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T. Connor Nelson, Lee Harrison, and Kristen L. Corbosiero

here to be the last recorded data point in the sounding below 500 m. Vertical velocity at these last data points for the sondes launched outside of convective regions is assumed to be negligible (see appendix for error analysis); V o is the estimated sea level still-air fall speed of each individual sonde based upon the median sonde parameter and the last observed data point density below 500 m ( ρ o ) after data quality control and removal have been completed (see below), and V is the

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Robert L. Creasey and Russell L. Elsberry

the bottom surface assist in visualizing the vortex tilt in latitude and longitude. Elevations, latitudes, and longitudes of the ZWCs are provided in the insets. Although preliminary HDSS wind observations (or GPS latitude–longitude positions) did exist above 10 km in the level 1 TCI data fields, it is difficult to extend the ZWC analysis and vortex tilt calculation above 10 km. While this may be due to questionable data quality (values were omitted by the TCI data quality control team), the eye

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

restricted domains and durations. More importantly, applications in numerical weather prediction (NWP) have often been constrained to 6-h data assimilation cycles and AMV dataset thinning. In this study it will be demonstrated that shorter sampling times and continuous rapid scanning combined with the advanced sensors on these new-generation satellites will substantially improve the quality and quantity of the AMVs, and thus their potential impacts on the U.S. Navy regional and global model analyses and

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Shixuan Zhang, Zhaoxia Pu, and Christopher Velden

Meteorological Satellite Studies (CIMSS), University of Wisconsin. These datasets are derived from GOES data and are part of a demonstration for applications to advanced geosatellite imagers now becoming operational (GOES-R/S, Himawari-8/9 ). The enhanced AMVs are quality controlled before being entered into the HWRF GSI; enhanced AMVs are assimilated only if the quality indicator (QI) is equal to or larger than an empirically determined value of 0.6 ( Wu et al. 2014 ). In addition, enhanced AMVs meeting

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Shixuan Zhang and Zhaoxia Pu

, temperature, and wind speed and direction. These dropsonde observations have been quality controlled via a combined “subjective-objective” procedure utilizing the Atmospheric Sounding Processing Environment (ASPEN) software ( Bell et al. 2016 ). As shown in Fig. 2 , the HDSS dropsonde observations provide substantive compensation for the lack of observations in the hurricane inner-core region ( Figs. 2a,b ), especially in the middle and upper troposphere ( Figs. 2c,d ). In addition, the HDSS dropsonde

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Daniel J. Cecil and Sayak K. Biswas

stage. Doyle et al. (2017) summarize the TCI flights and datasets. From the quality-controlled dropsonde wind profiles, a layer-average wind speed is computed over the lowest 150 m of the profile (WL150), or the lowest 500 m [mean boundary layer (MBL)] if low-level data are unavailable ( Franklin et al. 2003 ). This averaging removes some of the effect of gustiness in the dropsonde wind profile. Near-surface wind speed is estimated from WL150 using the coefficients in Uhlhorn et al.’s (2007) Fig

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Jonathan Martinez, Michael M. Bell, Robert F. Rogers, and James D. Doyle

horizontal velocity errors are reported as 1.5 hPa, 0.14°C, 1.8%, and 0.1 m s −1 , respectively ( Bell et al. 2016 ; Black et al. 2017 ). Each sounding is subjected to a combined objective–subjective quality control procedure, described in detail by Bell et al. (2016) , to ensure reliable data quality for the final product. The P-3 tail Doppler radar is an X-band (~3-cm wavelength) radar with two antennas, one scanning fore and the other scanning aft, both positioned at an ~20° offset from the aircraft

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James D. Doyle, Jonathan R. Moskaitis, Joel W. Feldmeier, Ronald J. Ferek, Mark Beaubien, Michael M. Bell, Daniel L. Cecil, Robert L. Creasey, Patrick Duran, Russell L. Elsberry, William A. Komaromi, John Molinari, David R. Ryglicki, Daniel P. Stern, Christopher S. Velden, Xuguang Wang, Todd Allen, Bradford S. Barrett, Peter G. Black, Jason P. Dunion, Kerry A. Emanuel, Patrick A. Harr, Lee Harrison, Eric A. Hendricks, Derrick Herndon, William Q. Jeffries, Sharanya J. Majumdar, James A. Moore, Zhaoxia Pu, Robert F. Rogers, Elizabeth R. Sanabia, Gregory J. Tripoli, and Da-Lin Zhang

experiment, the HDSS dropsonde and HIRAD observations went through a rigorous quality-control process. The dropsonde observations were quality controlled using the Atmospheric Sounding Processing Environment (ASPEN) software package along with a subsequent manual evaluation by a team of TCI scientists, with each data point being reviewed by at least two scientists ( Bell et al. 2016 ). For HIRAD, optimal combinations of frequency subbands and antenna elements were identified, and the most reliable

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Jie Feng and Xuguang Wang

particularly high resolution. The raw TCI dropsonde data have first gone through quality control (QC) by the TCI investigators, detailed in Bell et al. (2016) . Two additional preprocessing steps were performed before the assimilation in this study. Due to the dense sampling, the model resolution as configured in the current study may not resolve the fine spatial and temporal structure captured by the TCI dropsondes. Therefore, the TCI dropsonde observations are superobbed to improve the data assimilation

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

correction (FEC) on two receivers was implemented to improve data reception at ranges > 200 km. Beyond sensor uncertainties, overall data quality is affected by data gaps in the telemetered data. To minimize gaps, the XDD uses FEC to recover data packets having bit errors. In addition, merged data from four redundant receivers minimizes overall data dropouts that appear at different times on the four different receivers, providing a more continuous stream of observations for use in optimal time series

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