Abstract

The sensitivity of global tropical cyclone (TC) activity to changes in a zonally symmetric sea surface temperature (SST) distribution and the associated large-scale atmospheric circulation are investigated. High-resolution (~50-km horizontal grid spacing) atmospheric general circulation model simulations with maximum SST away from the equator are presented. Simulations with both fixed-SST and slab ocean lower boundary conditions are compared.

The simulated TCs that form on the poleward flank of the intertropical convergence zone (ITCZ) are tracked and changes in the frequency and intensity of those storms are analyzed between the different experiments. The total accumulated cyclone energy (ACE) increases as the location of the maximum SST shifts farther away from the equator. The location of the ITCZ also shifts in conjunction with changes to the SST profile, and this plays an important role in mediating the frequency and intensity of the TCs that form within this modeling framework.

1. Introduction

The effect of climate change on future tropical cyclone activity continues to garner significant interest within the scientific community and beyond. While much has been learned about the genesis of tropical cyclones (TCs) over the past few decades, a dynamical theory linking the annual global frequency of approximately 90 ± 10 TCs per year (Emanuel and Nolan 2004) to the large-scale environment remains elusive. Early studies of the environmental conditions coincident with the formation of observed TCs revealed several important “ingredients” that are favorable for TC genesis (e.g., Gray 1968). Broadly speaking, these requirements are 1) relatively high underlying sea surface temperature (SST), 2) sufficient ambient vorticity, 3) low vertical wind shear, and 4) abundant moisture. Subsequent studies have refined this ingredients-based approach, yielding various empirical or semiempirical TC genesis indices based on these (or similar) environment parameters (e.g., Emanuel and Nolan 2004; Tippett et al. 2011). Although the different indices deduced from the large-scale environment do a reasonable job at capturing the geographical and seasonal distribution of the observed frequency of genesis (Menkes et al. 2012), it is unclear whether these same relationships can be expected to hold in different climates.

Many studies utilizing a variety of techniques have projected a reduction in the global number of tropical cyclones in response to global warming (e.g., Sugi et al. 2002; Yoshimura and Sugi 2005; Bengtsson et al. 2007; Held and Zhao 2011; Murakami et al. 2012a,b), although others have suggested a possible increase (e.g., Emanuel 2013). There is less confidence when looking at individual basins as to the sign or magnitude of the change (Knutson et al. 2010) or when considering only the subset of storms that attain a certain threshold intensity. Among other factors, there is a significant sensitivity of future TC activity to both the horizontal and vertical structures of the pattern of warming (Vecchi and Soden 2007; Sugi et al. 2009; Camargo et al. 2014).

Many general circulation models (GCMs) are now routinely run at sufficient resolution to enable the internal generation of TC-like disturbances within the simulations (Walsh et al. 2007; Shaevitz et al. 2014) and can thus provide an important tool for investigating the link between climate and TCs. The current study follows a series of experiments using a 50-km-horizontal-resolution atmospheric GCM to look of the response of simulated TCs to various changes in Earth’s climate (e.g., Zhao et al. 2009, 2010; Held and Zhao 2011; Zhao and Held 2012; Vecchi et al. 2013; Merlis et al. 2013).

We have been accustomed for several decades to the use of idealized and comprehensive global atmospheric models in tandem to study the controls on midlatitude eddies (e.g., Brayshaw et al. 2008; Lu et al. 2010), justified by the quality of the extratropical simulations provided by these global models. Our feeling is that global models are now attaining the quality in their TC simulations (Shaevitz et al. 2014), as exemplified by the model utilized here, to warrant analogous idealization and manipulation with the goal of understanding the controls on tropical cyclogenesis.

Here we have designed a set of experiments to investigate the response of simulated tropical cyclones to systematic variations in the underlying SST pattern and the associated large-scale circulation. To remove complexities arising from the geometric distribution of the continents and other sources of zonal asymmetry, we employ a zonally symmetric aquaplanet configuration as a further idealization from Earth-like simulations. This enables our subsequent analysis to focus on the response of TC activity to changes in the zonal-mean circulation.

Simulations are performed in two different aquaplanet configurations: one set has a fixed, zonally symmetric SST boundary condition and the other set has interactive SSTs determined by a slab ocean boundary condition. The intertropical convergence zone (ITCZ) is a prominent feature of the zonal-mean circulation of the zonally symmetric aquaplanet. Merlis et al. (2013) recently showed that the location of the ITCZ plays an important role in mediating the frequency of TCs in this model configuration. The ITCZ can shift in response to the prescribed asymmetry in the SST distribution (in fixed-SST simulations) or in response to the magnitude of the cross-equatorial ocean heat transport (in slab ocean simulations; Kang et al. 2008; Merlis et al. 2013).

The model formulation and the setup of the fixed-SST and slab ocean aquaplanet experiments is described in section 2 with the simulation results presented first in section 3. The preferred latitude of TC formation is discussed in section 4, and analyzed changes in TC frequency and average intensity are presented in section 5. Some concluding remarks are offered in the final section 6.

2. HiRAM aquaplanet GCM

The Geophysical Fluid Dynamics Laboratory High-Resolution Atmospheric Model (HiRAM) uses a cubed-sphere atmospheric dynamical core with approximately 50-km horizontal resolution and 32 vertical levels (Zhao et al. 2009). When observed monthly mean sea surface temperatures are prescribed as the lower boundary condition, HiRAM is able to simulate the seasonal cycle of tropical cyclone frequency in individual ocean basins (Zhao et al. 2009). In addition, HiRAM captures the interannual variability in Atlantic hurricane frequency, has seasonal forecast skill, and has been used for projections of future tropical cyclone frequency (e.g., Zhao et al. 2009, 2010; Zhao and Held 2012; Camargo et al. 2014). In a recent comparison study, Shaevitz et al. (2014) identifies HiRAM as simulating the TC climatology remarkably well across a variety of metrics.

A substantial fraction of the tropical precipitation in HiRAM occurs in resolved motion; however, there is a convection parameterization, based on a bulk entraining–detraining plume (Bretherton et al. 2004), and the top-of-atmosphere radiation balance and tropical cyclone frequency are sensitive to the parameterization’s entrainment parameter (Zhao et al. 2009, 2012). The aquaplanet simulations that are presented use identical subgrid-scale parameterizations to the HiRAM simulations with comprehensive boundary conditions. HiRAM simulations are presented in two different aquaplanet configurations: one with a fixed, zonally symmetric SST boundary condition and the other with interactive SSTs determined by a slab ocean boundary condition.

a. Fixed-SST experiments

In the fixed-SST aquaplanet HiRAM simulations, we prescribe a zonally symmetric surface temperature profile of the form

 
formula

where SST (°C) is the surface temperature as a function of latitude θ (°). The functional form of SST(θ) is similar to the Qobs profile proposed in the Neale and Hoskins (2000) suite of aquaplanet experiments and is chosen here to approximate Earth’s observed zonal-mean SST distribution (see Fig. 2a). The maximum temperature (SST0) occurs at latitude [i.e., SST0(θ0) = SST0], and the profile decreases symmetrically to latitudes ± 70°, beyond which the SST is fixed at 0°C.

A series of three perpetual-summer control simulations were conducted in which the latitude of the SST maximum was varied by setting , all with = 28.5°C. HiRAM simulations where the prescribed SST maximum is equatorward of approximately ±10° (not shown here) do not generate a sufficient number of TCs for the analysis. However, as will be shown in the following section, the frequency of cyclones varies markedly as the maximum in SST latitude shifts from 10° to 16°N, and hence the chosen latitudes of the control experiments allow a focus on the sensitivity of these changes.

Perturbation SST profiles were formed by adding and subtracting a temperature perturbation (SST′) to the control profiles, .

The first set of SST perturbation simulations were designed to investigate the sensitivity of TC activity to a globally uniform warming or cooling. A uniform 1.5°C was added to the SSTs of the farthest poleward control run to form the global warming profile. Similarly, a uniform 1.5°C was subtracted from the = 16°N control run to form the global cooling profile.

The second set of SST perturbation simulations were designed to investigate the sensitivity of TC activity to a warming or cooling confined to tropical latitudes. The prescribed tropical perturbation has the form

 
formula

where is the magnitude of the perturbation centered on the latitude of the SST maximum (in the control run), with the perturbation decaying to zero at ± 30° (see Fig. 5a). Since the meridional extent of the surface temperature perturbation is narrower than that of the control profiles , the resulting warmer and cooler tropical profiles have a corresponding sharper or flatter meridional tropical SST gradient, respectively. Setting = 1.5°C, both warm () and cool () tropical perturbation simulations were conducted for each of the three control profiles ( = 10°, 13°, 16°)—six additional simulations in total.

For each simulation the top-of-atmosphere incoming solar radiation is set at a perpetual equinox, and the ozone distribution and greenhouse gas concentrations are hemispherically symmetric following similar aquaplanet experiment conventions (e.g., Neale and Hoskins 2000). The only aspect of the simulations that is hemispherically asymmetric is the prescribed SST. Each control simulation was run with its prescribed SST profile for a period of 10 years (10 × 365 model days); the perturbation simulations were each run for a period of 5 years (see Table 1).

Table 1.

A summary of the HiRAM aquaplanet simulations and the resulting mean genesis frequency of the TCs tracked within each simulation. The frequency is the rate of formation equatorward of 25°N for all TCs and strong TCs , with the mean and standard error computed over the length of the simulation. Only the final 5 years of each of the simulations in the slab ocean configuration were included in the analysis.

A summary of the HiRAM aquaplanet simulations and the resulting mean genesis frequency of the TCs tracked within each simulation. The frequency is the rate of formation equatorward of 25°N for all TCs  and strong TCs , with the mean and standard error computed over the length of the simulation. Only the final 5 years of each of the simulations in the slab ocean configuration were included in the analysis.
A summary of the HiRAM aquaplanet simulations and the resulting mean genesis frequency of the TCs tracked within each simulation. The frequency is the rate of formation equatorward of 25°N for all TCs  and strong TCs , with the mean and standard error computed over the length of the simulation. Only the final 5 years of each of the simulations in the slab ocean configuration were included in the analysis.

b. Slab ocean experiments

In the HiRAM slab ocean simulations, which are the same as in Merlis et al. (2013), the SST evolves in response to the turbulent surface enthalpy fluxes and surface radiative fluxes in an energetically consistent fashion. The heat capacity of the surface is equivalent to a water depth of 20 m. The surface albedo is uniformly 0.08, and there is no representation of sea ice. Hence, the surface temperature can be lower than the freezing point of water, which occurs in the high latitudes of these simulations. In addition to the surface fluxes and radiation, we prescribe an ocean heat flux convergence in the slab ocean. This is the only aspect of the model formulation that is hemispherically asymmetric.

The design of the prescribed ocean heat flux convergence Q in the slab ocean experiments follows Kang et al. (2008). A surface heating is applied to the Northern Hemisphere extratropics (poleward of 40°), and a compensating surface cooling is applied to the Southern Hemisphere extratropics of the form

 
formula

where (W m−2) is the amplitude of the heat flux convergence. Because the pattern and magnitude of the heating and cooling are equal and opposite, no heat is added or subtracted from the global system. Thus the forcing in these experiments is equivalent to an implied cross-equatorial heat flux , where [see Fig. 1 of Kang et al. (2008)].

The insolation is an idealized function of latitude with and

 
formula

where and . The factor-of-2 increase to the cosine of the zenith angle corresponds to a daytime average of the diurnal cycle [see Cronin (2014) for other choices] and is approximately an insolation-weighted annual mean of the daytime-average cosine of the zenith angle for orbital parameters similar to Earth’s. With , the insolation gradient is somewhat stronger than Earth’s annual mean but is weaker than equinox conditions (the insolation is not zero at the pole). The concentration is 300 ppm and there are no other greenhouse gases or aerosols. The ozone distribution (varying with height and latitude) is fixed as in Neale and Hoskins (2000) and is similar to Earth’s present-day zonal-mean climatology.

A series of four simulations were performed in which the strength of the cross-equatorial heat flux was varied by setting . Each simulation was run for 10 years (see Table 1) from an Earth-like initial condition, with the final 5 years retained for analyses. The 5-yr model spinup is adequate to reach a statistical steady state, and, given the absence of a seasonal cycle, 5-yr averages are sufficient for sampling tropical cyclone statistics for our purposes.

c. Cyclone detection and tracking

The cyclone detection and tracking algorithm is based on Vitart et al. (1997) and Knutson et al. (2007) and is discussed in detail in appendix B of Zhao et al. (2009); it has recently been compared with other similar detection and tracking algorithms in Horn et al. (2014). First, candidate warm-core vortices are identified using 6-hourly instantaneous 850-hPa relative vorticity, sea level pressure, and a measure of the upper-tropospheric temperature anomaly. The maximum “surface” wind speed is recorded at each 6-hr output interval, being the maximum of 10-m wind speed values of grid points surrounding the location of the candidate vortex, . A simple tracking scheme subsequently links warm-core vortices that are within 400 km of those in the preceding 6 h. Storms are not included in the final analysis unless their associated track lasts in excess of 3 days, with the additional requirement that a tropical storm wind speed criterion is satisfied for at least 3 days (not necessarily consecutive).

The maximum surface wind speed thresholds for classifying storms ( for tropical storms and for hurricanes) are reduced by about 10% as described in Zhao et al. (2012), which is consistent with the range recommended by Walsh et al. (2007) in order to account for the impact of the model’s roughly 50-km spatial resolution.

All tropical storm tracks meeting the above criteria (with ) are herein classified broadly as TCs, with “genesis” being defined to occur at the time and location where the storm is first analyzed having . Reference will on occasion be made to a strong subset of TCs that at some point during their lifetime attain hurricane-strength wind speeds .

3. Results of simulations

Forced with hemispherically asymmetric SSTs or ocean heat flux convergence, the simulated tropical climate has a relatively narrow region of ascent and enhanced precipitation shifted off the equator in the warmer Northern Hemisphere, which is similar to the summer climate that is realized over many of Earth’s tropical oceanic regions. Figure 1 shows a snapshot of the HiRAM aquaplanet’s tropics, taken from the control fixed-SST simulation where the maximum in SST is located at 16°N. The zonally elongated band of daily precipitation rate shows the location of the model’s ITCZ, which in the time mean resides at 8°N (the latitude of maximum precipitation rate) in this simulation (left panel of Fig. 1).

Fig. 1.

(right) A snapshot of the control HiRAM aquaplanet simulation, displaying the instantaneous 10-m wind speed (shading) and daily precipitation rate (blue contour of ). (left) Time-mean latitudinal profiles from the simulation are shown: precipitation rate (blue; ; scale on top axis) and the zonal (black) and meridional (red) components of the 10-m wind (; scale on bottom axis).

Fig. 1.

(right) A snapshot of the control HiRAM aquaplanet simulation, displaying the instantaneous 10-m wind speed (shading) and daily precipitation rate (blue contour of ). (left) Time-mean latitudinal profiles from the simulation are shown: precipitation rate (blue; ; scale on top axis) and the zonal (black) and meridional (red) components of the 10-m wind (; scale on bottom axis).

The ITCZ location is associated with low-level convergence in the meridional wind velocity field (red line in Fig. 1), where the surface branches of the summer and winter (cross equatorial) Hadley cells meet. The northward surface flow accelerates across the equator and turns to the right (eastward) under the influence of the Coriolis force. Hence the SH southeasterly trade winds and NH northeasterly trade winds are connected by a latitudinal zone of “monsoon” westerlies that coincide with the off-equatorial region of ascent (black line in Fig. 1). On the poleward flank of the ITCZ region the meridional gradient of the time-mean, zonal-mean zonal wind is therefore negative, yielding a “sweet spot” region of enhanced cyclonic vorticity coincident with surface convergence and large-scale ascent. Recall that the maximum in SST is also to the north of the ITCZ, and it is unsurprising that this region is observed to be favorable for the formation of TCs in the model.

Numerous TCs disturbances develop in HiRAM, some of which subsequently strengthen and propagate toward higher latitudes. Examples of these phenomena can be seen in Fig. 1 in the instantaneous 10-m wind speed field, giving a sense of the range of sizes and the spatial distribution of the disturbances. The following results focus on the relationship of the frequency of simulated TCs forming on the poleward flank of the ITCZ to the large-scale environmental conditions of the region. Table 1 provides a summary of the various HiRAM aquaplanet simulations conducted and the resulting mean genesis frequency of the TCs that were detected and tracked within each simulation. These results will be discussed through the remainder of this section.

a. Poleward-shift experiments

The meridional SST profiles for the three fixed-SST simulations are shown in Fig. 2a. By construction the maximum temperature (28.5°C) does not change, but the latitude of the maximum shifts poleward in 3° increments (10°, 13°, and 16°N). From the location of the maximum, there is a symmetrical decrease (northward and southward) of SST with latitude . For comparison, the zonal mean of Earth’s climatological September SST (HadISST; Rayner et al. 2003) is also plotted (black dashed line). The magnitude and general shape of the prescribed SST is similar to boreal summer conditions on Earth.

Fig. 2.

Time- and zonal-mean fields from the HiRAM aquaplanet fixed-SST control simulations: (a) SST, (b) precipitation rate, and (c) genesis frequency. The distribution of genesis frequency in (c) is shown for all tropical cyclones (; thick lines) and for the subset that attains hurricane-strength wind speeds (; thin lines). The black dashed line in (a) shows Earth’s zonal-mean SST during September.

Fig. 2.

Time- and zonal-mean fields from the HiRAM aquaplanet fixed-SST control simulations: (a) SST, (b) precipitation rate, and (c) genesis frequency. The distribution of genesis frequency in (c) is shown for all tropical cyclones (; thick lines) and for the subset that attains hurricane-strength wind speeds (; thin lines). The black dashed line in (a) shows Earth’s zonal-mean SST during September.

The equilibrium SST profiles from the four slab ocean simulations are shown in Fig. 3a. Without a cross-equatorial heat flux, the profiles would be symmetric about the equator; here the SSTs become more asymmetric as the heat flux is increased. The maximum temperature moves about 2° northward for each 10 W m−2 increase in heat flux amplitude. In addition, the maximum temperature itself increases by about 1°C (10 W m−2)−1, but remains cooler than the maximum prescribed in the fixed-SST control runs (28.5°C) in all but the strongest-heat-flux slab ocean simulation. The meridional SST gradient in the slab ocean simulations is markedly sharper than those of the fixed-SST control simulations.

Fig. 3.

Time- and zonal-mean fields from the HiRAM aquaplanet simulations in the slab ocean configuration: (a) SST, (b) precipitation rate, and (c) genesis frequency. The distribution of genesis frequency is shown for all tropical cyclones (; thick lines) and for the subset that attains hurricane-strength wind speeds (; thin lines).

Fig. 3.

Time- and zonal-mean fields from the HiRAM aquaplanet simulations in the slab ocean configuration: (a) SST, (b) precipitation rate, and (c) genesis frequency. The distribution of genesis frequency is shown for all tropical cyclones (; thick lines) and for the subset that attains hurricane-strength wind speeds (; thin lines).

Figure 2b shows that the ITCZ (as indicated by the location of the maximum precipitation rate) moves northward when the SST maximum is shifted northward in the fixed-SST simulations. In all cases the maximum precipitation rate is equatorward of the maximum SST. A small secondary local maximum in precipitation rate to the north of the SST maximum is apparent in the 10°N experiment but not in the experiments with the SST maximum farther north. As the precipitation shifts poleward, it broadens meridionally and the maximum precipitation rate decreases within the ITCZ region. The broadening is more pronounced on the poleward side of the maximum, so the subtropics (near 15°N) receive slightly higher rainfall.

The slab ocean simulations have a similar SST–ITCZ relationship (Figs. 3a,b). As the cross-equatorial heat flux increases, the precipitation rate maximum shifts to the north and the meridional profile of the precipitation rate broadens. Here the shift is quite marked and the latitude of the maximum precipitation is closer to (though still equatorward of) the location of the maximum SST. The mean meridional circulation is generally stronger in the slab ocean simulations (not shown here), which gives rise to higher precipitation in the tropical convergence zone and lower precipitation in the regions of subsidence compared to the fixed-SST simulations.

The extent to which the fixed-SST simulations can reproduce the behavior of the slab ocean model can be investigated if the prescribed SSTs are taken from the climatology of the latter. This comparison was made for two of the slab ocean cases, , with 5-yr fixed-SST simulations with the time-mean, zonal-mean SSTs previously diagnosed from the slab ocean model prescribed. The resulting zonal-mean profiles of precipitation are shown by the dashed lines in Fig. 3b and are barely distinguishable from their solid counterparts. Hence, the time-mean precipitation in the ITCZ region is (to a large extent) reproduced when the slab ocean lower boundary condition is replaced by fixed SSTs that have been fixed to the climatological average.

Meridional profiles of TC genesis frequency are produced from the results of the tropical cyclone tracking scheme (section 2c). For each simulation, the TC genesis locations are sorted into 1° latitude bins and the resulting histogram is normalized (TCs per 1° latitude per year) and smoothed using a 5°-latitude moving average for display purposes. The resulting profiles of genesis frequency for the fixed-SST simulations are shown in Fig. 2c. Thicker lines show genesis profiles of all TCs while thinner lines denote the subset of these storms that at some stage during their lifetime attain hurricane-strength wind speeds .

Genesis primarily occurs on the poleward flank of the ITCZ, and there is little qualitative difference in the latitudinal distribution of genesis when comparing all TCs and the stronger hurricane subset. While there is a slight northward shift in genesis as the SST and ITCZ moves northward, the primary genesis region remains within the range of approximately 8°–18°N latitude in these experiments. However, as the maximum SST shifts north and the ITCZ shifts and broadens, a substantial increase in genesis frequency is simulated. With the maximum SST located at 10°N, fewer than 15 TCs per year form in the most favorable (1° latitude) genesis latitude. This frequency increases to more than 30 TCs per year when the maximum SST is located farther poleward at 16°N. The proportion of storms that achieve hurricane-strength wind speeds increases slightly from about 45% (10°N simulation) to about 65% (16°N simulation).

The meridional profiles of TC genesis frequency for the slab ocean simulations are shown in Fig. 3c. There is a marked increase in TC genesis frequency as the SST maximum and ITCZ shift poleward, as in the fixed-SST simulations. There is a substantial increase in the frequency of genesis from the simulation with the weakest ocean heat transport experiment (; light-blue line) to the next simulation in the series (the heat flux convergence is doubled to ; green line). Further increases in TC genesis frequency occur as the asymmetry increases, although the rate of increase slows and there are indications of a potential saturation in the number of TCs developing in the model. As the asymmetry is increased, the genesis region moves northward at a rate similar to the shift in the profile of mean precipitation, remaining on the poleward flank of the ITCZ and broadening slightly. Very few of the TCs that form in the weakest experiment reach hurricane strength (2 out of 188 TC tracks in the 5 years analyzed), but this proportion increases to about 36% in the simulation.

Some interesting changes emerge in the resulting frequency of TCs when the simulations are conducted holding the SSTs fixed to the slab (dashed lines in Fig. 3c; see also the bottom two rows of Table 1). The comparison yields a greater number of TCs in the fixed-SST configuration, whereas the comparison yields fewer TCs. However, there are also changes in the intensity distribution of the resulting TCs: fewer achieve hurricane strength in the case with fixed SSTs, while a greater number of TCs reach hurricane strength in the fixed-SST simulation in than the corresponding slab ocean simulation. These differences warrant further investigation, but the increases in TC genesis frequency to increasing hemispheric asymmetry holds in both the fixed-SST and slab ocean configurations.

b. Global and tropical perturbation experiments

To test the sensitivity of genesis frequency to the magnitude of the SSTs and to changes in the tropical SST gradient, several further fixed-SST perturbation experiments were conducted as outlined earlier (section 2a). Results from the 16°N runs are shown in Figs. 4 and 5. The control run (black line) is the same as the 16°N profile that was plotted in Fig. 2; also shown here are the meridional profiles associated with the warm and cool perturbation experiments, plotted in red and blue, respectively.

Fig. 4.

Time- and zonal-mean fields from the HiRAM aquaplanet fixed-SST simulations with a globally uniform SST perturbation: (a) SST, (b) precipitation rate, and (c) genesis frequency. The distribution of genesis frequency is shown for all tropical cyclones (; thick lines) and for the subset that attains hurricane-strength wind speeds (; thin lines).

Fig. 4.

Time- and zonal-mean fields from the HiRAM aquaplanet fixed-SST simulations with a globally uniform SST perturbation: (a) SST, (b) precipitation rate, and (c) genesis frequency. The distribution of genesis frequency is shown for all tropical cyclones (; thick lines) and for the subset that attains hurricane-strength wind speeds (; thin lines).

Fig. 5.

Time- and zonal-mean fields from the HiRAM aquaplanet fixed-SST simulations with a tropical SST perturbation: (a) SST, (b) precipitation rate, and (c) genesis frequency. The distribution of genesis frequency is shown for all tropical cyclones (; thick lines) and for the subset that attains hurricane-strength wind speeds (; thin lines).

Fig. 5.

Time- and zonal-mean fields from the HiRAM aquaplanet fixed-SST simulations with a tropical SST perturbation: (a) SST, (b) precipitation rate, and (c) genesis frequency. The distribution of genesis frequency is shown for all tropical cyclones (; thick lines) and for the subset that attains hurricane-strength wind speeds (; thin lines).

Figure 4 shows results from a globally uniform 1.5°C perturbation. By construction, the meridional gradient of SST remains fixed in these runs (Fig. 4a). The maximum in the time-mean precipitation rate (Fig. 4b) increases in the warmer-SST simulation, which is consistent with various previous theoretical and modeling studies that describe changes to the hydrological cycle in a warmer climate (e.g., Allen and Ingram 2002). The model’s ITCZ also moves slightly equatorward in the warmer climate. In the globally cooler SST scenario the precipitation rate reduces slightly, with no clear shift in the position of the ITCZ.

The resulting TC genesis frequency is shown in Fig. 4c. A reduction (increase) in the genesis frequency of TCs occurs in the simulations with a globally warmer (cooler) SST. A similar change occurs in the subset of stronger TCs, such that the proportion (~65%) of hurricane-strength TCs is similar in both the and simulations. Table 1 shows that the simulated changes in genesis frequency (of all TCs) is for a 1.5°C uniform warming and for a 1.5°C uniform cooling. These results are consistent with previous studies by Yoshimura and Sugi (2005) and Held and Zhao (2011), who found a reduction in global genesis frequency ( and , respectively) with a 2°C uniform warming in SST, albeit with a smaller percentage decrease that may result from more realistic Earth-like boundary conditions (e.g., seasonally varying SSTs, and including continents). It is interesting that the uniform SST warming and cooling effects on tropical cyclone frequency appear to be nonlinear—a result also consistent with Yoshimura and Sugi (2005), who found no change in frequency in their 2°C uniform-cooling simulation.

The results of simulations with a 1.5°C tropical perturbation that is centered on the maximum SST and reduces to zero at 16°N ± 30° are shown in Fig. 5. Note the steeper (flatter) meridional SST gradients associated with the warm (cool) tropical perturbation (Fig. 5a). As in the globally uniform perturbation, the warmer tropical SST simulation has a higher average precipitation rate (Fig. 5b). However, the tropical warming SST perturbation simulation has a marked poleward shift (~2°) of the ITCZ toward the latitude of the maximum SST. In the case of the tropical cooling perturbation, there is a slight reduction in the maximum precipitation rate and a substantial equatorward shift (~3°) of the ITCZ.

The genesis statistics in Fig. 5c show a substantial increase (reduction) in the genesis frequency of all TCs in the simulations that have warmer (cooler) tropical SSTs. That is, the simulations with sharper (flatter) meridional SST gradients in the tropics yield more (fewer) TCs. While there is a marked increase and decrease in the amplitude of the genesis frequency distributions (compared with the control), there are only slight changes in the location of the peak of the distributions and the width of the latitude bands in which genesis occurs. The results differ when focusing on the subset of stronger TCs. About of TCs attain hurricane-strength wind speeds in the simulation, compared to more than in the simulation. Hence, the number of hurricane-strength TCs changes less than the total number of TCs because of opposing changes in the intensity distribution: TCs in simulations with sharper (flatter) meridional SST gradients are less (more) likely to reach hurricane-strength wind speed.

4. Latitude of TC genesis

The different simulations show subtle but distinct changes in the preferred region of tropical cyclogenesis. Recall that the latitude of tropical cyclogenesis here refers to the location of the first instance when a developing disturbance has . Only those TCs that are equatorward of 25°N at their first detection are included in the subsequent analyses. This appropriately avoids contamination of the results by those disturbances that have a subtropical origin (this smaller and well-separated mode is evident at higher latitudes in Figs. 2c, 4c, and 5c).

In Fig. 6 the mean latitude of TC genesis is plotted against the latitude of the maximum SST (the latitude prescribed in the fixed-SST simulations, or the latitude diagnosed from the slab ocean simulations) and also the latitude of the maximum precipitation rate (°N). Each marker reflects a different 5-yr simulation of the HiRAM aquaplanet, with colored markers denoting fixed-SST experiments that share the same prescribed latitude of the maximum SST (green: 10°N, blue: 13°N, pink: 16°N; see Fig. 2a). Upward (downward) triangular markers denote the positive (negative) tropical perturbation experiments that were conducted at all three latitudes. Square markers show results from the accompanying slab ocean experiments.

Fig. 6.

The mean latitude of tropical genesis plotted against (a) the latitude of the maximum SST and (b) the latitude of the maximum precipitation rate as a measure of the location of the ITCZ. Black solid lines indicate the linear fit through those simulations that have the same (or similar) tropical SST gradient. Each marker summarizes the TC statistics (genesis latitude < 25°N) from a 5-yr HiRAM aquaplanet simulation (see text for details).

Fig. 6.

The mean latitude of tropical genesis plotted against (a) the latitude of the maximum SST and (b) the latitude of the maximum precipitation rate as a measure of the location of the ITCZ. Black solid lines indicate the linear fit through those simulations that have the same (or similar) tropical SST gradient. Each marker summarizes the TC statistics (genesis latitude < 25°N) from a 5-yr HiRAM aquaplanet simulation (see text for details).

Markers above and to the left of the 1:1 black dashed line in Fig. 6a indicate preferred genesis poleward of the maximum SST, while markers below and to the right of the line have genesis primarily occurring equatorward of the maximum SST. The black solid lines indicate the linear fit through the different sets of simulations that share the same tropical SST gradient (or nearly the same SST gradient in the case of the slab ocean experiments where the SSTs are interactively determined).

The experiments that prescribe the flattest tropical SST gradients (those with cool tropical perturbations) show no sensitivity of the preferred genesis location to the latitude of the maximum SST; when the peak SST is shifted from 10° to 16°N the resulting genesis remains centered near 14.5°N. However, in the sets of simulations with stronger SST gradients, a sensitivity to the location of the SST maximum emerges as the preferred genesis region is observed to shift toward the latitude of the peak SST. The latitude of TC genesis tends toward the maximum SST as the SST gradient increases.

The observed linear relationship of the mean genesis latitude to the latitude of the maximum SST within subsets of HiRAM aquaplanet simulations sharing similar SST gradients can be expressed simply as . The sensitivity appears to be related to the strength of the tropical SST gradient, such that as and as (i.e., zero once the SST gradient is sufficiently flat). Since the lines in Fig. 6a are seen to intersect the approximate point of (14.5°N, 14.5°N), the preferred genesis latitude can be related to the latitude of the maximum SST by the simple expression, .

Figure 6b shows the relationship between the latitude of TC genesis and the location of the ITCZ , denoted here as the latitude of the maximum in time-mean precipitation rate within each of the simulations. Genesis is centered on the poleward flank of the ITCZ (above and to the left of the dashed line) in all experiments. In simulations where the prescribed latitude of the maximum SST is fixed (those with the same colored markers), genesis occurs closer to the ITCZ in the simulations with a warm tropical perturbation and farther away from the ITCZ in simulations with a cool tropical perturbation. Furthermore, the linear fit lines through these subsets of experiments suggest a systematic shift of accompanies the movement of toward the latitude where .

For each of the colored lines in Fig. 6b, we observe that as and as , hence one can write the general linear expression

 
formula

relating the genesis latitude to the latitude of the maximum SST and ITCZ alone. Hence the aforementioned sensitivity of to shifts in (the slopes of the black lines in Fig. 6a) can be approximated by .

The results from both panels of Fig. 6 confirm that the ITCZ shifts toward (away from) the maximum in SST as the tropical meridional SST gradient increases (decreases). Furthermore, within the HiRAM aquaplanet configuration TC genesis remains centered around 14.5°N unless the latitude of the maximum SST is a sufficient distance away from 14.5°N and the tropical meridional SST gradient is strong enough to draw the ITCZ away from the equator toward the latitude of the maximum SST.

The simulation results may be interpreted as approximately 14.5°N being a preferred latitude for genesis in the HiRAM aquaplanet in the limit of a vanishing SST gradient. The role of planetary vorticity in TC genesis suggests that it is physically plausible for the preferred latitude to be off equator, and the bulk of TC genesis in the globally uniform SST simulation of Shi and Bretherton (2014) occurs near 15° latitude. While this similarity is suggestive, the extent to which such a latitude is robust across different models or depends on the tracking scheme parameters is uncertain.

5. Discussion of TC activity

The accumulated cyclone energy (ACE; Bell et al. 2000; Camargo and Sobel 2005) of an individual TC track is defined as the square of the estimated maximum sustained 10-m wind speed summed over all 6-h periods from genesis through the end of the cyclone’s track:

 
formula

The total , summed over all analyzed TCs per year of model simulation will be used henceforth to broadly characterize the overall TC activity within each experiment. This measure of total TC activity depends on the TC genesis frequency (number of TCs per year), duration, and the mean ACE, a measure of the average intensity of TCs within a simulation,

 
formula

Note that has here been computed after normalizing by the duration of the individual cyclone tracks so as to present a metric that, when compared between experiments, focuses on changes in the maximum wind speed alone. As in the previous section, only TCs that form equatorward of 25°N are included in the analysis to ensure the focus remains on the tropical disturbances that are associated with the northern flank of the ITCZ.

a. Dependence on the SST and ITCZ configuration

The impact of the meridional SST profile and associated latitude of maximum precipitation rate (ITCZ) on the resulting TC statistics for each of the simulations are summarized in Fig. 7. Figures 7a–c display the total TC activity , Figs. 7d–f display the TC genesis frequency , and Figs. 7g–i display the average intensity of TCs, normalized by track duration . The same convention for identifying different experiments as in Fig. 6 has been adopted here. Also shown here are the results from the two globally uniform SST perturbation simulations at 16°N, marked with a plus sign and multiplication sign .

Fig. 7.

Tropical cyclone frequency and accumulated cyclone energy, plotted against (a),(d),(g) the latitude of the maximum SST, (b),(e),(h) the latitude of the maximum precipitation rate, and (c),(f),(i) the latitudinal separation between those maxima. (top) The total ACE, (middle) the TC genesis frequency, and (bottom) the mean ACE. Each marker summarizes the TC statistics (genesis latitude < 25°N) from a 5-yr HiRAM aquaplanet simulation (see text for details).

Fig. 7.

Tropical cyclone frequency and accumulated cyclone energy, plotted against (a),(d),(g) the latitude of the maximum SST, (b),(e),(h) the latitude of the maximum precipitation rate, and (c),(f),(i) the latitudinal separation between those maxima. (top) The total ACE, (middle) the TC genesis frequency, and (bottom) the mean ACE. Each marker summarizes the TC statistics (genesis latitude < 25°N) from a 5-yr HiRAM aquaplanet simulation (see text for details).

The TC statistics are plotted against the latitude of the maximum SST in Figs. 7a, 7d, and 7g. A clear relationship is observed in these experiments—the total ACE increases as the latitude of the maximum SST moves poleward (Fig. 7a). In the fixed-SST control and slab ocean simulations this increase is realized in the frequency of TC formation (Fig. 7d) as well as in the subsequent average intensity of the cyclones (Fig. 7g). Note that for the same latitude of , there is greater spread between the different experiments in the TC frequency and average intensity metrics when compared with the tighter fit seen in the overall product of these quantities. For example, while the fixed-SST experiments yield significantly fewer TCs than the slab ocean simulations, the per fixed-SST TC (in the control experiments) is about twice that of the slab ocean TCs, resulting in a close relationship between and total ACE across the different aquaplanet configurations. Similarly, in the fixed-SST simulations with a positive (negative) tropical SST perturbation, an increase (a decrease) in the genesis frequency for a certain prescribed latitude of is largely offset by a decrease (increase) in the average intensity of those TCs such that the total ACE remains relatively unchanged. In contrast, the average intensity of the TCs in the globally uniform warmer (cooler) model simulations remains unchanged while the frequency decreases (increases). This results in an overall decrease (increase) of TC activity, respectively.

The TC statistics are plotted against the latitude of the maximum precipitation rate in Figs. 7b, 7e, and 7h. The prescribed SST profile plays a key role in setting the location of the ITCZ in these aquaplanet simulations so it is unsurprising that the increasing TC activity, frequency, and average intensity observed with shifting the SSTs poleward (green to blue to pink markers) is also observed when the statistics are plotted against the latitude of the ITCZ. However, as discussed earlier (section 4), the shape of the meridional SST profile also influences the latitude of the ITCZ in these simulations, reflected here in the horizontal spread of the colored markers. Sharper (flatter) SST profiles move the ITCZ northward (southward) and toward (away from) the latitude of the maximum SST. While the total ACE in these experiments (Fig. 7b) appears to be relatively insensitive to changes in the meridional SST gradient alone, evidently the frequency of TC genesis increases as the ITCZ latitude moves poleward (Fig. 7e). Correspondingly, for the same latitude , a northward shift in the ITCZ (toward the SST maximum) is accompanied by a reduction in the average intensity of the simulated TCs (Fig. 7h).

This change in average intensity becomes clearer when the TC statistics are further plotted against the latitudinal separation between the location of the maximum SST and the ITCZ, , shown in Figs. 7c, 7f, and 7i. This abscissa provides a simple measure of the relative strength of the meridional SST gradient in driving the intertropical convergence toward the latitude of the maximum SST; the stronger the meridional SST gradient, the smaller the separation. As the latitudinal separation increases, there is little sensitivity in the total TC activity (Fig. 7c) or frequency (Fig. 7f) metrics; however, the average intensity is observed to increase robustly (Fig. 7i). Hence, in these aquaplanet experiments the average intensity of TCs increase as the meridional temperature gradient flattens (Fig. 7i). This is consistent with the increase in the fraction of TCs that reach hurricane strength shown in Fig. 5c.

b. Dependence on environmental variables

Many previous investigations have sought to link the observed rate of TC genesis to the mean environmental ingredients known to be conducive for tropical cyclones. The quantities typically included in these tropical cyclogenesis indices include both thermodynamic quantities, such as SST (absolute or relative to a tropical mean), potential intensity, and relative humidity, and kinematic quantities, such as vertical wind shear and absolute vorticity. We do not seek here to rigorously test the various published indices (e.g., Emanuel and Nolan 2004; Tippett et al. 2011) or to propose a new index derived from these experiments. Rather, we give an overview of the relationship of select mean environmental quantities and the resulting frequency of TCs realized across this set of simulations.

To capture the mean value of a particular environmental field coincident at the genesis locations in these simulations, we follow the convention introduced by Held and Zhao (2011) by defining the “genesis weighted” quantity here as

 
formula

where is the zonal-mean quantity of interest and is the histogram of genesis latitudes from the corresponding simulation; both and are recorded as monthly mean quantities. The overbar indicates the global mean (cosine-weighted latitude) of the quantities, further averaged (in time) over the whole simulation.

The frequency of TC formation in the HiRAM aquaplanet simulations is plotted against the genesis-weighted absolute sea surface temperature in Fig. 8a. Note the large vertical spread in observed frequency for a given value of average underlying SST (e.g., ~100–400 TCs per year at 28°C). These results confirm that absolute SST alone (averaged over the genesis region) is not the dominant factor governing the number of simulated TCs in these experiments. Qualitatively similar results are found if tropical- or global-mean SST is plotted as the abscissa. While Held and Zhao (2011) found a TC frequency sensitivity of approximately −5.5% K−1 global-mean surface temperature in HiRAM simulations, Merlis et al. (2013) showed that the TC frequency sensitivity to warming could be appreciably masked or enhanced by a coincident change in the mean latitude of the ITCZ. Across our experiments, there are significant changes in the ITCZ time-mean latitude (along with its width and strength), and hence these movements likely contribute greatly to the observed changes in TC genesis. The exception is in the case of the globally uniform perturbation simulations , which can be appropriately compared with the 16°N control (pink circle markers) as there is little change to the latitude of the ITCZ between those simulations. This comparison confirms a decreasing tendency of genesis with a uniform increase in SST alone.

Fig. 8.

Tropical cyclone frequency plotted against several genesis-weighted environmental variables: (a) SST, (b) magnitude of the vertical velocity , (c) absolute vorticity, and (d) relative vorticity. The notation indicates the spatial- and time-mean quantities over the region of TC genesis.

Fig. 8.

Tropical cyclone frequency plotted against several genesis-weighted environmental variables: (a) SST, (b) magnitude of the vertical velocity , (c) absolute vorticity, and (d) relative vorticity. The notation indicates the spatial- and time-mean quantities over the region of TC genesis.

The strength of the mean upward mass flux has been previously linked to changes in TC genesis frequency (e.g., Held and Zhao 2011; Sugi et al. 2012; Sugi and Yoshimura 2012), and here we show the genesis-weighted magnitude of the pressure velocity (Fig. 8b). TC genesis frequency is observed to increase with in fixed-SST simulations, but this relationship is not apparent in the accompanying slab ocean experiments. While in Held and Zhao (2011) a clear relationship was found between mean mass flux and TC frequency when examining one environmental field at a time, Camargo et al. (2014) more recently used vertical velocity as one of the predictors in a set of more comprehensive genesis indices for the simulations of the HiRAM model in present and future climate and found that the inclusion of the vertical velocity did not explain the changes in TC frequency in the future climates.

One can question whether the strength of the vertical motion in the genesis region is controlled by the TC activity rather than the converse. Zhao et al. (2012) have discussed how TC genesis in a version of HiRAM with realistic SSTs can be reduced dramatically by smoothing the horizontal divergence field without modifying the distribution and mean vertical motion significantly. The implication is that the latter is hardly affected by the amount of TC activity. It will be of interest to perform similar parameter sensitivity studies of this and other types in the future to explore these issues more fully.

Along with the strength of the convergence, the latitude of the ITCZ is also an important influence on the number of developing disturbances (Fig. 7e). A standard parameter typically included in various TC genesis indices is a measure of the absolute vorticity , the sum of the latitude-dependent planetary vorticity , and the relative vorticity of the environmental flow. The genesis-weighted absolute vorticity for the various HiRAM simulations is shown in Fig. 8c.

The different HiRAM simulations show a compact and correlated relationship of increasing TC genesis frequency with increasing absolute vorticity, although the slab ocean and fixed-SST experiments do not align on the same curve. The relatively higher frequency of TC genesis in the slab ocean simulations for similar values of in the fixed-SST simulations (Fig. 8c) may help to partially explain the discrepancy in (Fig. 8b), where higher values of upward mass flux in the slab ocean simulations do not yield an increase in TC genesis frequency consistent with the relationship suggested by the fixed-SST experiments. An index that combined proxies for both the strength and latitude of the ITCZ would thus likely yield a tighter relationship. The results shown here are consistent with the “threshold”-type behavior discussed in McGauley and Nolan (2011), where TCs are unable to form without a sufficient value of environmental absolute vorticity.

The changes in between different experiments largely reflect the changes to the mean latitude of TC genesis (recall Fig. 6) and the associated ambient planetary vorticity of the environment. A smaller part of the change in comes from changes in the relative component of vorticity shown in Fig. 8d, which is associated with the structure of the time-mean zonal flow on the poleward flank of the ITCZ. Here the relative vorticity appears to be more sensitive to changes in the shape of the SST profile than to shifts in the latitude of the maximum SST. Changes in the zonal-mean flow may be important in setting the stability of the ITCZ and the propensity for breakdown and generation of TC-like disturbances (e.g., Nieto Ferreira and Schubert 1997) and will be the focus of further investigation.

Motivated by our earlier finding (in section 4) that suggested a relatively flat-SST environment (with the ITCZ remaining close the equator) would prefer to form TCs centered about the latitude of 14.5°N, we consider finally here the environment of this region across all experiments without concerning ourselves with knowing where genesis actually occurs. Figure 9 shows the potential utility of focusing solely (for simplicity) on the environment centered over 14.5°N. Here the time-mean upward vertical motion has been spatially averaged over a latitude band centered at 14.5°N. A Gaussian kernel of width 10° latitude has been used for the spatial averaging, but in fact the result is very similar to that shown if one only analyzes the time-mean at the grid box nearest to 14.5°N (without any latitudinal averaging). The number of TCs that form across the various configurations of the HiRAM aquaplanet that we have analyzed show a striking relationship with the upward mass flux over the 14.5°N latitude region. Moreover, the relationship is shown to tighten further if an adjustment is made to the TC frequency to account for changes in the mean tropical SST between the experiments (e.g., −5% K−1; not shown here).

Fig. 9.

Tropical cyclone frequency plotted against the time-mean vertical velocity, spatially averaged over a region centered at 14.5°N, where TC genesis occurs in the limit of weak SST gradient.

Fig. 9.

Tropical cyclone frequency plotted against the time-mean vertical velocity, spatially averaged over a region centered at 14.5°N, where TC genesis occurs in the limit of weak SST gradient.

6. Conclusions

In the zonally symmetric, interhemispherically asymmetric climates of the HiRAM aquaplanet presented in this study, tropical cyclones form on the poleward flank of the off-equatorial ITCZ, subsequently strengthening and decaying in their intensity as they propagate to higher latitudes. When analyzing the TC activity in these simulations, it is difficult to separate any influences from the prescribed SST profile and the latitude of the ITCZ; the latter is of course related to the former in some nontrivial way. However, by fixing some aspect of the SST profiles between experiments (e.g., the magnitude of the maximum SST and ) while adjusting some other characteristic (e.g., the latitude of the maximum SST), a set of aquaplanet climatologies were formed, each with a small perturbation to the SST profile and associated changes in the latitude of the ITCZ.

The resulting variations in the genesis latitude, frequency, and intensity have been investigated across this range of SST–ITCZ environments in order to identify consistent and robust changes in the statistics of simulated TCs. We find in these simulations that when the tropical meridional SST profile is sufficiently flat that the TCs typically form near 14.5°N. However, as the tropical meridional SST gradient increases, both the ITCZ and genesis region shift toward the latitude of the maximum SST.

The total TC activity (defined by ACE) increases as the latitude of the maximum SST moves poleward. This occurs because of increases in both the genesis frequency and the average intensity of the TCs that form as the maximum SST location shifts poleward. The simulated increase in the genesis frequency may be attributed to the concurrent and related poleward shift in the latitude of the ITCZ. The experiments that move the ITCZ farther poleward while holding the latitude of the maximum SST fixed (through changes in the magnitude of ) result in a higher genesis frequency. These experiments also reveal that the TCs that form in environments where the ITCZ is farther poleward and closer to the latitude of the maximum SST are on average less intense, and hence the total activity is relatively insensitive to the changes in the latitude of the ITCZ alone. We recognize that storm intensities in this model are a function of resolution, so one must assume that results on statistics such as the accumulated cyclone energy will change quantitatively at higher resolution. Whether the qualitative results described here will change at higher resolution remains to be seen.

While the strength of midlevel ascent has been shown here (and elsewhere) to be an important mediator of TC frequency, the upward mass flux over the genesis region alone is not determinative of TC frequency, as notably demonstrated in the slab ocean experiments. Changes in the latitude of the genesis region, and thus the absolute vorticity available to developing TCs, also influence the genesis frequency. Although beyond the scope of this investigation, convectively coupled waves that propagate throughout the tropical region, along with instabilities that develop along the ITCZ itself, are likely important in the formation of the precursor disturbances from which a certain fraction develop into self-sustaining tropical cyclones. The extent to which the large scale influences the fraction of disturbances that develop into tropical cyclones remains an open question.

The aquaplanet configuration of HiRAM or other atmospheric general circulation models with comparable resolution provides an ideal test bed in which to continue to explore the sensitivity of genesis to various aspects of the model’s climatology. A natural extension to this work will explore TC activity when zonal asymmetries in the SST are introduced.

Acknowledgments

The authors wish to acknowledge colleagues at the Geophysical Fluid Dynamics Laboratory of the National Oceanic and Atmospheric Administration for ongoing computing support and helpful discussions, in particular Hiroyuki Murakami and Lucas Harris who reviewed an earlier draft of the manuscript. The comments of three anonymous reviewers helped to refine the final manuscript. This work was supported in part by U.S. Department of Energy Grant DE-SC0006841. The findings are those of the authors and do not necessarily reflect the views of the U.S. Department of Energy.

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