantic and therefore it is inappropriate to develop a single model for TC size for the entire Atlantic basin. The most important variable for explaining variations in mean annual TC size is the maximum tangential wind (VMAX). VMAX is negatively related to RMAX in all subbasins and positively related to R34 in all subbasins except the Gulf of Mexico, suggesting that years with more intense TCs tend to have smaller (larger) than average RMAX (R34). Other factors, such as the relationships between sea surface temperature, sea level pressure, and Nino 3.4 suggest that environmental factors may play a secondary role in modulating mean annual TC size. Although there are some similarities with the models developed for predicting short-term changes in TC size, our results indicate that it is not appropriate to apply these models to explain variations in TC size at larger spatial scales and longer temporal scales.

Atlantic tropical cyclones in the twentieth century: natural variability and secular change in cyclone count

The twentieth century record of the annual count of Atlantic tropical cyclones (TCs) is analyzed to develop consistent estimates of its natural variability and secular change components. The analysis scheme permits development of multidecadal trends from natural variability alone, reducing aliasing of the variability and change components. The scheme is rooted in recurrent variability modes of the influential SST field and cognizant of Pacific-Atlantic links. The origin of increased cyclone counts in the early 1930s, suppressed counts in 1950–1960s, and the recent increase (since 1990s) is investigated using the count data set developed by Landsea et al. (J Clim 23: 2508–2519, 2010). We show that annual TC counts can be more closely reconstructed from Pacific and Atlantic SSTs than SST of the main development region (MDR) of Atlantic TCs; the former accounting for ~60% of the decadal count variance as opposed to ~30% for MDR SST. Atlantic Multidecadal Oscillation (AMO) dominates the reconstruction, accounting for ~55% of the natural decadal count variance, followed by the ENSO Non-Canonical and Pan-Pacific decadal variability contributions. We argue for an expansive view of the domain of influential SSTs—extending much beyond the MDR. The additional accounting of count variance by SSTs outside the MDR suggests a role for remotely-forced influences over the tropical Atlantic: the Pan-Pacific decadal mode is linked with decreased westerly wind shear (200–850 hPa) in its warm phase, much as the AMO impact itself. Non-canonical ENSO variability, in contrast, exerts little influence on decadal timescales. Interestingly, the secular but non-uniform warming of the oceans is linked with increased westerly shear, leading to off-setting dynamical and thermodynamical impacts on TC activity! The early-1930s increase in smoothed counts can be partially (~50%) reconstructed from SST natural variability. The 1950–1960s decrease, in contrast, could not be reconstructed at all, leading, deductively, to the hypothesis that it results from increased aerosols in this period. The early-1990s increase is shown to arise both from the abatement of count suppression maintained by SST natural variability and the increasing SST secular trend contribution; the abatement is related to the AMO phase-change in early-1990s. Were it not for this suppression, TC counts would have risen since the early 1970s itself, tracking the secular change contribution. The analysis suggests that when SST natural variability begins to significantly augment counts in the post-1990 period—some evidence for which is present in the preceding decade—Atlantic TC counts could increase rapidly on decadal timescales unless offset by SST-unrelated effects which apparently account for a non-trivial amount (~40%) of the decadal count variance.

Annual Volume and Area Variations in Tropical Cyclone Rainfall over the Eastern United States

Abstract This paper examines tropical cyclone (TC) rainfall in the eastern United States from the perspective of documenting accumulated annual water volumes and areas of the precipitation. Volume is a value that merges both rainfall depth and rainfall area into a single metric for each year that can be directly compared between individual years. Area represents the total land area affected by tropical rains. These TC rainfall metrics were then compared to the ENSO and the Atlantic multidecadal oscillation (AMO). Time series of annual TC water volumes show an annual average of 107 km3. The maximum volume was produced in 1985 with 405.8 km3, driven by Hurricanes Bob, Claudette, Danny, Elena, Gloria, Henri, Juan, and Kate as well as by Tropical Storms Henri and Isabel. The lowest TC volume occurred in 1978 with 8.9 km3. ENSO phases did not show any statistical correlation with TC frequency in the eastern United States. However, AMO showed a significant correlation with volume and the number of storms affecting the region. TC rainfall volume and area in the eastern United States showed a strong correlation. However, there are exceptions, whereby 1985 stands out as an exceptional volume year though the area affected is not as impressive. In contrast, 1979 is an example when TCs covered a large area with a corresponding small rainfall volume, in part because of the rapid forward movement of the storms, for example, Hurricanes David and Frederic. Since 1995, TCs have become more numerous, producing larger volumes and affecting larger areas.

Interannual and interdecadal variations of tropical cyclone activity in the South China Sea

AbstractThis study attempts to identify the factors affecting annual tropical cyclone (TC) activity in the South China Sea (SCS) using data during the period 1965–2005. The results indicate that the total number of TCs and number of TCs entering the SCS from the Western North Pacific are below normal in El Niño events but above normal during La Niña events. However, for TCs formed inside the SCS, the difference in numbers between the two phases of the El Niño‐Southern Oscillation (ENSO) is not as obvious. In addition, the positive phase of the Pacific Decadal Oscillation (PDO) generally favours less TCs in all categories, while the negative PDO phase favours more. These results may be explained by the fact that the ENSO and the PDO affect TC behaviour through altering the conditions in the WNP to be favourable or unfavourable for TC genesis and movement into the SCS. Copyright © 2009 Royal Meteorological Society

Foreignness as a constraint on learning: The impact of migrants on disaster resilience in small islands

Knowledge about natural hazard management has increased significantly since Gilbert White's seminal research in 1945, yet people are still badly affected by natural hazards. A key question remains in natural hazards research: why, when all the conditions for effective disaster risk reduction are in place, do some people not take action to reduce their risk of harm? Through a questionnaire-based study we investigated the motivating factors that led residents of the Cayman Islands to prepare for annual tropical cyclones (hurricanes). Factors that increase the likelihood of individuals preparing for hurricanes are: previous experience of major storms, having linking networks and ties, having a child under the age of 15 in the home, and residency status—expatriate residents are less likely to prepare. Factors that appear to prevent adaptive behaviour include: living close to or adjacent to the coast, recent migration to the islands, and living in rented accommodation. The findings of the survey confirm that even within societies that are well prepared for tropical cyclones, there are still sub-groups who do not engage with the preparedness process. In the case of the Cayman Islands, new migrants are the most vulnerable to tropical cyclones as they tend to fall into the demographic groups least likely to prepare for cyclones, live in locations with high levels of exposure to cyclone impacts, and interact mostly with other expatriates with no previous experience of cyclone impacts. As climate change promises to bring an increasing intensity of tropical cyclones, these findings have relevance for all islands which draw on migrant workers to support economic growth.

On the incompleteness of the historical record of North Atlantic tropical cyclones

There is some question as to whether the historical record of observed North Atlantic tropical cyclones prior to the advent of satellite coverage is complete. This question is central to understanding the historical trend in tropical cyclone activity and the effect of environmental factors on it. To address this question, a statistical model of the relationship between annual cyclone counts between 1870 and 2004 and sea surface temperature and the state of the Southern Oscillation is extended to allow for non‐decreasing observation probability prior to 1966. The estimated observation probabilities increase from 0.72 in 1870 to 1 in 1964. Allowing for record incompleteness reduces the estimated effect of sea surface temperature on annual tropical cyclone activity.

The influence of climate state variables on Atlantic Tropical Cyclone occurrence rates

We analyzed annual North Atlantic tropical cyclone (TC) counts from 1871‐2004, considering three climate state variables—the El Niño/Southern Oscillation (ENSO), peak (August‐October or ‘ASO’) Sea Surface Temperatures (SST) over the main development region (‘MDR’: 6‐18°N, 20‐60°W), and the North Atlantic Oscillation (NAO)—thought to influence variations in annual TC counts on interannual and longer timescales. The unconditional distribution of TC counts is observed to be inconsistent with the null hypothesis of a fixed rate random (Poisson) process. However, using two different methods, we find that conditioning TC counts on just two climate state variables, ENSO and MDR SST, can account for much or all of the apparent non‐random variations over time in TC counts. Based on statistical models of annual Atlantic TC counts developed in this study and current forecasts of climate state variables, we predicted m = 15 ± 4 total named storms for the 2007 season.

Interannual and interdecadal variations of tropical cyclone activity over the western North Pacific

This paper reviews the interannual and interdecadal variations in tropical cyclone (TC) activity over the western North Pacific (WNP) and the possible physical mechanisms responsible for such variations. Interannual variations can largely be explained by changes in the planetary-scale flow patterns. Sea-surface temperatures (SSTs) in the WNP, however, do not contribute to such variations. Rather, SSTs in the central and eastern equatorial Pacific are significantly correlated with TC activity over the WNP. Causality can be established: changes in the SST in the equatorial Pacific are related to the El Nino/Southern Oscillation (ENSO) phenomenon, and modifications of the planetary-scale flow associated with ENSO alter the conditions over the WNP and hence TC activity there. Variations in annual TC activity are also associated with different phases of the stratospheric quasi-biennial oscillations due to its modification of the vertical wind shear of the environment in which TCs form. Interdecadal variations in TC activity are apparently related to the location, strength and extent of the North Pacific subtropical high. However, the mechanisms responsible for modifying these characteristics of the subtropical high have yet to be identified.

Bayesian Change-Point Analysis of Tropical Cyclone Activity: The Central North Pacific Case*

Abstract Bayesian analysis is applied to detect change points in the time series of annual tropical cyclone counts over the central North Pacific. Specifically, a hierarchical Bayesian approach involving three layers—data, parameter, and hypothesis—is formulated to demonstrate the posterior probability of the shifts throughout the time from 1966 to 2002. For the data layer, a Poisson process with gamma distributed intensity is presumed. For the hypothesis layer, a “no change in the intensity” hypothesis and a “single change in the intensity” hypothesis are considered. Results indicate that there is a great likelihood of a change point on tropical cyclone rates around 1982, which is consistent with earlier work based on a simple log-linear regression model. A Bayesian approach also provides a means for predicting decadal tropical cyclone variations. A higher number of tropical cyclones is predicted in the next decade when the possibility of the change point in the early 1980s is taken into account.

Interannual and decadal variability of landfalling tropical cyclones in the southeast coastal states of the united states

The interannual variability of the Atlantic tropical cyclone (TC) frequency is well known. Separately, recent studies have also suggested that a much longer, multidecadal (40-60 year) trend might be emerging from the recent increase in Atlantic TC activity. However, the overall structure of the intrinsic frequencies (or temporal modes) of Atlantic TC activity is not yet known. The focus of this study is to systematically analyze the intrinsic frequencies of Atlantic TC activity using hurricane and tropical storm landfall data collected along the southeast coast (SEC) of the United States. Based on an Empirical Mode Decomposition (EMD) analysis of the frequency of landfall TCs along the SEC from 1887–1999, we have found that Atlantic TC activity has four primary, temporal modes. The interannual and multidecadal modes reported in the published literature are two such modes. After identifying all primary modes, the relative importance of each mode and its physical cause can be analyzed. For example, the most energetic mode is the interannual mode (2–7 year period). This mode is known to be associated with the 2–7 year El Nino / La Ni na cycle. The average number of annual landfalling TCs along the SEC decreased by 24% during El Nino years, but did not show significant increase during weak and moderate La Nina years. However, intense La Nina years were generally associated with more than average landfalling TCs along the SEC. The effects of El Nino and La Nina also became more significant when only hurricanes were considered. The significance of the effects of El Nino and La Nina on landfalling TCs and hurricanes in different US southeast coastal states showed significant differences.

Prediction of annual tropical cyclone activity over the western North Pacific and the South China Sea

AbstractThis study investigates the relationship between the spatial distribution of sea‐surface temperature (SST) and the annual tropical cyclone (TC) activity over the western North Pacific and the South China Sea. Monthly distributions of SST are represented by a set of empirical orthogonal functions (EOFs). The principal components (PCs) of the monthly SST associated with these EOFs are then correlated statistically with the annual number of TCs occurring over (i) the western North Pacific and (ii) the South China Sea using a forward stepwise linear multiple regression scheme.It is found that four PCs of the monthly SST distribution together explain 89 per cent of the total variance of the annual number of TCs over the western North Pacific. Predictions of this number from both the dependent and independent (simulated using the jack‐knife method) samples have errors of less than half a standard deviation of the actual number. Two of these PCs are from the September SST, whereas the other two are from May and June SSTs. If only the latter two PCs are used, the accuracies of the prediction are slightly reduced. Therefore, a preliminary prediction can be made using these two PCs and a modified prediction can be performed at the end of September.Two PCs are found to correlate significantly with annual TC activity over the South China Sea, representing the SST distribution in May and July. Predictions using these two PCs also give very reasonable results for both the dependent and independent samples.

The distribution of annual tropical cyclone frequency

In preparation for studying and fitting tropical cyclone frequency distributions certain time trends in the climatological series are tested statistically and explanations of their possible cause proposed. The annual frequency of tropical cyclones and hurricanes is hypothesized to be a rare-event type of series. On the basis of physical and statistical principles it is shown how the Poisson and negative binomial distributions are adapted to fitting the climatological series under prescribed physical conditions. These distributions are shown to provide good statistical fits and therefore good estimates of probabilities of annual cyclone frequency. Where necessary, the effects of trend are removed and corresponding adjustments made in the distribution parameters.