@article{8536e521f5f74a7586621eff94408502,
title = "Process-oriented diagnosis of tropical cyclones in high-resolution GCMs",
abstract = "This study proposes a set of process-oriented diagnostics with the aim of understanding how model physics and numerics control the representation of tropical cyclones (TCs), especially their intensity distribution, in GCMs. Three simulations are made using two 50-km GCMs developed at NOAA's Geophysical Fluid Dynamics Laboratory. The two models are forced with the observed sea surface temperature [Atmospheric Model version 2.5 (AM2.5) and High Resolution Atmospheric Model (HiRAM)], and in the third simulation, the AM2.5 model is coupled to an ocean GCM [Forecast-Oriented Low Ocean Resolution (FLOR)]. The frequency distributions of maximum near-surface wind near TC centers show that HiRAM tends to develop stronger TCs than the other models do. Large-scale environmental parameters, such as potential intensity, do not explain the differences between HiRAM and the other models. It is found that HiRAM produces a greater amount of precipitation near the TC center, suggesting that associated greater diabatic heating enables TCs to become stronger in HiRAM. HiRAMalso shows a greater contrast in relative humidity and surface latent heat flux between the inner and outer regions of TCs. Various fields are composited on precipitation percentiles to reveal the essential character of the interaction among convection, moisture, and surface heat flux. Results show that the moisture sensitivity of convection is higher in HiRAM than in the other model simulations. HiRAM also exhibits a stronger feedback from surface latent heat flux to convection via near-surface wind speed in heavy rain-rate regimes. The results emphasize that the moisture-convection coupling and the surface heat flux feedback are critical processes that affect the intensity of TCs in GCMs.",
keywords = "Convective parameterization, Diagnostics, General circulation models, Tropical cyclones",
author = "Daehyun Kim and Yumin Moon and Camargo, {Suzana J.} and Wing, {Allison A.} and Sobel, {Adam H.} and Hiroyuki Murakami and Vecchi, {Gabriel Andres} and Ming Zhao and Eric Page",
note = "Funding Information: Acknowledgments. This work is a contribution to the process-oriented diagnostics effort of the NOAA MAPP Model Diagnostics Task Force. We thank the Task Force members for their valuable comments during the course of this work. This study was supported by NOAA{\textquoteright}s Climate Program Office{\textquoteright}s Modeling, Analysis, Predictions, and Projections program through Grant NA15OAR4310087. D. Kim was also supported by the Korea Meteorological Administration Research and Development Program under Grant KMIPA 2016-6010 and by a startup grant from the University of Washington. Y. Moon was supported from a NSF AGS Postdoctoral Research Fellowship (AGS-1524270). The authors also thank Dr. Kun Gao (GFDL) for his constructive comments on an earlier version of the manuscript. Comments from anonymous reviewers have greatly helped the authors to improve the manuscript. Funding Information: This work is a contribution to the process-oriented diagnostics effort of the NOAA MAPP Model Diagnostics Task Force.We thank the Task Force members for their valuable comments during the course of this work. This study was supported by NOAA's Climate Program Office's Modeling, Analysis, Predictions, and Projections program through Grant NA15OAR4310087. D. Kim was also supported by the Korea Meteorological Administration Research and Development Program under Grant KMIPA 2016-6010 and by a startup grant fromtheUniversity ofWashington. Y. Moon was supported from a NSF AGS Postdoctoral Research Fellowship (AGS-1524270). The authors also thank Dr. Kun Gao (GFDL) for his constructive comments on an earlier version of themanuscript. Comments from anonymous reviewers have greatly helped the authors to improve the manuscript Publisher Copyright: {\textcopyright} 2018 American Meteorological Society.",
year = "2018",
month = mar,
day = "1",
doi = "10.1175/JCLI-D-17-0269.1",
language = "English (US)",
volume = "31",
pages = "1685--1702",
journal = "Journal of Climate",
issn = "0894-8755",
publisher = "American Meteorological Society",
number = "5",
}