CORRIGENDUM

Xingchao Chen aDepartment of Meteorology and Atmospheric Science, The Pennsylvania State University, University Park, Pennsylvania
bCenter for Advanced Data Assimilation and Predictability Techniques, The Pennsylvania State University, University Park, Pennsylvania

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Kun Zhao cKey Laboratory for Mesoscale Severe Weather, Ministry of Education, Nanjing University, Nanjing, China
dSchool of Atmospheric Science, Nanjing University, Nanjing, China

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https://orcid.org/0000-0002-6022-6226
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© 2024 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Kun Zhao, zhaokun@nju.edu.cn

© 2024 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Kun Zhao, zhaokun@nju.edu.cn

Because of a production error, the figure published as Fig. 7 in Chen et al. (2017) is actually identical to Fig. 8 and is therefore incorrect. The correct Fig. 7 is provided herein.

Fig. 7.
Fig. 7.

(a) Cross section of mean wind vectors (streamlines) and onshore wind (color shadings); cross sections of perturbation wind vectors (streamlines) and onshore wind (color shadings) at (b) 0000, (c) 0300, (d) 0600, (e) 0900, (f) 1200, (g) 1500, (h) 1800, and (i) 2100 LST from the HiWind100 experiment. All cross sections are along the long axis of the blue box in Fig. 1 and averaged along the short axis of this box. The highest topographic profilers along the long axis of the blue box in Fig. 1 are shown by the black shading. Positive perturbation temperature is shown by the solid red contours (that start from +1 K and have a 0.5-K interval), and negative ones are shown by the solid blue contours (that start from −1 K and have a −0.5-K interval).

Citation: Journal of the Atmospheric Sciences 81, 2; 10.1175/JAS-D-23-0219.1

The staff of the Journal of the Atmospheric Sciences regrets any inconvenience this error may have caused.

REFERENCE

Chen, X., F. Zhang, and K. Zhao, 2017: Influence of monsoonal wind speed and moisture content on intensity and diurnal variations of the mei-yu season coastal rainfall over South China. J. Atmos. Sci., 74, 28352856, https://doi.org/10.1175/JAS-D-17-0081.1.

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  • Chen, X., F. Zhang, and K. Zhao, 2017: Influence of monsoonal wind speed and moisture content on intensity and diurnal variations of the mei-yu season coastal rainfall over South China. J. Atmos. Sci., 74, 28352856, https://doi.org/10.1175/JAS-D-17-0081.1.

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  • Fig. 7.

    (a) Cross section of mean wind vectors (streamlines) and onshore wind (color shadings); cross sections of perturbation wind vectors (streamlines) and onshore wind (color shadings) at (b) 0000, (c) 0300, (d) 0600, (e) 0900, (f) 1200, (g) 1500, (h) 1800, and (i) 2100 LST from the HiWind100 experiment. All cross sections are along the long axis of the blue box in Fig. 1 and averaged along the short axis of this box. The highest topographic profilers along the long axis of the blue box in Fig. 1 are shown by the black shading. Positive perturbation temperature is shown by the solid red contours (that start from +1 K and have a 0.5-K interval), and negative ones are shown by the solid blue contours (that start from −1 K and have a −0.5-K interval).

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