Journal Article
Atmospheric Chemistry and Physics, vol. 21, iss. 4, pp. 3103-3121, 2021
Authors
Zhibo Zhang, Qianqian Song, David B. Mechem, Vincent E. Larson, Jian Wang, Yangang Liu, Mikael K. Witte, Xiquan Dong, Peng Wu
Abstract
Abstract. 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 (qc) and cloud droplet number
concentration (Nc) 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 qc and Nc variations that tends to make EF > 1, the strong positive correlation between qc and Nc results in a
suppressing effect that tends to make EF < 1. This effect is
especially strong at cloud top, where the qc and Nc correlation can
be as high as 0.95. We also found that the physically complete EF that
accounts for the covariation of qc and Nc is significantly smaller
than its counterpart that accounts only for the subgrid variation of
qc, especially at cloud top. Although this study is based on limited
cases, it suggests that the subgrid variations of Nc and its
correlation with qc both need to be considered for an accurate
simulation of the autoconversion process in GCMs.
