Evaluation of the contribution of tropical cyclone seeds to changes in tropical cyclone frequency due to global warming in high-resolution multi-model ensemble simulations

Yamada, Yohei; Kodama, Chihiro; Satoh, Masaki; Sugi, Masato; Roberts, Malcolm; Mizuta, Ryo; Noda, Akira; Nasuno, Tomoe; Nakano, Masuo; Vidale, Pier Luigi

doi:10.1186/s40645-020-00397-1

Cited by 34 publications

(41 citation statements)

References 59 publications

(84 reference statements)

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“…Emanuel et al (2013) identifies three thermodynamic variables useful to understand the formation of TCs: 1) the presence of moist convection; 2) mid-tropospheric humidity and 3) Potential Intensity (PI). We have focused so far on the last two variables, part of GPI, and their role in the conversion of TC seeds; our findings are supportive of the conclusions in Vecchi et al (2019) and Yamada et al (2021). The role of moist convection may not be revealed by GPI, but can be investigated by Watson et al (2017) for the same model.…”

Section: E Gpi Terms and Their Control On The Climatology Of Tcs In Each Basinsupporting

confidence: 81%

Impact of Stochastic Physics and Model Resolution on the Simulation of Tropical Cyclones in Climate GCMs

et al. 2021

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The role of model resolution in simulating geophysical vortices with the characteristics of realistic Tropical Cyclones (TCs) is well established. The push for increasing resolution continues, with General Circulation Models (GCMs) starting to use sub-10km grid spacing. In the same context it has been suggested that the use of Stochastic Physics (SP) may act as a surrogate for high resolution, providing some of the benefits at a fraction of the cost. Either technique can reduce model uncertainty, and enhance reliability, by providing a more dynamic environment for initial synoptic disturbances to be spawned and to grow into TCs. We present results from a systematic comparison of the role of model resolution and SP in the simulation of TCs, using EC-Earth simulations from project Climate-SPHINX, in large ensemble mode, spanning five different resolutions. All tropical cyclonic systems, including TCs, were tracked explicitly. As in previous studies, the number of simulated TCs increases with the use of higher resolution, but SP further enhances TC frequencies by ≈ 30%, in a strikingly similar way. The use of SP is beneficial for removing systematic climate biases, albeit not consistently so for interannual variability; conversely, the use of SP improves the simulation of the seasonal cycle of TC frequency. An investigation of the mechanisms behind this response indicates that SP generates both higher TC (and TC seed) genesis rates, and more suitable environmental conditions, enabling a more efficient transition of TC seeds into TCs. These results were confirmed by the use of equivalent simulations with the HadGEM3-GC31 GCM.

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Section: E Gpi Terms and Their Control On The Climatology Of Tcs In Each Basinsupporting

confidence: 81%

Impact of Stochastic Physics and Model Resolution on the Simulation of Tropical Cyclones in Climate GCMs

et al. 2021

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“…This is somewhat contrary to previous studies (Hsieh et al, 2020;Vecchi et al, 2019;Yamada et al, 2021) which revealed that the change in TC seed frequency has a large impact on TC frequency in the future warmer climate. However, Yamada et al (2021) noted in their multimodel analysis that survival rate is also influential in some models, and Duvel (2021) showed that seasonal and interannual variations in TC frequency over the North Atlantic is more attributed to survival rate than to the number of vortices from Africa. It seems that definitions or tracking algorithms of TC seeds cannot account for this contradiction because they are different even among the aforementioned studies with similar conclusions.…”

Section: Conclusion and Discussioncontrasting

confidence: 99%

Climatology of Tropical Cyclone Seed Frequency and Survival Rate in Tropical Cyclones

Ikehata

Satoh

2021

Geophysical Research Letters

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Elucidating the mechanism that determines the number of tropical cyclones (TCs) is fundamental for understanding variations in TC activity and predicting future changes. An average of about 80 TCs form each year around the world, with the exact number varying interannually and seasonally (Gray, 1968;Schreck et al., 2014;Webster et al., 2005). Although these variations have been described in relation to large-scale environmental fields represented by a genesis potential index (Emanuel & Nolan, 2004;Gray, 1975;Murakami & Wang, 2010;Tippett et al., 2011), such a relationship does not necessarily hold for future global warming conditions (Camargo et al., 2014). Davis et al. (2008) proposed focusing on pre-TC vortices to clarify how large-scale conditions affect cyclogenesis efficiency. The modulation of TC frequency by the Madden-Julian Oscillation (MJO) is more attributed to tropical depression (TD) frequency than to the probability of TDs intensifying in the western Pacific and the Indian Ocean (Duvel, 2015;Liebmann et al., 1994), though TDs are relatively mature. Recent studies considered TC frequency as the product of the number of weak pre-TC vortices (TC seeds) and the percentage of TC seeds that develop to TCs (survival rate), and proposed that this framework could help to uncover the mechanism behind the variation in TC frequency (Sugi et al., 2020;Vecchi et al., 2019;Yamada et al., 2021). To determine the change in TC frequency due to global warming, for example, it has been suggested that the change in TC seed frequency is most important (Sugi et al., 2020;Vecchi et al., 2019). However, an analysis of results from multiple high-resolution models showed that the contribution of survival rate to TC frequency cannot be ignored (Yamada et al., 2021). Such analyses of TC frequency have more

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“…Previous studies have shown that the probability and seeds framework could help explain diverging responses of TC frequency to radiative climate forcing induced by greenhouse gases ( 3 , 11 , 21 , 22 ). Here we test and validate that the seeds-probability framework also works in a different scenario: climatological variations driven by the annual cycle radiative forcing.…”

Section: Summary and Discussionmentioning

confidence: 99%

Hurricane annual cycle controlled by both seeds and genesis probability

Yang

Hsieh

Vecchi

2021

Proc. Natl. Acad. Sci. U.S.A.

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Understanding tropical cyclone (TC) climatology is a problem of profound societal significance and deep scientific interest. The annual cycle is the biggest radiatively forced signal in TC variability, presenting a key test of our understanding and modeling of TC activity. TCs over the North Atlantic (NA) basin, which are usually called hurricanes, have a sharp peak in the annual cycle, with more than half concentrated in only 3 mo (August to October), yet existing theories of TC genesis often predict a much smoother cycle. Here we apply a framework originally developed to study TC response to climate change in which TC genesis is determined by both the number of pre-TC synoptic disturbances (TC “seeds”) and the probability of TC genesis from the seeds. The combination of seeds and probability predicts a more consistent hurricane annual cycle, reproducing the compact season, as well as the abrupt increase from July to August in the NA across observations and climate models. The seeds-probability TC genesis framework also successfully captures TC annual cycles in different basins. The concise representation of the climate sensitivity of TCs from the annual cycle to climate change indicates that the framework captures the essential elements of the TC climate connection.

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Evaluation of the contribution of tropical cyclone seeds to changes in tropical cyclone frequency due to global warming in high-resolution multi-model ensemble simulations

Cited by 34 publications

References 59 publications

Impact of Stochastic Physics and Model Resolution on the Simulation of Tropical Cyclones in Climate GCMs

Impact of Stochastic Physics and Model Resolution on the Simulation of Tropical Cyclones in Climate GCMs

Climatology of Tropical Cyclone Seed Frequency and Survival Rate in Tropical Cyclones

Hurricane annual cycle controlled by both seeds and genesis probability

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