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J. C. Hubbert

antenna pattern so that power transmitted and received through the antenna sidelobes does not bias the measurement. For the following datasets, S-Pol was in FHV mode with a pulse repetition time (PRT) of 1 ms. Thus, a cross-polar power pair, separated by 1 ms, comes from nearly the identical resolution volume of scatterers, since neither they nor the antenna moves appreciably in 1 ms. To ensure good data quality, several thresholds are used for the CP powers: 20 dB dB (signal-to-noise ratio) and

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Samuel K. Degelia, Xuguang Wang, and David J. Stensrud

, respectively. The gray box in (b) indicates the plotting domain for Fig. 8 , below. The states of Kansas (KS), Nebraska (NE), Missouri (MO), and Oklahoma (OK) are also labeled in (b). The plots in (a) and (b) are created using model analyses from the Rapid Refresh model ( Benjamin et al. 2016 ). The sounding in (c) is plotted using the quality-control checks provided by Loehrer et al. (1996) . Except for the wind data being superob-ed to a depth of 20 hPa, the data in (c) are processed using the same

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Brian J. Carroll, Belay B. Demoz, David D. Turner, and Ruben Delgado

permanent lidar profiling networks. The DC-8 carried the NASA Lidar Atmospheric Sensing Experiment (LASE) ( Browell et al. 1997 ; Ferrare et al. 2016 ), a DIAL system for water vapor mixing ratio profiling. Instrument parameters for all lidars are listed in Table 1 . Values reported indicate what was used in this study; e.g., FP3 DIAL minimum range is technically 225 m but was quality controlled to 450 m. Instrument quality control measures were executed at the direction of the instrument PIs. Quality

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Tammy M. Weckwerth, Kristy J. Weber, David D. Turner, and Scott M. Spuler

contain the most angle-sensitive narrowband filter stage. To minimize angular errors, the wide channel return is used as feedback to align the main channel and produce quality data at low ranges with excellent solar background suppression. The wide channel will have varying day/night performance due to the larger field of view and the lack of one filtering stage, and it is not useful as a daytime data product; therefore, it is used for alignment only and is not used for data analysis. One of the most

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Elizabeth N. Smith, Joshua G. Gebauer, Petra M. Klein, Evgeni Fedorovich, and Jeremy A. Gibbs

vertical profiles of kinematic and thermodynamic variables at several point locations with prescribed frequency (usually on the order of 2–5 min). While the PECAN dataset offers high-quality, extensive spatial and temporal observations of the NLLJ, these observations still cannot provide information beyond these set points. Numerical simulations are not as limited in space and time as observations. Depending on the available computational resources, simulations can provide data on fine temporal and

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Aaron Johnson and Xuguang Wang

wind profiler platforms, and radiosondes, are assimilated every 3 h on a domain approximately covering the continental United States with 12-km grid spacing ( Fig. 1 ). For the outer domain, a 3-h observation window is used with 4D EnKF, which uses first-guess and ensemble covariance values valid at the same time as the observation, which can be different than the analysis time ( Johnson et al. 2015 ). Additional quality control checks are also performed with the GSI part of the system to check for

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Aaron Johnson, Xuguang Wang, Kevin R. Haghi, and David B. Parsons

used by Jones et al. (2016) , except that the minimum assimilated reflectivity is 30 dB Z instead of 10 dB Z , due to the enhanced nonmeteorological echoes in these nocturnal observations. In the future, dual-polarization radar variables should be added to the quality control (QC) process to better remove nonmeteorological reflectivity (e.g., Mueller and Larkin 1985 ). Here, we simply omit the questionable data as described above since we find this method to maintain both the assimilation of

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Matthew D. Flournoy and Michael C. Coniglio

and WSR-88D radars listed in Fig. 8 . All radar data were quality controlled and dealiased using Py-ART software ( Helmus and Collis 2016 ) as well as subjectively using the Earth Observing Laboratory Solo3 software. The reflectivity and Doppler velocity data were then analyzed onto a 6-km grid with a two-pass Barnes scheme ( Barnes 1964 ) using Observation Processing and Wind Synthesis (OPAWS) software before assimilation onto the 3-km grid. Standard errors of 5 dB Z and 2 m s −1 were assumed

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W. G. Blumberg, T. J. Wagner, D. D. Turner, and J. Correia Jr.

AERIoe is to improve the retrieval in locations within the profile where the AERI spectra may lack information and therefore improve the algorithm’s overall estimate of the entire tropospheric thermodynamic profile. When such observations are available, they are linearly interpolated to the AERIoe vertical grid and are treated in the algorithm as having perfect sensitivity (a value of 1) in . 3. Data and methods a. Datasets and quality control To investigate the performance of the AERI in convective

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Samuel K. Degelia, Xuguang Wang, David J. Stensrud, and Aaron Johnson

. 2006 ; Rogers et al. 2009 ). Multiple passes of quality control are performed on the dataset at NCEP, and additional gross error checks occur within GSI. The radar observations (radar reflectivity factor and radial velocity) are NEXRAD level 2 data obtained from the National Centers for Environmental Information (NCEI). The location of the WSR-88Ds that are used can be seen by the circles in Fig. 2a . We note that the KDDC radar in southwestern Kansas was offline until 0115 UTC 25 June. Thus

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