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Moist static energy budget analysis of tropical cyclone intensification in high-resolution climate models

Cited 37 time in Web of Science Cited 37 time in Scopus
Authors

Wing, Allison A.; Camargo, Suzana J.; Sobel, Adam H.; Kim, Daehyun; Moon, Yumin; Murakami, Hiroyuki; Reed, Kevin A.; Vecchi, Gabriel A.; Wehner, Michael F.; Zarzycki, Colin; Zhao, Ming

Issue Date
2019-09
Publisher
American Meteorological Society
Citation
Journal of Climate, Vol.32 No.18, pp.6071-6095
Abstract
Tropical cyclone intensification processes are explored in six high-resolution climate models. The analysis framework employs process-oriented diagnostics that focus on how convection, moisture, clouds, and related processes are coupled. These diagnostics include budgets of column moist static energy and the spatial variance of column moist static energy, where the column integral is performed between fixed pressure levels. The latter allows for the quantification of the different feedback processes responsible for the amplification of moist static energy anomalies associated with the organization of convection and cyclone spinup, including surface flux feedbacks and cloud-radiative feedbacks. Tropical cyclones (TCs) are tracked in the climate model simulations and the analysis is applied along the individual tracks and composited over many TCs. Two methods of compositing are employed: a composite over all TC snapshots in a given intensity range, and a composite over all TC snapshots at the same stage in the TC life cycle (same time relative to the time of lifetime maximum intensity for each storm). The radiative feedback contributes to TC development in all models, especially in storms of weaker intensity or earlier stages of development. Notably, the surface flux feedback is stronger in models that simulate more intense TCs. This indicates that the representation of the interaction between spatially varying surface fluxes and the developing TC is responsible for at least part of the intermodel spread in TC simulation.
ISSN
0894-8755
URI
https://hdl.handle.net/10371/200968
DOI
https://doi.org/10.1175/JCLI-D-18-0599.1
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  • College of Natural Sciences
  • Department of Earth and Environmental Sciences
Research Area Climate Change, Earth & Environmental Data, Severe Weather, 기후과학, 위험기상, 지구환경 데이터과학

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