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  • View in gallery
    Fig. 1.

    The TC datasets and the ocean boundary definitions used in this analysis. (a) The ocean basin boundary definitions. Note that the north Indian Ocean is excluded from this analysis for reasons explained in the text. (b),(c) All TCs in the respective datasets from 1981 to 2016 by life cycle point with genesis in blue, LMI in red, and lysis in green. Note that the NHC–JTWC dataset reports a much earlier lysis point for TCs in the South Pacific.

  • View in gallery
    Fig. 2.

    The zonally asymmetric HC defined in the annual-mean divergent meridional overturning ψ at 500 hPa and near-surface horizontal divergent winds in ERA-Interim for 1981–2016. Hadley cell termini are marked by the red curves.

  • View in gallery
    Fig. 3.

    Quantile regressions for the meridional distribution of TC activity in both hemispheres: (a)–(c) Northern and (d)–(f) Southern Hemisphere. The 95% confidence intervals are shown by the shaded regions. Trends from both dataset aggregations are shown: WMO (lighter colors) and NHC–JTWC (darker colors). The maximum and minimum latitudes for each life cycle point at the 20th, 40th, 60th, and 80th percentiles are shown at the bottom of each panel. The red horizontal lines shown the overall mean trends with the WMO mean marked with triangles and NHC–JTWC marked by squares.

  • View in gallery
    Fig. 4.

    As in Fig. 3, but for the individual NH ocean basins: (a)–(c) the western North Pacific, (d)–(f) the North Atlantic, and (g)–(i) the eastern North Pacific.

  • View in gallery
    Fig. 5.

    As in Fig. 3, but for the individual SH ocean basins: (a)–(c) the South Pacific and (d)–(f) the south Indian Ocean.

  • View in gallery
    Fig. 6.

    Time series for HC extent diagnostic at each basin and hemisphere computed in ERA-Interim, JRA-55, and MERRA-2.

  • View in gallery
    Fig. 7.

    Regressions between seasonal-mean HC extent and seasonal-mean TC meridional distribution at different life cycle stages. All time series had their linear trends removed. Pink shading shows regressions that exceed a 95% confidence estimated using two-tailed p values from t statistics. As there are no two independent observational records in the North Atlantic and eastern North Pacific, only the WMO data are shown for these basins.

  • View in gallery
    Fig. 8.

    Time series for both hemisphere’s seasonal-mean HC extent (blue) from ERA-Interim and TC genesis LMI latitudes (red) from the NHC–JTWC observational record.

  • View in gallery
    Fig. 9.

    Time series for the North Atlantic’s seasonal-mean HC extent (blue) from ERA-Interim and TC poleward [P(75)] lysis latitudes (red) from the NHC–JTWC observational record.

  • View in gallery
    Fig. 10.

    As in Fig. 6, but for HC absolute intensity.

  • View in gallery
    Fig. 11.

    As in Fig. 7, but for HC intensity and seasonal-mean TC meridional distribution at different life cycle stages.

  • View in gallery
    Fig. 12.

    Time series for the eastern North Pacific’s seasonal-mean HC intensity (blue) from ERA-Interim and TC equatorward {10th percentile [P(10)]} genesis latitudes (red) from the NHC–JTWC observational record.

  • View in gallery
    Fig. 13.

    Regression coefficients for seasonal-mean (a) SST and (b) VWS (200–850-hPa wind vector difference) against the respective hemisphere’s HC extent diagnostic 1981–2016. The NH data in both panels are over JASO, and the SH data are over JFM. All TC life cycle points over the same period are overlaid in green: genesis in (a) and LMI in (b).

  • View in gallery
    Fig. 14.

    As in Fig. 13, but against eastern North Pacific local HC intensity diagnostic.

  • View in gallery
    Fig. A1.

    Monthly mean meridional mass flux streamfunction derived with the divergent winds in ERA-Interim and the identified termini of the Hadley cells. (a) The western Pacific in July 1980 and (b) the Atlantic in August 1989.

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Concurrent Changes to Hadley Circulation and the Meridional Distribution of Tropical Cyclones

Joshua StudholmeShirshov Institute of Oceanology, Russian Academy of Sciences, and Moscow State University, Moscow, Russia

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Sergey GulevShirshov Institute of Oceanology, Russian Academy of Sciences, and Moscow State University, Moscow, Russia

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Abstract

Poleward trends in seasonal-mean latitudes of tropical cyclones (TCs) have been identified in direct observations from 1980 to the present. Paleoclimate reconstructions also indicate poleward–equatorward migrations over centennial–millennial time scales. Hadley circulation (HC) is often both implicitly and explicitly invoked to provide dynamical linkages to these shifts, although no direct analysis of concurrent changes in the recent period has been presented. Here, the observational TC record (1981–2016) and ERA-Interim, JRA-55, and MERRA-2 are studied to examine potential relationships between the two. A zonally asymmetric HC is defined by employing Helmholtz theory for vector decomposition, and this permits the derivation of novel HC diagnostics local to TC basins.

Coherent variations in both long-term linear trends and detrended interannual variability are found. TC genesis and lifetime maximum intensity latitudes share trend sign and magnitude with shifts in local HC extent, with rates being approximately 0.25° ± 0.1° lat decade−1. Both these life cycle stages in hemispheric means and all Pacific TC basins, as well as poleward-extreme North Atlantic lysis latitudes, shared approximately 35% of their interannual variability with HC extent. Local HC intensity is linked only to eastern North Pacific TC latitudes, where strong local overturning corresponds to equatorward TC shifts. Examination of potential dynamical linkages implicates La Niña–like sea surface temperature gradients to poleward HC termini. This corresponds to increased tropical and reduced subtropical vertical wind shear everywhere except in the North Atlantic and western North Pacific, where the opposite is true. These results quantify a long-hypothesized link between TCs and the large-scale oceanic–atmospheric state.

Denotes content that is immediately available upon publication as open access.

© 2018 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Joshua Studholme, josh.studholme@gmail.com

Abstract

Poleward trends in seasonal-mean latitudes of tropical cyclones (TCs) have been identified in direct observations from 1980 to the present. Paleoclimate reconstructions also indicate poleward–equatorward migrations over centennial–millennial time scales. Hadley circulation (HC) is often both implicitly and explicitly invoked to provide dynamical linkages to these shifts, although no direct analysis of concurrent changes in the recent period has been presented. Here, the observational TC record (1981–2016) and ERA-Interim, JRA-55, and MERRA-2 are studied to examine potential relationships between the two. A zonally asymmetric HC is defined by employing Helmholtz theory for vector decomposition, and this permits the derivation of novel HC diagnostics local to TC basins.

Coherent variations in both long-term linear trends and detrended interannual variability are found. TC genesis and lifetime maximum intensity latitudes share trend sign and magnitude with shifts in local HC extent, with rates being approximately 0.25° ± 0.1° lat decade−1. Both these life cycle stages in hemispheric means and all Pacific TC basins, as well as poleward-extreme North Atlantic lysis latitudes, shared approximately 35% of their interannual variability with HC extent. Local HC intensity is linked only to eastern North Pacific TC latitudes, where strong local overturning corresponds to equatorward TC shifts. Examination of potential dynamical linkages implicates La Niña–like sea surface temperature gradients to poleward HC termini. This corresponds to increased tropical and reduced subtropical vertical wind shear everywhere except in the North Atlantic and western North Pacific, where the opposite is true. These results quantify a long-hypothesized link between TCs and the large-scale oceanic–atmospheric state.

Denotes content that is immediately available upon publication as open access.

© 2018 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Joshua Studholme, josh.studholme@gmail.com

1. Introduction

Tropical cyclones (TCs) play an important role in the climate system and are useful indicators of climate variability. Since there are strong regional signals of ongoing climate variability in both the Atlantic and Indo-Pacific Oceans (e.g., Rhein et al. 2013; Li et al. 2015), the responses of TCs to these signals are of great interest. TCs are also hypothesized to play an active role in influencing climate at both the local and global scales (e.g., Emanuel 2008; Manucharyan et al. 2011; Fedorov et al. 2010, 2013; Huang et al. 2017). TCs represent important extreme climate events and impact financial markets, especially the insurance and reinsurance industries (Pielke 2007; Reed et al. 2015). In this respect, TC tracks are of great physical and societal relevance.

Numerous approaches have been used to quantify TC tracks and their variability in climate records and numerical simulations. A binary classification of “straight moving” (typically zonal propagation) versus “recurving” (moving poleward after genesis and curving back upon themselves) is very widely employed. Other metrics include point and track densities (e.g., Elsner et al. 2012), trajectory mass moments (e.g., Nakamura et al. 2009), and probabilistic clustering (e.g., Gaffney et al. 2007; Kossin et al. 2010). A description of TCs using zonal and meridional averages along the life cycle has been employed in a number of recent analyses (e.g., Kossin et al. 2014, 2016; Wu et al. 2015; Wang et al. 2016). This approach has particular merit when relating TC activity to hemispheric climate modulations.

Considerable intraseasonal and interannual variability as well as the long-term trend in TC tracks is well documented, although substantial issues remain for analysis. Difficulty persists since available time series are short and changes in operational centers and practices occur throughout the available record (e.g., Sandgathe 1987; Chia and Ropelewski 2002; Landsea 2015; Klotzbach and Landsea 2015; Landsea et al. 2010). A poleward migration in the seasonal-mean latitude of TC lifetime maximum intensity (LMI) in both hemispheres has been identified with rates of 0.48° and 0.56° lat decade−1 between 1982 and 2012, in the Northern Hemisphere (NH) and Southern Hemisphere (SH), respectively (Kossin et al. 2014). Daloz and Camargo (2017) found LMI migration corresponds to poleward migration of Pacific TC genesis. Changes in TC latitudes, linked to recurvature, have also been identified regionally in both the western North Pacific and North Atlantic (Wu and Wang 2004; Kossin et al. 2010; Murakami and Wang (2010); Ha et al. 2014; Daloz et al. 2015; Mei and Xie 2016; Hart et al. 2016; Kossin et al. 2016). Over centennial and millennial time scales, TC latitudes have been shown to migrate poleward and equatorward at various times in numerous paleoclimatic reconstructions (e.g., Baldini et al. 2016; van Hengstum et al. 2016).

Coincident with these poleward migrations in seasonal-mean TC latitudes, there has been an expansion of the dominant feature of the large-scale tropical atmospheric flow, the Hadley circulation (HC; e.g., Lucas et al. 2014). Reported magnitudes for the migration of the HC poleward extent are approximately 0.5°–0.81° lat decade−1 (e.g., Hu and Fu 2007; Stachnik and Schumacher 2011; Davis and Rosenlof 2012; Allen et al. 2012; Nguyen et al. 2013; Davis and Birner 2013). There is thus some amount of consistency between the reported poleward trends in TC latitudes and HC extent.

TC tracks are principally determined by the large-scale mean tropospheric flow and, to a lesser extent, genesis locations (e.g., Riehl and Shafer 1944; Colbert and Soden 2012; Colbert et al. 2015). Genesis locations (i.e., positions where disturbances reach TC intensity) are chiefly determined by sea surface temperature (SST; e.g., Emanuel 2005; Vecchi and Soden 2007b; Elsner et al. 2008; Vecchi et al. 2008; Villarini et al. 2010; Ramsay and Sobel 2011; Villarini and Vecchi 2012; Defforge and Merlis 2017) and vertical wind shear (VWS; e.g., Emanuel and Nolan 2004; Vecchi and Soden 2007a; Vimont and Kossin 2007; Kossin and Vimont 2007; Kossin 2017). An influence of second-order importance is TC recurvature, which is an intrinsic property resulting from a differential horizontal advection of planetary vorticity, sometimes referred to as beta drift (Bin et al. 1998; Chan and Chan 2016). Since TC tracks are influenced by their environmental large-scale winds and SST, links to large-scale structure of the tropical circulation are of great interest (Latif et al. 2007; Kossin et al. 2010; Vecchi et al. 2013).

The HC is often implicitly and explicitly invoked to provide a mechanistic interpretation of the poleward–equatorward migration of seasonal-mean TC latitudes. Kossin et al. (2014, 2016) relate the recent poleward migration of TCs to increases in seasonal-mean VWS in the tropics and decreases in the subtropics by subtracting composites of an early and late period, thus implicitly invoking HC as it is known to have migrated poleward over the period. This pattern corresponds to an increase in TC potential intensity (connected to tropical SSTs and ocean–atmosphere thermal disequilibria). They went on to indeed hypothesize that these changes are directly linked to the well-documented expansion of the HC (e.g., Fu et al. 2006; Lucas et al. 2014).

Furthermore, Baldini et al. (2016) hypothesized that the consistent poleward migration of North Atlantic TCs that they found dating back to AD 1550 in stalagmite-derived paleoclimate records is linked to concurrent HC changes. They propose a mechanistic link of the HC’s impact of TC latitudes through displacement of the Bermuda high. On even longer time scales, van Hengstum et al. (2016) used a 3000-yr sedimentary record to conclude that the HC has likely contributed to the meridional distribution of intense TCs in the North Atlantic over millennial–centennial scales.

Despite comparable magnitudes in poleward trends and the conceptual dynamical linkages, an explicit analysis between TC latitudes and the HC in the direct observational record has not yet been performed. Recently, local Hadley cells have been diagnosed from the divergent component of the meridional winds (e.g., Zhang and Wang 2013; Schwendike et al. 2014; Schwendike et al. 2015; Zhang and Wang 2015; Nguyen et al. 2018). This method is particularly appropriate for studying TCs in relation to the HC as HC is notably zonally asymmetric. Zhang and Wang (2013, 2015) used this diagnostic to examine how the Atlantic and eastern North Pacific local HC affects TC frequency and intensity.

Here, we present a novel analysis of TC–HC concurrencies using the 35-yr observational TC record and three reanalysis products to address the hypothesized connection directly. Specifically, the analysis has the following aims:

  1. Identify poleward–equatorward migrations in seasonal-mean TC latitudes along the cyclone life cycle (genesis, LMI, and lysis).

  2. Diagnose the local HC, and compute and discuss the magnitudes of long-term linear trends in these diagnostics directly in relation to concurrent trends in seasonal-mean TC latitudes.

  3. Directly relate interannual HC modulations to TC latitudes irrespective of any long-term linear trends in either.

As far as the authors are aware, this is the first attempt to make such an explicit covariance analysis between TC and local HC. The structure of this paper is as follows: In section 2, the data and methodology are detailed. Section 3 describes changes in TC meridional distribution over recent decades. Sections 4 and 5 analyze the HC meridional extent and intensity and their relationship to TC latitudes, respectively. A brief exploration of potential dynamical linkages is provided in section 6 before a summary in section 7.

2. Data and methodology

a. Observational TC data

TC track data are taken from the International Best Track Archive for Climate Stewardship (IBTrACS), version 03r10 (Knapp et al. 2010). This archive is maintained by the U.S. National Oceanic and Atmospheric Administration (NOAA) National Climatic Data Center and is considered the most complete set of global historical TC data (e.g., Kossin et al. 2014; Walsh et al. 2016; Kossin 2017).

Uncertainties in TC observational records have a strong impact on analysis reliability (e.g., Landsea et al. 2010; Kossin et al. 2014; Landsea 2015; Klotzbach and Landsea 2015; Daloz et al. 2015). Data have improved since 1980 with global satellite coverage, but even postsatellite records contain significant uncertainties (Ren et al. 2011; Barcikowska et al. 2012; Torn and Snyder 2012; Landsea and Franklin 2013). The length of reliable records is important for trend detection since natural variability at decadal and longer scales is high (Sobel et al. 2016). Inhomogeneities also hamper analyses, and there is particular observational bias toward times and locations when TCs are within a forecaster’s “realm of interest” (i.e., the system is intense, and there is landfall risk). This bias chiefly affects records of genesis and lysis as this is when cyclones are typically weak and far from landfall (Kossin et al. 2014). To maximize robustness and analyze sensitivity, where possible, it is optimal to use more than one dataset (Camargo and Sobel 2010; Schreck et al. 2014).

We use IBrACS-WMO (the archive’s own homogenization product) and another aggregation combining National Hurricane Center (NHC) data [HURDAT2; the NHC is the WMO Regional Specialized Meteorological Center (RSMC) in Miami], which covers the Atlantic and eastern North and central Pacific, and the JTWC, which covers all other basins (together referred to as NHC–JTWC). We employ both IBTrACS-WMO and NHC–JTWC in all basins except the North Atlantic and eastern North Pacific (where the NHC is the WMO observational agency). We only show analysis using the IBTrACS-WMO data for the North Atlantic and eastern North Pacific. We note that using two datasets does not completely exclude bias as both are depend upon their own set of potentially flawed subjective operational procedures. Different agencies use different wind averaging periods. Following Schreck et al. (2014), we use 1-min winds and thus convert where appropriate after their methodology.

NH and SH means are constructed from both IBTrACS-WMO and NHC–JTWC. We deem this a valid approach in the NH since the majority of TCs there occur in the western North Pacific where two independent records exist. Regional boundaries used in this study (defined following WMO guidelines) and all TCs (by key life cycle point) are shown in Fig. 1a.

Fig. 1.
Fig. 1.

The TC datasets and the ocean boundary definitions used in this analysis. (a) The ocean basin boundary definitions. Note that the north Indian Ocean is excluded from this analysis for reasons explained in the text. (b),(c) All TCs in the respective datasets from 1981 to 2016 by life cycle point with genesis in blue, LMI in red, and lysis in green. Note that the NHC–JTWC dataset reports a much earlier lysis point for TCs in the South Pacific.

Citation: Journal of Climate 31, 11; 10.1175/JCLI-D-17-0852.1

For consistency and reproducibility, we examine periods when tracks are considered either tropical or subtropical as indicated by archive flags, a categorization that is standardized by IBTrACS. We also use only the “main” (archive’s terminology) time series of all TCs as denoted by archive flags. The inclusion of wind speed data is variable across ocean basins and time. Again for consistency, we define genesis with a constant wind speed threshold. Some tracks in the archive do not include any wind speed data and are thus excluded from the analysis.

We consider three specific stages covering the TC life cycle: genesis, LMI, and lysis (Figs. 1b,c). Here, the genesis location is defined as the location of the TC center when it first reaches tropical storm intensity [defined as maximum sustained wind speed ≥18 m s−1 or ≥33 kt (1 kt ≈ 0.51 m s−1)]. If a TC’s first recorded wind speed is above this threshold, this first point is taken as genesis. Such tracks are <1% of the archive and their inclusion/exclusion does not affect the conclusions reached. LMI is the time at which the highest magnitude maximum sustained wind speed over the entire life cycle is recorded. LMI can be viewed as the most robust measure as this depends solely on the maximum intensity and this will occur well into the life cycle, whereas genesis and lysis will be more sensitive to operational changes and forecaster subjectivity. Lysis location is the position of the track when its “nature” (archive’s terminology) is last recorded as tropical. In practice, TCs at this point in their life cycle may indeed experience actual lysis (i.e., a disintegration of the defining coherent warm core) or may undergo extratropical transition (ET). Determining ET in observational data is nontrivial (e.g., Studholme et al. 2015); thus, aggregating actual warm core disintegration and ET into the category of lysis in this analysis is considered to be a reasonable and meaningful approximation.

b. Hadley circulation extent and intensity diagnostics

Estimates for HC extent and intensity are derived from three reanalyses: ERA-Interim (Dee et al. 2011), JRA-55 (Kobayashi et al. 2015), and MERRA-2 (Gelaro et al. 2017) using three-dimensional monthly means of daily means on their native grids (¾° × ¾° for ERA-Interim, ½° × ½° for JRA-55, and ½° × ⅔° for MERRA-2) at all available pressure levels. It is important to use multiple reanalyses as considerable variation in HC has been shown to exist between them (e.g., Nguyen et al. 2013). These data are then linearly interpolated onto ¼° horizontal resolution and 10-hPa vertical resolution in pressure coordinates to aid comparison.

To diagnose the local HC, we employ the Helmholtz decomposition following Schwendike et al. (2014). This takes advantage of the fact that a vector field in R3 space may be unambiguously partitioned into two contributions: 1) a divergent (irrotational) component where ∇ × V ≡ 0 and 2) a nondivergent (solenoidal) component where ∇ ⋅ V ≡ 0 (e.g., Bourne and Kendall 1992). This is necessary for defining the zonally asymmetric HC since the commonly used Stokes streamfunction computed using hemispheric zonal-mean meridional velocities depends upon the assumption of nondivergence; that is, ∂υ/∂y + ∂ω/∂p = 0 (using standard geophysical notation; e.g., Oort and Rasmusson 1970; Oort and Yienger 1996). It therefore requires there to be no zonal component to the net mass flux. In a zonal mean of the atmospheric wind field over an entire hemisphere, this condition is trivially satisfied. However, between any two arbitrary zonal bands λ1 and λ2, where λ1λ2 < 2π, this ceases to be true. Over such regional domains, the net zonal mass flux is nonnegligible, and the streamfunction may not be computed from υ. Using the divergent component of the Helmholtz-decomposed winds ensures that this condition is satisfied. In the interest of brevity, we direct the reader to Schwendike et al. (2014) for a full derivation of this approach. Summarizing, vertical motion can thus be written as
e1
Where ω is vertical motion in pressure coordinates and subscripts ϕ and λ denote the vertical velocity in the meridional and zonal planes, respectively. The component ωϕ can be viewed as the meridional overturning circulation (i.e., Hadley circulation) and the component ωλ as zonal overturning (Walker circulation). In this analysis, we are only interested in ωϕ which satisfies
e2
where υχ is the divergent component of the meridional velocity. Although this method ensures ωϕ and ωλ are two unique orthogonal circulations, it does not imply independence between the zonal and meridional components of the flow, and such a coupling has been implicated in interbasin associations (e.g., Chiang et al. 2000, 2002). The meridional streamfunction in spherical coordinates for the local HC can thus be derived as (Zhang and Wang 2013; Nguyen et al. 2018)
e3
where a is the mean radius of the planet and g is gravitational acceleration.

The integration is taken from the top of the atmosphere, which yields positive (negative) values for annual-mean ψ in the NH (SH) tropics. This corresponds to a clockwise (counterclockwise) circulation when viewed from the east. We compute ψ between zonal bands corresponding to different TC basins: North Atlantic (NA; 20°–70°W), eastern North Pacific (105°–150°W), western North Pacific and South Pacific (SP; 130°E–180°), and south Indian Ocean (SI; 50°–110°E). We verified all results against reasonable perturbations (i.e., ±10° longitude) around these boundaries, and they had no meaningful effect on results.

The HC is characterized with two diagnostics derived from ψ: HC extent and intensity. Traditionally, HC extent has been defined as the ψ = 0 isoline (e.g., Oort and Yienger 1996). However, in the zonally asymmetric HC, this line is not necessarily crossed (Fig. 2). Nguyen et al. (2018) first encountered this issue when looking at regional HC in the SH. They devised a new definition of the edge of the local HC, defining it as where the overturning weakens to a specified threshold percentage of the maximum overturning within the tropical cell. The edge of the HC is therefore taken as the average position of the weakened peak value between 700 and 400 hPa. We use 800–400 hPa as we found that shallow cells, particularly in the North Atlantic, were better detected by including lower levels without losing skill elsewhere. Nguyen et al. (2018) conducted sensitivity tests with thresholds of 10%, 15%, 20%, and 25%. We conducted our own tests and reach similar conclusions. Specifically that while the absolute latitude of the HC edge is sensitive to the threshold value, the variability is not. Higher thresholds more robustly detect the HC edge, so here, as in Nguyen et al. (2018), we use 25%. We tested this definition against the traditional zero isoline for the hemispheric zonal mean, and it indeed captures the same variability (correlation coefficient of 0.95). More details of the HC diagnostic algorithm are in the appendix.

Fig. 2.
Fig. 2.

The zonally asymmetric HC defined in the annual-mean divergent meridional overturning ψ at 500 hPa and near-surface horizontal divergent winds in ERA-Interim for 1981–2016. Hadley cell termini are marked by the red curves.

Citation: Journal of Climate 31, 11; 10.1175/JCLI-D-17-0852.1

HC intensity is taken as the vertically averaged maximum value of ψ between 900 and 200 hPa in each overturning cell. The interested reader is directed to Nguyen et al. (2013) for an analysis of global zonal-mean HC in reanalyses and Nguyen et al. (2018) for a discussion of local HC variability in the Southern Hemisphere.

Time series for local HC diagnostics are produced by applying the diagnostic algorithm to ψ computed with monthly mean . HC has a strong seasonal cycle, distinct not only between hemispheres but also ocean basins. For this reason, when taking seasonal means of HC diagnostics, we weight each month’s value of HC extent and intensity by the corresponding TC count in that basin or hemisphere for that specific month.

c. Study period

The analysis covers 1981–2016; 1981 is the start of global coverage for both TC datasets and approximates the start of satellite data coverage. Note that the IBTrACS-WMO record of the northern Indian Ocean begins in 1990. As a result, and as meteorological conditions that affect TCs in this ocean are markedly different from elsewhere, we exclude north Indian Ocean TCs. The last complete year currently included in the TC archive is 2016. We define July–October (JASO) and January–March (JFM) as TC seasons in the NH and SH, respectively, corresponding to months with approximately 75% of all TC activity there. None of the time series in this analysis exhibited autocorrelation as determined by the Durbin–Watson test statistic.

3. Results: Changes in meridional TC distribution in recent decades

a. Reference climatology of TCs

Figures 1b and 1c show climatological distributions of all TC life cycle points in the IBTrACS-WMO (hereinafter WMO) and NHC–JTWC datasets, respectively. TC genesis is generally confined between the equator and 20°N or 20°S and is more tightly bound in the SH. This is possibly due to differences in operational procedures (e.g., Hodges et al. 2017). The SH TC life cycle follows a strict meridional progression that is zonally symmetric across the south Indian and South Pacific Oceans. SH TCs reach LMI between 10° and 20°S and experience lysis poleward of this. WMO and NHC–JTWC notably differ in detecting lysis latitudes in the South Pacific. The WMO archive tracks cyclones for much longer, as south as 60°S, while NHC–JTWC terminates tracks around 40°S. In all other respects, the two datasets are very consistent with one another in terms of spatial distributions.

In the NH, the TC life cycle is notably zonally asymmetric. TC genesis in the western North Pacific occurs very close to the equator, while in the eastern North Pacific and North Atlantic, it is bounded on the equatorward side at 10°N. This might reflect differences in source disturbances leading to genesis such as easterly waves. Eastern North Pacific TC genesis does not occur more poleward than approximately 15°N, while in the western North Pacific and North Atlantic, it can occur as far northward as 40°N (again, this is strongly dependent on observational procedures). LMI latitudes show a similar spread between 10° and 40°N in both the western North Pacific and North Atlantic but are not observed poleward of 20°N in the eastern North Pacific. NH lysis latitudes are very zonally asymmetric. In the western North Pacific, they are bimodal with peaks at approximately 20° and 40°N. In the eastern North Pacific, TC lysis occurs at approximately 25°N ± 5° latitude, with a tendency to occur farther north as cyclones propagate eastward. In the North Atlantic, lysis is distributed across the entire ocean but most prominently occurs along the North American east coast soon after landfall or at approximately 40°N.

Long-term regional statistics are given in Table 1. The NH exhibits well over twice the number of TCs than the SH. According to WMO estimates, the NH experiences an average of 59 TCs per year versus 25 TCs per year in the SH. This is partly related to differences in inclusion of subtropical cyclones (e.g., Hodges et al. 2017). However, it predominately results from the presence of an additional active TC basin (three in the NH vs two in the SH) and also because the western North Pacific is particularly active, with 25 TCs on average per year according to WMO estimates. The western North Pacific thus largely dominates the NH average. This is most probably due to the large area of very warm SSTs there. Even for seasonal statistics, differences in TC records between datasets (WMO vs NHC–JTWC) are apparent.

Table 1.

Description of the IBTrACS TC count time series used in the analysis for both datasets: WMO and NHC–JTWC. Note that only one dataset is available in the North Atlantic and eastern North Pacific.

Table 1.

b. Meridional quantile regressions

To examine changes in mean meridional TC locations, we compute quantile regressions (e.g., Elsner et al. 2008) in both hemispheres and all basins for TC genesis, LMI, and lysis. This is done by fitting linear ordinary least squares models to time series of TC latitudes for percentiles across the meridional distribution. These are characterized by a regression coefficient, interpreted as linear poleward trend, and the corresponding 95% confidence limits. We use the model implementation of the Python Statsmodels environment (Seabold and Perktold 2010).

Figure 3 shows results for hemispheric domains. We note that all TC instances are equally weighted regardless of ocean basin (i.e., all TCs are uniformly weighted) and again, that in the North Atlantic and eastern North Pacific, WMO and NHC–JTWC data are the same. Signs of LMI trends (Figs. 3b,c) are in agreement with Kossin et al. (2014). We find a poleward migration of the annual-mean TC LMI latitudes for both hemispheres. In the SH, this trend is robust at the 95% significance level in both datasets. In the NH, it is only robust at this confidence level in WMO data and, even so, is very slight. Kossin et al. (2014), from an alternative dataset aggregation and time period (1982–2009, IBTrACS, selecting sources for each TC with the most poleward LMI), reported tendencies in LMI of 53 and 62 km decade−1 in the NH and SH, respectively. We find trends of 0.1° and 0.45° lat decade−1, which correspond to 11 and 50 km decade−1, respectively, between 1981 and 2016. Given this comparison to Kossin et al.’s (2014) 1982–2009 trend estimates, it would stand to reason that while the SH trend has continued on, the NH LMI poleward migration has halted in the most recent period. This is confirmed by inspection of time series (see Fig. 8). There is also a notable agreement between datasets in the hemispheric-mean trend estimates for poleward migration of LMI in both hemispheres (shown as red horizontal lines in Fig. 3).

Fig. 3.
Fig. 3.

Quantile regressions for the meridional distribution of TC activity in both hemispheres: (a)–(c) Northern and (d)–(f) Southern Hemisphere. The 95% confidence intervals are shown by the shaded regions. Trends from both dataset aggregations are shown: WMO (lighter colors) and NHC–JTWC (darker colors). The maximum and minimum latitudes for each life cycle point at the 20th, 40th, 60th, and 80th percentiles are shown at the bottom of each panel. The red horizontal lines shown the overall mean trends with the WMO mean marked with triangles and NHC–JTWC marked by squares.

Citation: Journal of Climate 31, 11; 10.1175/JCLI-D-17-0852.1

Both datasets also reveal a robust poleward migration of the most equatorward (below the 50th percentile) NH LMI locations (significant at the 95% level in the WMO). By contrast, there are considerable uncertainties concerning migration at the most poleward (above the 50th percentile) TC LMI latitudes in the NH. In SH LMI, there is no robustness in trends below the 40th percentile (most equatorward LMI locations), but both datasets at the 95% confidence level show that the 60% most poleward LMI latitudes are migrating farther southward. Again, this phenomenon occurs at a rate of 0.4° lat decade−1.

NH TC genesis is migrating poleward at a faster rate than the LMI, with a rate of 0.4° lat decade−1. This is confirmed by the two datasets and is robust at the 95% significance level. This trend is dominated by the poleward migration of the most equatorward (below the 50th percentile) half of genesis latitudes, while the trend for the poleward half is not statistically robust. In the SH, while the NHC–JTWC dataset shows a robust trend in the mean genesis latitude of a poleward migration at 0.43° lat decade−1, this trend is not identified in the WMO data.

Quantile regressions for NH ocean basins (Fig. 4) show robust poleward migration in seasonal-mean LMI in WMO data of 0.25° lat decade−1 in the western North Pacific but no such trend in NHC–JTWC. We also find a robust poleward migration of the same magnitude in the lower 50th percentile of seasonal genesis latitudes in both data sources. At the same time, we find no robust trends in the North Atlantic, and this is consistent with Wang et al. (2016) and Kossin et al. (2014) results. In the eastern North Pacific, the poleward migration of TC genesis at 0.45° lat decade−1 is robustly consistent across the distribution. This trend indicates a wholesale poleward shift in TC genesis in this region and compliments with the genesis shift in the western North Pacific. No such corresponding trend is found in LMI. We find that the core of the eastern North Pacific lysis meridional distribution (20th–70th percentiles) follows a statistically significant equatorward trend of 0.33° lat decade−1.

Fig. 4.
Fig. 4.

As in Fig. 3, but for the individual NH ocean basins: (a)–(c) the western North Pacific, (d)–(f) the North Atlantic, and (g)–(i) the eastern North Pacific.

Citation: Journal of Climate 31, 11; 10.1175/JCLI-D-17-0852.1

In the South Pacific, we find a statistically robust mean LMI poleward migration in both datasets of 0.42° lat decade−1 (Fig. 5a). We also find a poleward migration in mean genesis latitudes in NHC–JTWC of 0.58° lat decade−1, but it is not significant in the WMO data. These trends are matched in the south Indian Ocean (Figs. 5d,e,f). We find statistically significant trends in seasonal-mean LMI in both datasets with differing magnitude: WMO has 0.5° lat decade−1, and NHC–JTWC 0.45° has lat decade−1.

Fig. 5.
Fig. 5.

As in Fig. 3, but for the individual SH ocean basins: (a)–(c) the South Pacific and (d)–(f) the south Indian Ocean.

Citation: Journal of Climate 31, 11; 10.1175/JCLI-D-17-0852.1

Taken in aggregate, these trends can be summarized by four major points:

  • A poleward migration of seasonal-mean TC LMI occurs in both the NH (0.1° lat decade−1) and SH (0.45° lat decade−1) in unweighted hemispheric averages.

  • A Pacific-wide poleward migration of seasonal-mean TC genesis occurs (approximately 0.45° lat decade−1).

  • An equatorward shift in seasonal-mean eastern North Pacific lysis occurs by 0.3° lat decade−1.

  • Notable uncertainties remain despite efforts for dataset homogenization and ever-lengthening time series.

4. Results: Hadley circulation extent and comparison to TC latitudes

The climatological divergent winds and meridional overturning in ERA-Interim (Fig. 2) shows that HC extent varies notably from basin to basin. It is particularly more poleward in the western Pacific (WP). Three main centers of action are clear: over the African continent, the Indo-Pacific region, and the Americas. The intertropical convergence zone (ITCZ) is clearly seen with mean values of ψ at 500 hPa approaching zero and convergence in the near-surface wind vectors.

a. Long-term trends

Persistent poleward shifts over the second half of the last century in HC extent are well documented and observable in a number of diagnostics, with the strongest trends identified in the 1980s and 1990s [see review by Lucas et al. (2014)]. Figure 6 shows the annual and TC seasonal-mean time series derived for this analysis (corresponding linear trends 1981–2016 in Table 2). In the annual hemispheric means across the whole period, we find no significant linear trend in any of the three reanalyses in the NH (Fig. 6a). In the SH, the three reanalysis products disagree even over the sign of the trends (Fig. 6b). Trends computed between 1981 and 2005 show a clear poleward shift of approximately 0.8° lat decade−1 in the NH and approximately 0.5° lat decade−1 in the SH, which agrees with estimates derived from streamfunction methods over a similar time period (e.g., Hu and Fu 2007; Johanson and Fu 2009; Allen et al. 2012). Between 1999 and 2009, the annual-mean HC extent in both hemispheres (Figs. 6a,b) is remarkably stable as noted in other studies (e.g., Stachnik and Schumacher 2011; Davis and Rosenlof 2012; Nguyen et al. 2013; Davis and Birner 2013). The period 2010–2016 shows a strong equatorward tendency in the NH, this being the counterbalance to the earlier poleward shifts that results overall in the absence of linear trend between 1981 and 2016 as a whole.

Fig. 6.
Fig. 6.

Time series for HC extent diagnostic at each basin and hemisphere computed in ERA-Interim, JRA-55, and MERRA-2.

Citation: Journal of Climate 31, 11; 10.1175/JCLI-D-17-0852.1

Table 2.

Poleward linear trends (° lat decade−1) in Hadley cell terminus latitudes over 1981–2016 (EP is eastern Pacific). The p values are in brackets (95% confidence level in boldface).

Table 2.

Trends for time series averaged over TC seasons and weighted for TC counts (Fig. 6 c,d) show poleward shifts in both hemispheres of 0.3° lat decade−1. These trends are very robust in the SH with all reanalyses agreeing, and trends exceed a 95% confidence. Interannual variability is much greater in the NH, this being driven by the western North Pacific local HC (Fig. 6g). In individual TC basins, there are no statistically robust poleward shifts consistent in all reanalyses (Figs. 6e–h; Table 2).

Comparing HC and TC poleward trends reveals reasonable overall coherence within a shared relatively tight range of estimated magnitudes. Summarizing, in all but a few cases (in particular in the northern Pacific), HC and TCs have tended poleward together with rates of approximately 0.25° ± 0.1° lat decade−1 (Table 2; Figs. 3, 4, and 5). TCs in the SH exhibit the strongest poleward migration of 0.45° lat decade−1 at LMI, while over the same period, SH HC has shifted poleward at a mean rate of 0.3° lat decade−1. In the NH, while the HC has also shifted poleward at 0.3° lat decade−1 (albeit less conclusively and with much higher interannual variability), TC LMI has shifted at a mean rate of approximately 0.1° lat decade−1.

b. Shared interannual variability

When we directly regress detrended seasonal-mean TC latitudes onto seasonal-mean local HC extent, we find robust statistical covariance across the TC life cycle occurring irrespective of long-term shifts (Fig. 7). In general, we find Pacific and North Atlantic TC genesis shares variability with HC extent (r = 0.6; Fig. 7a). The covariance strength is lower for LMI (r = 0.5; Fig. 7b) and negligible for lysis (r < 0.4; Fig. 7c). Different reanalysis products generally produce similar results, but there are some differences between the two TC observational records.

Fig. 7.
Fig. 7.

Regressions between seasonal-mean HC extent and seasonal-mean TC meridional distribution at different life cycle stages. All time series had their linear trends removed. Pink shading shows regressions that exceed a 95% confidence estimated using two-tailed p values from t statistics. As there are no two independent observational records in the North Atlantic and eastern North Pacific, only the WMO data are shown for these basins.

Citation: Journal of Climate 31, 11; 10.1175/JCLI-D-17-0852.1

In particular, the covariance between genesis and LMI latitudes and HC extent appears to be predominantly a Pacific phenomenon. At genesis, although notable covariance is found with North Atlantic TC latitudes, R2 values are half that of the NH Pacific basins (Fig. 7a). In the south Indian Ocean, there is no notable relationship whatsoever.

Two hemispheric-mean time series demonstrate the covariance strength itself has varied over the period (Fig. 8). For NH HC extent and TC genesis latitudes (Fig. 8a), the period 1981–91 shows remarkable common interannual variability (rolling correlations of 0.9). During the 1990s, the correlation drops to 0.5 as the HC shifts poleward nearly year on year, and genesis latitudes remain remarkably consistent. From 2000 onward, the high correspondence returns. A similar situation is demonstrated for SH TC LMI latitudes (Fig. 8b).

Fig. 8.
Fig. 8.

Time series for both hemisphere’s seasonal-mean HC extent (blue) from ERA-Interim and TC genesis LMI latitudes (red) from the NHC–JTWC observational record.

Citation: Journal of Climate 31, 11; 10.1175/JCLI-D-17-0852.1

This set of regressions is repeated for the equatorward and poleward parts of the seasonal TC latitudes but are not produced here since they are more or less consistent with the means. The exception is that the most poleward quartile {75th percentile [P(75)]} of North Atlantic lysis latitudes are found to significantly covary with local HC extent (r = 0.62). As in the hemispheric case, we see that the observed covariance is time dependent (Fig. 9). In particular, it is very weak in the 1990s but strong in the 1980s and 2000s.

Fig. 9.
Fig. 9.

Time series for the North Atlantic’s seasonal-mean HC extent (blue) from ERA-Interim and TC poleward [P(75)] lysis latitudes (red) from the NHC–JTWC observational record.

Citation: Journal of Climate 31, 11; 10.1175/JCLI-D-17-0852.1

In aggregate, these results indicate that TC genesis and LMI latitudes share long-term trend sign and magnitude with concurrent shifts in local HC extent with rates around about 0.25° lat decade−1. Seasonal-mean TC genesis and LMI mean latitudes in both hemispheres and in all Pacific basins, as well as poleward-extreme North Atlantic lysis latitudes, share about 35% of their interannual variability with HC extent.

5. Results: Hadley circulation intensity and comparison to TC latitudes

a. Long-term trends

HC intensity has been subject to notable debate in the recent past. Thermodynamic scaling arguments predict a weakening of convective mass flux in the tropics resulting from changes in atmospheric humidity (Held and Soden 2006). This is consistent with long-term [O(100) yr] model simulations, although such a weakening has been found to occur preferentially in the zonal (i.e., Walker) circulation rather than in the HC (Vecchi and Soden 2007c). Analyses of HC intensity over the past 30 years have found weak signals of either increasing, decreasing, or no change in estimates, and large uncertainties exist depending on datasets, methodology, and time periods (e.g., Lau and Kim 2015).

Nguyen et al. (2013) studied hemispheric-mean HC in eight reanalyses, including ERA-Interim but not JRA-55 and MERRA-2, for 1980–2009 using streamfunction methods. They found intensification or weakening in NH HC intensity ranging from −0.5 to 12.7 × 109 kg s−1 decade−1. In the SH, trends ranged from −3.2 to 9.0 × 109 kg s−1 decade−1. Between 1981 and 2009, annual-means trends for the present analysis (Figs. 10a,b) in the NH range from −0.1 to 6.8 × 109 kg s−1 decade−1 and in the SH from 0.4 to 5.3 × 109 kg s−1 decade−1. Thus, our estimates largely agree with Nguyen et al. (2013) despite different HC algorithms and reanalysis products.

Fig. 10.
Fig. 10.

As in Fig. 6, but for HC absolute intensity.

Citation: Journal of Climate 31, 11; 10.1175/JCLI-D-17-0852.1

All HC intensity time series exhibit very considerable interannual variability. Annual-mean NH HC shows persistent intensification (Fig. 10a; Table 3), while the seasonal mean (Fig. 10c) shows trend ambiguity until 2005 when ERA-Interim and JRA-55 indicate intensification and MERRA-2 shows rapid weakening. This divergence between reanalyses seems to arise in the western North Pacific (Fig. 10g). Over the entire period, all reanalyses show slight linear strengthening in the SH (Fig. 10d; Table 3), while it is not evident in individual TC basins. Thus, the weakening could be attributed to regions that do not experience TCs such as the African continent or eastern South Pacific. The seasonal-mean NH HC appears to have weakened, with a trend of approximately −10 × 109 kg s−1 decade−1 over the last five years in all three reanalyses.

Table 3.

As in Table 2, but for HC overturning absolute intensity (109 kg s−1 decade−1).

Table 3.

b. Shared interannual variability

Regressions between detrended seasonal-mean HC intensity and seasonal-mean TC latitudes (Fig. 11) do not indicate any robust covariance across hemispheric means in all but one ocean basin. We find a robust link between seasonal-mean eastern North Pacific HC intensity and seasonal-mean latitudes of TC genesis and LMI in all reanalysis products. The same conclusions also hold for the most equatorward and poleward edges of genesis and LMI latitudes.

Fig. 11.
Fig. 11.

As in Fig. 7, but for HC intensity and seasonal-mean TC meridional distribution at different life cycle stages.

Citation: Journal of Climate 31, 11; 10.1175/JCLI-D-17-0852.1

Corresponding time series of TC genesis equatorward-extreme latitudes (Fig. 12) shows strong, time-invariant negative covariance (r = −0.75). A more intense eastern North Pacific HC is associated with equatorward shifts in TC genesis and LMI there. The flow in this basin is strongly influenced by the Walker circulation, orthogonal to the HC, which makes it unlike other basins. This zonal influence might perhaps be related to this anomalous negative covariance. Note also that, over this period, there is no consistent trend across reanalysis products for an intensification or weakening of the local overturning circulation (Table 3), but there is a persistent and very robust wholesale poleward shift in the latitudes of eastern North Pacific tropical cyclogenesis.

Fig. 12.
Fig. 12.

Time series for the eastern North Pacific’s seasonal-mean HC intensity (blue) from ERA-Interim and TC equatorward {10th percentile [P(10)]} genesis latitudes (red) from the NHC–JTWC observational record.

Citation: Journal of Climate 31, 11; 10.1175/JCLI-D-17-0852.1

Summarizing, long-term HC intensity trends (Table 3) show that although there is broad consensus that over the period HC has generally intensified while TCs have migrated poleward, the spread in HC intensity trend estimates is so large (>12 × 109 kg s−1 decade−1) that concluding any coherent relationship is somewhat dubious. Results indicate there is no common interannual variability between seasonal-mean TC latitudes and HC intensity except in the eastern North Pacific.

6. Potential dynamical linkages

Significant uncertainties remain in fundamental understanding of both TCs’ relationship to large-scale climate dynamics and the HC despite it being the oldest known large-scale atmospheric circulation (e.g., Gastineau et al. 2011; Levine and Schneider 2011; Holton and Hakin 2013; Gleixner et al. 2014; Zhan et al. 2017; Yan et al. 2017). It is well understood that TCs are strongly sensitive to both SSTs and VWS (e.g., Murakami et al. 2011; Kossin et al. 2014, 2016; Yan et al. 2017). Regressing the hemispheric-mean HC extent diagnostic against seasonal means of these quantities from ERA-Interim reveals strongly coherent spatial patterns implicated in potential underlying dynamical linkages (Fig. 13).

Fig. 13.
Fig. 13.

Regression coefficients for seasonal-mean (a) SST and (b) VWS (200–850-hPa wind vector difference) against the respective hemisphere’s HC extent diagnostic 1981–2016. The NH data in both panels are over JASO, and the SH data are over JFM. All TC life cycle points over the same period are overlaid in green: genesis in (a) and LMI in (b).

Citation: Journal of Climate 31, 11; 10.1175/JCLI-D-17-0852.1

We see a more poleward HC is linked to reduced meridional SST gradients in all ocean basins and warm SST anomalies at TC latitudes in the North Atlantic, western North Pacific, and South Pacific. There are even slight warm anomalies in the eastern North Pacific and south Indian Ocean SSTs around TC locations despite generally being cooler in these basins on the whole (Fig. 13a). This pattern is remarkably reminiscent of a strong La Niña event (e.g., Lim et al. 2016) and links between an expanded HC and La Niña have been noted before (e.g., Seager et al. 2005, 2010). In idealized numerical experiments, HC extent has been shown to have a complex relationship to absolute SSTs and meridional SST gradients (e.g., Walker and Schneider 2006; Levine and Schneider 2011; Gastineau et al. 2011; Seo et al. 2014).

Tropical VWS generally increases and subtropical VWS generally decreases with a more poleward HC (Fig. 13b). Kossin et al. (2014) arrived at the same result by subtracting zonally averaged composites over 1980–94 and 1995–2010, implicitly linking TC poleward migrations to HC. Here, we arrive at the same general conclusion but additionally reveal strong zonal asymmetries. In particular, we see tropical (subtropical) VWS reduction (increase) in the North Atlantic and western North Pacific (i.e., the inverse of the zonally integrated pattern).

In the eastern North Pacific, we find more intense local HC strongly reduces equatorward VWS (Fig. 14b) and is linked to basinwide warmer SST (Fig. 14a). This environmental change is linked to an equatorward shift in seasonal-mean TC latitudes. With this method, we are able to identify basin-specific heterogeneity, which may explain the differences we observe in trends and covariance. These linkages beg for further analysis.

Fig. 14.
Fig. 14.

As in Fig. 13, but against eastern North Pacific local HC intensity diagnostic.

Citation: Journal of Climate 31, 11; 10.1175/JCLI-D-17-0852.1

Previous works have identified large-scale dynamic and thermodynamic changes modulating TC meridional distribution (e.g., Kimberlain and Elsner 1998; Saunders and Lea 2008; Li et al. 2010; Kossin et al. 2010, 2014; Gleixner et al. 2014; Kossin 2017; Yan et al. 2017). El Niño–Southern Oscillation (ENSO) in particular has been linked to changes in both TC distributions and HC (e.g., Wang and Chan 2002; Chia and Ropelewski 2002; Tao et al. 2012; Oort and Yienger 1996; Nguyen et al. 2013; Seager et al. 2005; Seager et al. 2010). In recent decades, SSTs have been trending toward a La Niña–like anomaly pattern similar to the one identified in Fig. 13a (e.g., Lim et al. 2016).

7. Summary and discussion

We present an analysis comparing seasonal-mean poleward–equatorward migrations of TCs with concurrent changes in HC extent and intensity. Over the period 1981–2016, we find a poleward migration of TC LMI in the NH of 0.1° lat decade−1 and in the SH of 0.45° lat decade−1 in hemispheric averages. While the SH trend is comparable to the previously identified poleward migration there, the NH trend is about a quarter of the magnitude reported by Kossin et al. (2014) for the period 1982–2009. In the last five years, NH LMI latitudes have tended equatorward. We also observe a Pacific-wide poleward migration of seasonal-mean latitudes of tropical cyclogenesis (approximately 0.45° lat decade−1) and an equatorward shift in seasonal-mean eastern North Pacific lysis by 0.33° lat decade−1. These results generally agree with estimates derived in other analyses (e.g., Kossin et al. 2014; Wang et al. 2016; Daloz and Camargo 2017).

Over the same period, both hemispheres’ mean HC extent have shifted poleward at an approximate rate of 0.3° lat decade−1. There are no robust poleward shifts in local HC extent that occur in all reanalyses. However, reanalysis products generally agree on the sign and magnitude of trends. Detecting local trends is challenging in part because of very high interannual variability. Over the entire period, HC intensity averaged over TC seasons has no consistent trend. Reanalyses agree that hemispheric-mean HC overturning has strengthened, although at the resolution of individual TC basins, this is not evident. These findings are broadly in agreement with other works (e.g., Hu and Fu 2007; Johanson and Fu 2009; Stachnik and Schumacher 2011; Allen et al. 2012; Davis and Rosenlof 2012; Nguyen et al. 2013; Davis and Birner 2013).

After removing long-term trends, we find that latitudes of seasonal-mean TC genesis and LMI in the hemispheric mean and in the Pacific basins have approximately 35% of their interannual variability in common with HC extent. We also find that the poleward extremes in North Atlantic TC lysis latitudes and local HC extent share 40% of their detrended interannual variability. HC intensity has little to no relation to TC latitudes everywhere except in the eastern North Pacific, where there is a strong negative covariance. As far as we are aware, this is the first attempt to derive statistics of this type. Thus, we find quantitative evidence for concurrent TC and HC meridional shifts at both interannual and long-term time scales. Notable issues remain with available data, and uncertainty is considerable.

At the hemispheric scale, we find a more poleward HC is linked to reduced meridional SST gradients and warm SST anomalies at TC latitudes in such a way as to resemble a La Niña–like oceanic state. This corresponds to tropical (subtropical) VWS generally increasing (decreasing). Locally, the inverse is observed in the North Atlantic and western North Pacific. Projections into the next century find trends toward weakened zonal SST gradients (i.e., El Niño–like) and in fact failed to produce the recently observed La Niña–like trends (e.g., Xie et al. 2010; Collins et al. 2013). Thus, it could well be that poleward–equatorward migrations in TCs and HCs reverse in the near future. However, there is significant model uncertainty in long-term ENSO simulations (e.g., Kociuba and Power 2015; Chen et al. 2017; Rashid and Hirst 2016). Additionally, changes to TC latitudes relative to large-scale dynamic conditions such as HC may well change rates of extratropical transition (Mokhov et al. 2014; Evans et al. 2017).

Aside from outstanding dynamical questions, various issues surrounding diagnostics remain important. When studying uniformly weighted hemispheric zonal-mean TC statistics as we do, interbasin changes in TC frequency can impact results. It is known that such changes contribute equally to poleward migration as those of environmental changes (Kossin et al. 2014; Moon et al. 2015). Changes in genesis locations affect the number of recurving TCs and thus have a strong impact on life cycle latitude metrics such as LMI (Wang and Chan 2002; Elsner and Liu 2003; Chan and Liu 2004; Sobel and Camargo 2005; Camargo et al. 2007; Yonekura and Hall 2014). Thus, while direct impact of large-scale SST patterns (e.g., ENSO) on TCs are mainly found in genesis locations, this signal is projected onto subsequent TC tracks and in the TC meridional distributions throughout the life cycle (Yonekura and Hall 2014).

Some scholars have concluded that contemporary models are capable of simulating TCs with acceptable veracity (e.g., Zhao and Held 2010; Murakami et al. 2013, 2015; Han et al. 2016). However, using modeling to study HC, ITCZ dynamics, and TC tracks remains a difficult undertaking since characteristic spatial scales are orders of magnitude apart. In this respect, there is much work to be done to improve physical understanding and projections of future HC and TC track changes (e.g., Levine and Schneider 2015; Daloz et al. 2015). In this regard, hypohydrostatic rescaling and its effect of altering the aspect ratio of resolved eddies, bringing them closer to those of the unaltered large-scale, nearly hydrostatic flow, may prove great utility in near-global simulations of TCs and large-scale climate and advancing fundamental understanding (Boos et al. 2016; Fedorov et al. 2018).

Acknowledgments

The authors thank Kevin Hodges very much indeed for the in-depth and helpful discussions and reading of the manuscript that have led to great improvements. Conversations with Alexey Fedorov and Xavier Levine about Hadley circulation dynamics and the interaction of TCs with large-scale climate are also recognized and very much appreciated. Also, James Kossin and Carl Schreck III for very useful conversations and guidance on handling the many nuances of the tropical cyclone observational record and IBTrACS data. Likewise, we thank Hanh Nguyen very much for friendly discussions about diagnostic algorithms for Hadley circulation. We much appreciate the extremely helpful comments and suggestions of the anonymous reviewers and the editor John Chiang for having helped to improve the manuscript immensely. Finally, we thank NASA, ECMWF, and JMA for releasing their data to the public and the open-source Python and data-analysis community. This work was funded through the Agreement 14.W0331.006 with Ministry of Education and Science of the Russian Federation and Grant 14-50-00095 from the Russian Science Foundation.

APPENDIX

Algorithms for Diagnosing Zonally Asymmetric Hadley Circulation

In a zonally asymmetric HC, extent is notably harder to robustly identify than in the hemispheric zonal mean. In the latter, Hadley cell termini can be identified with the ψ500hPa = 0 isoline, whereas in the former, this line is not necessarily crossed at all. To account for this, we implemented and built upon the approach of Nguyen et al. (2018). We detail this in the methods section. In implementing this algorithm, it became clear that a few notable “edge cases” exist where unexpected results are produced. We document these here for two reasons. First, it is clear that the specifics of any diagnostic algorithm have a strong effect upon the resultant time series. Therefore, explicitly demonstrating how they work is important for clarity. Second, we include this appendix to aid reproducibility.

The first case is when a second maximum in the overturning exists in the midlatitudes of the same sign as the tropical cell. The HC over the western Pacific warm pool region is a particular example of this (Fig. A1a). This second higher-latitude maximum is often greater in magnitude than its tropical counterpart. The weakening threshold algorithm we implement here does a good job at identifying the terminus (blue vertical line at 28°N) despite this second maximum and the fact that the zero isoline is never crossed. This situation seems to occur when the local HC is merged or dominated by monsoonal flow in the boreal summer.

Fig. A1.
Fig. A1.

Monthly mean meridional mass flux streamfunction derived with the divergent winds in ERA-Interim and the identified termini of the Hadley cells. (a) The western Pacific in July 1980 and (b) the Atlantic in August 1989.

Citation: Journal of Climate 31, 11; 10.1175/JCLI-D-17-0852.1

The second case we highlight is shown in Fig. A1b. This occurs when the local Hadley cell is particularly weak and does not penetrate deep into the troposphere. Classical definitions of Hadley cell termini are defined relative to a vertical average between 600 and 400 hPa or a slice at 500 hPa (e.g., Stachnik and Schumacher 2011). Using an algorithm based on the weakening between 800 and 400 hPa captures these shallow weak overturning cells well (see blue NH vertical in Fig. A1b).

As noted above, the absolute values for the latitude of HC extent that this algorithm detects are typically lower than the classical zero isoline variant. However, the variability of HC is better captured, and configurations of atmospheric overturning that are beyond the classical definition’s scope are accounted for.

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