Post-tropical cyclones (PTCs) can cause extensive damage across Europe through extreme winds and heavy precipitation. With increasing sea surface temperatures, tropical cyclones (TCs) may form and travel further poleward and eastward than observed historically. Recent work has suggested that the frequency of intense Europe-impacting PTCs may increase substantially in the future.
Using an objective feature-tracking scheme and TC identification method, we track and identify the full life cycle of TCs in the North Atlantic in five CMIP6 climate models in the historical (1984–2014) period and in the future under the SSP5-85 scenario (2069–2099). These five models are selected based on their ability to simulate TC frequency similar to observed in the North Atlantic, although model deficiencies remain.
We find no robust changes in Europe-impacting PTC frequency or intensity in the future. This is because two competing factors – a significant decrease in TC frequency of 30 %–60 % and an increase in the proportion of TCs reaching Europe – are approximately the same size. The projected increase in the proportion of TCs reaching Europe is largely driven by an increase in the likelihood of recurvature and is consistent with projected decreases in vertical wind shear and increases in potential intensity along the US East Coast in the future. The projected increased likelihood of recurvature is also associated with a shift in TC genesis away from the main development region, where model biases cause very few TCs to recurve. This study indicates that large uncertainties surround future Europe-impacting PTCs and provides a framework for evaluating PTCs in future generations of climate models.
Post-tropical cyclones (PTCs) can bring Europe hazardous weather such as extreme precipitation, high winds, and large waves (Bieli et al., 2019; Evans et al., 2017; Jones et al., 2003). Compared to the overall European cyclone climatology, PTCs are disproportionately responsible for the most intense windstorms to impact Europe during hurricane season (Sainsbury et al., 2020) and often attain their maximum intensity a couple of days after impacting the region, enhancing their destructive potential (Baker et al., 2021; Dekker et al., 2018).
In 2017, Hurricane Ophelia (Rantanen et al.,
2020) became the easternmost major hurricane on record
(Stewart, 2018), and in 2019 Hurricane Lorenzo became the
easternmost category 5 hurricane on record. Both cyclones later impacted
Europe as PTCs, and Ophelia was responsible for Ireland's highest-recorded
wind gust of 53 m s
Few studies have investigated the projected changes of Europe-impacting
PTCs, and those that do only considered storm-force
(Baatsen et al.,
2015) and hurricane-force (Haarsma et
al., 2013) PTCs. Using a high-resolution (
Liu et al. (2017) considered North Atlantic TCs undergoing extratropical
transition (ET) more generally and found an increase in TC density in the
eastern North Atlantic under the RCP 4.5 emission scenario by the end of the
century in a flux-adjusted version of the FLOR model
(Vecchi et al., 2014),
indicating an increase in TC-related risks for Europe. A statistically
significant increase in the fraction of TCs undergoing ET is also found in
the future
(Liu
et al., 2017). This trend has also been found in several (but not all)
reanalyses (Baker et al., 2021), and mixed results have
been found in climate model studies
(Michaelis
and Lackmann, 2019; Bieli et al., 2020). Using a pseudo-global-warming (PGW)
approach to dynamical downscaling, Jung and
Lackmann (2019) found that Hurricane Irene (Avila and
Cangialosi, 2011) would be considerably stronger (
Given the potential for an increased PTC risk to Europe in the future, a multi-model study with a focus on Europe is necessary to quantify the associated model uncertainty and to assess whether lower-resolution models can provide insight into future PTC changes. Many lower-resolution climate models do not simulate a realistic TC frequency (e.g. Camargo, 2013), and even high-resolution climate models are unable to capture the strongest TCs (e.g. Walsh et al., 2015; Vidale et al., 2021; Roberts et al., 2020a). In this paper we investigate the projected changes in Europe-impacting PTCs in an ensemble of five CMIP6 models which are shown to simulate a realistic North Atlantic TC frequency compared to observations. Some of these models have a lower horizontal resolution than previous studies (e.g. Baker et al., 2022; Haarsma et al., 2013), and thus simulated TCs are expected to be weaker. However, a multi-model study using models containing multiple ensemble members allows for a greater sample size and greater uncertainty quantification. It is unknown whether low-resolution CMIP6 models can give insight into projected changes in TC and PTC statistics despite their deficiencies and biases. This is investigated in this study. As far as the authors are aware, a multi-model study with a focus particularly on Europe-impacting PTCs has never been undertaken.
This paper aims to answer the following questions.
To what extent can CMIP6 models capture the characteristics of the North
Atlantic TC climatology? How well do CMIP6 models capture the disproportionate intensity associated
with Europe-impacting PTCs relative to the overall cyclone climatology? Are there any areas of model consensus regarding projected changes in PTC
frequency over Europe?
In Sect. 2, we describe the cyclone detection and tracking scheme, TC
identification procedure, and CMIP6 models included in this study. Section 3
contains an overview of the TC climatologies in the selected CMIP6 models,
the projected changes in the frequency and intensity of Europe-impacting
PTCs, and further analysis to investigate the cause of the projected
changes. The paper concludes with a discussion in Sect. 4.
For this study, we use data from the fully coupled historical and SSP5-85
model simulations from phase 6 of the Coupled Model Intercomparison Project
(CMIP6; Eyring et al., 2016). Although many CMIP6 models
have a resolution too low to simulate the observed structure and intensity
of TCs, low-resolution climate models can often still simulate TC-like
vortices (Haarsma et al., 1993). On
average, there are 6.4 North Atlantic hurricanes (wind speeds
The chosen five models are CNRM-CM6-1-HR (CNRM hereafter), HadGEM3-GC31-MM (HadGEM hereafter), KIOST-ESM (KIOST hereafter), MIROC6 (MIROC hereafter), and IPSL-CM6A-LR (IPSL hereafter). CNRM and HadGEM have a higher horizontal resolution in the atmosphere and ocean than the other selected models (Table 1). While CNRM and HadGEM also have HighResMIP simulations available, they use a different experimental protocol (e.g. different aerosol forcing and land surface scheme) and only run out to the year 2050. In this study we focus on the ScenarioMIP simulations for consistency with the other selected models. The period 1984–2014 is used for the historical run and 2069–2099 for the SSP5-85 scenario, giving an 85-year difference between the midpoints of the two time periods considered in this study. More information can be found in Table 1. Key results have been reproduced using only ensemble members which are available for both the historical and SSP5-85 scenario simulations and are shown in the Supplement (Fig. S7 and Table S1). The 6-hourly wind components are utilized at 850, 500, and 250 hPa for calculation of the vorticity fields necessary for TC identification (more information in Sect. 2.2). The 6-hourly mean sea level pressure and 10 m wind data are also used to investigate the intensity of the cyclones. Monthly mean temperature and specific humidity profiles are utilized to calculate potential intensity (PI), monthly mean relative humidity, wind, and SSTs to construct the genesis potential index (Emanuel and Nolan, 2004).
Summary of the CMIP6 models used in this study, including model name (column 1), reference to model development (column 2), number of ensemble members used (column 3), atmospheric model resolution (column 4), ocean model resolution (column 5), and number of vertical layers in the atmosphere (column 6) and ocean (column 7) models.
Using the same tracking and TC identification scheme as CMIP6 models, the European Centre for Medium-Range Weather Forecasts fifth reanalysis (ERA5; Hersbach et al., 2020) is used for verification of model TC climatologies from 1984–2014. The 6-hourly relative vorticity fields from ERA5 are used for cyclone tracking and TC identification, and 6-hourly sea level pressure and 10 m winds from ERA5 are used to investigate cyclone intensity.
The 6-hourly position, 10 m wind speed, and sea level pressure data from the Hurricane Database version 2 (HURDAT2; Landsea and Franklin, 2013) are used between 1984 and 2014 in Sect. 3.1 to compare TC intensity and spatial distribution with those simulated in ERA5 and CMIP6.
Cyclone detection and tracking is performed using the objective feature-tracking scheme, TRACK
(Hodges, 1994, 1995,
1999), configured for TCs. The tracking is performed on the spectrally
filtered (T63 resolution) relative vorticity fields vertically averaged
(600–850 hPa) for ERA5 and at 850 hPa (spectrally filtered to T42) for CMIP6
due to data availability. Vorticity anomalies exceeding
The spatial distribution of the TC track and genesis densities are calculated
from the cyclone tracks using the spherical kernel method described in
Hodges (1996). Densities are expressed as
cyclones per year per unit area, where the unit area is equivalent to a
spherical cap with a radius of 5
Genesis density (storms per unit area per year, where the unit
area is equal to a spherical cap with a 5
As in Fig. 1 but for track density. Densities less than 0.2
have been masked for clarity. Black contours in panel
TCs are identified from the larger sample of tracked cyclones using the
methodology of Hodges et al. (2017). A cyclone track is identified as a TC if the following criteria are
met:
the first point in the cyclone track (genesis) is equatorward of 30 the T63 relative vorticity exceeds the difference in T63 relative vorticity between 850 and 200 hPa exceeds
a T63 relative vorticity signature must exist at each pressure level between
250 and 850 hPa to indicate a coherent vertical structure.
Cyclone tracking and TC identification are performed entirely using relative
vorticity fields, and no wind speed or sea level pressure thresholds are
used. TC identification methods which use wind speed thresholds often have
to account for model resolution by modifying the thresholds depending on
model resolution (Walsh et al., 2015), whereas this
methodology aims to be as resolution independent as possible. Criteria 2–4
must be met for at least four consecutive time steps (1 d) over the ocean.
This method of TC identification allows us to capture the entire life cycle
of TCs, including the pre- and post-TC stages. Only tracks which form in the
North Atlantic hurricane season (1 June–30 November) are
considered in this study. The TC identification criteria are applied to the
vorticity fields at the 850, 700, 600, 500, 400, 300, and 250 hPa pressure
levels for ERA5 but only to the 850, 500, and 250 hPa levels for CMIP6 models
due to data availability. Previous (unpublished) work found little
sensitivity on cyclone statistics to this difference in data and methodology
for tracking and TC identification (not shown). The SSTs are expected to
increase as a result of climate change, and so the poleward extent of TC
genesis may move poleward, potentially beyond 30
The TC identification method used here has been used in numerous studies based on reanalyses (Hodges et al., 2017; Baker et al., 2021) and climate models (e.g. Baker et al., 2022; Roberts et al., 2015; Vidale et al., 2021). It has been shown that PTC impacts over Europe in the present climate are similar whether this objective TC identification method or objective track matching with observational data is used (Sainsbury et al., 2020).
Changes in TC statistics, recurving TC statistics, and Europe-impacting PTC
statistics are considered in this study. A recurving TC is defined as a TC
which enters a domain in the North Atlantic midlatitudes from 36–70
In Sect. 3.2.2, we investigate North Atlantic TC genesis regionally. North
Atlantic TCs are separated based on genesis into three regions: the main
development region (MDR, 0–20
Changes in large-scale environment fields known to be associated with TC
genesis and intensification are investigated in CMIP6 using the genesis
potential index (GPI; Emanuel and Nolan, 2004).
Deep layer steering flow is also used and is defined as in Colbert and Soden (2012). However, due to data availability, we use the 250 hPa field instead of the 200 hPa field.
In this section we examine the climatology and properties of the TCs simulated by each of the selected CMIP6 models. If we wish to learn something about how PTC impacts may change across Europe in the future, we need to understand whether these models are able to capture features of the observed TC climatology and also identify any biases which may translate into biases in the projected changes in PTC statistics.
Figure 1 shows the genesis density in the historical period for the five
selected CMIP6 models (panels a–e) and ERA5 and HURDAT2 (panel f). Comparisons between
HURDAT2 and ERA5/CMIP6 models should be made cautiously due to differences
in how TCs are identified. For example, the cyclone detection and tracking
scheme used in this study allows for the identification of TC precursors.
Therefore, the genesis densities shown for the CMIP6 models and ERA5
represent the genesis density of the precursors to TCs, whereas the HURDAT2
genesis density shows where these precursors developed into TCs. This
explains the differences in genesis density between CMIP6/ERA5 and HURDAT2
over west Africa. The CMIP6 models, ERA5 and HURDAT2, typically show two
regions of genesis maxima: one centred between 0 and 30
All of the models capture the maxima in track density in the main
development region (MDR) and the maxima in track density recurving around
the US East Coast, heading towards Europe (as shown in
Baker et al., 2021). As with genesis density (Fig. 1), many of the models have two apparent storm tracks, one associated with
storms originating in the MDR and one associated with storms originating
further west in the basin. In all models except CNRM, track density
decreases rapidly from east to west across the MDR, and this is particularly
clear in IPSL (Fig. 2e). The lysis density (Fig. S3) is greater in the MDR
in KIOST, MIROC, and IPSL than it is in ERA5, indicating that in these
models TCs forming in the MDR dissipate too quickly. This is particularly
clear for IPSL, which shows almost all MDR TCs dissipating whilst still in
the MDR, close to where they formed. MDR-forming TCs in ERA5 have a mean
track length of
Coupled with the lack of genesis in the western MDR in these models (Fig. 1), the track (Fig. 2) and lysis (Fig. S3) density plots suggest that
conditions in the models are too hostile for TC genesis or intensification
in this region. In particular, vertical wind shear in all models except CNRM
is higher (
Figure 3 shows the seasonal cycle for the selected CMIP6 models and ERA5. TCs in HURDAT2 are identified later in their life cycle than TCs tracked and identified objectively (Sect. 2.2 and 2.3) in ERA5 and CMIP6 models. HURDAT2 data are therefore not included in Fig. 3. CNRM has a bias towards early season North Atlantic TC activity (compared to ERA5), with a peak in August. This can also be seen in KIOST but to a lesser extent. The other three CMIP6 models all show a peak in North Atlantic TC formation in September, the same as in ERA5. While the seasonal cycle is captured well by the models, all but CNRM underestimate North Atlantic TC frequency during hurricane season, with the largest underestimation found in HadGEM during the months of peak activity (August–October), consistent with too few simulated TCs originating in the MDR (Figs. 1 and 2). All models except the CNRM underestimate Europe-impacting PTC frequency (Fig. 3b). This is because in all models except CNRM, proportionally too few TCs originating in the MDR recurve (Table 3). As a result, there are fewer TCs reaching the midlatitudes – the region which often provides the baroclinicity to facilitate extratropical transition and future reintensification on approach to Europe. All selected CMIP6 models except KIOST have similar SST gradients along the midlatitude storm track to those found in ERA5 during hurricane season. In the KIOST, SST gradients are slightly higher, which may be associated with the greater proportion of recurving TCs reaching Europe in the historical period (Table 2).
Seasonal cycle of North Atlantic TCs
Counts of Europe-impacting PTCs, North Atlantic TCs, likelihood of recurvature, and likelihood that a recurving TC will reach Europe for the historical (1984–2014) period and the future (2069–2099) period under the SSP5-85 scenario. Fractional changes are shown under the “Diff” columns. Bold values represent significance at the 95 % level using a bootstrapping method.
Tabulated values of the terms of the right-hand side of Eq. (3) for the historical run (top), the future run under SSP5-85 (middle), and the fractional change (bottom) for the five selected CMIP6 models. Bolded differences represent statistical significance at the 95 % level.
TC lifetime maximum intensity (LMI) distributions for the selected CMIP6
models are shown in Fig. 4. All models use the same sampling frequency for
wind speed (all are indexed as 3hrPt on the CMIP6 archive). All selected CMIP6 models underestimate the mean TC LMI
and are unable to simulate the strongest observed TCs. CNRM is able to
simulate stronger TCs than the other CMIP6 models and ERA5, with some TCs
approaching 50 m s
TC lifetime maximum intensity distributions for the historical (1984–2014) period for selected CMIP6 models, ERA5 (black, solid), and HURDAT2 (black, dashed). Only TCs forming during the North Atlantic hurricane season are considered. Densities are approximated as kernel density estimates. Vertical grey lines represent the different categories on the Saffir–Simpson scale. The number of ensemble members used for each model is shown in brackets in the key.
The majority of TCs identified in the historical period of IPSL are
extremely weak, with 10 m wind speeds less than tropical storm (17 m s
Despite clear model biases, the selected CMIP6 models represent many
features of the observed TC climatology, with spatial patterns and
frequencies in qualitative agreement with observations. TC frequency,
seasonal cycle, and spatial distribution in these selected CMIP6 models are
comparable to those found in higher-resolution modelling studies, such as
Climate-SPHINX
(Vidale
et al., 2021), UPSCALE
(Roberts
et al., 2015), and HighResMIP-PRIMAVERA
(Roberts
et al., 2020a; Haarsma et al., 2016; Baker et al., 2022), which used the
same tracking and identification scheme. However, many high-resolution
climate models are able to simulate TCs with intensities greater than
50 m s
To gain insight into the projected changes in Europe-impacting PTCs, CMIP6 models must also capture the key features of the recurving TC and Europe-impacting PTC climatologies. Previous work has shown that, to first order, TC activity governs recurving TC frequency (Sainsbury et al., 2022a). The selected CMIP6 models also capture the strong relationship between TC frequency and recurving TC frequency (Fig. S6), highlighting that the models can capture the main driver of the interannual variability of recurving TCs, which may have important implications for European PTC risk.
A key feature of the observed PTC climatology is that PTC maximum intensities over Europe are, on average, larger than those found for the broader class of midlatitude cyclones (MLCs, defined as all cyclones which are not PTCs) forming during hurricane season (Sainsbury et al., 2020). In Fig. 5, we identify the maximum intensity associated with each PTC and MLC over Europe and subregions (northern/southern Europe, shown in Fig. 1) and investigate the fraction of cyclones in each intensity bin which are PTCs.
Fraction of hurricane-season-forming, Europe-impacting cyclones
which are PTCs for CNRM
To ensure that the sample size remains reasonable across bins and across
models, we bin the cyclones based on percentiles of the combined
distribution. For each model, we combine the (Europe-impacting) PTC and MLC
cyclone tracks over both time periods (historical and future) and calculate
percentiles of this joint distribution of their maximum 10 m wind speeds over
Europe. These percentiles are then used to bin the data. The bins therefore
correspond to 0–20th, 20–40th, 40–60th, 60–80th,
80–90th, 90–95th, and
In ERA5, only 0.56 % of cyclones reaching Europe during the North Atlantic
hurricane season are PTCs. However, when considering the highest-intensity
bin (
In this section we investigate the projected changes in Europe-impacting PTC counts. We consider the projected changes in three key components: (i) changes in basin-wide North Atlantic TC counts, (ii) changes in the likelihood that a North Atlantic TC will recurve, and (iii) changes in the likelihood that a recurving North Atlantic TC will reach Europe.
While some overlap exists, these three components are likely driven by different factors. Changes in basin-wide TC counts to an extent depend on how the large-scale environment (sea surface temperature, vertical wind shear, atmospheric moisture, etc.) and teleconnections (e.g. ENSO) change in the future (e.g. genesis potential index; Camargo, 2013). Changes in likelihood of recurvature may depend on changes to the large-scale steering flow, changes in TC intensity (stronger TCs survive longer), changes in where TCs are forming (TCs in some regions are more prone to recurve than in other regions; Sainsbury et al., 2022a), and changes to the large-scale environmental conditions in the subtropical Atlantic (more favourable conditions for TCs in the subtropics may lead to a larger proportion of TCs successfully making the transit from the tropics to the extratropics; Haarsma et al., 2013). Changes in the likelihood that a recurving TC will reach Europe may be related to changes in the midlatitude jet and the intensity of TCs (Haarsma, 2021; Sainsbury et al., 2022b).
Europe-impacting PTC counts are therefore expressed as
All five selected models project a statistically significant (to 95 %)
decrease in North Atlantic TC frequency (
In all models except CNRM, the fractional decrease in TC counts is much
larger than the fractional change in Europe-impacting PTC counts, with two
models even projecting an increase in Europe-impacting PTC counts in the
future. Therefore, in four of the five models, there is a projected increase
in the proportion of North Atlantic TCs which reach Europe in the future
(
Projected change (future minus historical) in the GPI (first
column) and the individual terms of the GPI equations (columns 2–5) for CNRM
(top row), HadGEM (second row), KIOST (third row) MIROC (fourth row), and
IPSL (fifth row) and ensemble mean (sixth row): vorticity term (second
column), humidity term (third column), PI term (fourth column), and shear
term (fifth column). Note that the vertical wind shear term is a function of
the reciprocal of the wind shear, and so a positive difference indicates
less vertical wind shear in the future. The number of ensemble members used for the historical and future periods are shown in the upper right of the first column (historical, future). Stippling represents statistical significance at the 95 % level using Welch's
To investigate the significant projected decrease in North Atlantic TC
counts (Table 2), the projected change in the genesis potential index and
its terms (as calculated in Sect. 2.5) during the North Atlantic hurricane
season are calculated and shown in Fig. 6. The historical biases in GPI
and its terms for the selected CMIP6 models can be found in the
Supplement (Fig. S4). Although all models have some biases in
GPI and comprising terms, the main similarity between the selected CMIP6
models is a positive wind shear bias in the MDR in all models except CNRM.
Overall, the genesis potential index is projected to significantly increase
along the US East Coast between approximately 30 and 40
While the projected changes in Fig. 6 are consistent with an increased probability of recurvature, they do not help to explain the significant decrease in basin-wide TC counts towards the end of the century. Previous studies have shown that saturation deficit may be a better metric for TC genesis potential than relative humidity (Emanuel et al., 2008) and is projected to increase in the future (increasing hostility). Furthermore, it has been proposed that an increase in static stability may lead to a reduction in TC frequency (Bengtsson et al., 2007; Sugi et al., 2002). These factors may help to explain why we see such a large projected decrease in TC counts in the North Atlantic despite an overall increase in the GPI.
Table 2 shows a statistically significant increase in the likelihood of
recurvature in three of the five models. Whether or not a TC recurves could depend
on multiple factors (Sainsbury et al.,
2022a): the location in which the TC forms, TC intensity (stronger TCs are
more resilient to hostile conditions), and the steering flow
(Colbert and
Soden, 2012). In this subsection, we aim to investigate which of these
factors – if any – are responsible for the projected increased in
Projected increases in GPI along the US East Coast are consistent with the
increased likelihood of recurvature. In this region, a reduction in wind
shear is collocated with a projected increase in PI (Fig. 6). This is
consistent with CMIP5 models
(Camargo, 2013) and
indicates that future TCs traversing the US East Coast may retain TC-like
conditions further poleward, increasing their likelihood of both making it
to the midlatitudes (and being identified as recurving as a result) and
potentially also reaching Europe. The projected increase in GPI along the US
East Coast supports previous studies which suggest an increase in the
latitude of TC LMI and an overall expansion of the tropical genesis region
(Kossin et al., 2014; Haarsma, 2021). However,
all five models show an increase in GPI along the US East Coast, but only
three models have a significant increase in
Figure 7 shows the normalized TC track density for the historical and future
periods, along with the difference (future minus historical). The track
densities are normalized by dividing by the total number of TCs, so the
differences show the geographical redistribution of North Atlantic TCs
rather than the change in total number (
Normalized TC track density for the five selected CMIP6 models during the historical (first column) period, towards the end of the century under SSP5-85 (middle) and the difference (future minus historical, right column). Densities less than 1 have been masked for clarity. Black domains represent the boundaries of the MDR, SUB, and WEST regions.
HadGEM, IPSL, and MIROC have many similarities in normalized track density difference. There is proportionally less track density in the MDR and proportionally higher track density in the future along the East Coast of the US heading towards Europe. The large decrease in normalized TC track density in the MDR indicates a potential shift in genesis, away from the MDR towards the west of the North Atlantic, as confirmed by the normalized genesis densities (Fig. S8). To investigate this further, we separate the North Atlantic TCs based on genesis into three regions: the main development region (MDR), subtropical Atlantic (SUB), and western Atlantic (WEST). These regions are constructed such that all North Atlantic TCs form in one of these regions, and the boundaries for these regions can be found in Sect. 2.4.
We decompose the likelihood of recurvature based on these three regions of
genesis:
Rows 2–6 of Table 3 highlight the significant bias historically of many of
the models (all but CNRM) for recurvature of TCs originating in the MDR.
Approximately 46 % of MDR-forming TCs recurve in ERA5, but this value is
between 3 % and 19 % in four of the five models, with only CNRM
correctly capturing this fraction. The three models which have a significant
increase in
Term 2 dominates for the three models which have a significant increase in
Contribution to projected change in
While shifts in genesis explain most of the projected change in
Figure 8 shows the change in the hurricane-season mean deep layer steering
flow (Colbert
and Soden, 2012). All models have a significantly weaker westerly flow
between 30 and 40
Difference (future minus historical) in the hurricane-season
averaged deep layer steering flow for the five selected CMIP6 models.
Statistically significant differences between the future and historical
period at the 95 % level are shown in red and are calculated using Welch's
Three of the five CMIP6 models project a significant increase in
While four of the five CMIP6 models agree on the sign of the change in
Figure 9 shows the absolute number (per ensemble member) of Europe-impacting PTCs in each bin during the historical and future periods (bars), with the fractional change overlaid. CNRM and KIOST show a decrease in the absolute number of strong Europe-impacting PTCs (Fig. 9a and e). IPSL and MIROC ensembles show an increase. HadGEM is mixed, with a decrease in the number of PTCs in the highest-intensity bin but increases in the second- and third-highest-intensity bins (Fig. 9b). The projected changes in Europe-impacting PTC intensity shown in Fig. 9 are not significantly different if reproduced using only ensemble members common to both the historical and future periods (Fig. S7).
Bar plot showing the number of Europe-impacting PTCs (per ensemble
member) in each intensity bin for the five selected CMIP6 models for the
historical (1984–2014, lighter colours) period and towards the end of the
century under the SSP5-85 scenario (2069–2099, darker colours). Fractional
change in the counts in the future period compared to historical is shown as
the black line corresponding to the right-hand-side
In HadGEM, KIOST, MIROC, and IPSL, the decrease in TC frequency basin-wide is considerably larger than the change in strong Europe-impacting PTCs. For example, MIROC has an increase in the number of strong Europe-impacting PTCs despite a 31 % reduction in the number of North Atlantic TCs. This implies that the proportion of North Atlantic TCs which impact Europe as strong PTCs is projected to increase. This is illustrated in Fig. 10, which shows the proportion of all North Atlantic TCs which reach Europe as strong PTCs (Fig. 10b) and very strong PTCs (Fig. 10c). Strong PTCs are defined as PTCs which impact Europe with winds greater than the 90th percentile of the distribution of maximum winds over Europe during hurricane season (considering all PTCs and MLCs in the historical and future period). Very strong PTCs are PTCs which impact Europe with winds greater than the 95th percentile.
Bar charts showing the proportion of North Atlantic TCs which
impact Europe as
Four of the five models show an increase in the proportion of North Atlantic TCs which reach Europe as strong and very strong PTCs, and this difference is statistically significant in IPSL and MIROC. Our results therefore suggest that the future risk posed by PTCs to Europe may depend on how TC activity basin-wide changes in the future. If TC frequency decreases substantially (as suggested by this analysis), then the number of strong Europe-impacting PTCs is unlikely to change significantly. However, if TC frequency does not decrease much, or potentially increases, then Europe could be subject to significantly more strong PTCs in the future, as was found in Haarsma et al. (2013).
Haarsma et al. (2013) find a large increase in the frequency of hurricane-force PTCs reaching Europe by the end of the century. The interpretation of Figs. 9 and 10 does not change when using the regions (Norway, North Sea, west UK and Ireland, and Bay of Biscay) and season (August–October) used in Haarsma et al. (2013; Figs. S10–S12). Despite using RCP 4.5, the prescribed SSTs used in Haarsma et al. (2013) are similar to the projected SST changes found in this study (not shown). The differences between Fig. S10 and Fig. 2f in Haarsma et al. (2013) could be caused by different projected changes in North Atlantic TC counts (which were not investigated in their study), differences in model resolution, differences in TC identification methodology, or differences model configuration (coupled vs. atmosphere only).
In this study, we have presented the first multi-model analysis of how Europe-impacting PTC frequency and intensity may change by 2100. Using a vorticity-based tracking scheme and objective TC identification method, we identify all North Atlantic TCs in five CMIP6 models in the historical (1984–2014) period and the future (2069–2099) period under the SSP5-85 scenario, using all available ensemble members. These five models were selected from a wider sample of CMIP6 models based on their ability to simulate North Atlantic TC frequency compared to observations (Fig. S1 in the Supplement). While CMIP6 models do not have sufficient resolution to resolve all TC-related processes, the number of models and ensemble members allows us to investigate projected Europe-impacting PTCs changes with a considerably larger TC sample size than available for previous studies. The key results are as follows.
The five selected CMIP6 models are able to simulate many aspects of the
North Atlantic TC climatology compared to observations. They capture the
relationship between TC frequency and recurving TC frequency and capture
the disproportionate risk associated with PTCs compared to extratropical
cyclones over Europe. However, the models still have many deficiencies. In
particular, TCs forming in the MDR are too short lived and therefore
unlikely to recurve, and TC intensity is significantly underestimated. No robust model response in Europe-impacting PTC frequency (overall or as
strong storms) is found in the future. This is because two competing factors
– a decrease in North Atlantic TC frequency and an increase in the
proportion of TCs reaching Europe – are of approximately the same size. The projected decrease in North Atlantic TC frequency is statistically
significant in all five models, with decreases of between 30 % and 60 %
found by the end of the 21st century. The projected increase in the proportion of TCs reaching Europe is found in
four of the five models and is associated with a projected increase in the
likelihood of recurvature. The increased likelihood of recurvature may be
associated with a more favourable environment for TCs along the US East
Coast, where wind shear is projected to decrease and potential intensity is
projected to increase in the future. This result is also consistent with
previous studies which highlight that conditions between where TCs typically
form and Europe are overall likely to become more favourable for tropical
cyclogenesis in the future
(Haarsma
et al., 2013; Baatsen et al., 2015; Liu et al., 2017). The projected increase in the likelihood of recurvature in the North
Atlantic is also associated with a shift in genesis, with proportionally
fewer TCs forming in the MDR in the future, where model biases cause very few
TCs to recurve.
Our results highlight the large uncertainty associated with projected
changes in Europe-impacting PTC intensity and frequency. Even the model with
the largest projected increase in intense Europe-impacting PTCs has a
considerably lower increase than found in previous studies
(Haarsma
et al., 2013; Baatsen et al., 2015). The large uncertainties in the
projected responses are anticipated – model uncertainties in TC genesis
(Yamada
et al. 2021; Yang et al. 2021; Vecchi et al. 2019;
Camargo
2013; Ting et al., 2015), TC recurvature
(Colbert and
Soden, 2012), TC intensity (Kossin et al., 2020), and
midlatitude environment (for example, jet location and intensity;
Harvey et al., 2020) could translate to model
uncertainty in Europe-impacting PTCs due to the complex life cycle of these
systems.
Projected decreases in North Atlantic TC counts are found in many previous studies which explicitly track TCs (Roberts et al., 2015; Gualdi et al., 2008; Rathman et al., 2014), but not all (e.g. Bhatia et al. 2018). There are also physical arguments which support a decrease in TC activity due to an increase in static stability (e.g. Bengtsson et al., 2007; Sugi et al., 2002). However, other methods such as statistical and dynamical downscaling are more mixed in terms of the sign of the projected change (Emanuel, 2021, 2013; Jing et al., 2021), and there are often sensitivities to the tracking scheme when TCs are tracked explicitly (Roberts et al., 2020b). Previous studies have also suggested a broadening of weak TC circulations in the future (Sugi et al., 2020), which would result in future TCs having lower associated vorticity. As a result, tracking schemes which used a fixed vorticity threshold may capture a lower proportion of all model-simulated TCs in the future. The use of a percentile-based vorticity threshold may alleviate this problem. It is therefore necessary to reduce the uncertainty associated with North Atlantic TC frequency projections before greater confidence in future European PTC risk can be achieved. This should involve further work on our theoretical understanding of what drives TC genesis and further quantification of the uncertainty associated with different TC identification methods (e.g. Bourdin et al., 2022).
Model biases, particularly in the MDR, are likely to manifest in the future projections. Furthermore, TC LMI, which is not adequately captured by these models, has been shown to be associated with the likelihood of recurvature (Sainsbury et al., 2022a) and the likelihood that a recurving TC will reach Europe (Sainsbury et al., 2022b). The model deficiencies in TC intensity may therefore be contributing to the low bias in likelihood of recurvature across many of the models during the historical period. Additionally, there is a mismatch between climate model projections and observations of the zonal temperature gradient in the tropical Pacific, which has implications for North Atlantic vertical wind shear (Seager et al., 2019), which is important for TC genesis and may be important for the projected change in the likelihood of recurvature of North Atlantic TCs. Therefore, CMIP6 models must be used cautiously when investigating projected changes to TC recurvature or Europe PTC impacts in the future. Previous studies suggest that TCs will be more intense in the future (Knutson et al., 2010, 2019; Bhatia et al., 2018; Bender et al., 2010; Emanuel, 2021; Walsh et al., 2019), implying greater longevity and a greater probability of reaching Europe (Sainsbury et al., 2022b). Multi-model studies using high-resolution climate models, which are capable of better simulating the distribution of TC intensities, are therefore necessary to fully explore the projected changes in Europe-impacting PTCs.
By splitting the North Atlantic basin into different spatial regions, the
fraction of recurving North Atlantic TCs in the historical, H, and future,
HURDAT2 data can be downloaded from the NOAA's Hurricane Research Division
(
The supplement related to this article is available online at:
EMS designed the study with input from RKHS, KIH, AJB, LCS, and KTB. EMS performed TC identification and the analysis on cyclone tracks and environmental fields. All authors provided valuable feedback and shaped the study. KIH performed cyclone tracking on ERA5 and the CMIP6 models. EMS prepared the manuscript with input from all co-authors. RKHS, KIH, AJB, and LCS obtained the funding for this project. SB read the manuscript and provided feedback.
The contact author has declared that none of the authors has any competing interests.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
The authors thank Michiel Baatsen and an anonymous reviewer for their comments which greatly improved the clarity of this paper. Elliott Michael Sainsbury was funded by the Natural Environment Research Council (NERC) via the SCENARIO Doctoral Training Partnership with additional CASE funding from BP. Reinhard K. H. Schiemann, Kevin I. Hodges, Alexander J. Baker, and Len C. Shaffrey are supported by the UK National Centre for Atmospheric Science (NCAS) at the University of Reading. Alexander J. Baker acknowledges funding from the PRIMAVERA project received from the European Commission and NERC funding through the North Atlantic Climate System Integrated Study (ACSIS) grant. We thank Olivier Boucher and Thibaut Lurton (IPSL) for re-running the IPSL-CM6A-LR model to provide us with the SSP5-85 scenario data needed to include the model in this study. The IPSL-CM6 experiments were performed using the HPC resources of TGCC (project gencmip6), provided by GENCI (Grand Équipement National de Calcul Intensif). This work benefited from French state aid, managed by the ANR under the “Investissements d'avenir” programme. Stella Bourdin is supported by public funding from the CEA and the EUR IPSL-Climate. Len C. Shaffrey and Reinhard K. H. Schiemann acknowledge funding from the NERC CANARI project.
This research has been supported by the Natural Environment Research Council (grant nos. NE/S0077261/1, NE/N018044/1, and NE/W004984/1), the European Commission Horizon 2020 Framework Programme (PRIMAVERA, grant no. 641727), the Grand Équipement National De Calcul Intensif (grant no. 2021-A0100107732), and the Commissariat Général à l'Investissement (grant no. ANR-11-IDEX-0004-17-EURE-0006).
This paper was edited by Christian M. Grams and reviewed by Michiel Baatsen and one anonymous referee.