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Title: Physical understanding of the tropical cyclone wind-pressure relationship

Abstract

The relationship between the two common measures of tropical cyclone intensity, the central pressure deficit and the peak near-surface wind speed, is a long-standing problem in tropical meteorology that has been approximated empirically yet lacks physical understanding. Here we provide theoretical grounding for this relationship. We first demonstrate that the central pressure deficit is highly predictable from the low-level wind field via gradient wind balance. We then show that this relationship reduces to a dependence on two velocity scales: the maximum azimuthal-mean azimuthal wind speed and half the product of the Coriolis parameter and outer storm size. This simple theory is found to hold across a hierarchy of models spanning reduced-complexity and Earth-like global simulations and observations. Therefore, the central pressure deficit is an intensity measure that combines maximum wind speed, storm size, and background rotation rate. This work has significant implications for both fundamental understanding and risk analysis, including why the central pressure better explains historical economic damages than does maximum wind speed.

Authors:
ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [3]
  1. Purdue Univ., West Lafayette, IN (United States)
  2. Stony Brook Univ., NY (United States)
  3. Colorado State Univ., Fort Collins, CO (United States)
Publication Date:
Research Org.:
Univ. of California, Davis, CA (United State)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1513293
Grant/Contract Number:  
SC0016605
Resource Type:
Accepted Manuscript
Journal Name:
Nature Communications
Additional Journal Information:
Journal Volume: 8; Journal Issue: 1; Journal ID: ISSN 2041-1723
Publisher:
Nature Publishing Group
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; 58 GEOSCIENCES

Citation Formats

Chavas, Daniel R., Reed, Kevin A., and Knaff, John A. Physical understanding of the tropical cyclone wind-pressure relationship. United States: N. p., 2017. Web. doi:10.1038/s41467-017-01546-9.
Chavas, Daniel R., Reed, Kevin A., & Knaff, John A. Physical understanding of the tropical cyclone wind-pressure relationship. United States. doi:10.1038/s41467-017-01546-9.
Chavas, Daniel R., Reed, Kevin A., and Knaff, John A. Wed . "Physical understanding of the tropical cyclone wind-pressure relationship". United States. doi:10.1038/s41467-017-01546-9. https://www.osti.gov/servlets/purl/1513293.
@article{osti_1513293,
title = {Physical understanding of the tropical cyclone wind-pressure relationship},
author = {Chavas, Daniel R. and Reed, Kevin A. and Knaff, John A.},
abstractNote = {The relationship between the two common measures of tropical cyclone intensity, the central pressure deficit and the peak near-surface wind speed, is a long-standing problem in tropical meteorology that has been approximated empirically yet lacks physical understanding. Here we provide theoretical grounding for this relationship. We first demonstrate that the central pressure deficit is highly predictable from the low-level wind field via gradient wind balance. We then show that this relationship reduces to a dependence on two velocity scales: the maximum azimuthal-mean azimuthal wind speed and half the product of the Coriolis parameter and outer storm size. This simple theory is found to hold across a hierarchy of models spanning reduced-complexity and Earth-like global simulations and observations. Therefore, the central pressure deficit is an intensity measure that combines maximum wind speed, storm size, and background rotation rate. This work has significant implications for both fundamental understanding and risk analysis, including why the central pressure better explains historical economic damages than does maximum wind speed.},
doi = {10.1038/s41467-017-01546-9},
journal = {Nature Communications},
number = 1,
volume = 8,
place = {United States},
year = {2017},
month = {11}
}

Journal Article:
Free Publicly Available Full Text
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Cited by: 12 works
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Figures / Tables:

Fig. 1 Fig. 1: Storm count density across simulations and observations. a OMEGA. b AMIP. c Observations. Density is defined as number of track points per (1000 km)2 per year, calculated from data binned into lat-lon boxes of side length 5° weighted by the cosine of the box central latitude. Maximum valuemore » set to 99th percentile for clarity; gray dashed line denotes zero density contour. No data filters are applied« less

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