Characteristics of tropical cyclones in high‐resolution models in the present climate

Shaevitz, Daniel A.; Camargo, Suzana J.; Sobel, Adam H.; Jonas, J.; Kim, Dae Hyun; Kumar, Arun; LaRow, Timothy E.; Lim, Young‐Kwon; Murakami, Hiroyuki; Reed, Kevin A.; Roberts, Malcolm; Scoccimarro, Enrico; Vidale, Pier Luigi; Wang, Hui; Wehner, Michael; Zhao, Ming; Henderson, Naomi

doi:10.1002/2014ms000372

Cited by 118 publications

(169 citation statements)

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“…The U.S. CLIVAR HWG experimental suite provides a common experimental framework to isolate model-dependent responses. Preliminary multimodel results have been reported in Zhao et al (2013), Daloz et al (2015), Shaevitz et al (2014), and Walsh et al (2015).…”

Section: Introductionmentioning

confidence: 87%

Resolution Dependence of Future Tropical Cyclone Projections of CAM5.1 in the U.S. CLIVAR Hurricane Working Group Idealized Configurations

et al. 2015

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The four idealized configurations of the U.S. CLIVAR Hurricane Working Group are integrated using the global Community Atmospheric Model version 5.1 at two different horizontal resolutions, approximately 100 and 25 km. The publicly released 0.9° × 1.3° configuration is a poor predictor of the sign of the 0.23° × 0.31° model configuration’s change in the total number of tropical storms in a warmer climate. However, it does predict the sign of the higher-resolution configuration’s change in the number of intense tropical cyclones in a warmer climate. In the 0.23° × 0.31° model configuration, both increased CO2 concentrations and elevated sea surface temperature (SST) independently lower the number of weak tropical storms and shorten their average duration. Conversely, increased SST causes more intense tropical cyclones and lengthens their average duration, resulting in a greater number of intense tropical cyclone days globally. Increased SST also increased maximum tropical storm instantaneous precipitation rates across all storm intensities. It was found that while a measure of maximum potential intensity based on climatological mean quantities adequately predicts the 0.23° × 0.31° model’s forced response in its most intense simulated tropical cyclones, a related measure of cyclogenesis potential fails to predict the model’s actual cyclogenesis response to warmer SSTs. These analyses lead to two broader conclusions: 1) Projections of future tropical storm activity obtained by a direct tracking of tropical storms simulated by coarse-resolution climate models must be interpreted with caution. 2) Projections of future tropical cyclogenesis obtained from metrics of model behavior that are based solely on changes in long-term climatological fields and tuned to historical records must also be interpreted with caution.

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Section: Introductionmentioning

confidence: 87%

Resolution Dependence of Future Tropical Cyclone Projections of CAM5.1 in the U.S. CLIVAR Hurricane Working Group Idealized Configurations

et al. 2015

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“…While it is clear that simply increasing the resolution does not necessarily improve intensity distribution (Shaevitz et al 2014), results from the HWG simulations indicate that a very significant improvement in a GCM's ability to simulate both TC formation and intensity occurs at resolutions finer than 50 km, with good results shown at 25 km (Strachan et al 2013;Roberts et al 2015;Lim et al 2015;Wehner et al 2015;Mei et al 2014). In addition, if such high resolution is employed, it is possible to simulate reasonably well the observed intensity distribution of tropical cyclones (Bender et al 2010;Lavender and Walsh 2011; Murakami et al 2012b;Chen et al 2013;Zarzycki and Jablonowski 2014).…”

Section: Simulation Of the Intensity Distribut Ion Of Tr O Pical Cyclmentioning

confidence: 98%

“…1 has been improved following the development of the new version of the model (see Fig. 4 in Shaevitz et al 2014).The annual cycle of formation is reasonably well simulated in many regions, although there is a tendency for the amplitude of the simulated annual cycle to be less than observed. A common factor in many such model assessments is the poorer performance at simulating Atlantic tropical cyclone formation than for other basins, although recent finer-resolution models give an improved simulation.…”

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confidence: 99%

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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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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“…Here we will evaluate the ability of the different models to correctly simulate the main characteristics of North Atlantic tropical cyclones, such as track types, frequency, intensity, and duration. A description of the global characteristics of the tropical cyclones in the same set of models for the present climate was presented in Shaevitz et al (2015).…”

Section: Introductionmentioning

confidence: 99%

Cluster Analysis of Downscaled and Explicitly Simulated North Atlantic Tropical Cyclone Tracks

et al. 2015

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A realistic representation of the North Atlantic tropical cyclone tracks is crucial as it allows, for example, explaining potential changes in U.S. landfalling systems. Here, the authors present a tentative study that examines the ability of recent climate models to represent North Atlantic tropical cyclone tracks. Tracks from two types of climate models are evaluated: explicit tracks are obtained from tropical cyclones simulated in regional or global climate models with moderate to high horizontal resolution (18-0.258), and downscaled tracks are obtained using a downscaling technique with large-scale environmental fields from a subset of these models. For both configurations, tracks are objectively separated into four groups using a cluster technique, leading to a zonal and a meridional separation of the tracks. The meridional separation largely captures the separation between deep tropical and subtropical, hybrid or baroclinic cyclones, while the zonal separation segregates Gulf of Mexico and Cape Verde storms. The properties of the tracks' seasonality, intensity, and power dissipation index in each cluster are documented for both configurations. The authors' results show that, except for the seasonality, the downscaled tracks better capture the observed characteristics of the clusters. The authors also use three different idealized scenarios to examine the possible future changes of tropical cyclone tracks under 1) warming sea surface temperature, 2) increasing carbon dioxide, and 3) a combination of the two. The response to each scenario is highly variable depending on the simulation considered. Finally, the authors examine the role of each cluster in these future changes and find no preponderant contribution of any single cluster over the others.

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Characteristics of tropical cyclones in high‐resolution models in the present climate

Cited by 118 publications

References 51 publications

Resolution Dependence of Future Tropical Cyclone Projections of CAM5.1 in the U.S. CLIVAR Hurricane Working Group Idealized Configurations

Resolution Dependence of Future Tropical Cyclone Projections of CAM5.1 in the U.S. CLIVAR Hurricane Working Group Idealized Configurations

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

Cluster Analysis of Downscaled and Explicitly Simulated North Atlantic Tropical Cyclone Tracks

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