# Poleward expansion of tropical cyclone latitudes in warming climates

Joshua Studholme, Alexey V. Fedorov, Sergey Gulev, Kerry Emanuel, Kevin Hodges

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Joshua Studholme, Alexey V. Fedorov, Sergey Gulev, Kerry Emanuel, Kevin Hodges. Poleward expansion of tropical cyclone latitudes in warming climates. Nature Geoscience, 2022, 15 (1), pp.14-28. 10.1038/s41561-021-00859-1 . hal-03560276

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# Poleward expansion of tropical cyclone latitudes in warming climates

Article

Accepted Version

Studholme, J., Fedorov, A. V., Gulev, S. K., Emanuel, K. and Hodges, K. ORCID: https://orcid.org/0000-0003-0894-229X (2022) Poleward expansion of tropical cyclone latitudes in warming climates. Nature Geoscience, 15. pp. 14-28. ISSN 1752-0894 doi: 10.1038/s41561-021-00859-1 Available at https://centaur.reading.ac.uk/101025/

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POLEWARD EXPANSION OF TROPICAL CYCLONE

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LATITUDES IN WARMING CLIMATES

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‘In principle accepted’ as a review article for Nature Geoscience

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Initial submission December 2020.

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Revisions prepared April, May, June 2021.

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Further revisions prepared September, October 2021.

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Joshua Studholme*, Yale University, CT, USA.

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Alexey Fedorov, Yale University, CT, USA.

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Sergey Gulev, *Shirshov Institute of Oceanology, Moscow, Russia*.

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Kerry Emanuel, *Massachusetts Institute of Technology, MA, USA*.

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Kevin Hodges, *Reading University, Berks., UK*.

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*Corresponding author email - joshua.studholme@yale.edu

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24 Abstract

25 Tropical cyclones (TCs, aka hurricanes and typhoons) generally form at low latitudes with
26 access to the warm waters of the tropical oceans but far enough off the equator to allow
27 planetary rotation to cause aggregating convection to spin up into coherent vortices. Yet,
28 current prognostic frameworks for TC latitudes make contradictory predictions for climate
29 change. Simulations of past warm climates, such as the Eocene and Pliocene, show TCs
30 forming and intensifying at higher latitudes than preindustrial conditions. Observations and
31 model projections for the twenty-first century indicate TCs may again migrate poleward in
32 response to anthropogenic greenhouse gas emissions, posing profound risks to the planet's
33 most populous regions. Previous studies largely neglected the complex processes occurring at
34 temporal and spatial scales of individual storms since these are poorly resolved in numerical
35 models. Here we review this mesoscale physics in the context of the responses to climate
36 warming of the Hadley circulation, jet streams and Intertropical Convergence Zone (ITCZ).
37 We conclude that twenty-first century TCs will likely occupy a broader range of latitudes
38 than over the last 3 million years as low latitude genesis will be supplemented with increasing
39 midlatitude TC favourability, although precise estimates for future migration remain beyond
40 current methodologies.
41 Tropical cyclones (TCs) start as O(10⁴) km² clusters of individual thunderstorms weakly
42 rotating around a common axis. The transition into a TC involves increasing vorticity by two
43 orders of magnitude to produce surface winds over 15 ms⁻¹[¹].; although it may take weeks for
44 disaggregated convection to fully transform into a cyclone[²]. Once formed, TCs generally
45 move poleward and westward before interacting with midlatitude westerlies and weather
46 systems, and in some cases transitioning into frontal systems (Fig. 1). Locally, the physics of
47 evaporation, friction, convection, entrainment, and radiation determine the vortex
48 lifecycle[³][⁴]. Box 1 summarizes these core elements in TC formation, intensification, and
49 propagation – the TC lifecycle. How this local physics and the equator-to-pole TC
50 distribution relate to one another has been discussed for at least a century[⁵] and yet
51 fundamental disagreement about how TC latitudes depend on climate persists[⁶]. In this
52 review we will synthesize recent advances and attempt to connect the heuristic view above
53 with a well-defined physical basis for TC latitudinal distribution.

54 One of the central outcomes of this review is to establish the fundamental roles that
55 convective mesoscale processes play in linking climatological TC occurrence to large-scale
56 atmospheric dynamics in different climates. This emergent view is novel because the
57 lifecycle evolution of TCs, and its intrinsic mesoscale processes, have historically been
58 overlooked in TC climate studies. Instead, the focus has been on whether or not TCs would
59 emerge from a given climatology of wind, temperature, and humidity[7] (see section
60 ‘Tropical Cyclogenesis as a Dynamical Process’). This well-established framework is
61 underpinned by empirical ‘genesis potential indices’ (GPIs) - best-guesses at the functional
62 forms and coefficients for controls on TC formation that are calibrated against the observed
63 TC distribution. Often GPIs are used in tandem with simple TC models either passively
64 propagating cyclones through environmental winds (see Box 1) and neglecting their two-way
65 interactions with the atmospheric environment (known as ‘statistical downscaling’) [⁸].
These diagnostic methods are adopted in part because climate simulations with General Circulation Models (GCMs) struggle to resolve realistic TCs[9]. A contrasting approach nests higher resolution models within lower resolution ones (known as 'dynamical downscaling'). Both dynamical and statistical downscaling approaches are used to enumerate how past, present, and future climates produce TCs (see section 'Past, Present, And Potential Latitudinal Migrations'). The problem is that these contrasting approaches yield vastly differing interpretations of twenty-first century climate projections[10, 11, 12, 13] which thus establishes the necessity for prognostic understanding of the relationship between TCs and climate[6]. In this review, we conclude that a joint consideration of the convective mesoscale processes occurring within TCs and the large-scale dynamics of the atmospheric Hadley circulation, Intertropical Convergence Zone (ITCZ) and tropospheric jet streams enables a new framework for understanding the relationship of TCs to climate (see section 'Linking Mesoscale Physics to Large-Scale Climate Dynamics'). As discussed later, these links have implications for reducing uncertainty in projections of twenty-first century TCs.

## 81 TROPICAL CYCLOGENESIS AS A DYNAMICAL PROCESS

As a core methodology in modern TC-climate studies, GPIs reproduce the broad-brush characteristics of observed TC genesis, particularly at the basin averaged scale[3]. GPIs do significantly worse at reproducing characteristics of TC genesis simulated in GCM simulations[9, 14]. We note that while appropriate GPI formulations should only use variables explicitly relevant to TC physics, they often use free tropospheric relative humidity rather than water vapor saturation deficit (or free tropospheric dryness relative to the boundary layer) as the moisture variable despite the established physical relevance of the latter but not the former[15]. While GPI variants perform equally well in reproducing TC genesis patterns of current climate, they diverge in describing future changes[15]. Moreover, the greenhouse
warming response of an individual state-of-the-art GPI, that used the physically consistent moisture variable of saturation deficit, was shown to change sign when the empirical coefficient for that variable was modified without degrading the fit to observations[11]. More troubling still, the statistical relationship between the time-mean environmental fields used to calculate GPIs and TC distribution is not necessarily consistent between the observations and models, and between models using different dynamical cores, resolutions, and physics[16, 17].

Behind GPIs is the assumption that climatological tropical cyclogenesis, approximated as genesis potential, is a localised process. This assumption therefore abstracts away the complex set of planetary, synoptic, and mesoscale processes that give rise to the observational distributions against which GPIs are calibrated. The problem is that these processes resulting in cyclogenesis and intensification occur over a wide range of overlapping spatial and temporal scales and can be dislocated from one another[16, 18, 19, 20] (see Extended Data Figs. 1 and 2 for examples). This issue likely gives rise to the aforementioned apparent limitations of GPIs. Thus, to generate fundamental understanding of physical controls over TC distribution with robust prognostic skill requires making explicit the links between the synoptic and mesoscale processes inherent to TCs and the large-scale dynamics within which they emerge, intensify, and dissipate.

It is remarkable that the relationship between convective mesoscale processes underpinning TCs and large-scale dynamical structures has been largely ignored[21] since the first GPI was published in 1979[7]. This is all the more striking because much observed TC genesis is embedded within the belts of climatological convection that are very well studied: roughly 70% of first recorded TC positions occur within the ITCZ (inside the green contour in Fig. 2a). Idealised simulations, historical evidence, and paleo-climatological reconstructions[23, 24, 25] all find strong relationships between ITCZ characteristics and TC frequency.
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Diversity in TC genesis mechanisms (Fig. 1) is part of this problem and presents a
challenge for deriving a simple prognostic framework for TC genesis and intensification.

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While typically TC genesis occurs in non-baroclinic large-scale environments, 30% of
genesis events do involve baroclinic influence[26]. Globally, one in six TCs form via ‘tropical
transition’ whereby transient upper tropospheric disturbances trigger deep convection and
low-level moisture convergence upon coinciding with lower tropospheric lows[27] (Fig. 1b
and Extended Data Fig. 2). This process is possible over much lower sea surface
temperatures (SSTs, < 17°C) and at higher latitudes (>40 °N) than canonical TC genesis[28].

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These upper tropospheric disturbances originate from anticyclonic wave breaking following
planetary wave amplification and thus have strong, established sensitivity to planetary
warming[29]. GPIs computed at higher frequency can capture some of these ‘non-traditional’
genesis pathways, including polar lows and Mediterranean hurricanes[30] (Extended Data Fig.

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3), but these routes are poorly captured by GPIs computed from monthly mean variables as is
done nearly universally. Significantly, genesis pathways that are marginal in the present day
may have been non-marginal in the past and may become non-marginal again as climate
warms[31, 32, 33, 34].

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Most non-canonical genesis pathways occur on the poleward edge of the TC
distribution. On the equatorward side, convectively coupled equatorial waves (CCEWs),
easterly waves (EW) and the Madden-Julian Oscillation (MJO) play a critical role in TC
genesis and intensification[4], which further complicates analysis of climates' TC
favourability. These synoptic and mesoscale convective phenomena can all trigger convective
aggregation but also interact with each other [35]. CCEWs are estimated to be involved in
~85% of North Atlantic and western North Pacific TC genesis events[36, 37], enabling the
necessary convective organisation for genesis[38]. However, this may simply determine the
location and timing of genesis, not overall TC frequency[39]. Indirectly, CCEWs can

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condition the atmosphere to either encourage or suppress TC genesis locally as their
convective anomalies modulate vorticity, temperature, moisture, and wind shear at a range of
scales. They also induce remote responses[40.][41.][42.]
such as far-field suppression of TC
potential intensity (PI; see Box 1) via upper tropospheric temperature homogenisation
maintaining weak horizontal temperature gradients in the tropics (the WTG; see Box 1).

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PAST, PRESENT, AND POTENTIAL LATITUDINAL MIGRATIONS

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(a.) *Paleoclimate reconstructions and modelling*

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At geologic timescales, it is likely that the secular cooling throughout the Cenozoic (the past 66 million years) resulted in the contraction of latitudes with both high genesis potential and PI towards the equator in both hemispheres (Fig. 3)[43.]. This would have been coincident with contraction of the Hadley circulation and equatorward shifts in the subtropical jet streams[43.]. During the Early Eocene climate optimum (53-51 million years ago) – the warmest prolonged climate interval of the Cenozoic – paleo-proxies show atmospheric CO₂ concentrations around 1400 ppm (with a very large uncertainty range[44.]). This may have resulted in the equator-to-pole temperature gradient being up to 10 °C flatter than the modern era[45.][46.] and summertime surface continental temperatures in the Arctic reaching ~23 °C[47.]. During the geologically brief Paleocene-Eocene Thermal Maximum (PETM, ~55 mya), these differences were likely even more exaggerated[48.][49.].

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While the circulation dynamics associated with Eocene climate remain under
debate[45.][50.], available reconstructions and climate models forced with Eocene continental
configuration and CO₂ concentrations suggest increased extratropical humidity, poleward jet
stream shifts, and Hadley circulation expansion relative to present[43.][47.][51.][52.][53.]
This
implies a marked poleward expansion of areas favourable to TC formation and intensification
(Fig. 3; Extended Data Fig. 4). Eocene simulations show genesis potential centred around the

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subtropics (~25 degrees latitude) in both hemispheres in contrast to the modern era where it dominates the deep tropics (~10 degrees latitude)[³⁴.][⁴³.] (Fig. 3c). Moreover, a recent PETM simulation using a 25 km horizontal resolution atmospheric GCM shows very strong suppression of low latitude TCs, and both hemispheres' midlatitudes (30-60 degrees latitude) producing many TCs[³⁴.] (Figure 3b). These results agree with cloud-system resolving simulations of an idealized Eocene-like climate[³².] (Fig. 5, yellow line).

Contemporary TC distributions were likely established sometime towards the end of the warm Pliocene[⁴³.][⁵⁴.] (2.6-5.3 million years ago). For most of this period, proxy-based reconstructions indicate atmospheric CO₂ concentrations 350-450 ppm[⁵⁵.], latitudinal SST gradients up to 5°C degrees flatter than present[⁵⁶.], and surface westerlies weaker and possibly more poleward[⁵⁷.]. In addition, Pliocene climate may have featured an expanded low-latitude warm pool, reduced equatorial and coastal upwelling, weakened Hadley circulation, and TC activity enhanced and shifted poleward relative to present[⁵⁴.][⁵⁸.][⁵⁹.][⁶⁰.]. During the late Pliocene, atmospheric CO₂ decline among other factors led to the establishment of colder climate patterns culminating with the onset of northern hemisphere glaciation[⁶¹.]. This marked the start of a period, ending in the present century, when latitudinal variations in TCs became more muted and were primarily controlled by orbitally driven insolation changes and resultant glacial cycles, shorter millennial climate variability, and varying aerosol emissions.

GCMs forced with continental ice sheet reconstructions and low atmospheric CO₂ concentrations (185 ppm) indicate that the planet's TC distribution during the Last Glacial Maximum (LGM, 21 k.y.a) was not significantly different from the present day albeit mean TC intensity was likely lower[⁶².][⁶³.][⁶⁴.]. These models however disagree over large-scale atmospheric circulation structure, specifically over whether the southern hemisphere subtropical jet was poleward or equatorward relative to modern and whether atmospheric
convection in western Pacific was stronger or weaker[65.][66.]. Since the LGM, multi-millennial scale TC variability was likely dominated by the slow increase in the boreal summer equator-to-pole insolation gradient until ~10 kya and the subsequent decline associated with orbital precession[67.]. The increased insolation gradient at the precession minima (~10 kya) may have caused amplified tropical convection and strengthened midlatitude jets[68.][69.][70.][71.]. This seems to correspond to suppressed genesis potential of the most equatorward TCs[67.].

Orbitally driven variations were punctuated by millennial-scale abrupt climate changes, including the cold Heinrich and the Younger Dryas events. The slowdown of Atlantic Meridional Overturning Circulation[72.] (AMOC) typically associated with those events cooled the North Atlantic, suppressing PI[67.]. The increased meridional temperature gradient in the northern hemisphere would have led to an intensification and equatorward shift of both the subtropical jet and Hadley cell[73.][74.], presumably suppressing higher latitude TC genesis and intensification[67.]. Changes in large-scale climate over the last 21 thousand years (CO₂ ~180-280 ppm) were likely smaller in comparison to changes driven by atmospheric CO₂ since the Eocene (CO₂ ~500-2000 ppm) and Pliocene (CO₂ ~300-500 ppm): in particular, mean ITCZ shifts since the LGM were probably less than 1 degree latitude[75.].

Atmospheric aerosols provide an additional control on shorter timescales. They were suppressed during the “green Sahara” period centred around the mid-Holocene[76.][77.] (6 k.y.a.) but sporadically increased following volcanic eruptions[25.][78.]. Mineral dust has hemispherically asymmetric impacts on temperature, and consequentially ITCZ location[79.] and tropical cyclone latitudes[25.]. Further north, reduced dust increases SSTs, which results in PI increases and poleward jet shifts expanding regions of tropical cyclone favourability[25.][76.][77.]. Moreover, North Atlantic TCs were probably shifted poleward relative to present as Sahara greening caused a poleward displacement of easterly waves[76.][77.].
Over the last two thousand years, model simulation based GPI and PI show no secular trends prior to the Industrial Revolution[78.][80.]. Integrated Atlantic paleo-tempestological records (16 – 32 °N) however suggest persistent poleward migration of eastern tropical Atlantic TCs over the last 450 years in concert with ITCZ poleward migration[81.]. Other records show TC activity shifting from the Caribbean and Gulf of Mexico toward the Bahamas and New England around A.D 1400, correlated with warm central tropical Atlantic SSTs prior to this shift and a relatively warmer western North Atlantic afterwards[82.]. This would have been coincident with high basin-integrated TC activity in the Medieval Warm Period (MWP; A.D. ~900 – 1450) followed by a lull during the Little Ice Age[83.] (LIA; A.D. ~1450 – 1850). Paleo-reconstructions and historical evidence imply poleward western North Pacific TC and ITCZ shifts during the MWP and equatorward shifts during the LIA[24.][84.]. The North Atlantic poleward and western North Pacific equatorward TC shifts across the MWP-LIA transition occurred, presumably, with Pacific warm pool cooling, Pacific Walker circulation weakening, East Asian summer monsoon weakening and a narrowing and southward shift in the ITCZ[84.][85.]. Finally, tree rings suggest a secular twentieth century TC poleward migration in the western North Pacific (33-45 °N)[86.].

TC activity may also fluctuate with changes in ENSO, Atlantic Multidecadal Variability (AMV) and the Pacific Decadal Oscillation (PDO) over centennial and millennial timescales[83.][87.]. The MWP-LIA transition arguably marked an increase in ENSO amplitude, a change from predominately negative to predominately positive AMV, and change from a persistent negative PDO state to a muted PDO signal (ref. [88.] reviews these modes throughout the Holocene). Most casual interpretations of TC latitudinal variability in the paleo-records over centennial to millennial timescales are understood via connections to the ITCZ, often mediated by ENSO variability[24.][81.][89.]. Further, TC coupling to large-scale stationary circulation features like the subtropical highs is also recognised[25.][81.][90.].
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We stress that reconstructions of TCs throughout Earth's history suffer large
uncertainties. Model biases and uncertainties in boundary conditions and radiative forcing
diminish the utility of climate simulations and their GPI estimates. There is even continued
debate over how TCs are identified and tracked in these numerical simulations[13].

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Conversely, proxy-based TC reconstructions only record local storm transits and are biased
towards intense events near coastlines[91.], while centennial variability in individual
paleorecords of intense TCs may be random and not reflective of large-scale climate
dynamics[92.]. Thus, synthesising paleo-hurricanes records is important, yet complicated by
significant spatial under-sampling[93.].

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(b.) *Poleward TC migration in recent observations*

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Subtle but robust poleward trends of 53 ±43 and 62 ±48 km per decade[94.] in TC
seasonal-mean LMI latitudes are detectable in observations of the northern and southern
hemispheres respectively (1982 to 2012). While these estimates are largely drawn from
analyses of the IBTrACS archive, which aggregates multiple records, such poleward
migration is found across different datasets and also for genesis latitudes[94.][95.][96.]. The
magnitudes of these trends depend on the period and TC intensity considered[94.]. Life-time
maximum intensity is used since it does not rely on absolute intensity magnitudes which are
inconsistently recorded and poorly represented in reanalysis[94.][97.]. Dynamical reanalysis
data reproduce TC LMI latitudes mostly within a few degrees of observations[97.]. However,
simulated TCs tend to persist too long into high latitudes where they expand radially and
become better resolved thus achieving higher intensities there and distorting higher latitude
(>30 °) LMI estimates[97.]. Thus, satellite-based records provide the most reliable source for
trends in TC latitudes.

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Over half the recently observed poleward migration is explained by inter-basin frequency changes (Fig. 2d), with the North Atlantic (average LMI 2,800 km from the equator versus hemispheric mean of 2,150 km) and South Pacific (1,990 km vs 1,900 km) increasingly producing more cyclones relative to other basins in the same hemisphere[94.][98.].

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Poleward migration is also not uniform over LMI latitude percentiles[96.] and one of the most equatorward hurricanes on record occurred in 2016 (Hurricane Pali, ~2.3°N). These present-day trends appear to be associated with changes in both the ocean (SST patterns; Fig. 4a), and atmospheric thermodynamics (PI; Fig. 4b), and dynamics (vertical shear, large-scale tropospheric winds)[94.][96.][99.]. Additionally, genesis potential has increased during this period (Fig. 4e). Twentieth-century global-mean SST increases may have forced increases in storm radii in the western North Pacific TCs[100.]. These larger TCs tend to propagate further poleward following increased beta drift (Box 1) and interaction with the subtropical highs and tropical upper tropospheric troughs (TUTTs)[101.]. These poleward migration trends are coincident with increase rates of observed extratropical transition[102.].

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In addition to observed gradual poleward migration, pronounced transient zonal and meridional TC migrations occur in response to ENSO, PDO and AMV cycles[103.]. During negative PDO phases (warmer SSTs in the western and central subtropical Pacific), maximum PI latitudes extend poleward, encouraging higher latitude Pacific TC genesis[104.].

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Poleward migration of North Atlantic TCs associated with ENSO occurs following both dynamic and thermodynamic suppression of low latitude TCs. During El Niño, Pacific Walker circulation weakening intensifies upper-tropospheric westerlies over the North Atlantic amplifying vertical wind shear over the Caribbean and eastern Northern Pacific[105.][106.], while CCEWs originating in the Pacific push the tropical North Atlantic atmosphere out of thermodynamic equilibrium with its underlying SSTs to suppress TC genesis[41].

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Over the past three to four decades the west-east equatorial SST gradient across the tropical Pacific has strengthened, with the eastern equatorial Pacific getting colder while the western Pacific warmer, and the Walker circulation intensified[¹⁰⁷,][¹⁰⁸,][¹⁰⁹]. This trend pattern may reflect a negative PDO phase with possible contributions from aerosol effects and a thermostat-like response to greenhouse gas forcing[¹⁰⁹]. Transition to a positive AMV circa A.D. 2000 [¹⁰⁸,][¹¹⁰.] and greater inter-basin temperature contrasts[¹⁰⁷.] are also invoked to explain this strengthening of the Walker circulation. Regardless of the cause, the stronger Pacific Walker circulation has intensified vertical wind shear over the equatorial central Pacific and the deep tropical North Atlantic, contributing to TC poleward migration[⁹⁸,][¹¹⁰].

In contrast, by century's end, a relaxation of the SST gradient across the Pacific with pronounced eastern equatorial Pacific warming and corresponding weakening of the Walker circulation are projected in nearly all CMIP6 models[¹⁰⁹]. All else being equal, this would correspond to lower vertical wind shear over the equatorial central Pacific and equatorial North Atlantic, an equatorward ITCZ shift and thus encouraged low latitude TC formation and intensification.

### (c.) Simulated climate change

Idealised aquaplanet TC simulations (no continents, see ref.[²³] for a review) have been conducted with atmospheric models and fixed SSTs or simplified ‘slab-ocean’ representation of fixed oceanic heat transport (via the ‘q-flux’ abstraction). These simulations generally neglect zonal climate asymmetries and the seasonal cycle and have other limitations. For example, only models with dynamic oceanic heat transport can provide strong negative feedback on ITCZ displacements. Consequentially, changes in ITCZ position and strength under variable climatic forcing differ dramatically between aquaplanet and fully-coupled simulations – in the former the ITCZ can move poleward by 10-20 degrees latitude,
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while in the latter ITCZ intensity changes but its shifts do not exceed ~1 degree[111]. In
addition, aquaplanet ITCZs are sensitive to model resolution and convective
parameterisation [112].

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Nevertheless, aquaplanet simulations with imposed atmospheric cross-equatorial heat transport variations suggest a TC genesis scaling of a 40 % increase in global TC frequency per degree of latitude of poleward ITCZ shift[113]. However, increases in TC genesis can occur on warming aquaplanets even with an equatorward ITCZ shift as changes in the subtropical jet and reductions in midlatitude baroclinicity increase the likelihood of TC genesis (Fig. 5). Aquaplanet TC activity appears to be correlated with atmospheric static stability but is only sensitive to vertical shear above a certain threshold value (~5 m s⁻¹; [114]). The climatological relationship of TC latitudes with PI seems to be weak and non-monotonic[31, 32, 114]. Rather, poleward migrations reflect the aerial expansion of high (>70 m s⁻¹) PI values. These poleward migrations follow tropical expansion, but not simply the concurrent dilation of the Hadley circulation[33].

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Full continent slab-ocean, statistical downscaling experiments with large CO₂ increases (x8 and x32 preindustrial concentration) show LMI poleward migration (1.6°, 7.4° respectively) and prolonged TC lifecycles[31]. Overall maximum PI does not increase with these hyper-exaggerated warnings (consistent with ref. [114]). This statistical downscaling method involves inserting O(10⁶) artificial random weak vorticity anomalies (referred to as TC ‘seeds’) over the global ocean in an effort to simulate realistic pre-TC disturbances which – as we stress above – may come from a number of spatially and temporally variable processes, potentially poorly resolved in GCMs (Fig. 1 and Box 1). Most of these artificial vorticity anomalies decay rapidly, but a few survive and are then passively advected by the large-scale winds and beta drift. Computing the thermodynamics of these vortices yields the corresponding TC lifecycle (i.e. the progression through genesis, intensification and

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cyclolysis; this methodology does not represent extratropical transition). The results from this
approach depend on the number of “seeds” used and thus this method requires calibration to
reproduce realistic TC frequency<sup>[115.]</sup>

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Some coupled 2x and 4x CO₂ experiments with dynamically simulated TCs exhibit small poleward shifts of several degrees of latitude in the northern hemisphere[116.], but other coupled 2xCO₂ experiments find zonal, but not poleward TC migration[16.]. Ref. [16.] find that in these experiments the pre-TC synoptic and convective mesoscale disturbances, defined as seasonal variance in 3-10 day bandpassed 850 hPa vorticity, are the principle atmospheric driver of TC frequency responses in increasing CO₂ simulations. Such TC source disturbances are found to be highly concentrated within climatological convection (the ITCZ and Pacific Warm Pool) with potential links between their frequency and time-mean local tropospheric pressure velocity, ω̄[1]. This result contrasts with statistical downscaling methods that assume a constant number of TC “seeds” (the artificially inserted pre-TC source disturbances), but does not invalidate the random seeding approach as long as the “seeds” are sufficiently weak and numerous.

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Attribution work using coupled models finds that recent TC distribution changes are very likely anthropogenically forced[117.]. However, CMIP5 models and various regional downscaling experiments project a range of 21st century TC migration scenarios from no further migration, to poleward LMI migration of a few degrees (but less than the 5 degrees implied by continuation of the ½ degree per decade trend[94.]), and zonal migration of Pacific TCs[118.][119.]. Early analysis of CMIP6 finds no consensus on 21st century distribution changes in explicitly resolved TCs[13.] but statistical downscaling shows poleward migration in the northern hemisphere, particularly in the North Atlantic[11]. Climate models' dynamically resolved TC activity is projected to be globally suppressed by greenhouse gases; however, statistical downscaling predicts increases in line with monthly-mean GPI values

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that reflect increasing PI and decreasing wind shear tempered against increasing mid-
tropospheric relative dryness[11.][12.][120.].

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Some broad patterns in end-of-century TC predictions have been established, although
the statistical reliability of these findings depends upon the selection of climate models
studied. In the northern hemisphere, TC poleward shifts of a few degrees in the North
Atlantic and both sides of the North Pacific alongside the suppression of the most western of
Pacific TCs is found in some but not all analyses[102.][121.][122.]. This is accompanied by a shift
in Pacific TC activity towards the central Pacific[123.] and increasing recurvature of western
North Pacific TC tracks[118.][124.]. Southern hemisphere projections show no clear deviation in
TC genesis latitudes between current and future climate[11.][119.]. However, statistical
downscaling of CMIP6 models shows a significant poleward expansion of TC activity both in
the North Atlantic and South Indian oceans[11.]. All these projections of increased high
latitude TC activity under greenhouse warming are consistent with other projections of
increased rates and intensity of extratropical transition in the western North Pacific and North
Atlantic[125.][126.][127.]. Additionally, TC translation speed is projected to decrease over the 21st
century, following poleward shifts in the midlatitude westerlies, which would increase
midlatitude TC track density[128.].

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While GCMs do reproduce modern TC climatologies reasonably well, strong errors
persist particularly at the distribution edges[117.][118.][119.]. Models overestimate historical
genesis rates in the central North Pacific and the southern hemisphere but underestimate
eastern North Pacific and North Atlantic TCs[11.][13.][129.]. Although SST patterns are
considered the principal cause behind spreads in projected TC climatologies[12.][16.], this
implicates a complex set of processes such as AMOC slowdown and radiative feedbacks.
Moreover, inter-model spread in projected SSTs cannot account entirely for the lack of

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consensus and another likely factor is differences in models’ representation of atmospheric

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deep convection[129.][130.]

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LINKING MESOSCALE PHYSICS TO LARGE-SCALE CLIMATE DYNAMICS

393

An emergent hypothesis explaining recent TC poleward migration relates it to observed

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tropical expansion through the areal expansion of low vertical wind shear and high PI regions

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of the subtropics[94.]. This invokes changes in the latitudes of the descending branches of the

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Hadley circulation and midlatitude jet streams. PI has increased in recent decades (Fig. 4b)

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and model simulations indicate that changes in TC distribution track the aerial expansion of

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high PI values[78.][114.]. Such an expansion, which follows increasing modified Carnot

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efficiency and lower TC outflow temperatures (Box 1), is present in the recent record (Fig.

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4d,f). These results broadly agree with the Eocene and Pliocene model reconstructions

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showing wider tropics during those epochs coincident with higher latitude TC activity.

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However, assumptions of tropical expansion *causally driving* TC poleward migration require

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careful examination[33.]. As the limitations of GPIs and existing frameworks have shown, the

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challenge lies in integrating the sensitivity of convective mesoscale processes to planetary

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temperature with the summertime mean circulation’s broader sensitivities, including the jet

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stream shifts, Hadley cell expansion and ITCZ changes[131.][132.][133.], each driven by their own

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distinct set of dynamics.

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One major confounding aspect of process-based understanding of recent subtropical

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decrease in vertical wind shear and increase in PI[94.] is the link – or lack thereof – between

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changes in the Hadley cells and the subtropical jet. A ~1/2° per decade poleward expansion

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of the Hadley cells, normally shorthand for ‘the tropics’, can be identified in several metrics

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and datasets[132.]. However, no robust trend is found for the subtropical jet[134.], despite the

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expectation that they would covary because the subtropical jet enables strong vertical wind
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shear and the Hadley cell terminates where the shear is maximal[135]. The much weaker
poleward trend, if any, in the subtropical jet implies that different aspects of tropical
expansion are only partially coupled[136].

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The latitude of the Hadley cell edge is however negatively correlated on interannual timescales, at least in CMIP5 models, with the *strength* (not latitude) of the subtropical jet[137]. Furthermore, the coherent midlatitude jet stream in the time-mean zonal-mean circulation represents the superposition of two distinct, yet dynamically connected features: the subtropical jet and the eddy-driven jet at higher latitudes. The Hadley cell edge is shown to be positively correlated with the latitude of the eddy-driven jet[138], but not of the subtropical jet. While midlatitude baroclinicity associated with the eddy-driven jet is relatively weak during TC seasons, it still produces significant wind shear[139]. How this relationship between the Hadley cell edge, eddy-driven jet latitude and subtropical jet strength affects the synoptic and mesoscale processes of baroclinically enabled TC genesis[26], intensification and extratropical transition (Fig. 1b) remains a pressing open research question. Indeed, this type of TC genesis becomes common in the midlatitudes in idealised models of warm climates[31, 32, 33, 34], in particular when the two jets split (Fig. 5; Extended Data Fig. 5). In these simulations the summer subtropical jet shifts equatorward while the eddy-driven jet shifts poleward.

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A separate explanation for recent TC poleward migration invokes suppressed genesis in the deep tropics caused by increased dry static stability in the warming tropical atmosphere[99] (Fig. 4a). However, the extent to which changes in time-mean static stability effect actual TC processes is unclear. We suggest that static stability is best viewed as a co-factor with PI since both are related to atmospheric lapse rates. In fact, concurrent observations exhibit long-term increases in higher-frequency CCEWs[140] and increases in ITCZ precipitation (Extended Data Fig. 6), which contradicts the assertion that increased

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time-mean static stability implies less convective activity. Besides, SST increase in the deep
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 tropics also leads to both greater mid-tropospheric ‘saturation deficit’ (or tropospheric
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 dryness relative to the boundary layer), a well-established thermodynamic TC
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 inhibitor[115.][141.], and potentially also poleward shifts in the midlatitude westerlies[133.], which
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 would likely correspond to aerial expansion of favourable TC latitudes with high PI and
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 lower vertical shear.

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Another core aspect in discussions of TCs and climate change is ITCZ migrations and
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dynamics, even though ITCZ responses to warming may depend on the metric considered
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and have been muted during recent climate change[131.]. Despite large inter-model differences,
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overall precipitation responses in CMIP6 models show a stronger, wider, and equatorward
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ITCZ by the end of the twenty-first century (Fig. 6, Extended Data Fig. 7), which follows
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changes in SST patterns and constraints from the Clausius-Clapeyron relation (the “wet gets
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wetter” paradigm[142.]). However, unlike the precipitation-based metrics used here, circulation
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measures computed for in the previous CMIP5 models showed only little ITCZ latitudinal
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changes, with muted narrowing and weakening[131.]. Reconciling these differences will be
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critical to understanding changes in low latitude TCs in the 21st century.

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Idealised simulations confirm that the further off-equator the ITCZ is, the more ambient
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vorticity is available for TC genesis[1.][143.]. The wider and stronger it is by precipitation
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measures, the higher free tropospheric specific humidity is likely to be[23.]. Lastly,
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experiments with the moist shallow water equations indicate that a more poleward ITCZ is
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more susceptible to barotropic instability[144.]. All these factors would enhance TC genesis,
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but how these idealized inferences of TC dynamics relate to more realistic ITCZs, and GCM
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biases, is not yet fully examined.

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Changes at both the tropical-extratropical margin and within the ITCZ also raise
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questions about the degree of independence between source disturbances for TCs and the

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mature cyclones themselves. For example, suppressing easterly waves in the North Atlantic,
the primary source of pre-TC disturbances there, may alter the location and timing of genesis,
but not overall TC frequency[39]. Moreover, the stronger the ITCZ is by circulation measures,
the more initial disturbances may be available for TC genesis[1][16]. However, the ITCZ is
strong and well defined in the central North Pacific where TC genesis is sparse (Fig. 2a),
confirming that the climatologies of source disturbances and TC development can be
dislocated.

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Indeed, convective organisation is possible through multiple pathways such as CCEWs,
MJO, easterly waves, barotropic ITCZ breakdown, convective self-aggregation and, in the
Indian Ocean, orographically induced vortices[2.][32.][145.][146.][147.] (Fig. 1b). Yet, investigating
the resultant pre-TC disturbances with contemporary climate GCMs is problematic since
models struggle to propagate convective disturbances realistically because of their mismatch
between surface wind convergence and precipitation patterns caused by convective
parameterisations[148.]. As the realism of model simulations improves, it will become possible
to ask: *What is the best way to identify these pre-TC convective disturbances? How strongly
are these disturbances linked to CCEWs? What are the climate sensitivities of these waves
and disturbances? How are they affected by changes in ITCZ latitude, width, and strength?*

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While the previous paragraphs discussed the potential links between convective
mesoscale processes and large-scale circulations, changes in the thermodynamic contribution
to TC genesis and intensification favourability are also critical. These are likely tied to SST
changes with greenhouse warming as PI increases in a pattern not dissimilar to tropical SST
changes (compare Fig. 4 a and b), which may be related to recent time-mean enthalpy flux
increase (Extended Data Fig. 8) concomitant with SST warming (Fig. 4a)[110]. At the same
time, since most atmospheric moisture is in the lower troposphere and its content grows
exponentially following the Clausius-Clapeyron scaling, the lower levels gain more water

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vapor with warming than the free troposphere. The resultant increase in the relative dryness
of the free troposphere (with respect to the boundary layer) discourages genesis[¹¹⁵,]. This
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491 effect could be the strongest thermodynamic control over TC formation in a warming
492 climate[¹¹], but since moisture in the free troposphere is not controlled by the WTG, it can
493 vary across longitudes and depend on the large-scale tropical circulation (Box 1).

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This entire discussion has been focused on how the synoptic and mesoscale processes
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critical to the TC lifecycle respond to climate change as manifested in the time-averaged
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planetary-scale fields. We have neglected consideration of feedbacks of TCs upon climate
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itself. Three particular effects are noteworthy: the effect of TCs in drying free troposphere[3.],
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TCs' role in the upper ocean mixing and oceanic heat transport[3.][54.][149.][150.], and low-cloud
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suppression by TCs[151]. These effects are not well-handled by GCMs and may significantly
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affect their responses to radiative forcing, especially in paleo-context[54.][150.].

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502

IMPLICATIONS FOR TWENTY-FIRST CENTURY WARMING

503

The contemporary distribution of TCs was likely established during the late Pliocene around
3 million years ago and has been slightly modulated since then by glacial cycles on orbital
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timescales, abrupt climate changes on millennial timescales, gradual aerosol variations, and
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volcanism on sub-decadal timescales. The warm Pliocene (atmospheric CO2 ~400 ppm) and
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warmer Eocene (~1000 ppm) epochs likely produced TCs at significantly higher latitudes
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than the pre-industrial climate (~280 ppm). However, recent studies have been divided on
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whether twenty-first century levels of atmospheric CO2 (400 – 1000 ppm)[152.] will indeed
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result in a continuation of the present poleward trend in TC activity, as implied by those
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warm past climates.
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Since at least the 1970s, the planet's TC distribution has unambiguously altered,
evidenced in a poleward migration in latitudes of peak TC intensity at a rate of ~1/2 degree
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513
514 latitude per decade. This subtle but robust poleward shift has occurred during an expansion of
515 the tropics at approximately the same rate but during a period of stable latitudes of the ITCZ
516 and subtropical jet. During the 21st century, responding to increasing atmospheric CO2, the
517 global ITCZ may become stronger but move closer to the equator (Fig. 6). The effects of this
518 change on low latitude TCs are ambiguous since a stronger ITCZ implies more convective
519 mesoscale disturbances that could form into TCs as well higher free tropospheric humidity to
520 fuel their intensification, but also implies less planetary vorticity available for them to acquire
521 rotation and axisymmetric structure. Furthermore, these longitudinally averaged changes are
522 dominated by the Pacific where the eastern equatorial Pacific warming pattern is expected to
523 emerge during the 21st century. This will have the effect of drawing some of TC genesis away
524 from the western and eastern Pacific towards the central Pacific. In the North Atlantic,
525 changes in the favourability of baroclinic non-traditional TC genesis, vertical wind shear, and
526 ITCZ changes will be controlled by polar-amplified ocean warming (favourable to TC
527 poleward shift) possibly moderated by AMOC weakening (generally favourable to TC
528 equatorward shift).

529 Further tropical expansion is likely, primarily driven by amplified warming in the
530 tropical troposphere's upper levels, but will be constrained by the patterns of surface
531 warming. Crucially, new modelling of TCs at the changing tropical-extratropical margin
532 suggests that genesis and intensification between 30- and 40-degrees latitudes could
533 contribute significantly to the TC climatology of the twenty-first century. However, deep-
534 tropical TCs will remain a critical feature of Earth's climate, most clearly following the
535 anticipated equatorward ITCZ shift. Thus, we conclude that TCs will likely occupy a broader
536 range of latitudes by the end of the twenty-first century than during the pre-industrial period
537 following equatorward ITCZ shifts and continued increasing midlatitude favourability. We
538 propose that the bleeding-edge research questions critical for addressing uncertainties in
539 twenty-first century TCs are all centred around evaluating dynamical links between TC's

540 convective mesoscale processes and the better understood large-scale warming sensitivities

541 of the atmosphere and ocean. Potential feedbacks from TCs to climate is another broad

542 avenue for research.
543

FIGURES

544

[FIGURE 1]

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**Fig. 1** | **Tropical cyclogenesis in weather and climate.** *a* Earth's atmosphere on 22/07/2017 from NASA EOSDIS[153]. This day exhibits the most simultaneously existing tropical cyclones (TCs) in the satellite record. Tropical Storm Roke (peak intensity 40 mph), Sonca (40 mph), Kulap (45 mph) and Typhoon Noru (110 mph) are seen in the western subtropical North Pacific. In the eastern North Pacific, Hurricane Fernanda (145 mph), Tropical Storm Greg (60 mph), Hurricane Hilary (110 mph) and Hurricane Irwin (90 mph) at various development stages. *b* Schematic of traditional and baroclinically-enabled tropical cyclogenesis embedded into the large-scale flow and modulated by atmospheric dynamics (see Extended Data Figs. 1 and 2 for examples). ITCZ is an acronym for Intertropical Convergence Zone. Schematic style of the tropical mean circulation following ref [154].

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**Fig. 2** | Planetary-scale atmospheric circulation, precipitation, and TC activity. **a** Seasonal mean precipitation and lower-tropospheric winds and first recorded positions of disturbances that develop into tropical cyclones (TCs), **b** upper-tropospheric winds and TC tracks, **c** normalised average zonal-mean track density 2000-2019 (red) and 1980-1999 (blue), and **d** track density linear trends (units: local TC passages per year). The 6.5 mm/day contour in panel **a** corresponds to the 90th percentile seasonal-mean precipitation and marks the region of tropical convection during the TC seasons. Underlying environmental fields from ref. [155] and TC data from ref. [156]. Seasonal averages are computed for months of peak TC activity: July, August, September and October in the northern hemisphere and January, February, and March in the southern hemisphere (methods).
**Fig. 3** | Changes in TC latitudinal distribution over geological timescales. **a** Modern TC tracks as in Fig. 2b with blue curves corresponding to the period 1980-1999 and red to 2000-2019, **b** simulated PETM tracks[34.], and **c** changes in simulated seasonal-mean genesis potential relative to pre-industrial throughout the Cenozoic. In **c**, yellow dashes indicate shifts in hemispheres' maximum genesis potential latitudes while green/blue columns mark their upper and lower bounds (defined as latitudes of 25% drop-offs on either side of maxima). The data in **b** and **c** are based on GCM simulations[34.][43.][78.] and hold large uncertainties. Red circles indicate observed satellite era poleward TC migration[94.]. Pre-industrial TC lifetime maximum intensity latitudes are 18°N and 16°S. Given the wide range in twenty-first century projections (see text), no future estimates are plotted.
**Fig. 4 | Recent linear trends in key thermodynamic variables affecting tropical cyclones (TCs) and their genesis potential.**

**a** SST trends. **b** Trends in TC potential intensity (see Box 1) are controlled by the product of **c** air-sea thermodynamic disequilibrium and **d** modified Carnot efficiency. Thermodynamic disequilibrium represents the main heat source for TCs. **e** Trends in the modified Carnot efficiency depend on **a** SST and **f** TC outflow temperature. **f** Carnot efficiency represents the maximum efficiency at which the atmosphere can use available heat to maintain TC winds (Box 1). **g** Trends in genesis potential. See methods for the calculation of these variables. As in Fig. 2, seasonal averages are computed for months of peak TC activity. Underlying environmental fields are from ERA5 data[155]. trends are computed for 1980-2019. Only values with *p* < 0.05 are plotted.
**Fig. 5** | Large-scale circulations and TC latitudinal distributions under idealized climate warming scenarios in cloud-system-resolved aquaplanet simulations. This model is forced by **a** three fixed sea surface temperature (SST) meridional profiles ranging from contemporary climate (blue) to moderate midlatitude warming (purple) to exaggerated Eocene-like warming (yellow). The plot shows **b** 20 m/s zonal velocity contours marking the jet streams, **c** ±30 x 10⁹ kg/s streamlines of the Hadley and Ferrel cells, and **d** mean updraft strength measured as the time-mean of the zonal minima pressure velocity at 500hPa multiplied by -1. Divergent influences lead to the northward shift of **e** TC life-time maximum intensity (LMI) distribution (despite non-monotopic changes at low latitudes). Data from ref.[³²], which also finds that GPI calculations underestimate the magnitude of midlatitude genesis response to warming.
**Fig. 6** | Changes in the northern hemisphere Intertropical Convergence Zone (ITCZ) under different warming scenarios in CMIP6. a ITCZ intensity, b width, and c latitudinal position. For higher tropical SSTs climate models predict a stronger and broader ITCZ shifted toward the equator (Methods; see Extended Data Fig. 7. for changes in the southern hemisphere). Data from refs [157.] [158.] [159.] [160.] [161.] [162.] [163.] [164.] [165.] [166.] [167.] [168.] [169.] [170.] [171.] [172.] [173].
607 **Box 1 | Elemental controls**

608

609 **Potential intensity**

610 Potential intensity (PI) theory[174.], the only extant analytical framework for TC's
611 environmental dependences, states that TC strength is regulated by (1) the rate of oceanic
612 heat extraction - mainly through evaporation, (2) frictional dissipation at the ocean surface,
613 and (3) thermodynamic efficiency, also called Carnot efficiency (the normalised difference
614 between ocean surface and TC outflow temperatures), see Methods. The Carnot efficiency
615 concept from classical thermodynamics is modified in the context of TCs to incorporate
616 additional heating due to frictional energy dissipation. An upper bound on TC wind speeds is
617 inferred from this framework and computed in various ways from gridded climate data. PI
618 theory predicted three decades ago that anthropogenic warming would increase PI in warmer
619 climates[175.], increasing occurrence of intense TCs (as opposed to more TCs of all strengths).
620 This expectation has now been validated in recent observational data[176.].

621

622 **Convective aggregations**

623 When PI is high enough and an aggregation of high entropy air has occurred, the necessary
624 thermodynamic conditions for TC genesis are satisfied[4]. High entropy, or alternatively high
625 moist static energy (MSE), follows warm and moist air columns that are established by
626 surface evaporation and sensible heat transfer, radiative fluxes, and horizontal advection.
627 These aggregations may originate from a wide variety of synoptic and mesoscale
628 disturbances with embedded convective systems: easterly waves, the barotropic breakdown
629 of the ITCZ, convectively coupled equatorial waves, the Madden-Julian Oscillation (MJO),
630 or the remnants of baroclinic activity in the midlatitudes (Fig. 1b). Convective self-
631 aggregation may be another potentially important mechanism[2.][177.].
632 Large-scale winds

633 Environmental winds advect the developing vortex, thereby steering it, while interfering with 634 its structure and energetics. Vertical wind variations, or wind shear, are intrinsic to all 635 planetary atmospheres characterized by horizontal temperature gradients, leading to time- 636 mean atmospheric features like low-level subtropical anticyclonic flows (Fig. 2a) and upper- 637 level zonal jets (Fig. 1b; Fig. 2b). Vertical shear is the major dynamical inhibitor of TC 638 intensification acting against the formation of coherent deep columns of high entropy air 639 required for genesis. This shear dilutes entropy thereby weakening convective updrafts and 640 slowing the surface winds required for extracting heat from the ocean to fuel continued 641 convection [178].

642

643 Planetary rotation

644 Two key scaling hypotheses exist for the dependence of TCs on the planet's rotation.
645 Planetary rotation is manifest as the Coriolis parameter $f (= 2\Omega\sin\phi, \phi$ - latitude, $\Omega$ -
646 rotation rate of the planet), also called planetary vorticity. A first hypothesis predicts an $f$-
647 scaling, i.e., all else ignored, TCs should become more frequent towards the poles[141]. The
648 Coriolis parameter is zero at the equator and increases with latitude, setting a meridional
649 vorticity gradient (Fig. 1b). This gradient, the so-called $\beta$-effect, is also relevant:

$$
\beta = \frac{df}{dy} = \frac{2\Omega}{a} \cos\phi. \quad [1.]
$$

650 Opposite to f, β is largest at the equator and zero at the poles. This gradient is what causes
651 TC to move poleward and westward (the process known as beta drift) by establishing
652 secondary "beta gyre" circulations[179] on either side of the TC (Fig. 1b). Beta drift scales
653 with the square root of β[180]. Consequently, TC westward tracks rapidly curve poleward in
654 the tropics, but this effect diminishes at higher latitudes. β provides a non-climatological (i.e.,
655 dependent on planetary size and rotation rate as opposed to mean climate) constraint on TC
latitudes by limiting the size of cyclonic disturbances and hence reducing beta drift. [143.] If TC radii are to increase with climate warming, as has been hypothesised[100.], then we would expect stronger beta drift.

659

## 660 Climatological Convection

The majority of TCs (~70%) are spun out directly from climatological convection (Fig. 2a). The large-scale structure of this convection, including the ITCZ, can be deduced by combining two conceptual building blocks of tropical dynamics – convective quasi-equilibrium theory [181.] (CQE) and the weak temperature gradient approximation [182.] (WTG) – into a single framework [183.]. This framework provides an explanation for the structure of large-scale convective circulations resulting from time-mean spatial variations in MSE. CQE abstracts that the upward flow of MSE into the sub-cloud boundary layer due to enthalpy fluxes (latent and sensible heat transfer from the ocean surface) is balanced by a downward transfer of low MSE air from the dry free troposphere through convective downdrafts and large-scale subsidence (Fig. 1b). Employing this balance, ref. [183.] provides the following zeroth order diagnostic expression for controls on the strength of climatological convective updrafts in the ITCZ and Pacific Warm Pool:

$$M_u \propto w + \frac{SEF}{\Delta MSE}, \quad [2.]$$

where $M_u$ is the mass flux of the deep convective updrafts, $w$ – the tropical average vertical velocity at the top of the boundary layer, $SEF$ – the surface moist enthalpy fluxes, and $\Delta MSE$ – the difference between the boundary layer MSE and free tropospheric MSE (per unit volume). The corresponding convective updrafts release local instabilities and transport MSE from the boundary layer into the free troposphere. Eq. [2.] implies that the horizontal distribution of updraft strength is constrained by horizontal variations in surface fluxes, boundary layer MSE and free tropospheric MSE. Since atmospheric moisture content
680 declines rapidly with altitude and the effect of latent heat flux dominates over sensible heat

681 flux, the spatial distribution of climatological convection largely reflects surface evaporative

682 fluxes and lower-level tropospheric moisture[184].
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1322

1323 **Correspondence and requests for materials** should be addressed to JS

1324 (joshua.studholme@yale.edu).

1325

1326 **Acknowledgements** We thank the four anonymous reviewers and the editor for their

1327 constructive comments that have improved the manuscript. We also thank Mike Byrne (at the

1328 Universities of St. Andrews & Oxford) and Gabriel Vecchi (at Princeton University) for

1329 helpful discussions. We thank Colin Zarzycki (at Penn State University) for providing the

1330 PETM data and Naomi Henderson (at Columbia University) for assistance with CMIP6 data

1331 access. We recognise and thank NASA, NOAA, ECMWF, and the CMIP6 group of the

1332 World Climate Research Programme for making their data publicly and freely available. JS

1333 and AF have been supported in part by grants from NASA (NNX17AH21G), NOAA

1334 (NA20OAR4310377) and the ARCHANGE project of the “Make our planet great again”

1335 program (ANR-18-MPGA-0001, the Government of the French Republic). SG benefited

1336 from the Russian Science Foundation grant #20-17-00139 and from the Agreement
1337 #14.W0331.0006 with the Russian Ministry of Science and Higher Education. KE is
1338 supported by the U.S.'s National Science Foundation (ICER-1854929). KH acknowledges
1339 funding from the U.K.'s Natural Environment Research Council.

1340

1341 **Author contributions** JS conceived the study, wrote the drafts, produced the figures, and led
1342 the preparation of the manuscript with input from all the co-authors.

1343

1344 **Competing interests** The authors declare no competing interests.

1345

1346 **Data Availability Statement** All data used in this study is freely and publicly available in
1347 perpetuity.

1348

1349 *Tropical cyclone observational record* The tropical cyclone data for the contemporary period
1350 (Fig. 2 and Ext. Data Fig. 4) is plotted directly from the International Best Track Archive for
1351 Climate Stewardship[156]. (IBTrACS). These data are freely available at
1352 https://doi.org/10.25921/82ty-9e16. Version v04r00 was downloaded and the World
1353 Meteorological Organisation's homogenisation was used.

1354

1355 *Contemporary environment* Fields, used in Figs. 2 and 4, and Extended Data Figs. 4, 6 and 8,
1356 were taken from the European Centre for Medium Range Weather Forecasting's (ECMWF's)
1357 ERA5 reanalysis product[155]. All data was downloaded at native horizontal resolution (¼ x ¼
1358 degree) as monthly means for the years 1979 to 2020. These raw data are freely and publicly
1359 available for download at https://doi.org/10.24381/cds.6860a573.

1360
1361 *Cloud-resolving modelling* The idealised cloud-resolving modelling data is replotted from
1362 ref.[32]. This data is freely available in the following Dryad repository:
1363 doi:10.5061/dryad.8pk0p2np2

1364

1365 *Paleocene-Eocene Thermal Maximum modelling data* These data, from ref. [34], are available
1366 at https://doi.org/10.1016/j.palaeo.2021.110421.

1367

1368 CMIP6 Data for the ITCZ plotted in Fig. 6 and Ext. Data Fig. 7 was taken from 17 model
1369 centres that contributed to Climate Model Intercomparison Project Phase 6 (CMIP6). These
1370 data are available from the Earth System Grid Federation. Our CMIP6 analysis relies on
1371 subsets of the total model ensemble (+50 models). We used data from the following models:
1372 ACCESS-CM2[157], ACCESS-ESM1-5[158], BCC-CSM2-MR[159], CAMS-CSM1-0[160],
1373 CESM2-WACCM[161], CIESM[162], CanESM5[163], EC-Earth3-Veg[164], GFDL-CM4[165],
1374 GFDL-ESM4[166], INM-CM4-8[167], INM-CM5-0[168], IPSL-CM6A-LR[169], MIROC6[170],
1375 MPI-ESM1-2-HR[171], MRI-ESM2-0[172], NorESM2-LM[173].

1376

1377 **METHODS**

1378 *a. Tropical cyclone track density*

1379 Track density is computed from the IBTrACS archive as the annual count of TC track points
1380 within 4 degrees of each grid square (using a ¼ by ¼ degree grid to match the ECMWF
1381 environmental fields). The temporal resolution of the underlying track data is 3-hourly. Note
1382 that North Indian Ocean tracks are masked since TCs there began to be recorded in the
1383 dataset only in recent years.

1384

1385 *b. Climate diagnostics*
1386 Climate diagnostics shown in Figs. 4, 6 and Extended Data Fig. 7 are computed from ERA5 data (detailed in Section S1.b directly above) using the following methods:

1388

1389 *Tropical cyclone potential intensity* – Potential intensity (PI, units ms⁻¹) calculations were done for ERA5 data using Daniel Gilford's pyPI algorithm[¹⁸⁵], an implementation of the Bister and Emanuel algorithm[¹⁸⁶]. This method is based on the following expression:

1391

PI² = C_k / C_D × T_s / T_o × (CAPE* - CAPE) |_RMW, [M1.]

where C_k and C_D are the exchange coefficients for enthalpy and momentum, T_s and T_o are temperature at the sea surface and at the TC outflow branch in the upper troposphere, both in units of K. CAPE* and CAPE are the convective available potential energies of the saturated air lifted from the ocean surface to the outflow level and of boundary layer air respectively, both evaluated at the radius of maximum winds (RMW). An alternative, more conceptually intuitive, expression for PI can be also used[¹⁸⁷].

1392
1393
1394
1395
1396
1397

PI² = C_k / C_D × (T_s - T_o) / T_o × (k_s* - k) / Air-sea thermodynamic disequilibrium, [M2.]

where k_s* is the saturation moist enthalpy of air right at the sea surface and k is the moist enthalpy of air in the boundary layer overlying the surface. Expression M1 is more accurate than M2 because the former better estimates the amount of energy available for convection[¹⁸⁸]. PI can be then decomposed into the terms in M2 while using expression M1 to compute thermodynamic disequilibrium as a residual.

1398
1399
1400
1401
1402
1403

1404

Genesis potential – The genesis potential (GP) is calculated using the form [189].

GP = |η|^3 χ^{-4/3} MAX[PI - 35ms⁻¹), 0]² (V_shear + 25ms⁻¹)^{-4}
where $\eta$ is absolute vorticity of the flow at 850 hPa, capped at the value of $5 \times 10^{-5} \text{s}^{-1}$, PI is expressed as a flow speed, $V_{shear}$ is the magnitude of wind shear estimated as wind speed difference between 850 and 250 hPa (in m/s). $\chi$ is the moist entropy deficit in the middle troposphere defined as

where $s_b$, $s_m$ and $s_s^*$ are the moist entropies of the boundary layer and middle troposphere, and the saturation moist entropy at the sea surface, respectively. Moist entropy $s$ is defined as

where $T$ and $p$ are temperature (in K) and pressure, $c_p$ is the specific heat capacity at constant pressure of air, $L_v$ is the latent heat of vaporisation, $q$ is the specific humidity, $R_d$ and $R_v$ are the gas constants for dry air and water vapour respectively, and $H$ is the relative humidity.

Moist Static Energy is defined here as follows:

where $g$ is gravitational acceleration, $z$ is the height above the surface.

ITCZ metrics - Three metrics for the Intertropical Convergence Zone (ITCZ) were computed using CMIP6 data, all by standard methods (e.g. ref.[131]). intensity, latitude and width as described below. All metrics are computed from hemispheric zonal-mean precipitation [units mm day$^{-1}$] and are averaged over the last three decades of each CMIP6 experiment during TC seasons for the respective hemisphere – July to October in the northern hemisphere and January to March in the southern hemisphere. These metrics are plotted in Fig. 6 and

$$ \chi = \frac{s_b - s_m}{s_s^* - s_b} $$

$$ s = c_p \ln T - R_d \ln p + \frac{L_v q_v}{T} - R_v q \ln H, $$

$$ h = c_p T + gz + L_v q_v, $$
1425 Extended Data Fig. 7. against the global maximum in zonal-mean sea surface temperature
1426 (SST, units °C) during the respective TC season.

1427

1428 *ITCZ intensity* - is defined as the maximum in zonal-mean seasonal-mean precipitation.

1429

1430 *ITCZ latitude* - is defined as the latitude of the maximum in zonal-mean seasonal-mean
1431 precipitation.

1432

1433 *ITCZ width* - is defined as the cartesian distance between latitudes of zonal-mean seasonal-
1434 mean precipitation crossing the 5 mm day⁻¹ threshold on either side of the ITCZ latitude.

1435

1436 METHODS REFERENCES

1437 [185.] Gilford, D. M. pyPI (v1.3): Tropical Cyclone Potential Intensity Calculations in Python.

1438 Geosci. Model Dev. **14**. 2351-2369 (2021).

1439 https://gmd.copernicus.org/articles/14/2351/2021/gmd-14-2351-2021.pdf

1440 [186.] Bister, M. & Emanuel, K. A. Low frequency variability of tropical cyclone potential
1441 intensity. 1. Interannual and interdecadal variability. *J. Geophys. Research :*

1442 Atmospheres. **107** (D24). 4801 (2002).

1443 https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2001JD000776

1444 [187.] Emanuel, K. Tropical cyclones. *Ann. Rev. of Earth and Planetary Sciences.* **31** 75-104
1445 (2003).

1446 https://www.annualreviews.org/doi/10.1146/annurev.earth.31.100901.141259

1447 [188.] Garner, S. The relationship between hurricane potential intensity and CAPE. *J. Atmos. Sci.* **72**, 141-163. (2015).

1449 https://journals.ametsoc.org/view/journals/atsc/72/1/jas-d-14-0008.1.xml
1450 [189.] Emanuel, K. Tropical cyclone activity downscaled from NOAA-CIRES reanalysis,

1451 1908-1958. JAMES. 2 (1) (2010).

1452 https://agupubs.onlinelibrary.wiley.com/doi/full/10.3894/JAMES.2010.2.1
EXTENDED DATA

[EXTENDED DATA FIGURE 1]

1455 Extended Data Fig. 1 | The development and intensification of Hurricane Goni (2020, 1456 peak intensity 195 mph). Poorly organised convection over the west Pacific warm pool 1457 aggregates over the course of three days between October 22th and 24th (a b c), and then 1458 acquires coherent rotation over the subsequent three days (25th to 27th, d e f) while propagating 1459 westward away from its seeding region. Between Oct 28th and 30th, Goni developed into a 1460 fully-fledged TC (g h i) and made the strongest recorded landfall event by landfalling in the 1461 Philippines on Oct 31st. Data from ref [153].
1462

[EXTENDED DATA FIGURE 2]

1463

1464

1465

1466

1467

1468

1469

1470

1471

1472

**Extended Data Fig. 2** | The extratropical transition of Hurricane Paulette and the simultaneous tropical transition of Subtropical Storm Alpha. Hurricane Paulette, which originally developed out of an easterly wave on Sept 7th, reached its peak intensity on Sept 14th (105 mph) and then underwent extratropical transition to become an extratropical cyclone on Sept 17th. It then moved south and underwent tropical transition to intensify as a tropical cyclone on Sept 22. Subtropical Storm Alpha (peak intensity 50 mph) was the first ever tropical cyclone to make landfall in Portugal and the eastern-most genesis event in the North Atlantic record. At the same time as these events, a rare medicane tropical cyclogenesis event occurred forming Cyclone Ianos (peak intensity 75 mph) which made landfall in Greece, seen in Extended Data Figure 3. Data from ref. [153].
1473

[EXTENDED DATA FIGURE 3]

1474

**Extended Data Fig. 3 | The North Atlantic on September 16th, 2020.** Hurricane Sally

1475

(peak intensity 105 mph) can be seen making landfall over Alabama in the US, while

1476

Hurricane Teddy (peak intensity 140 mph) was intensifying over the tropical North Atlantic
and to its northeast, Tropical Storm Vicky is being weakened by strong environmental wind

1477

shear. Hurricane Paulette can be seen midway through its extratropical transition of the coast

1478

1479

of Nova Scotia and the extratropical cutoff low that became Subtropical Storm Alpha can be
seen off the coast of Portugal. In the Mediterranean, the rare Medicane Ianos can be seen

1480

1481

south of Italy. Tropical Storms Wilfred and Beta later developed out of the organising
convection visible off equatorial Africa and in the Gulf of Mexico respectively. Data from

1482

1483

ref. [153].
[EXTENDED DATA FIGURE 4]

Extended Data Fig. 4 | Planetary-scale atmospheric circulation, precipitation, and TC activity during the simulated Paleocene-Eocene Thermal Maximum (PETM) and the modern period. a, c First tracked positions and b, d TC tracks for PETM and modern climates. The green overlay in b and d show the 6.5 mm/day climatological TC season precipitation contours. PETM data is replotted from simulations in ref. [34] and modern data is from IBTrACs (methods). Red and blue dots are as in Fig. 2, blue for 1980-1999 and red for 2000-2019. Note that the lysis definition marking the end of the tracks between the PETM tracking and modern data are not easily reconcilable. The suppression of the low latitude TCs in the PETM is related to the splitting of the summertime subtropical and eddy-driven jets (Extended Data Fig. 5 and Fig. 5).

1495
1496

[EXTENDED DATA FIGURE 5]

1497

Extended Data Fig. 5 | Zonal-mean large-scale climate and north-south TC lifetime maximum intensity during the Paleocene-Eocene Thermal Maximum (PETM, CO2 1590 ppm). Replotted from the ~0.25-degree resolution atmospheric GCM simulations of ref. [34].

1498

1499

1500

1501

1502

Note the strong agreement on coincident jet split and TC activity in the midlatitude with the idealised cloud-system-resolving aquaplanet simulations of ref. [32] shown in Fig. 5 of the main manuscript.
[EXTENDED DATA FIGURE 6]

1503

1504

1505

1506

1507

1508

1509

1510

1511

**Extended Data Fig. 6** | Surface precipitation and tropospheric winds and recent linear trends from ERA5. a, b, c the 1980-2019 precipitation, and upper (300 hPa) and lower level (850 hPa) wind climatology for the tropical cyclone season (July through September for the northern hemisphere, January through March for the southern hemisphere). b The linear trend for the same seasons over the same period. Only trends for which *p* values are < 0.05 are plotted. The contour lines in b, d, and f are used to visualise the ITCZ (6.5 mm day<sup>-1</sup>), and the jet streams (5 m s<sup>-1</sup> in the lower troposphere in d and 20 m s<sup>-1</sup> in the upper troposphere in f). Data from ERA5<sup>[155]</sup>.
[EXTENDED DATA FIGURE 7]

**Extended Data Fig. 7** | As in Fig. 6 but for the southern hemisphere during TC season

**there: January-February-March.** Note the wide range in projections for the atmosphere only ('amip') simulations in blue, highlighting the significance of atmosphere-ocean coupling for tropical climate. The largest contribution to this “southern ITCZ” comes from the South Pacific Convergence Zone (SPCZ). Also note that these results may be affected by the models' double-ITCZ problem, which exaggerates the magnitude of the tropical convection to the south of the equator. Data from refs [157.] [158.] [159.] [160.] [161.] [162.] [163.] [164.] [165.] [166.] [167.] [168.] [169.] [170.] [171.] [172.] [173.]
[EXTENDED DATA FIGURE 8]

**Extended Data Fig. 8 | Surface enthalpy fluxes and recent linear trends from ERA5 (1980-2019).** Plotted as in Extended Data Fig. 6. Climatology and trends are for the tropical cyclone season (July through September for the northern hemisphere, January through March for the southern hemisphere). Data from ERA5[155].

ENDS
<figure><img src="image_2.png" /></figure>

b Thermally and eddy driven jets

<figure><img src="image_3.png" /></figure>
<figure><img src="image_4.png" /><figcaption>b</figcaption></figure>

<figure><img src="image_5.png" /><figcaption>d Track density linear trend, 1980-2019</figcaption></figure>

<figure><img src="image_6.png" /></figure>
a Modern tracks

<figure><img src="image_7.png" /></figure>

b Paleocene-Eocene Thermal Maximum tracks

<figure><img src="image_8.png" /></figure>

c

<figure><img src="image_9.png" /></figure>
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<figure><img src="image_17.png" /></figure>

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<figure><img src="image_26.png" /></figure>

<figure><img src="image_27.png" /></figure>
a Model surface forcing

<figure><img src="image_28.png" /></figure>

b $\bar{u} = 20 \text{ m s}^{-1}$

<figure><img src="image_29.png" /></figure>

c $\bar{\psi} = \pm 30 \times 10^9 \text{ kg s}^{-1}$

<figure><img src="image_30.png" /></figure>

d $\omega_{500}$

<figure><img src="image_31.png" /></figure>

e Tropical cyclone maximum intensity latitude distribution

<figure><img src="image_32.png" /></figure>
<figure><img src="image_33.png" /></figure>

<figure><img src="image_34.png" /></figure>

<figure><img src="image_35.png" /></figure>

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