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Xiaoli Zhou Department of Atmospheric and Oceanic Sciences, McGill University, Montreal, Quebec, Canada, and Department of Atmospheric Sciences, University of Washington, Seattle, Washington

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Andrew S. Ackerman NASA Goddard Institute for Space Studies, New York, New York

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Ann M. Fridlind NASA Goddard Institute for Space Studies, New York, New York

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Pavlos Kollias School of Marine and Atmospheric Sciences, Stony Brook University, State University of New York, Stony Brook, and Department of Environmental and Climate Sciences, Brookhaven National Laboratory, Upton, New York

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© 2018 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Xiaoli Zhou, xiaoliz@uw.edu

© 2018 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Xiaoli Zhou, xiaoliz@uw.edu

There were errors in the units for the variance spectra in the legend of Fig. 4 and in the y-axis labels of Figs. 5a, 7, 14b, and 14c in Zhou et al. (2018). These errors did not affect any discussion or conclusions of the study. The corrected figures (Figs. 4, 5, 7, and 14) are shown below.

Fig. 4.
Fig. 4.

Variance spectra of total water mixing ratio at 700 m, LWP, pseudoalbedo, and optical depth for simulation Nd10 at 10 h multiplied by the wavenumber k.

Citation: Journal of the Atmospheric Sciences 75, 11; 10.1175/JAS-D-18-0144.1

Fig. 5.
Fig. 5.

(a) Variance spectra of total water mixing ratio at 700 m at 10 h multiplied by the wavenumber k and (b) temporal evolution of total water mixing ratio variance length scale (defined in Zhou et al. 2018) at 700 m for Nd10, Nd35, and Nd65. Simulations as in Fig. 2 of Zhou et al. (2018).

Citation: Journal of the Atmospheric Sciences 75, 11; 10.1175/JAS-D-18-0144.1

Fig. 7.
Fig. 7.

Variance spectra of total water mixing ratio of (a) Nd10 at different levels at 10 h, (b) Nd10 at 700 m at three times, and (c) Nd65 at 700 m at three times.

Citation: Journal of the Atmospheric Sciences 75, 11; 10.1175/JAS-D-18-0144.1

Fig. 14.
Fig. 14.

(a) Spectral decomposition of the production term in Eq. (1) of Zhou et al. (2018), (b) variance spectra of vertical wind velocity, and (c) variance spectra of total water mixing ratio at altitude 700 m and time 10 h. Setup of simulations as indicated in legend and as described in main text and summarized in Table 1 of Zhou et al. (2018).

Citation: Journal of the Atmospheric Sciences 75, 11; 10.1175/JAS-D-18-0144.1

REFERENCE

Zhou, X., A. S. Ackerman, A. M. Fridlind, and P. Kollias, 2018: Simulation of mesoscale cellular convection in marine stratocumulus. Part I: Drizzling conditions. J. Atmos. Sci., 75, 257–274, https://doi.org/10.1175/JAS-D-17-0070.1.

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  • Zhou, X., A. S. Ackerman, A. M. Fridlind, and P. Kollias, 2018: Simulation of mesoscale cellular convection in marine stratocumulus. Part I: Drizzling conditions. J. Atmos. Sci., 75, 257–274, https://doi.org/10.1175/JAS-D-17-0070.1.

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  • Fig. 4.

    Variance spectra of total water mixing ratio at 700 m, LWP, pseudoalbedo, and optical depth for simulation Nd10 at 10 h multiplied by the wavenumber k.

  • Fig. 5.

    (a) Variance spectra of total water mixing ratio at 700 m at 10 h multiplied by the wavenumber k and (b) temporal evolution of total water mixing ratio variance length scale (defined in Zhou et al. 2018) at 700 m for Nd10, Nd35, and Nd65. Simulations as in Fig. 2 of Zhou et al. (2018).

  • Fig. 7.

    Variance spectra of total water mixing ratio of (a) Nd10 at different levels at 10 h, (b) Nd10 at 700 m at three times, and (c) Nd65 at 700 m at three times.

  • Fig. 14.

    (a) Spectral decomposition of the production term in Eq. (1) of Zhou et al. (2018), (b) variance spectra of vertical wind velocity, and (c) variance spectra of total water mixing ratio at altitude 700 m and time 10 h. Setup of simulations as indicated in legend and as described in main text and summarized in Table 1 of Zhou et al. (2018).

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