The critical role of cloud–infrared radiation feedback in tropical cyclone development

The tall clouds that comprise tropical storms, hurricanes, and typhoons—or more generally, tropical cyclones (TCs)—are highly effective at trapping the infrared radiation welling up from the surface. This cloud–infrared radiation feedback, referred to as the “cloud greenhouse effect,” locally warms...

Full description

Saved in:
Bibliographic Details
Published inProceedings of the National Academy of Sciences - PNAS Vol. 117; no. 45; pp. 27884 - 27892
Main Authors Ruppert, James H., Wing, Allison A., Tang, Xiaodong, Duran, Erika L.
Format Journal Article
LanguageEnglish
Published United States National Academy of Sciences 10.11.2020
Subjects
Angular momentum
Clouds
Cyclones
Feedback
Gestation
Greenhouse effect
Hurricanes
Infrared radiation
Life cycles
Physical Sciences
Storms
Tropical cyclones
Tropical storms
Troposphere
Typhoons
feedback
tropical cyclone
hurricane
clouds
radiation
Online AccessGet full text

Cover

More Information
Summary:The tall clouds that comprise tropical storms, hurricanes, and typhoons—or more generally, tropical cyclones (TCs)—are highly effective at trapping the infrared radiation welling up from the surface. This cloud–infrared radiation feedback, referred to as the “cloud greenhouse effect,” locally warms the lower–middle troposphere relative to a TC’s surroundings through all stages of its life cycle. Here, we show that this effect is essential to promoting and accelerating TC development in the context of two archetypal storms—Super Typhoon Haiyan (2013) and Hurricane Maria (2017). Namely, this feedback strengthens the thermally direct transverse circulation of the developing storm, in turn both promoting saturation within its core and accelerating the spin-up of its surface tangential circulation through angular momentum convergence. This feedback therefore shortens the storm’s gestation period prior to its rapid intensification into a strong hurricane or typhoon. Further research into this subject holds the potential for key progress in TC prediction, which remains a critical societal challenge.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
Edited by Kerry A. Emanuel, Massachusetts Institute of Technology, Cambridge, MA, and approved September 21, 2020 (received for review June 29, 2020)
Author contributions: J.H.R. designed research; J.H.R., A.A.W., X.T., and E.L.D. performed research; J.H.R. analyzed data; and J.H.R. wrote the paper.
ISSN:0027-8424
1091-6490
1091-6490
DOI:10.1073/pnas.2013584117