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Michael Horn, Kevin Walsh, Ming Zhao, Suzana J. Camargo, Enrico Scoccimarro, Hiroyuki Murakami, Hui Wang, Andrew Ballinger, Arun Kumar, Daniel A. Shaevitz, Jeffrey A. Jonas, and Kazuyoshi Oouchi

Abstract

Future tropical cyclone activity is a topic of great scientific and societal interest. In the absence of a climate theory of tropical cyclogenesis, general circulation models are the primary tool available for investigating the issue. However, the identification of tropical cyclones in model data at moderate resolution is complex, and numerous schemes have been developed for their detection.

The influence of different tracking schemes on detected tropical cyclone activity and responses in the Hurricane Working Group experiments is examined herein. These are idealized atmospheric general circulation model experiments aimed at determining and distinguishing the effects of increased sea surface temperature and other increased CO2 effects on tropical cyclone activity. Two tracking schemes are applied to these data and the tracks provided by each modeling group are analyzed.

The results herein indicate moderate agreement between the different tracking methods, with some models and experiments showing better agreement across schemes than others. When comparing responses between experiments, it is found that much of the disagreement between schemes is due to differences in duration, wind speed, and formation-latitude thresholds. After homogenization in these thresholds, agreement between different tracking methods is improved. However, much disagreement remains, accountable for by more fundamental differences between the tracking schemes. The results indicate that sensitivity testing and selection of objective thresholds are the key factors in obtaining meaningful, reproducible results when tracking tropical cyclones in climate model data at these resolutions, but that more fundamental differences between tracking methods can also have a significant impact on the responses in activity detected.

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Hui Wang, Lindsey Long, Arun Kumar, Wanqiu Wang, Jae-Kyung E. Schemm, Ming Zhao, Gabriel A. Vecchi, Timothy E. Larow, Young-Kwon Lim, Siegfried D. Schubert, Daniel A. Shaevitz, Suzana J. Camargo, Naomi Henderson, Daehyun Kim, Jeffrey A. Jonas, and Kevin J. E. Walsh

Abstract

The variability of Atlantic tropical cyclones (TCs) associated with El Niño–Southern Oscillation (ENSO) in model simulations is assessed and compared with observations. The model experiments are 28-yr simulations forced with the observed sea surface temperature from 1982 to 2009. The simulations were coordinated by the U.S. Climate Variability and Predictability Research Program (CLIVAR) Hurricane Working Group and conducted with five global climate models (GCMs) with a total of 16 ensemble members. The model performance is evaluated based on both individual model ensemble means and multimodel ensemble mean. The latter has the highest anomaly correlation (0.86) for the interannual variability of TCs. Previous observational studies show a strong association between ENSO and Atlantic TC activity, as well as distinctions during eastern Pacific (EP) and central Pacific (CP) El Niño events. The analysis of track density and TC origin indicates that each model has different mean biases. Overall, the GCMs simulate the variability of Atlantic TCs well with weaker activity during EP El Niño and stronger activity during La Niña. For CP El Niño, there is a slight increase in the number of TCs as compared with EP El Niño. However, the spatial distribution of track density and TC origin is less consistent among the models. Particularly, there is no indication of increasing TC activity over the U.S. southeast coastal region during CP El Niño as in observations. The difference between the models and observations is likely due to the bias of the models in response to the shift of tropical heating associated with CP El Niño, as well as the model bias in the mean circulation.

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Christina M. Patricola, R. Saravanan, and Ping Chang

Abstract

Atlantic tropical cyclone (TC) activity is influenced by interannual tropical Pacific sea surface temperature (SST) variability characterized by the El Niño–Southern Oscillation (ENSO), as well as interannual-to-decadal variability in the interhemispheric gradient in tropical Atlantic SST characterized by the Atlantic meridional mode (AMM). Individually, the negative AMM phase (cool northern and warm southern tropical Atlantic SST anomalies) and El Niño each inhibit Atlantic TCs, and vice versa. The impact of concurrent strong phases of the ENSO and AMM on Atlantic TC activity is investigated. The response of the atmospheric environment relevant for TCs is evaluated with a genesis potential index.

Composites of observed accumulated cyclone energy (ACE) suggest that ENSO and AMM can amplify or dampen the influence of one another on Atlantic TCs. To support the observational analysis, numerical simulations are performed using a 27-km resolution regional climate model. The control simulation uses observed SST and lateral boundary conditions (LBCs) of 1980–2000, and perturbed experiments are forced with ENSO phases through LBCs and eastern tropical Pacific SST and AMM phases through Atlantic SST.

Simultaneous strong El Niño and strongly positive AMM, as well as strong concurrent La Niña and negative AMM, produce near-average Atlantic ACE suggesting compensation between the two influences, consistent with the observational analysis. Strong La Niña and strongly positive AMM together produce extremely intense Atlantic TC activity, supported largely by above average midtropospheric humidity, while strong El Niño and negative AMM together are not necessary conditions for significantly reduced Atlantic tropical cyclone activity.

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Wei Mei, Shang-Ping Xie, and Ming Zhao

Abstract

Interannual–decadal variability of tropical cyclone (TC) track density over the North Atlantic (NA) between 1979 and 2008 is studied using observations and simulations with a 25-km-resolution version of the High Resolution Atmospheric Model (HiRAM) forced by observed sea surface temperatures (SSTs). The variability on decadal and interannual time scales is examined separately. On both time scales, a basinwide mode dominates, with the time series being related to variations in seasonal TC counts. On decadal time scales, this mode relates to SST contrasts between the tropical NA and the tropical northeast Pacific as well as the tropical South Atlantic, whereas on interannual time scales it is controlled by SSTs over the central–eastern equatorial Pacific and those over the tropical NA. The temporal evolution of the spatial distribution of track density is further investigated by normalizing the track density with seasonal TC counts. On decadal time scales, two modes emerge: one is an oscillation between track density over the U.S. East Coast and midlatitude ocean and that over the Gulf of Mexico and the Caribbean Sea and the other oscillates between low and middle latitudes. They might be driven by the preceding winter North Atlantic Oscillation and concurrent Atlantic meridional mode, respectively. On interannual time scales, two similar modes are present in observations but are not well separated in HiRAM simulations. Finally, the internal variability and predictability of TC track density are explored and discussed using HiRAM ensemble simulations. The results suggest that basinwide total TC counts/days are much more predictable than local TC occurrence, posing a serious challenge to the prediction and projection of regional TC threats, especially the U.S. landfall hurricanes.

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Enrico Scoccimarro, Silvio Gualdi, Gabriele Villarini, Gabriel A. Vecchi, Ming Zhao, Kevin Walsh, and Antonio Navarra

Abstract

In this work the authors investigate possible changes in the intensity of rainfall events associated with tropical cyclones (TCs) under idealized forcing scenarios, including a uniformly warmer climate, with a special focus on landfalling storms. A new set of experiments designed within the U.S. Climate Variability and Predictability (CLIVAR) Hurricane Working Group allows disentangling the relative role of changes in atmospheric carbon dioxide from that played by sea surface temperature (SST) in changing the amount of precipitation associated with TCs in a warmer world. Compared to the present-day simulation, an increase in TC precipitation was found under the scenarios involving SST increases. On the other hand, in a CO2-doubling-only scenario, the changes in TC rainfall are small and it was found that, on average, TC rainfall tends to decrease compared to the present-day climate. The results of this study highlight the contribution of landfalling TCs to the projected increase in the precipitation changes affecting the tropical coastal regions.

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Gabriele Villarini, David A. Lavers, Enrico Scoccimarro, Ming Zhao, Michael F. Wehner, Gabriel A. Vecchi, Thomas R. Knutson, and Kevin A. Reed

Abstract

Heavy rainfall and flooding associated with tropical cyclones (TCs) are responsible for a large number of fatalities and economic damage worldwide. Despite their large socioeconomic impacts, research into heavy rainfall and flooding associated with TCs has received limited attention to date and still represents a major challenge. The capability to adapt to future changes in heavy rainfall and flooding associated with TCs is inextricably linked to and informed by understanding of the sensitivity of TC rainfall to likely future forcing mechanisms. Here a set of idealized high-resolution atmospheric model experiments produced as part of the U.S. Climate Variability and Predictability (CLIVAR) Hurricane Working Group activity is used to examine TC response to idealized global-scale perturbations: the doubling of CO2, uniform 2-K increases in global sea surface temperature (SST), and their combined impact. As a preliminary but key step, daily rainfall patterns of composite TCs within climate model outputs are first compared and contrasted to the observational records. To assess similarities and differences across different regions in response to the warming scenarios, analyses are performed at the global and hemispheric scales and in six global TC ocean basins. The results indicate a reduction in TC daily precipitation rates in the doubling CO2 scenario (on the order of 5% globally) and an increase in TC rainfall rates associated with a uniform increase of 2 K in SST (both alone and in combination with CO2 doubling; on the order of 10%–20% globally).

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Hiroyuki Murakami, Pang-Chi Hsu, Osamu Arakawa, and Tim Li

Abstract

The influence of model biases on projected future changes in the frequency of occurrence of tropical cyclones (FOCs) was investigated using a new empirical statistical method. Assessments were made of present-day (1979–2003) simulations and future (2075–99) projections, using atmospheric general circulation models under the Intergovernmental Panel on Climate Change (IPCC) A1B scenario and phase 5 of the Coupled Model Intercomparison Project (CMIP5) models under the representative concentration pathway (RCP) 4.5 and 8.5 scenarios. The models project significant decreases in global-total FOCs by approximately 6%–40%; however, model biases introduce an uncertainty of approximately 10% in the total future changes. The influence of biases depends on the model physics rather than model resolutions and emission scenarios. In general, the biases result in overestimates of projected future changes in basin-total FOCs in the north Indian Ocean (by +18%) and South Atlantic Ocean (+143%) and underestimates in the western North Pacific Ocean (−27%), eastern North Pacific Ocean (−29%), and North Atlantic Ocean (−53%). The calibration of model performance using the smaller bias influence appears crucial to deriving meaningful signals in future FOC projections. To obtain more reliable projections, ensemble averages were calculated using the models less influence by model biases. Results indicate marked decreases in projected FOCs in the basins of the Southern Hemisphere, Bay of Bengal, western North Pacific Ocean, eastern North Pacific, and Caribbean Sea and increases in the Arabian Sea and the subtropical central Pacific Ocean.

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Yohei Yamada and Masaki Satoh

Abstract

Cloud feedback plays a key role in the future climate projection. Using global nonhydrostatic model (GNHM) simulation data for a present-day [control (CTL)] and a warmer [global warming (GW)] experiment, the authors estimate the contribution of tropical cyclones (TCs) to ice water paths (IWP) and liquid water paths (LWP) associated with TCs and their changes between CTL and GW experiments. They use GNHM with a 14-km horizontal mesh for explicitly calculating cloud microphysics without cumulus parameterization. This dataset shows that the cyclogenesis under GW conditions reduces to approximately 70% of that under CTL conditions, as shown in a previous study, and the tropical averaged IWP (LWP) is reduced by approximately 2.76% (0.86%). Horizontal distributions of IWP and LWP changes seem to be closely related to TC track changes. To isolate the contributions of IWP/LWP associated with TCs, the authors first examine the radial distributions of IWP/LWP from the TC center at their mature stages and find that they generally increase for more intense TCs. As the intense TC in GW increases, the IWP and LWP around the TC center in GW becomes larger than that in CTL. The authors next define the TC area as the region within 500 km from the TC center at its mature stages. They find that the TC’s contribution to the total tropical IWP (LWP) is 4.93% (3.00%) in CTL and 5.84% (3.69%) in GW. Although this indicates that the TC’s contributions to the tropical IWP/LWP are small, IWP/LWP changes in each basin behave in a manner similar to those of the cyclogenesis and track changes under GW.

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Sarah Strazzo, James B. Elsner, Timothy LaRow, Daniel J. Halperin, and Ming Zhao

Abstract

Of broad scientific and public interest is the reliability of global climate models (GCMs) to simulate future regional and local tropical cyclone (TC) occurrences. Atmospheric GCMs are now able to generate vortices resembling actual TCs, but questions remain about their fidelity to observed TCs. Here the authors demonstrate a spatial lattice approach for comparing actual with simulated TC occurrences regionally using observed TCs from the International Best Track Archive for Climate Stewardship (IBTrACS) dataset and GCM-generated TCs from the Geophysical Fluid Dynamics Laboratory (GFDL) High Resolution Atmospheric Model (HiRAM) and Florida State University (FSU) Center for Ocean–Atmospheric Prediction Studies (COAPS) model over the common period 1982–2008. Results show that the spatial distribution of TCs generated by the GFDL model compares well with observations globally, although there are areas of over- and underprediction, particularly in parts of the Pacific Ocean. Difference maps using the spatial lattice highlight these discrepancies. Additionally, comparisons focusing on the North Atlantic Ocean basin are made. Results confirm a large area of overprediction by the FSU COAPS model in the south-central portion of the basin. Relevant to projections of future U.S. hurricane activity is the fact that both models underpredict TC activity in the Gulf of Mexico.

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James B. Elsner, Sarah E. Strazzo, Thomas H. Jagger, Timothy LaRow, and Ming Zhao

Abstract

A statistical model for the intensity of the strongest hurricanes has been developed and a new methodology introduced for estimating the sensitivity of the strongest hurricanes to changes in sea surface temperature. Here, the authors use this methodology on observed hurricanes and hurricanes generated from two global climate models (GCMs). Hurricanes over the North Atlantic Ocean during the period 1981–2010 show a sensitivity of 7.9 ± 1.19 m s−1 K−1 (standard error; SE) when over seas warmer than 25°C. In contrast, hurricanes over the same region and period generated from the GFDL High Resolution Atmospheric Model (HiRAM) show a significantly lower sensitivity with the highest at 1.8 ± 0.42 m s−1 K−1 (SE). Similar weaker sensitivity is found using hurricanes generated from the Florida State University Center for Ocean–Atmospheric Prediction Studies (FSU-COAPS) model with the highest at 2.9 ± 2.64 m s−1 K−1 (SE). A statistical refinement of HiRAM-generated hurricane intensities heightens the sensitivity to a maximum of 6.9 ± 3.33 m s−1 K−1 (SE), but the increase is offset by additional uncertainty associated with the refinement. Results suggest that the caution that should be exercised when interpreting GCM scenarios of future hurricane intensity stems from the low sensitivity of limiting GCM-generated hurricane intensity to ocean temperature.

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