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Interannual Variability of Tropical ...

Shields, Shannon.

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Interannual Variability of Tropical Cyclone Potential Intensity and Lifetime Maximum Intensity: An Analysis of Influential Factors.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Interannual Variability of Tropical Cyclone Potential Intensity and Lifetime Maximum Intensity: An Analysis of Influential Factors./
Author:	Shields, Shannon.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2019,
Description:	102 p.
Notes:	Source: Masters Abstracts International, Volume: 81-02.
Contained By:	Masters Abstracts International81-02.
Subject:	Meteorology. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13810821
ISBN:	9781085595391

Interannual Variability of Tropical Cyclone Potential Intensity and Lifetime Maximum Intensity: An Analysis of Influential Factors.
Shields, Shannon.

Interannual Variability of Tropical Cyclone Potential Intensity and Lifetime Maximum Intensity: An Analysis of Influential Factors. - Ann Arbor : ProQuest Dissertations & Theses, 2019 - 102 p.

Source: Masters Abstracts International, Volume: 81-02.

Thesis (M.S.)--The Florida State University, 2019.

This item must not be sold to any third party vendors.

Many tropical cyclone studies have been conducted on basin-averaged potential intensity trends and the influence of sea surface temperatures (SSTs) on tropical cyclone intensity, but there is less research on along-track potential intensity (PI) and lifetime maximum intensity (referred to here as actual intensity or AI) and the factors that influence their variability. Potential intensity is a theory that predicts the maximum intensity that a tropical cyclone can achieve given certain large-scale environmental variables. Understanding interannual variability in PI and its relation to AI interannual variability is of great importance for assessing the impact of future climate conditions on tropical cyclones. Theoretically, warmer SSTs and cooler outflow temperatures would cause an increase in overall PI which in turn would lead to an increase in AI. This thesis examined the relationship between PI and AI on interannual time scales and the factors affecting PI variability: thermodynamic efficiency and air-sea enthalpy disequilibrium.Using best-track data and three reanalysis products, variability in PI and AI was examined for the North Atlantic, North Indian, South Indian, South Pacific, Eastern North Pacific, and Western North Pacific basins from 1980-2013. Overall, the Western North Pacific was the only basin that yielded high and consistently significant correlations between AI and PI. Despite the expectation from a previous study, the North Atlantic did not yield robust significant correlations. Multiple tests were then conducted to determine the sensitivity of the North Atlantic correlations to different datasets and time periods. Ultimately, it was determined that the North Atlantic AI vs. PI correlation results were very dependent upon the time period and the individual years within the time period. In the comparison of all contributors, air-sea disequilibrium was the dominant contributor to PI variability. When AI variability was correlated with PI variability, disequilibrium (which is largely controlled by SSTs) was also the dominant contributor to AI variability. Although disequilibrium was the dominant factor in PI and AI interannual variability, efficiency also played a role. In fact, this study found that variances in efficiency explained 13-93% of PI interannual variability, indicating that variability in outflow temperatures (which cause much of the variability in efficiency) must be taken into account.

ISBN: 9781085595391Subjects--Topical Terms:

542822
Meteorology.

Interannual Variability of Tropical Cyclone Potential Intensity and Lifetime Maximum Intensity: An Analysis of Influential Factors.
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520 $a Many tropical cyclone studies have been conducted on basin-averaged potential intensity trends and the influence of sea surface temperatures (SSTs) on tropical cyclone intensity, but there is less research on along-track potential intensity (PI) and lifetime maximum intensity (referred to here as actual intensity or AI) and the factors that influence their variability. Potential intensity is a theory that predicts the maximum intensity that a tropical cyclone can achieve given certain large-scale environmental variables. Understanding interannual variability in PI and its relation to AI interannual variability is of great importance for assessing the impact of future climate conditions on tropical cyclones. Theoretically, warmer SSTs and cooler outflow temperatures would cause an increase in overall PI which in turn would lead to an increase in AI. This thesis examined the relationship between PI and AI on interannual time scales and the factors affecting PI variability: thermodynamic efficiency and air-sea enthalpy disequilibrium.Using best-track data and three reanalysis products, variability in PI and AI was examined for the North Atlantic, North Indian, South Indian, South Pacific, Eastern North Pacific, and Western North Pacific basins from 1980-2013. Overall, the Western North Pacific was the only basin that yielded high and consistently significant correlations between AI and PI. Despite the expectation from a previous study, the North Atlantic did not yield robust significant correlations. Multiple tests were then conducted to determine the sensitivity of the North Atlantic correlations to different datasets and time periods. Ultimately, it was determined that the North Atlantic AI vs. PI correlation results were very dependent upon the time period and the individual years within the time period. In the comparison of all contributors, air-sea disequilibrium was the dominant contributor to PI variability. When AI variability was correlated with PI variability, disequilibrium (which is largely controlled by SSTs) was also the dominant contributor to AI variability. Although disequilibrium was the dominant factor in PI and AI interannual variability, efficiency also played a role. In fact, this study found that variances in efficiency explained 13-93% of PI interannual variability, indicating that variability in outflow temperatures (which cause much of the variability in efficiency) must be taken into account.
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