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Jonathan Zawislak, Haiyan Jiang, George R. Alvey III, Edward J. Zipser, Robert F. Rogers, Jun A. Zhang, and Stephanie N. Stevenson

Sensor Microwave Imager/Sounder (SSMIS), and the Advanced Microwave Scanning Radiometer 2 (AMSR2). The brightness temperature ( T B ) data are from the GPM level-1C algorithm ( NASA GSFC 2010 ), which provides intercalibration of those sensors using GMI as the reference. Fig . 5. Time series of 30-min infrared (IR) brightness temperature T B for the period between 1200 UTC 11 Sep and 0000 UTC 19 Sep, shown with respect to the shear-relative azimuth (shear heading is 0°); T B is averaged along

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Sergio F. Abarca, Michael T. Montgomery, Scott A. Braun, and Jason Dunion

Abstract

A first observationally based estimation of departures from gradient wind balance during secondary eyewall formation is presented. The study is based on the Atlantic Hurricane Edouard (2014). This storm was observed during the National Aeronautics and Space Administration’s (NASA) Hurricane and Severe Storm Sentinel (HS3) experiment, a field campaign conducted in collaboration with the National Oceanic and Atmospheric Administration (NOAA). A total of 135 dropsondes are analyzed in two separate time periods: one named the secondary eyewall formation period and the other one referred to as the decaying double eyewalled storm period. During the secondary eyewall formation period, a time when the storm was observed to have only one eyewall, the diagnosed agradient force has a secondary maximum that coincides with the radial location of the secondary eyewall observed in the second period of study. The maximum spinup tendency of the radial influx of absolute vertical vorticity is within the boundary layer in the region of the eyewall of the storm and the spinup tendency structure elongates radially outward into the secondary region of supergradient wind, where the secondary wind maximum is observed in the second period of study. An analysis of the boundary layer averaged vertical structure of equivalent potential temperature reveals a conditionally unstable environment in the secondary eyewall formation region. These findings support the hypothesis that deep convective activity in this region contributed to spinup of the boundary layer tangential winds and the formation of a secondary eyewall that is observed during the decaying double eyewalled storm period.

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Robert F. Rogers, Jun A. Zhang, Jonathan Zawislak, Haiyan Jiang, George R. Alvey III, Edward J. Zipser, and Stephanie N. Stevenson

Abstract

The structural evolution of the inner core and near-environment throughout the life cycle of Hurricane Edouard (2014) is examined using a synthesis of airborne and satellite measurements. This study specifically focuses on differences in the distribution of deep convection during two periods: when Edouard intensified toward hurricane status, and when Edouard peaked in intensity and began to weaken. While both periods saw precipitation maximized in the downshear-left and upshear-left quadrants, deep convection was only seen from the aircraft during the intensifying period.

Deep convection was located farther inside the radius of maximum winds (RMW) during the intensifying period than the weakening period. This convection is traced to strong updrafts inside the RMW in the downshear-right quadrant, tied to strong low-level convergence and high convective available potential energy (CAPE) as the storm remained over warm water in a moist environment. Strong updrafts persisted upshear left and were collocated with high inertial stability in the inner core. During weakening, no deep convection was present, and the precipitation that was observed was associated with weaker convergence downshear right at larger radii, as CAPE was reduced from lower sea surface temperatures, reduced humidity from subsidence, and a stronger warm core. Weak updrafts were seen upshear left, with little coincidence with the high inertial stability of the inner core.

These results highlight the importance of the azimuthal coverage of precipitation and the radial location of deep convection for intensification. A more symmetrical coverage can occur despite the presence of shear-driven azimuthal asymmetries in both the forcing and the local environment of the precipitation.

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Anthony C. Didlake Jr., Gerald M. Heymsfield, Paul D. Reasor, and Stephen R. Guimond

on 15–17 October. This plane was equipped with the X-band TA Doppler radar. The TA radar scans around a horizontal axis and utilizes the fore/aft scanning technique (FAST; Jorgensen and DuGranrut 1991 ), collecting two independent looks at the three-dimensional wind vector as the plane flies along its track. The P3 TA radar data were processed using an automated algorithm ( Gamache 1997 ) that produces three-dimensional reflectivity and wind fields. The data first undergo an automated quality

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E. P. Nowottnick, P. R. Colarco, S. A. Braun, D. O. Barahona, A. da Silva, D. L. Hlavka, M. J. McGill, and J. R. Spackman

MODIS level 3 AOT retrievals at 550 nm from Collection 5.1 algorithms ( Remer et al. 2005 ; Levy et al. 2010 ). 4. The NASA GEOS-5 model and simulation setup The NASA GEOS-5 Earth system model and data assimilation system, developed by the NASA Goddard Global Modeling and Assimilation Office (GMAO), provides simulations of weather and climate for NASA instrument teams and the scientific community ( Rienecker et al. 2008 ). In addition to traditional meteorological quantities, such as winds and

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Zhining Tao, Scott A. Braun, Jainn J. Shi, Mian Chin, Dongchul Kim, Toshihisa Matsui, and Christa D. Peters-Lidard

snapshots of data from Collection 6 products utilizing the dark target algorithm ( Kaufman et al. 1997 ) that retrieves AOD over ocean and “dark” land. Fig . 1. Daily daytime MODIS AOD (colors) and clouds from Aqua and Terra on (a) 22 Aug, (b) 23 Aug, (c) 24 Aug, and (d) 25 Aug 2013. (c),(d) The Global Hawk flight path for 24–25 Aug, with the time on station being between the times of the two images. AOD data measured by sun photometers from the Aerosol Robotic Network (AERONET; Holben et al. 1998

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Lucas Merckelbach, Anja Berger, Gerd Krahmann, Marcus Dengler, and Jeffrey R. Carpenter

Explorer DVL. The CTD received a firmware update allowing it to sample at 1 Hz, rather than the default 0.5 Hz. A thermal lag correction algorithm, similar to that described by Garau et al. (2011) , was applied to correct the measured conductivity within the conductivity cell. The MicroRider sampled pressure and pitch at 64 Hz. The DVL mounted on glider COMET measured velocities acoustically along four beams in a Janus configuration at a 30° angle. The device was mounted in a separate hull section

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Scott A. Braun, Paul A. Newman, and Gerald M. Heymsfield

3119.1 . Guimond , S. R. , L. Tian , G. M. Heymsfield , and S. J. Frasier , 2014 : Wind retrieval algorithms for the IWRAP and HIWRAP airborne Doppler radars with applications to hurricanes . J. Atmos. Oceanic Technol. , 31 , 1189 – 1215 , doi: 10.1175/JTECH-D-13-00140.1 . Halverson , J. B. , J. Simpson , G. Heymsfield , H. Pierce , T. Hock , and L. Ritchie , 2006 : Warm core structure of Hurricane Erin diagnosed from high-altitude dropsondes during CAMEX-4 . J

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Erin B. Munsell, Fuqing Zhang, Jason A. Sippel, Scott A. Braun, and Yonghui Weng

version of the WRF Model (ARW; Skamarock et al. 2008 ) and an EnKF data assimilation algorithm. Data assimilated into this system include Global Telecommunication System (GTS) conventional data and reconnaissance data, including superobservations generated from the airborne tail Doppler radar (TDR) on NOAA’s P-3 aircraft ( Weng and Zhang 2012 ) and satellite-derived winds ( Weng and Zhang 2016 ). In addition, dropsondes deployed from the NOAA–National Center for Atmospheric Research (NCAR) Advanced

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Erin B. Munsell, Jason A. Sippel, Scott A. Braun, Yonghui Weng, and Fuqing Zhang

outlines the main conclusions of this study. 2. Methodology and data a. WRF-EnKF hurricane analysis and forecast system The deterministic and 60-member ensemble forecasts for Nadine are generated using version 3.5.1 of the Advanced Research version of the WRF model (ARW; Skamarock et al. 2008 ) and an EnKF data assimilation algorithm. The model setup is similar to what is described in Weng and Zhang (2012) , but with the added capability of continuous cycling assimilation of all conventional

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