Environmental control of tropical cyclones in CMIP5: A ventilation perspective

Dynamical downscaling of simulations of the Last Glacial Maximum (LGM) and late twentieth century (20C) were conducted using the Weather Research and Forecasting (WRF) model with the aim of (1) understanding how the downscaled kinematic and thermodynamic variables influence simulated tropical cyclone (TC) activity over the western North Pacific during the LGM and the 20C periods and (2) to test the relevance of TC genesis factors for the colder LGM climate. The results show that, despite the lower temperatures during the LGM, the downscaled TC climatology over the western North Pacific in the LGM simulation does not differ significantly from that in the 20C simulation. Among the TC environmental factors, the TC potential intensity, mid‐tropospheric entropy deficit, and vertical wind shear during the LGM were consistent with previous analyses of TC genesis factors in LGM global climate model simulations. Changes in TC genesis density between the LGM and the 20C simulations seem to be well represented by the ventilation index, a nondimensional measure of the combined effects of vertical wind shear, and thermodynamic properties, suggesting the potential applicability of those factors for TC activity evaluation during the LGM and possibly other climates.

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“…Interestingly, Tang and Camargo [2014] showed that the ventilation index changes are consistent with changes in TC frequency in the CMIP5 models.…”

Section: Journal Of Advances In Modeling Earth Systems 101002/2016msmentioning

confidence: 75%

Dynamical downscaling of tropical cyclones from CCSM4 simulations of the Last Glacial Maximum

Yoo

Galewsky

Camargo

et al. 2016

J Adv Model Earth Syst

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“…A potential limitation of the GPI methodology for application to a different climate is that it is trained on presentday climate. This was demonstrated in the 25-km version of the CAM5 GCM, where decreases in GPI estimated for the 2CO2 experiment were consistent with the direct simulation but increases in GPI estimated for the 2K and 2K2CO2 experiments were inconsistent with the direct simulation of changes in tropical cyclone numbers (Wehner et al 2015; see also Camargo 2013; Camargo et al 2014). …”

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confidence: 86%

“…Zhao et al (2013a,b) This relationship between TC frequency and vertical velocity was the closest association found among a suite of analyzed variables that included precipitation, 600-hPa relative humidity, and vertical wind shear. In addition, Camargo et al (2014) use a number of GPIs applied to the output of the GFDL HiRAM to show that in order to explain the reduction in TC frequency, it is necessary to include saturation deficit and potential intensity in the genesis potential index. While the response of the models in the other HWG experiments is more ambiguous, no model generated a substantial increase in global TC frequency for any experiment.…”

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confidence: 99%

“…Another large-scale environmental factor that should be considered is the ventilation, the import of cooler and drier air, which was shown to have an important influence in both tropical cyclogenesis and intensification (Tang and Emanuel 2012). Changes in TC frequency in future climates have also been related to the ventilation index for the CMIP5 models (Tang and Camargo 2014).The potential of such a technique is obvious: it could serve as a diagnostic tool to determine the reasons for changes in tropical cyclone numbers in a particular climate simulation, without the need to perform numerous sensitivity experiments, or (ultimately) it could enable the diagnosis of changes in tropical cyclone formation rate from different climates without the need to run a high-resolution GCM to simulate the storms directly, similar to what was done in the present climate for diagnostics of TC genesis modulation by El Niño-Southern Oscillation (Camargo et al 2007a) and the MaddenJulian oscillation ). Korty et al (2013Korty et al ( , 2012a show results where the GPI is used to diagnose the rate of tropical cyclone formation for a period 6,000 years before the present, showing considerable changes in GPI, with mostly decreases in the Northern Hemisphere and increases in the Southern Hemisphere.…”

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confidence: 99%

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Hurricanes and Climate: The U.S. CLIVAR Working Group on Hurricanes

Walsh

Camargo

Vecchi

et al. 2015

Bulletin of the American Meteorological Society

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182

172

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Although a theory of the climatology of tropical cyclone formation remains elusive, high-resolution climate models can now simulate many aspects of tropical cyclone climate. T he effect of climate change on tropical cyclones has been a controversial scientific issue for a number of years. Advances in our theoretical understanding of the relationship between climate and tropical cyclones have been made, enabling us to understand better the links between the mean climate and the potential intensity (PI; the theoretical maximum intensity of a tropical cyclone for a given climate condition) of tropical cyclones. Improvements in the capabilities of climate models, the main tool used to predict future climate, have enabled them to achieve a considerably improved and more credible simulation of the present-day climatology of tropical cyclones. Finally, the increasing ability of such models to predict the interannual variability of tropical cyclone formation in various regions of the globe indicates that they are capturing some of the essential physical relationships governing the links between climate and tropical cyclones. HURRICANES AND CLIMATEPrevious climate model simulations, however, have suggested some ambiguity in projections of future numbers of tropical cyclones in a warmer world. While many models have projected fewer tropical cyclones globally (Sugi et al. 2002;Bengtsson et al. 2007b; Gualdi et al. 2008; Knutson et al. 2010), other climate models and related downscaling methods have suggested some increase in future numbers (e.g., Broccoli and Manabe 1990;Haarsma et al. 1993; Emanuel 2013a). When future projections for individual basins are made, the issue becomes more serious: for example, for the Atlantic basin there appears to be little consensus on the future number of tropical cyclones or on the relative importance of forcing factors such as aerosols or increases in carbon dioxide (CO 2 ) concentration. One reason could be statistical: annual numbers of tropical cyclones in the Atlantic are relatively small, making the identification of such storms sensitive to the detection method used.Further, there is substantial spread in projected responses of regional tropical cyclone (TC) frequency and intensity over the twenty-first century from downscaling studies (Knutson et al. 2007; Emanuel 2013a). Interpreting the sources of those differences is complicated by different projections of large-scale climate and by differences in the present-day reference period and sea surface temperature (SST) datasets used. A natural question is whether the diversity in responses to projected twenty-firstcentury climate of each of the studies is primarily | a reflection of uncertainty arising from different large-scale forcing (as has been suggested by, e.g., Villarini et al. 2011;Villarini and Vecchi 2012;Knutson et al. 2013) or whether this spread reflects principally different inherent sensitivities across the various downscaling techniques, even including different sensitivity of responses within the same model due to...

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Section: June 2015 |mentioning

confidence: 99%

Hurricanes and Climate: The U.S. CLIVAR Working Group on Hurricanes

Walsh¹,

Camargo²,

Vecchi³

et al. 2015

Bull. Amer. Meteor. Soc.

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T he effect of climate change on tropical cyclones has been a controversial scientific issue for a number of years. Advances in our theoretical understanding of the relationship between climate and tropical cyclones have been made, enabling us to understand better the links between the mean climate and the potential intensity (PI; the theoretical maximum intensity of a tropical cyclone for a given climate condition) of tropical cyclones. Improvements in the capabilities of climate models, the main tool used to predict future climate, have enabled them to achieve a considerably improved and more credible simulation of the present-day climatology of tropical cyclones. Finally, the increasing ability of such models to predict the interannual variability of tropical cyclone formation in various regions of the globe indicates that they are capturing some of the essential physical relationships governing the links between climate and tropical cyclones.Previous climate model simulations, however, have suggested some ambiguity in projections of future numbers of tropical cyclones in a warmer world. While many models have projected fewer tropical cyclones globally (Sugi et al. 2002;Bengtsson et al. 2007b; Gualdi et al. 2008; Knutson et al. 2010), other climate models and related downscaling methods have suggested some increase in future numbers (e.g., Broccoli and Manabe 1990;Haarsma et al. 1993; Emanuel 2013a). When future projections for individual basins are made, the issue becomes more serious: for example, for the Atlantic basin there appears to be little consensus on the future number of tropical cyclones (Knutson et al. 2010) or on the relative importance of forcing factors such as aerosols or increases in carbon dioxide (CO 2 ) concentration. One reason could be statistical: annual numbers of tropical cyclones in the Atlantic are relatively small, making the identification of such storms sensitive to the detection method used.Further, there is substantial spread in projected responses of regional tropical cyclone (TC) frequency and intensity over the twenty-first century from downscaling studies (Knutson et al. 2007; Emanuel 2013a). Interpreting the sources of those differences is complicated by different projections of large-scale climate and by differences in the present-day reference period and sea surface temperature (SST) datasets used. A natural question is whether the diversity in responses to projected twenty-firstcentury climate of each of the studies is primarily | a reflection of uncertainty arising from different large-scale forcing (as has been suggested by, e.g., Villarini et al. 2011;Villarini and Vecchi 2012;Knutson et al. 2013) or whether this spread reflects principally different inherent sensitivities across the various downscaling techniques, even including different sensitivity of responses within the same model due to, for instance, the use of different convective parameterizations (Kim et al. 2012). A similar set of questions relates to the ability of models to generate observed changes in...

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Environmental control of tropical cyclones in CMIP5: A ventilation perspective

Cited by 44 publications

References 80 publications

Dynamical downscaling of tropical cyclones from CCSM4 simulations of the Last Glacial Maximum

Dynamical downscaling of tropical cyclones from CCSM4 simulations of the Last Glacial Maximum

Hurricanes and Climate: The U.S. CLIVAR Working Group on Hurricanes

Hurricanes and Climate: The U.S. CLIVAR Working Group on Hurricanes

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