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. In the current global climate models (GCMs), the nonlinearity effect ofsubgrid cloud variations on the parameterization of warm-rain process, e.g.,the autoconversion rate, is often treated by multiplying the resolved-scalewarm-rain process rates by a so-called enhancement factor (EF). In thisstudy, we investigate the subgrid-scale horizontal variations andcovariation of cloud water content (qc) and cloud droplet numberconcentration (Nc) in marine boundary layer (MBL) clouds based on thein situ measurements from a recent field campaign and study the implicationsfor the autoconversion rate EF in GCMs. Based on a few carefully selectedcases from the field campaign, we found that in contrast to the enhancingeffect of qc and Nc variations that tends to make EF &gt; 1, the strong positive correlation between qc and Nc results in asuppressing effect that tends to make EF &lt; 1. This effect isespecially strong at cloud top, where the qc and Nc correlation canbe as high as 0.95. We also found that the physically complete EF thataccounts for the covariation of qc and Nc is significantly smallerthan its counterpart that accounts only for the subgrid variation ofqc, especially at cloud top. Although this study is based on limitedcases, it suggests that the subgrid variations of Nc and itscorrelation with qc both need to be considered for an accuratesimulation of the autoconversion process in GCMs.

atmospheric chemistry and physics

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