Dynamical Simulations of North Atlantic Tropical Cyclone Activity Using Observed Low-Frequency SST Oscillation Imposed on CMIP5 Model RCP4.5 SST Projections

Timothy E. LaRow Florida State University, Tallahassee, Florida

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Lydia Stefanova Florida State University, Tallahassee, Florida

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Chana Seitz Florida State University, Tallahassee, Florida

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Abstract

The effects on early and late twenty-first-century North Atlantic tropical cyclone statistics resulting from imposing the patterns of maximum/minimum phases of the observed Atlantic multidecadal oscillation (AMO) onto projected sea surface temperatures (SSTs) from two climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are examined using a 100-km resolution global atmospheric model. By imposing the observed maximum positive and negative phases of the AMO onto two CMIP5 SST projections from the representative concentration pathway (RCP) 4.5 scenario, this study places bounds on future North Atlantic tropical cyclone activity during the early (2020–39) and late (2080–99) twenty-first century. Averaging over both time periods and both AMO phases, the mean named tropical cyclones (NTCs) count increases by 35% when compared to simulations using observed SSTs from 1982 to 2009. The positive AMO simulations produce approximately a 68% increase in mean NTC count, while the negative AMO simulations are statistically indistinguishable from the mean NTC count determined from the 1995–2009 simulations—a period of observed positive AMO phase. Examination of the tropical cyclone track densities shows a statistically significant increase in the tracks along the East Coast of the United States in the future simulations compared to the models’ 1982–2009 climate simulations. The increase occurs regardless of AMO phase, although the negative phase produces higher track densities. The maximum wind speeds increase by 6%, in agreement with other climate change studies. Finally, the NTC-related precipitation is found to increase (approximately by 13%) compared to the 1982–2009 simulations.

Corresponding author address: Timothy E. LaRow, Florida State University, P.O. Box 3062741, Tallahassee, FL 32306-2741. E-mail: tlarow@fsu.edu

Abstract

The effects on early and late twenty-first-century North Atlantic tropical cyclone statistics resulting from imposing the patterns of maximum/minimum phases of the observed Atlantic multidecadal oscillation (AMO) onto projected sea surface temperatures (SSTs) from two climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are examined using a 100-km resolution global atmospheric model. By imposing the observed maximum positive and negative phases of the AMO onto two CMIP5 SST projections from the representative concentration pathway (RCP) 4.5 scenario, this study places bounds on future North Atlantic tropical cyclone activity during the early (2020–39) and late (2080–99) twenty-first century. Averaging over both time periods and both AMO phases, the mean named tropical cyclones (NTCs) count increases by 35% when compared to simulations using observed SSTs from 1982 to 2009. The positive AMO simulations produce approximately a 68% increase in mean NTC count, while the negative AMO simulations are statistically indistinguishable from the mean NTC count determined from the 1995–2009 simulations—a period of observed positive AMO phase. Examination of the tropical cyclone track densities shows a statistically significant increase in the tracks along the East Coast of the United States in the future simulations compared to the models’ 1982–2009 climate simulations. The increase occurs regardless of AMO phase, although the negative phase produces higher track densities. The maximum wind speeds increase by 6%, in agreement with other climate change studies. Finally, the NTC-related precipitation is found to increase (approximately by 13%) compared to the 1982–2009 simulations.

Corresponding author address: Timothy E. LaRow, Florida State University, P.O. Box 3062741, Tallahassee, FL 32306-2741. E-mail: tlarow@fsu.edu
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