Vertical dependence of horizontal variation of cloud microphysics: observations from the ACE-ENA field campaign and implications for warm-rain simulation in climate models

• Main Authors: Z. Zhang, Q. Song, D. B. Mechem, V. E. Larson, J. Wang, Y. Liu, M. K. Witte, X. Dong, P. Wu
• Format: Article
• Language: English
• Published: Copernicus Publications 2021-03-01
• Series: Atmospheric Chemistry and Physics
• Online Access: https://acp.copernicus.org/articles/21/3103/2021/acp-21-3103-2021.pdf
• ISSN: 1680-7316; 1680-7324

<p>In the current global climate models (GCMs), the nonlinearity effect of subgrid cloud variations on the parameterization of warm-rain process, e.g., the autoconversion rate, is often treated by multiplying the resolved-scale warm-rain process rates by a so-called enhancement factor (EF). In this study, we investigate the subgrid-scale horizontal variations and covariation of cloud water content (<span class="inline-formula"><i>q</i>_c</span>) and cloud droplet number concentration (<span class="inline-formula"><i>N</i>_c</span>) in marine boundary layer (MBL) clouds based on the in situ measurements from a recent field campaign and study the implications for the autoconversion rate EF in GCMs. Based on a few carefully selected cases from the field campaign, we found that in contrast to the enhancing effect of <span class="inline-formula"><i>q</i>_c</span> and <span class="inline-formula"><i>N</i>_c</span> variations that tends to make EF <span class="inline-formula">&gt;</span> 1, the strong positive correlation between <span class="inline-formula"><i>q</i>_c</span> and <span class="inline-formula"><i>N</i>_c</span> results in a suppressing effect that tends to make EF <span class="inline-formula">&lt;</span> 1. This effect is especially strong at cloud top, where the <span class="inline-formula"><i>q</i>_c</span> and <span class="inline-formula"><i>N</i>_c</span> correlation can be as high as 0.95. We also found that the physically complete EF that accounts for the covariation of <span class="inline-formula"><i>q</i>_c</span> and <span class="inline-formula"><i>N</i>_c</span> is significantly smaller than its counterpart that accounts only for the subgrid variation of <span class="inline-formula"><i>q</i>_c</span>, especially at cloud top. Although this study is based on limited cases, it suggests that the subgrid variations of <span class="inline-formula"><i>N</i>_c</span> and its correlation with <span class="inline-formula"><i>q</i>_c</span> both need to be considered for an accurate simulation of the autoconversion process in GCMs.</p>