Seasonal Influences upon and Long-Term Trends in the Length of the Atlantic Hurricane Season

Juliana M. Karloski and Clark Evans⁺

Atmospheric Science Program, Department of Mathematical Sciences

University of Wisconsin-Milwaukee, Milwaukee, Wisconsin

Submitted to the Journal of Climate for consideration as an Article

1 May 2015

Revised 4 August 2015

Abstract

Considering a subset of the North Atlantic Ocean south of 30°N and east of 75°W, Kossin (2008) found that the Atlantic tropical cyclone (TC) season increased in length by about two days per year between 1980 and 2007, albeit only to 80-90% confidence. It is uncertain, however, whether the same is true over the entire Atlantic basin or into the present. Separately, it is unclear as to whether meaningful sub-seasonal variability in the environmental factors necessary for TC formation exists between early- and late-starting and -ending seasons.

Quantile regression is used to evaluate long-term trends in Atlantic TC season length. No statistically-significant trend in season length exists for the period 1979-2007 when considering the entire Atlantic basin, or for the period 1979-2014 independent of the portion of the basin considered. Linear regression applied to June and November monthly-mean reanalysis data is used to examine sub-seasonal environmental variability between early- and late-starting and -ending seasons. Within an otherwise favorable environment for genesis, early-starting seasons are associated with increased lower tropospheric relative vorticity where most early-season TCs form. Late-ending seasons are associated with La Niña, negative-phase Pacific Decadal Oscillation events, and environmental conditions that promote an increased likelihood of TC development along the preferred genesis pathways for late-season TCs.

While confidence in these results is relatively high, they only explain a small portion of the total variation in Atlantic TC season length. More research is needed to understand how variability on all timescales influences Atlantic TC season length and its predictability.

Every year, multiple meteorological organizations, such as NOAA; research groups, such as that at Colorado State University (http://hurricane.atmos.colostate.edu/Forecasts/); and private firms release predictions of the number of tropical storms, hurricanes, and major hurricanes they expect to form that year, particularly within the North Atlantic basin. Other attributes of tropical cyclone (TC) activity, however, such as when the first TC will form or how long the season will last, are typically not forecast. Officially, the Atlantic TC season begins on 1 June and ends on 30 November. Over 97% of TC activity within the Atlantic basin occurs between these two dates (HRD 2015). However, as assessed utilizing the National Hurricane Center HURDAT2 database (Landsea and Franklin 2013), the average first TC formation for the period 1979-2014 occurred on 30 June and the average last TC formation occurred on 4 November. The question thus remains: what causes some seasons to be significantly shorter or longer than average?

It is worthwhile to consider whether there could be a relationship between the period over which the conditions necessary for TC development are present at one or more locations and the length of the TC season. Gray (1968, 1979) identified six necessary but not sufficient criteria for TC development: sea surface temperatures (SSTs) greater than or equal to 26.5°C, abundant lower- to mid-tropospheric relative humidity, conditional instability through a deep tropospheric layer, large lower tropospheric cyclonic relative vorticity, low vertical wind shear of the horizontal winds (roughly less than 10 m s^-1 between the surface and tropopause), and displacement by at least 5° latitude poleward from the equator. These six conditions may be condensed (e.g., as done by Frank 1987 and others) into four: sufficiently large cyclonic vertical vorticity, weak vertical wind shear of the horizontal winds, SSTs greater than or equal to 26°C, and abundant lower- to middle-tropospheric relative humidity. The SST criterion may alternatively be expressed in terms of upper oceanic heat content and/or potential intensity, the latter of which is influenced by both SST and outflow-layer temperatures (e.g., Emanuel 1986). Likewise, the relative humidity and vertical wind shear criteria may alternatively be represented by ventilation, which reflects the extent to which environmental, middle-tropospheric low entropy air may be imported into the circulation of a TC or predecessor disturbance (e.g., Tang and Emanuel 2012, Tang and Camargo 2014).

Subsequent investigators (e.g., Bruyere et al. 2012, Camargo et al. 2007, Emanuel 2010, Emanuel and Nolan 2004, McGauley and Nolan 2011, Schumacher et al. 2009, Tang and Camargo 2014, and Tippett et al. 2010) have utilized these criteria to develop, apply, and evaluate genesis potential indices. Such indices are designed to highlight whether conditions favorable for TC development exist in observations or climate model outputs at one or more locations and times. For example, applying the ventilation index of Tang and Emanuel (2012) to eight model outputs from the fifth Coupled Model Intercomparison Project (CMIP5), RCP8.5 experiment, Tang and Camargo (2014) identified a potential decrease in the average annual number of days that the ventilation index is favorable for TC genesis in the North Atlantic Ocean of up to two weeks by the end of the 21^st century. Alternatively, downscaling methods may be applied to climate model outputs to assess projected future changes in TC season length (e.g., Dwyer et al. 2015).

In the context of genesis potential indices, greater lower to middle-tropospheric moisture content, higher upper oceanic heat content and/or potential intensity, lower vertical wind shear, and sufficiently large cyclonic vertical vorticity indicate a greater potential for tropical cyclogenesis (e.g., McGauley and Nolan 2011). Presumably, TC seasons that start earlier or end later than normal are characterized by the presence of the necessary ingredients for TC formation at times when they are not typically present. The inverse is presumably true for seasons that begin later and/or end earlier than normal. Herein, we seek to examine the extent to which this is true on sub-seasonal time scales, particularly in the context of the genesis pathways that early- and late-season North Atlantic TCs typically follow (McTaggart-Cowan et al. 2008, 2013). Note that the genesis pathways identified by McTaggart-Cowan et al. (2008, 2013) describe the environments within which the physical processes believed to be responsible for tropical cyclogenesis (e.g., wind-induced surface heat exchange; Emanuel 1986) are triggered so as to lead to the formation of a tropical cyclone.

In addition to understanding the synoptic- to climate-scale factors that control the length of an individual TC season, it is worthwhile to consider whether the length of the Atlantic TC season has increased or decreased in recent decades. Focusing on an extended North Atlantic main development region (MDR) south of 30°N and east of 75°W where an increase of 0.5-1.5°C in mean June-November SST was observed between 1950 and 2007, Kossin (2008) utilized quantile regression to identify changes in the annual distribution of Atlantic TC formation dates. Their findings (Figure 4 of Kossin 2008) suggest that the Atlantic TC season has increased in length by ten or more days per decade since 1950, reflective of both earlier starts and later ends to the season, with a level of confidence between 80-90%. This was attributed, albeit also with low confidence, to warmer May SSTs across the extended MDR, with an increase of the area-averaged SST by 1°C corresponding to as much as a twenty day shift in the start and/or end of the season. Though quantile regression is relatively insensitive to individual outliers, to what extent this result is due to several TC seasons during the early-to-mid-2000s in which particularly late-forming TCs occurred within Kossin (2008)’s extended MDR (e.g., 2001, 2003, 2005, and 2007; Table 1) remains unclear. In addition, whether this result holds in whole or in part for the entire Atlantic basin, in which several TC seasons during the early-to-mid 2000s were also associated with particularly late end dates (Table 2), is uncertain. Evaluating long-term trends in Atlantic TC season length when considering the entire basin is particularly important given that many of the earliest- and latest-forming TCs undergo genesis outside of Kossin (2008)’s extended MDR (Figs. 1 and 2).

Our research thus has several aims. We first examine whether the positive but non-statistically-significant trend in Atlantic TC season length identified by Kossin (2008) is maintained when the period of record is extended to the present. Next, we examine whether the positive but non-statistically-significant trend in Atlantic TC season length identified by Kossin (2008) is maintained when the set of TCs considered is extended to the entire Atlantic basin, whether through 2007 or the present. Separately, we investigate how the synoptic- to planetary-scale distributions of proxies for the necessary conditions for tropical cyclogenesis vary on sub-seasonal to interannual time scales between early- and late-starting and -ending Atlantic TC seasons, particularly in light of the different genesis pathways followed by early- and late-season TCs. The remainder of this work is structured as follows. Section two outlines the data utilized and methodology followed in this study. Section three presents results regarding long-term trends in Atlantic TC season length for the period 1979-2014. Section four presents results regarding the synoptic- to planetary-scale conditions that characterize early and late starting and ending Atlantic TC seasons. A summary of the key findings of the work and a discussion of their implications is presented in section five.

2. Data and Methodology

In this study, the National Hurricane Center HURDAT2 database (Landsea and Franklin 2013) is used to identify Atlantic TC formations, excluding tropical depressions and subtropical cyclones, between 1979 and 2014. A total of 431 TC formation events are identified across the entire basin, with 228 of these being located within the extended MDR considered by Kossin (2008). The year 1979 is chosen as the start of our analysis period for several reasons. First, this is the first year for which ERA-Interim reanalysis data (Dee et al. 2011), the use of which is described below, are available. Second, substantial improvements in the quantity and quality of satellite clear-sky radiance and cloud-track wind observations were realized beginning in 1979, resulting in more robust atmospheric reanalysis products from 1979-onward (e.g., Uppala et al. 2005). Third, so as to facilitate direct comparison between our results and those of Kossin (2008), we desire that the start of our period of record closely match that of Kossin (2008). We note that the sensitivity to a starting year of 1979 versus 1980 in the results to be presented is negligible (not shown). Finally, as routine geostationary satellite surveillance of TCs began in the mid-1960s (e.g., Neumann et al. 1999), it is unlikely that TCs were systematically missed over part or all of the period of record considered herein (e.g., Landsea 2007). Landsea (2007) also notes that advances in observational and analysis capabilities appear to be contributing to one additional Atlantic TC event per year since 2002, with many of their cited examples occurring at the start or end of the TC season. While it is possible that this could influence both the results presented herein as well as those of Kossin (2008), no attempt is made to account for this possible change in classification practices.

To quantify long-term trends in Atlantic TC season length, we apply the method of quantile regression. In contrast to linear (or least squares) regression, which provides a method by which the nature of an assumed linear relationship between the means of grouped data can be evaluated, quantile (or percentile) regression (Koenker and Bassett 1978, Koenker and Hallock 2001) provides a method for evaluating the nature of an assumed linear relationship for conditional quantile functions. One common application of quantile regression is median regression, though quantile regression need not be limited exclusively to the median (or 50th percentile) of a data set. Quantile regression has been applied in the atmospheric sciences to examine long-term trends in Atlantic TC season length (Kossin 2008) and the intensity of the most-intense Atlantic TCs (Elsner et al. 2008). Quantile regression considers the topology of the full dataset of TC events, rather than just the first and last TCs for each season, thereby increasing the degrees of freedom of the statistical analysis; furthermore, unlike linear regression, it is relatively insensitive to individual outliers within the data (Kossin 2008).

Herein, quantile regression is first utilized to replicate the findings of Kossin (2008), considering only TCs that formed within their extended MDR between 1980 and 2007. Quantiles between the 5^th and 95^th percentile, at 5% intervals, are considered. This analysis is then replicated for the period beginning 1979; as noted earlier, the results are found to be insensitive to small differences in the start year. Next, to evaluate whether the positive but non-statistically-significant trend in Atlantic TC season length identified by Kossin (2008) is maintained when the period of record is extended to the present, the analysis is repeated with an ending year of 2014. Subsequently, to evaluate whether the positive but non-statistically-significant trend in Atlantic TC season length identified by Kossin (2008) is maintained when the set of TCs is extended to the full Atlantic basin, the analysis is repeated for the periods of 1979-2007 and 1979-2014 when considering all Atlantic basin TCs. Finally, the sensitivity in how changing the end of the period of record by one year at a time is examined by repeating the analysis, over both Kossin (2008)'s extended MDR and the full basin, for end years between 2001 and 2014. The 90^th percentile confidence interval is computed for each analysis utilizing bootstrapping (e.g., Efron and Tibshirani 1993) with 200 surrogates.

To assess how the synoptic- to planetary-scale distributions of the necessary conditions for TC formation vary on sub-seasonal to interannual time scales between early- and late-starting and -ending Atlantic TC seasons, linear regression is utilized. The 10%, 25%, 75%, and 90% TC formation date for each Atlantic TC season is first identified. These values are then linearly regressed against monthly mean fields of SST, 850 hPa relative vorticity, 600 hPa relative humidity, 500 hPa geopotential height, and 850-200 hPa vertical wind shear magnitude. Monthly-mean SST data are obtained from the NOAA Extended Reconstructed Sea Surface Temperature (ERSST) dataset, version 3b, on a 2° latitude x 2° longitude grid (Smith et al. 2008). It should be noted that this dataset differs slightly from that described by Smith et al. (2008) in that satellite-derived SST data are not used in its composition so as to remove a cold SST bias introduced by non-clear sky satellite SST retrievals. All monthly-mean atmospheric fields are obtained from the ERA-Interim (Dee et al. 2011) reanalysis on an approximate 0.7° latitude x 0.7° longitude grid. The results are insensitive to one isobaric level (50 hPa) shifts in the isobaric level(s) over which atmospheric fields are considered (not shown). Sensitivity in the results to the choice of SST or atmospheric reanalysis dataset is expected to be small but is not explicitly examined.

Herein, linear regression takes the form:

(1)

Four sets of linear regression analyses between monthly-mean values of each field and nth percentile formation date are conducted: (1) June monthly-mean to 10^th percentile formation date, (2) June and July monthly-means to 25^th percentile formation date, (3) October and November monthly-means to 75^th percentile formation date, and (4) November monthly-mean to 90^th percentile formation date. The results are found to be qualitatively similar between linear regressions conducted against the 10^th and 25^th percentile formation dates and between linear regressions conducted against the 75^th and 90^th percentile formation dates (not shown). Consequently, the results presented in Section 4 consider only linear regression computed between June monthly-mean fields and the 10^th percentile formation date and between November monthly-mean fields and the 90^th percentile formation date. As presented herein, positive values of (1) indicate an earlier start – as measured by the 10^th percentile formation date – or later end – as measured by the 90^th percentile formation date – of the TC season as a given oceanic or atmospheric field increases in value. All linear regression analyses are conducted globally with particular focus given to describing the results across the North Atlantic Ocean, North America, and equatorial Pacific Ocean. This area extends into the equatorial Pacific Ocean so as to reflect the potential influence of the El Niño Southern Oscillation (ENSO; e.g., Bjerknes 1969) upon Atlantic basin TC activity, particularly late in the Atlantic TC season (Dunion 2011; Klotzbach 2011a,b).

To complement the spatial linear regression analyses described above, we compute the linear correlation coefficient between the 10^th (90^th) percentile formation date and June (November) monthly mean values of selected teleconnection indices. Teleconnection indices considered include the Arctic Oscillation (AO; e.g., Thompson and Wallace 1998), Atlantic Meridional Mode (e.g., Moura and Shukla 1981), Atlantic Multidecadal Oscillation (AMO; e.g., Kerr 2000), North Atlantic Oscillation (e.g., Barnston and Livezey 1987), Oceanic Niño Index (ONI; e.g., L’Heureux et al. 2013), Pacific Decadal Oscillation (PDO; e.g., Mantua et al. 1997), Pacific-North American (PNA; e.g., Wallace and Gutzler 1981), Quasi-Biennial Oscillation (QBO; e.g., Baldwin et al. 2001), and Sahel Precipitation Index (SPI; e.g., Haywood et al. 2013). Many of these teleconnection indices have been shown to exert a control on North Atlantic TC activity on subseasonal to interannual scales, particularly for that which occurs at lower latitudes (e.g., Gray 1984, Kossin and Vimont 2007, Kossin et al. 2010, Villarini et al. 2010, Klotzbach 2011, Villarini et al. 2012, to cite but a few examples). Only linear relationships that are statistically-significant to ≥ 90% confidence, as assessed utilizing a Student’s t-test, are reported upon in the results that follow.

3. Results: Long-Term Trends in Season Length

Over the period 1979-2007, when considering only TCs that formed within the extended MDR of Kossin (2008), the Atlantic TC season increased in length by approximately 1.5 days per year, as primarily associated with a later end to the season (Fig. 3a). This trend is not statistically-significant to ≥ 90% confidence, however. These results are nearly identical to those obtained for the period 1980-2007 considered by Kossin (2008, their Fig. 4c), with subtle differences resulting from the inclusion of 1979 within our analysis. For the periods 1979-2001 and 1979-2002, no trend – statistically-significant or otherwise – in Atlantic TC season length can be identified (Figs. 3f,g). There is some indication of a broadening of the peak of the season – here defined as formation events occurring between the 25^th and 75^th percentiles – but this result is also not statistically-significant to ≥ 90% confidence. Introducing subsequent seasons into the analysis (Figs. 3b-e), particularly the active 2005 season (Beven et al. 2008), results in the gradual development of the positive but non-statistically-significant trend identified over the period 1979-2007 (Fig. 3a). This trend primarily results from four seasons (2001, 2003, 2005, and 2007) with TC season end dates – here represented by the 95^th percentile TC formation date to increase the degrees of freedom of the analysis – two to seven weeks later than the 1979-2014 average (Table 1).

Extending the end of the analysis through 2014 eliminates any trend in Atlantic TC season length (Fig. 3h). The below-average 2009 season (Berg and Avila 2011) contributes particularly strongly to the elimination of this trend, as manifest by a season end date approximately two-and-a-half weeks earlier than the long-term average (Table 2). This implies that the positive trend identified by Kossin (2008) to between 80-90% confidence is primarily a function of the several abnormally-long TC seasons seen during the early-to-mid-2000s. It should be noted that extending the analysis through 2014 also decreases uncertainty in the results, as manifest by a narrower 90% confidence interval at both the start and end of the season.

When considering TC formation events across the entire Atlantic basin, no statistically-significant trend in season length is identified for the period 1979-2007 (Fig. 4a) despite numerous late-ending TC seasons in the early-to-mid 2000s (Table 2). For the periods 1979-2001 and 1979-2002, a non-statistically-significant trend towards seasons that are shorter by one day per year is identified (not shown). The comparatively longer seasons of 2003 through 2007 (Table 2) act to eliminate this trend but are not sufficient to result in an identifiable trend toward longer seasons. Furthermore, no trend – statistically-significant or otherwise – in Atlantic TC season length is identified for the period 1979-2014 (Fig. 4b). As for the Kossin (2008) extended MDR, the uncertainty in this result is somewhat less than that associated with the period 1979-2007 (c.f. Figs. 4a and 4b). Consequently, it is argued that the positive but non-statistically-significant trend toward longer Atlantic TC seasons identified by Kossin (2008) is not indicative of a robust long-term trend but is primarily the result of both the subset of TC formation events considered and end date of the analysis. Fluctuations in season length therefore appear to be primarily controlled by subseasonal to interannual variability in the necessary conditions for TC formation, particularly early and late in the season.

Tropical cyclones that form before the 10^th percentile date for each season preferentially do so in the Gulf of Mexico, the northwestern Caribbean Sea, and near the southeastern United States coastline (Fig. 1). Note that the TCs within this composite that form in the MDR are almost exclusively associated with later-starting Atlantic TC seasons. The preferred genesis pathway for TCs that form in the preferred regions for early-season development is weak tropical transition, as evaluated utilizing the genesis pathway classification database of McTaggart-Cowan et al. (2013). For reference, tropical transition (TT; Davis and Bosart 2003, 2004) occurs in environments in which organized deep, moist convection upshear of an extratropical cyclone, through the horizontal and vertical redistribution of potential vorticity, acts to weaken initially strong vertical wind shear atop the surface low. If the cyclone is located over sufficiently warm waters (SST ≥ 24-26°C) for a sufficiently long period of time (≥ 24 h) and is of sufficient intensity so as to foster wind-induced surface heat exchange (e.g., Emanuel 1986), an initially cold-core extratropical cyclone may transform into a warm-core TC. In the preferred genesis locations for early-season Atlantic TCs, June monthly-mean SST is between 24-28°C (Fig. 5a), 600 hPa relative humidity is between 40-60% (Fig. 5b), 850 hPa relative vorticity is approximately zero (Fig. 5d), and the 850-200 hPa vertical wind shear magnitude is less than 10 m s^-1 (Fig. 5e). In the June monthly-mean, as compared to known TC genesis-supporting environments in the deep tropics (e.g., Gray 1968, 1979; Frank 1987) and subtropical to middle latitudes (e.g., Mauk and Hobgood 2012), the SST and deep-layer vertical wind shear criteria for tropical cyclogenesis generally are met, whereas the precursor disturbance and middle tropospheric relative humidity criteria for tropical cyclogenesis generally are not met.

Earlier-starting Atlantic TC seasons are associated with a statistically-significant (to ≥ 90% confidence, as assessed utilizing a Student’s t test) increase in June monthly-mean 850 hPa relative vorticity in the eastern Gulf of Mexico (Fig. 5d). A one standard deviation increase in 850 hPa relative vorticity (0.5 x 10^-5 s^-1; Fig. 7d) is associated with a six to nine day earlier start to the Atlantic TC season relative to its mean. As the June climatological mean 850 hPa relative vorticity is anticyclonic across the Gulf of Mexico (Fig. 5d), the presence of increased 850 hPa relative vorticity in the eastern Gulf of Mexico in June indicates a greater likelihood that a seedling disturbance for TC formation exists in the Gulf of Mexico in earlier-starting Atlantic TC seasons. Given that most early-forming Atlantic TCs do so via tropical transition (Fig. 1), it is believed that a stationary frontal boundary along and ahead of the June climatological mean 500 hPa trough in the far western Atlantic (Fig. 5c) is the likely source of such a disturbance. However, it is not immediately clear as to what is the driving force behind increased 850 hPa relative vorticity in the eastern Gulf of Mexico during earlier-starting Atlantic TC seasons. Though 500 hPa geopotential height is typically lower across the Gulf of Mexico and northwestern Caribbean Sea during earlier-starting Atlantic TC seasons, this correlation is not statistically-significant to ≥ 90% confidence (Fig. 5c). It is possible that this result is a reflection of the earlier-developing TCs themselves. However, this is unlikely given a typically short duration of TCs near land compared to the duration of June and the lack of a similar relationship between higher 600 hPa relative humidity and earlier-starting Atlantic TC seasons (Fig. 5b).

Though few coherent, statistically-significant (to ≥ 90% confidence) linear correlations between sub-seasonal variability and the 10^th percentile Atlantic TC formation date exist within the North Atlantic basin, the 10^th percentile Atlantic TC formation date is associated with statistically-significant linear correlations to large-scale variability in the Southern Hemisphere (Fig. 6). This is particularly manifest by variability in the 500 hPa longwave pattern (Fig. 6c) and its impacts upon and relationship with atmospheric and oceanic variability in the remaining fields considered (Fig. 6a,b,d,e). It is unclear, however, as to whether the relationship between such variability, whether in whole or in part, and the 10^th percentile Atlantic TC formation date is causal or merely associative in nature. The cause of this variability is also uncertain, as it does not closely resemble that associated with any predominant planetary-scale modes of climatic variability known to the authors. Therefore, further research is necessary to identify what is responsible for the synoptic- to planetary-scale variability associated with early-starting Atlantic TC seasons.

Tropical cyclones that form after the 90^th percentile formation date for each season preferentially do so in the western Caribbean Sea and subtropical western Atlantic (Fig. 2). Late-season TCs that form in the subtropical western North Atlantic almost exclusively are the result of tropical transition, whereas TCs that form in the western Caribbean Sea either result from tropical transition or form in non-baroclinic environments. In the preferred genesis locations for late-season Atlantic TCs, November monthly-mean SST is between 24-28°C (Fig. 8a), 600 hPa relative humidity is between 30-60% (Fig. 8b), 850 hPa relative vorticity is approximately zero (Fig. 8d), and the 850-200 hPa vertical wind shear magnitude is between 10-20 m s^-1 (Fig. 8e). In the November monthly-mean, as compared to known TC genesis-supporting environments, SST generally is sufficiently warm, deep-layer vertical wind shear is marginally favorable, and both middle tropospheric relative humidity and lower tropospheric relative vorticity are insufficiently large so as to promote tropical cyclogenesis.

To first order, late-ending Atlantic TC seasons preferentially occur during cool-phase (La Niña) ENSO events. This is manifest by a strengthened Walker circulation, as reflected in both November monthly-mean SST (Figs. 8a and 9a) and 600 hPa relative humidity (Figs. 8b and 9b) fields across the equatorial Pacific. This is also reflected by a statistically-significant (to ≥ 90% confidence, as assessed utilizing a Student’s t-test) inverse linear relationship between the 90^th percentile formation date and the November mean value of the ONI (R = -0.33). In the context of the linear regression analyses presented in Figs. 8 and 9, a one standard deviation reduction in SST (1-2°C; Fig. 10a) and 600 hPa relative humidity (7.5-12.5%; Fig. 10b) in the central to eastern equatorial Pacific is associated with a six to nine day extension of the Atlantic TC season relative to its mean.

The increased likelihood of late-season TC formation in the western Caribbean Sea during La Niña events is consistent with Dunion (2011) and Klotzbach (2011a,b). Together, these studies found that atmospheric conditions known to be hostile for TC development – namely, increased vertical wind shear, increased static stability, and decreased middle-tropospheric relative humidity – occur in the western Caribbean Sea during October and November more (less) frequently during El Niño (La Niña) events. To that end, increased November monthly-mean 600 hPa relative humidity (Fig. 8b), increased November monthly-mean 850 hPa relative vorticity (Fig. 8d), and decreased November monthly-mean 850-200 hPa vertical wind shear (Fig. 8e), relative to their respective climatologies, in the Caribbean Sea during later-ending Atlantic TC seasons are consistent with the influence of La Niña. It is uncertain, however, as to the extent that an increased (a decreased) likelihood of late-season TC formation at higher latitudes is directly attributable to La Niña (El Niño) and its influence upon the global circulation during boreal fall (e.g., Horel and Wallace 1981).

Late-ending Atlantic TC seasons also preferentially occur during negative-phase PDO events. This is manifest by abnormally cold November monthly-mean SST along the west coast of North America and abnormally warm November monthly-mean SST in the central North Pacific Ocean (Figs. 8a and 9a). This is also reflected by a statistically-significant (to ≥ 90% confidence, as assessed utilizing a Student’s t-test) inverse linear relationship between the 90^th percentile formation date and the November mean value of the PDO index (R = -0.34). In the context of the linear regression analyses presented herein, a one standard deviation increase in SST across the central North Pacific (0.5-1°C; Fig. 10a) and decrease in SST along the west coast of the United States (≈ 0.5°C; Fig. 10a) are associated with an approximate six day increase in the length of the Atlantic TC season relative to its mean. The relationship between late-season Atlantic TC activity and the PDO has, to the authors’ knowledge, not yet been documented within the refereed literature, and identification of the physical underpinnings behind this relationship is planned for further study.

In closer proximity to where late-season Atlantic TCs form, late-ending Atlantic TC seasons are associated with an eastward shift of the November monthly-mean 500 hPa longwave pattern across the United States and subtropical western North Atlantic Ocean (Fig. 8c). A one standard deviation (30-40 m; Fig. 10c) increase (decrease) in 500 hPa geopotential height across the central United States (subtropical western North Atlantic Ocean) is associated with a three to nine day extension of the Atlantic TC season relative to its mean. Though not statistically-significant to ≥ 90% confidence, late-ending Atlantic TC seasons are also associated with increased 500 hPa geopotential heights near Greenland (Fig. 8c), wherein a one standard deviation (≥ 50 m; Fig. 10c) increase in 500 hPa geopotential height is associated with an approximate three day extension of the Atlantic TC season relative to its mean. The occurrence of below-normal 500 hPa geopotential heights in the subtropical western North Atlantic Ocean with above-normal 500 hPa geopotential heights near Greenland is consistent with an elevated likelihood of cut-off extratropical cyclones in the subtropical western North Atlantic. Further, given sufficiently warm SSTs, this is consistent with an increased likelihood of late-season tropical transition (TT) occurrence in the subtropical western Atlantic so long as deep, moist convection associated with a given extratropical cyclone is able to locally reduce the 850-200 hPa vertical wind shear on meso- to synoptic time scales (Davis and Bosart 2003, 2004).

Spatial linear correlation is used to quantify the extent to which the linear regression analyses presented in Figs. 5-6 and 8-9 are representative of the variability in monthly-mean fields observed with both early- and late-starting and -ending seasons. Herein, spatial linear correlation is computed over the region 10°S-70°N, 150°-0°W, consistent with the region depicted in Figs. 5 and 8. The statistically-significant linear correlations between the 90^th percentile Atlantic TC formation date and boreal autumn atmospheric and oceanic variability associated with both the ENSO and PDO (Section 4b) motivate the selection of the southern and western extents of this domain. The genesis locations for many of the earliest- and latest-forming Atlantic TCs (Figs. 1 and 2), many of which originate from precursor disturbances of mid-latitude origin, motivate the selection of the northern extent of this domain. Similar qualitative insight to that described below is obtained when spatial linear correlation is computed only over the tropical North Atlantic (0°-30°N, 95°-10°W) or over a global domain (not shown). As a result, only the results for the region 10°S-70°N, 150°-0°W are presented below.

The results of the spatial linear correlation analyses are presented in Tables 3 and 4. To first order, the linear regression analyses are to some extent representative of variability in monthly-mean fields observed with both early- and late-starting and -ending seasons. Anomalies in the monthly-mean fields for the five earliest-starting and latest-ending Atlantic TC seasons are generally positively correlated with the linear regression fields, while anomalies in the monthly-mean fields for the five latest-starting and earliest-ending Atlantic TC seasons are generally negatively correlated with the linear regression fields. However, correlations are generally weak, highly variable between individual Atlantic TC seasons within a given five-member composite, and stronger for some variables than others. This implies a limit upon the predictive ability of the linear regression analyses.

For example, consider the Atlantic TC seasons with the five latest 90^th percentile formation dates, as listed in Table 4. Previously, La Niña and negative-phase PDO events were demonstrated to be associated with later-ending Atlantic TC seasons. Of the five-latest ending Atlantic TC seasons, as classified using the ONI, four were associated with neutral ENSO conditions and one (1994) was associated with El Niño conditions. Likewise, as classified by the PDO index, two of the five latest-ending Atlantic TC seasons were associated with weak positive-phase PDO conditions. Thus, while La Niña and negative-phase PDO events appear to increase the likelihood of a later-than-normal end to the Atlantic TC season, they do not represent the only pathways to a later-than-normal Atlantic TC season end. Further, slower-evolving fields with significant synoptic-scale structure in the linear regression analyses – particularly SST, but also 600 hPa relative humidity, 500 hPa geopotential height and 850-200 hPa vertical wind shear magnitude – are generally associated with stronger correlations. The more rapidly-evolving 850 hPa relative vorticity field, with primarily mesoscale structure in its linear regression analyses, is generally associated with weaker correlations. This implies that meso- to synoptic-scale variability not captured by the linear regression analyses, particularly with respect to whether or not a predecessor disturbance from which a TC can originate exists, contributes to variability in Atlantic TC season length.