Projected response of tropical cyclone intensity and intensification in a global climate model

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Abstract

As one of the first global coupled climate models to simulate and predict category 4 and 5 (Saffir-Simpson scale) tropical cyclones (TCs) and their interannual variations, the High-Resolution Forecast-Oriented Low Ocean Resolution (HiFLOR) model at the Geophysical Fluid Dynamics Laboratory (GFDL) represents a novel source of insight on how the entire TC intensification distribution could be transformed because of climate change. In this study, three 70-yr HiFLOR experiments are performed to identify the effects of climate change on TC intensity and intensification. For each of the experiments, sea surface temperature (SST) is nudged to different climatological targets and atmospheric radiative forcing is specified, allowing us to explore the sensitivity of TCs to these conditions. First, a control experiment, which uses prescribed climatological ocean and radiative forcing based on observations during the years 1986-2005, is compared to two observational records and evaluated for its ability to capture the mean TC behavior during these years. The simulated intensification distributions as well as the percentage of TCs that become major hurricanes show similarities with observations. The control experiment is then compared to two twenty-first-century experiments, in which the climatological SSTs from the control experiment are perturbed by multimodel projected SST anomalies and atmospheric radiative forcing from either 2016-35 or 2081-2100 (RCP4.5 scenario). The frequency, intensity, and intensification distribution of TCs all shift to higher values as the twenty-first century progresses. HiFLOR's unique response to climate change and fidelity in simulating the present climate lays the groundwork for future studies involving models of this type.

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Bhatia, K., Vecchi, G., Murakami, H., Underwood, S., & Kossin, J. (2018). Projected response of tropical cyclone intensity and intensification in a global climate model. Journal of Climate, 31(20), 8281–8303. https://doi.org/10.1175/JCLI-D-17-0898.1

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