Editing IPCC:AR6/WGI/Chapter-11 (section)

==== 11.7.1.4 Detection and Attribution, Event Attribution ====

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There is general agreement in the literature that anthropogenic greenhouse gases and aerosols have measurably affected observed oceanic and atmospheric variability in TC-prone regions (see Chapter 3). This underpinned the SROCC assessment of ''medium confidence'' that humans have contributed to the observed increase in Atlantic hurricane activity since the 1970s (Chapter 5, [[#Bindoff--2013|Bindoff et al., 2013]] ). Literature subsequent to AR5 lends further support to this statement ( [[#Knutson--2019|Knutson et al., 2019]] ). However, there is still no consensus on the relative magnitude of human and natural influences on past changes in Atlantic hurricane activity, and particularly on which factor has dominated the observed increase ( [[#Ting--2015|Ting et al., 2015]] ) and it remains uncertain whether past changes in Atlantic TC activity are outside the range of natural variability. A recent result using high-resolution dynamical model experiments suggested that the observed spatial contrast in TC trends cannot be explained only by multi-decadal natural variability, and that external forcing plays an important role ( [[#Murakami--2020|Murakami et al., 2020]] ).Observational evidence for significant global increases in the proportion of major TC intensities ( [[#Kossin--2020|Kossin et al., 2020]] ) is consistent with both theory and numerical modelling simulations, which generally indicate an increase in mean TC peak intensity and the proportion of very intense TCs in a warming world ( [[#Knutson--2015|Knutson et al., 2015]] , 2020; [[#Walsh--2015|Walsh et al., 2015]] , 2016). In addition, high-resolution coupled model simulations provide support that natural variability alone is ''unlikely'' to explain the magnitude of the observed increase in TC intensification rates and upward TC intensity trend in the Atlantic basin since the early 1980s ( [[#Bhatia--2019|Bhatia et al., 2019]] ; [[#Murakami--2020|Murakami et al., 2020]] ).

The cause of the observed slowdown in TC translation speed is not yet clear. [[#Yamaguchi--2020|Yamaguchi et al. (2020)]] used large ensemble simulations to argue that part of the slowdown is due to actual latitudinal shifts of TC tracks, rather than data artefacts, in addition to atmospheric circulation changes. G. [[#Zhang--2020|]] [[#Zhang--2020|]] [[#Zhang--2020|]] [[#Zhang--2020|Zhang et al. (2020)]] used large ensemble simulations to show that anthropogenic forcing can lead to a robust slowdown, particularly outside of the tropics at higher latitudes. [[#Yamaguchi--2020b|Yamaguchi and Maeda (2020b)]] found a significant slowdown in the western North Pacific over the past 40 years and attributed the slowdown to a combination of natural variability and global warming. The slowing trend since 1900 over the USA is robust and significant after removing multi-decadal variability from the time series (Kossin, 2019). Among the hypotheses discussed is the physical linkage between warming and slowing circulation ( [[#Held--2006|Held and Soden, 2006]] ; see also [[IPCC:Wg1:Chapter:Chapter-8#8.2.2.2|Section 8.2.2.2]] ), with expectations of Arctic amplification and weakening circulation patterns through weakening meridional temperature gradients ( [[#Coumou--2018|Coumou et al., 2018]] ; see also Cross-Chapter Box 10.1), or through changes in planetary wave dynamics ( [[#Mann--2017|Mann et al., 2017]] ). The tropics expansion and the poleward shift of the mid-latitude westerlies associated with warming is also suggested as the reason of the slowdown (G. [[#Zhang--2020|]] [[#Zhang--2020|]] [[#Zhang--2020|]] [[#Zhang--2020|Zhang et al., 2020]] ). However, the connection of these mechanisms to the slowdown has not been robustly shown. Furthermore, slowing trends have not been unambiguously observed in circulation patterns that steer TCs, such as the Walker and Hadley circulations ( [[IPCC:Wg1:Chapter:Chapter-2#2.3.1.4|Section 2.3.1.4]] ), although these circulations generally slow down in numerical simulations under global warming (Sections 4.5.1.6 and 8.4.2.2).

The observed poleward trend in western North Pacific TCs remains significant after accounting for the known modes of dominant interannual to decadal variability in the region ( [[#Kossin--2016a|Kossin et al., 2016a]] ), and is also found in CMIP5 model-simulated TCs (in the recent historical period 1980–2005), although it is weaker than observed and is not statistically significant ( [[#Kossin--2016a|Kossin et al., 2016a]] ). However, the trend is significant in 21st-century CMIP5 projections under the RCP8.5 scenario, with a similar spatial pattern and magnitude to the past observed changes in that basin over the period 1945–2016, supporting a possible anthropogenic greenhouse gas contribution to the observed trends ( [[#Kossin--2016a|Kossin et al., 2016a]] ; [[#Knutson--2019|Knutson et al., 2019]] ).

The recent active TC seasons in some basins have been studied to determine whether there is anthropogenic influence. For 2015, [[#Murakami--2017b|Murakami et al. (2017b)]] explored the unusually high TC frequency near Hawaii and in the eastern Pacific basin. W. [[#Zhang--2016b|Zhang et al. (2016b)]] considered unusually high Accumulated Cyclone Energy (ACE) in the western North Pacific; and S.-H. [[#Yang--2018|]] [[#Yang--2018|]] [[#Yang--2018|]] [[#Yang--2018|]] [[#Yang--2018|Yang et al. (2018)]] and [[#Yamada--2019|Yamada et al. (2019)]] looked at TC intensification in the western North Pacific. These studies suggest that the anomalous TC activity in 2015 was not solely explained by the effect of an extreme El Niño (see Box 11.4) and that there was also an anthropogenic contribution, mainly through the effects of SSTs in subtropical regions. In the post-monsoon seasons of 2014 and 2015, tropical storms with lifetime maximum winds greater than 46 m s <sup>−1</sup> were first observed over the Arabian Sea, and [[#Murakami--2017a|Murakami et al. (2017a)]] showed that the probability of late-season severe tropical storms is increased by anthropogenic forcing compared to the preindustrial era. [[#Murakami--2018|Murakami et al. (2018)]] concluded that the active 2017 Atlantic hurricane season was mainly caused by pronounced SSTs in the tropical North Atlantic and that these types of seasonal events will intensify with projected anthropogenic forcing. The trans-basin SST change, which might be driven by anthropogenic aerosol forcing, also affects TC activity. [[#Takahashi--2017|Takahashi et al. (2017)]] suggested that a decrease in sulphate aerosol emissions caused about half of the observed decreasing trends in TC genesis frequency in the south-eastern region of the western North Pacific during 1992–2011.

Event attribution is used in TC case studies to test whether the severities of recent intense TCs are explained without anthropogenic effects. In a case study of Hurricane Sandy (2012), [[#Lackmann--2015|Lackmann (2015)]] found no statistically significant impact of anthropogenic climate change on storm intensity, while projections in a warmer world showed significant strengthening. However, [[#Magnusson--2014|Magnusson et al. (2014)]] found that, in European Centre for Medium-Range Weather Forecast (ECMWF) simulations, the simulated cyclone depth and intensity, as well as precipitation, were larger when the model was driven by the warmer actual SSTs than the climatological average SSTs. In Super Typhoon Haiyan, which struck the Philippines on 8 November 2013, [[#Takayabu--2015|Takayabu et al. (2015)]] took an event attribution approach with cloud system-resolving (around 1 km) downscaling ensemble experiments to evaluate the anthropogenic effect on typhoons, and showed that the intensity of the simulated worst-case storm in the actual conditions was stronger than that in a hypothetical condition without historical anthropogenic forcing in the model. However, in a similar approach with two coarser parametrized convection models, Wehner et al. (2019) found conflicting human influences on Haiyan’s intensity. [[#Patricola--2018|Patricola and Wehner (2018)]] found little evidence of an attributable change in intensity of hurricanes Katrina (2005), Irma (2017), and Maria (2017) using a regional climate model configured between 3 km and 4.5 km resolution. They did, however, find attributable increases in heavy precipitation totals. These results imply that higher resolution, such as in a convective permitting 5 km or less mesh model, is required to obtain a robust anthropogenic intensification of a strong TC by simulating realistic rapid intensification ( [[#Kanada--2016|Kanada and Wada, 2016]] ; [[#Kanada--2017a|Kanada et al., 2017a]] ), and that whether the TC intensification can be attributed to the recent warming depends on the case.

The dominant factor in the extreme rainfall amounts during Hurricane Harvey’s passage onto the USA in 2017 was its slow translation speed. But studies published after the event have argued that anthropogenic climate change contributed to an increase in rain rate, which compounded the extreme local rainfall caused by the slow translation. [[#Emanuel--2017|Emanuel (2017)]] used a large set of synthetically-generated storms and concluded that the occurrence of extreme rainfall as observed in Harvey was substantially enhanced by anthropogenic changes to the larger-scale ocean and atmosphere characteristics; [[#Trenberth--2018|Trenberth et al. (2018)]] linked Harvey’s rainfall totals to the anomalously large ocean heat content from the Gulf of Mexico; and [[#van%20Oldenborgh--2017|van Oldenborgh et al. (2017)]] and [[#Risser--2017|Risser and Wehner (2017)]] applied extreme value analysis to extreme rainfall records in the Houston, Texas region, both attributing large increases to climate change. Large precipitation increases during Harvey due to global warming were also found using climate models ( [[#van%20Oldenborgh--2017|van Oldenborgh et al., 2017]] ; S.-Y.S. [[#Wang--2018|]] [[#Wang--2018|Wang et al., 2018]] ). Harvey precipitation totals were estimated in these papers to be three to 10 times more probable due to climate change. A best estimate from a regional climate and flood model is that urbanization increased the risk of the Harvey flooding by a factor of 21 (W. [[#Zhang--2018|]] [[#Zhang--2018|]] [[#Zhang--2018|Zhang et al., 2018]] ), using a regional climate and flood model, found that surface roughness from urbanization increased the risk of the Harvey flooding by a factor of 21. Anthropogenic effects on precipitation increases were also predicted in advance from a forecast model for Hurricane Florence in 2018 ( [[#Reed--2020|Reed et al., 2020]] ).

In summary, it is ''very likely'' that the recent active TC seasons in the North Atlantic, the North Pacific, and Arabian basins cannot be explained without an anthropogenic influence. The anthropogenic influence on these changes is principally associated to aerosol forcing, with stronger contributions to the response in the North Atlantic. It is ''more likely than not'' that the slowdown of TC translation speed over the USA has contributions from anthropogenic forcing. It is ''likely'' that the poleward migration of TCs in the western North Pacific and the global increase in TC intensity rates cannot be explained entirely by natural variability. Event attribution studies of specific strong TCs provide ''limited evidence'' for anthropogenic effects on TC intensifications so far, but ''high confidence'' for increases in TC heavy precipitation. There is ''high confidence'' that anthropogenic climate change contributed to extreme rainfall amounts during Hurricane Harvey (2017) and other intense TCs.

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