Search Results

You are looking at 1 - 10 of 16 items for :

  • Tropical Cyclone Intensity Experiment (TCI) x
  • Refine by Access: All Content x
Clear All
Robert G. Nystrom, Fuqing Zhang, Erin B. Munsell, Scott A. Braun, Jason A. Sippel, Yonghui Weng, and Kerry Emanuel

the northern Atlantic. While Joaquin’s motion slowed in the Bahamas, historic flooding commenced along the eastern coast of the United States when a cutoff low pressure system developed over the southeastern United States and transported moisture from Joaquin into the region. By 1200 UTC 3 October, Joaquin had turned northward and began to track to the northeast, away from the U.S. coast ( Fig. 1e ). The westerly winds in the southern region of the low pressure system located over the southeastern

Full access
Patrick Duran and John Molinari

, respectively; is the saturation mixing ratio; is the total condensate mixing ratio; and is the moist adiabatic lapse rate: where is the latent heat of vaporization and is the specific heat of moist air at constant pressure. In the tropopause layer, , , , and approach zero. In this limiting case, Eq. (1) reduces to where θ is the potential temperature. Equation (1) is the appropriate expression for in moist environments, whereas Eq. (3) applies strictly in the absence of moisture

Full access
Benjamin C. Trabing, Michael M. Bell, and Bonnie R. Brown

atmosphere when including realistic longwave cooling due to the colder cloud-top emission temperature, but increases the local cloud-top cooling rate due to increased radiative flux divergence. The results suggest that the Eliassen framework is more appropriate when seeking to understand the impacts rather than a Carnot engine perspective. The actual maximum intensity of any particular ensemble member is sensitive to small moisture perturbations in the initial conditions, especially in the longwave

Full access
Nannan Qin and Da-Lin Zhang

an intensification rate of greater than 15.4 m s −1 day −1 in V MAX , following Kaplan and DeMaria (2003) . In hindsight, Patricia’s strong intensity was expected, but not the degree to which it would intensify, and it did so rapidly ( Kimberlain et al. 2016 ), given its development in a very favorable environment with high sea surface temperature (SST), high ocean heat content, weak vertical wind shear (VWS), and ample low-tropospheric moisture ( Gray 1968 ; Holliday and Thompson 1979

Full access
David R. Ryglicki, James D. Doyle, Daniel Hodyss, Joshua H. Cossuth, Yi Jin, Kevin C. Viner, and Jerome M. Schmidt

boundary layer by low moisture air ( Riemer et al. 2010 ; Riemer and Laliberté 2015 ). Despite those thermodynamic effects, Onderlinde and Nolan (2016) and Finocchio et al. (2016) have demonstrated that given the correct environmental setup, the helicity of the background flow or the depth of the background winds can drastically change the evolution of a simulated TC. It is the depth of the background flow that Ryglicki et al. (2018a , hereafter Part I ) have argued is instrumental for

Full access
Robert G. Nystrom and Fuqing Zhang

pressure at 39 h indicate that inner-core moisture may also have played some role in the forecast uncertainty ( Fig. 8c ), consistent with many previous studies (e.g., Rotunno and Emanuel 1987 ; Tao and Zhang 2014 ; Emanuel and Zhang 2017 ; Nystrom et al. 2018 ). However, differences here appeared minimal compared to differences in the primary and secondary circulations (not shown) and a moisture swap experiment in which the initial QVAPOR of a bad member (member 31) and the analysis mean are

Free access
Russell L. Elsberry, Eric A. Hendricks, Christopher S. Velden, Michael M. Bell, Melinda Peng, Eleanor Casas, and Qingyun Zhao

AMVs outside the cirrus cloud shield to analyze the outer TC vortex wind structure as well as represent the environmental mass influx. In conjunction with AMVs derived from the water vapor channels, the middle-tropospheric moisture flux from the environment to the outer regions of the TC can be continuously monitored. Although the details will not be provided in this model proof-of-concept demonstration, it may be useful to at least describe the expected model physical linkages connecting the

Full access
Peter Black, Lee Harrison, Mark Beaubien, Robert Bluth, Roy Woods, Andrew Penny, Robert W. Smith, and James D. Doyle

sensor used in the RD-94s. Nonetheless, a comparison of humidity profiles in Figs. 4a,b between RD-94 and XDD sondes shows consistent features in the humidity measurements: 1) the upper moist layer at the base of a temperature inversion (3–3.5 km; Fig. 4a ); 2) the dry adiabatic layer from the top of the marine layer inversion (1.25 km) to the base of the upper moist layer (2.7 km); 3) the strong moisture gradient from the top of the marine layer inversion to the top of the adiabatic marine layer

Full access
Xu Lu and Xuguang Wang

model integration to satisfy the mass conservation ( Fig. 7t ). The weak updraft is hypothesized to be related to the unrealistically discontinuous vertical diffusion parameterization as mentioned in section 1 ( Fig. 1 ), where the lack of vertical diffusion at the boundary layer top constrains the upward moisture and energy transport and therefore the updraft triggered by latent heat release in the eyewall is constrained. Such an inefficient vertical energy and moisture transport is reflected by

Full access
William A. Komaromi and James D. Doyle

2014. The number of dropsondes in each bin is labeled in magenta. A meaningful relationship between the θ of the maximum 100–500-km radially averaged V r and the present intensity was not observed ( Fig. 9c ). However, a notable positive relationship between the θ of the outflow layer and the θ e of the boundary layer inflow, which is a proxy for low-level moisture and SSTs, does occur ( Fig. 9d ). These values are obtained by first computing azimuthal-mean V r in radius– θ (radius θ e

Full access