This study investigates droplet size distribution (DSD) characteristics from condensational growth and transport in Eulerian dynamical models with bin microphysics. A hierarchy of modeling frameworks is utilized, including parcel, one-dimensional (1D), and three-dimensional large-eddy simulation (LES). The bin DSDs from the 1D model, which includes only vertical advection and condensational growth, are nearly as broad as those from the LES and in line with observed DSD widths for stratocumulus clouds. These DSDs are much broader than those from Lagrangian microphysical calculations within a parcel framework that serve as a numerical benchmark for the 1D tests. In contrast, the bin-modeled DSDs are similar to the Lagrangian microphysical benchmark for a rising parcel in which Eulerian transport is not considered. These results indicate that numerical diffusion associated with vertical advection is a key contributor to broadening DSDs in the 1D model and LES. This DSD broadening from vertical numerical diffusion is unphysical, in contrast to the physical mixing processes that previous studies have indicated broaden DSDs in real clouds. It is proposed that artificial DSD broadening from vertical numerical diffusion compensates for underrepresented horizontal variability and mixing of different droplet populations in typical LES configurations with bin microphysics, or the neglect of other mechanisms that broaden DSDs such as growth of giant cloud condensation nuclei. These results call into question the ability of Eulerian dynamical models with bin microphysics to investigate the physical mechanisms for DSD broadening, even though they may reasonably simulate overall DSD characteristics.

Satellite retrievals of cloud effective radius r e are frequently validated using aircraft in situ measurements. Past intercomparisons have found a significant bias toward larger remotely sensed r e . Explanations for this bias have focused on retrieval algorithms and large-scale heterogeneity, with in situ measurement uncertainty regarded as a minor factor. We compare Moderate Resolution Imaging Spectroradiometer r e with in situ observations of marine stratocumulus clouds from three aircraft campaigns using a phase Doppler interferometer probe. Retrieved and in situ r e typically agree within uncertainty in both nonprecipitating and drizzling conditions with no apparent systematic bias (mean bias of −0.22 μm, mean relative bias 3%). Agreement depends on the choice of in situ probe as well as microphysical context. We demonstrate that probes must adequately characterize the width of the drop size distribution to avoid systematic underestimation of r e .Plain Language Summary Satellite measurements provide the only global-scale picture of cloud properties and are widely used in the research community. Since the first comparisons of satellite and aircraft measurements of characteristic cloud drop size, significant disagreement between the two has been found. Past studies assumed that disagreement is because of faults in how the satellite observations are handled as opposed to issues with the aircraft measurements. In this study we show that which aircraft instrument is chosen for comparison with satellite measurements can affect whether satellite and aircraft measurements agree and that an appropriate choice of aircraft instrument leads to robust agreement between satellite and aircraft measurements. Using a database of over 200,000 aircraft measurements in cloud, we show why some aircraft instruments are unable to accurately measure cloud properties in certain meteorological settings.

Abstract. Cumulus clouds exhibit a life cycle that consists of (a) the growth phase (increasing size, most notably in the vertical direction); (b) the mature phase (growth ceases; any precipitation that develops is strongest during this period); and (c) the dissipation phase (cloud dissipates because of precipitation and/or entrainment; no more dynamical support). Although radar can track clouds over time and give some sense of the age of a cloud, most aircraft in situ measurements lack temporal context. We use large eddy simulations of trade wind cumulus cloud fields from cases during the Barbados Oceanographic and Meteorological Experiment (BOMEX) and Rain In Cumulus over the Ocean (RICO) campaigns to demonstrate a potential cumulus cloud "clock." We find that the volume-averaged total water mixing ratio r t is a useful cloud clock for the 12 clouds studied. A cloud's initial r t is set by the subcloud mixed-layer mean r t and decreases monotonically from the initial value due primarily to entrainment. The clock is insensitive to aerosol loading, environmental sounding and extrinsic cloud properties such as lifetime and volume. In some cases (more commonly for larger clouds), multiple pulses of buoyancy occur, which complicate the cumulus clock by replenishing r t . The clock is most effectively used to classify clouds by life phase.

Abstract. In the current global climate models (GCM), 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 ran 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 makes tends to make EF