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Yi Dai, Sharanya J. Majumdar, and David S. Nolan

–200 km of the center. In section 3e , we will also investigate two real cases: Hurricanes Edouard (2014) and Matthew (2016), both of which intensified in moderately high shear. To show the outflow of these two real cases, we use the upper-level atmospheric motion vectors (AMVs; Velden et al. 1997 ), together with geostationary (GOES) water vapor satellite imagery, collected from the Cooperative Institute for Meteorological Satellite Studies (CIMSS) at the University of Wisconsin–Madison. In

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David R. Ryglicki, Joshua H. Cossuth, Daniel Hodyss, and James D. Doyle

TC outflow or computing AMV-based vertical wind shear values (e.g., Velden and Sears 2014 ). In addition to AMVs, geostationary satellite measurements have also been used in a diagnostic way to physically characterize certain phenomena of TCs. Olander and Velden (2009) used the difference between infrared and water vapor bands to investigate overshooting tops in convection, while Griffin et al. (2016) used infrared (IR) imagery augmented with CloudSat and MODIS imagery to further

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Yi Dai, Sharanya J. Majumdar, and David S. Nolan

) Upper-level atmospheric motion vectors (AMVs) superposed on the GOES-East water vapor images of Hurricane Edouard at 0000, 0600, and 1200 UTC 16 Sep 2014. The red arrow represents the calculated vertical wind shear (~8 m s −1 ) using ERA-Interim data. (d)–(f) As in (a)–(c), but for the corresponding infrared brightness temperature (K). This inconsistency between the VWS and convection not only occurred in Hurricane Edouard (2014). In a recent idealized simulation of the TC interacting with a

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

work serves as a numerical model-based companion to Part I and as a follow-up to Ryglicki et al. (2018b , hereafter Part II ). In the satellite observations presented in Part I , they noted two key identifying features: tilt-modulated convective asymmetries (TCA), which appear prior to RI and with a period of 4–8 h and upper-level arcs, which appear in the water vapor (WV) satellite imagery. Part II demonstrated that these TCAs are associated with the nutation 1 of the tilt of the vortex

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Patrick Duran and John Molinari

-level static stability and cold-point tropopause structure throughout Patricia’s RI. The cold-point tropopause is defined as the level of minimum temperature in a sounding ( Highwood and Hoskins 1998 ). This tropopause definition is widely used in the tropics because the cold-point temperature influences the exchange of ozone and water vapor between the troposphere and stratosphere ( Mote et al. 1996 ), which has important climatological implications ( Holton et al. 1995 ). Although few papers have

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

water vapor bands are most sensitive to the middle- to upper-tropospheric humidity. Given this high spatial, spectral, and temporal resolution, these new-generation imagers are better able to track coherent clouds and water vapor features to derive atmospheric motion vectors (AMVs) that provide estimates of tropospheric winds ( Velden et al. 2005 ). That is, clouds or water vapor features can be selected from an image at time t and then the backward and forward motion vectors from t − 10 min to

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David R. Ryglicki, James D. Doyle, Yi Jin, Daniel Hodyss, and Joshua H. Cossuth

that given the structural differences between tropopause cyclonic and anticyclonic potential vorticity (PV) anomalies ( Hoskins et al. 1985 ; Wirth 2001 ), the strongest environmental winds associated with anticyclones are likely to be confined to a similar layer as the outflow from the TC—usually around 200 hPa ( Merrill and Velden 1996 ). Part I also demonstrated that before the eyes appeared in infrared (IR) and water vapor (WV), each storm exhibited what we referred to as a tilt

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

-to-sonde variance of ±0.7°C and a profile mean XDD warm bias relative to RD-94 mean temperature profiles averaging +1.2°C, in close agreement with bias estimates relative to the surface buoy observations as well as Twin Otter aircraft profile observations discussed in section 3b . Also shown is the sonde miniradiometer SSTir profile typical of one of the XDDs. The observed values in the profile indicate the sum total of true SSTir plus intervening atmospheric water vapor and cloud attenuation. Linear

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Daniel J. Cecil and Sayak K. Biswas

7 m s −1 . A fixed atmospheric profile of temperature, water vapor, and cloud liquid water is taken from idealized numerical simulations of hurricanes described by Amarin et al. (2012) . At HIRAD’s C-band frequencies, sensitivity to realistic variations in these atmospheric profiles is small ( Smith 1982 ; Tsang et al. 1977 ) compared to the instrument’s measurement error. The scene construction and the brightness temperature calibration are conducted separately for each of HIRAD’s four

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Nannan Qin and Da-Lin Zhang

( Tao et al. 1989 ), MP Morrison ( Morrison et al. 2009 ), and MP WDM6 ( Lim and Hong 2010 ) plus the CTL simulation ( Thompson et al. 2008 ). All of these schemes contain six classes of hydrometeors: water vapor, cloud water, rain, snow, ice, and graupel. In addition, MP LIN , MP WSM6 , and CTL are one-moment schemes containing the mixing ratios of the hydrometeors, while the others are two-moment schemes predicting both the mixing ratios and the number concentrations of the hydrometeor species

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