The cloudy atmospheric boundary layer is a complex, open, dynamical system that is difficult to fully characterize through observations. Aircraft measurements provide cloud dynamical, thermodynamical, and microphysical properties along a flightpath, at high spatial/temporal resolution (order 10 m/0.1 s). These data are essentially contiguous "snapshots"in time of the state of the cloud and its environment. Polar-orbiting satellite-based remote sensing yields snapshots of retrieved cloud and aerosol properties once or twice a day at spatial scales on the order of 250 m, but these are usually averaged to scales of ≈20-100 km to reduce data variability. Neither approach tracks a parcel of air in time, a view that would yield more direct insights into the evolving system. Nevertheless, our long experience with aircraft and satellite-based remote sensing has taught us much about atmospheric processes, suggesting that one can gain insights into processes from these snapshots. Using mostly previously published work we present examples of collections of observation snapshots that reveal various degrees of process-level understanding. We couch the discussion in terms of the concepts of space-Time exchange, ergodicity, and process vs. observation timescales. It is our hope that this paper will encourage the atmospheric sciences community to explore the value of these concepts more deeply.

Marine cloud brightening (MCB) is the deliberate injection of aerosol particles into shallow marine clouds to increase their reflection of solar radiation and reduce the amount of energy absorbed by the climate system. From the physical science perspective, the consensus of a broad international group of scientists is that the viability of MCB will ultimately depend on whether observations and models can robustly assess the scale-up of local-to-global brightening in today's climate and identify strategies that will ensure an equitable geographical distribution of the benefits and risks associated with projected regional changes in temperature and precipitation. To address the physical science knowledge gaps required to assess the societal implications of MCB, we propose a substantial and targeted program of research-field and laboratory experiments, monitoring, and numerical modeling across a range of scales.

Aerosol-cloud interactions (ACIs) are considered to be the most uncertain driver of present-day radiative forcing due to human activities. The nonlinearity of cloud-state changes to aerosol perturbations make it challenging to attribute causality in observed relationships of aerosol radiative forcing. Using correlations to infer causality can be challenging when meteorological variability also drives both aerosol and cloud changes independently. Natural and anthropogenic aerosol perturbations from well-defined sources provide "opportunistic experiments"(also known as natural experiments) to investigate ACI in cases where causality may be more confidently inferred. These perturbations cover a wide range of locations and spatiotemporal scales, including point sources such as volcanic eruptions or industrial sources, plumes from biomass burning or forest fires, and tracks from individual ships or shipping corridors. We review the different experimental conditions and conduct a synthesis of the available satellite datasets and field campaigns to place these opportunistic experiments on a common footing, facilitating new insights and a clearer understanding of key uncertainties in aerosol radiative forcing. Cloud albedo perturbations are strongly sensitive to background meteorological conditions. Strong liquid water path increases due to aerosol perturbations are largely ruled out by averaging across experiments. Opportunistic experiments have significantly improved process-level understanding of ACI, but it remains unclear how reliably the relationships found can be scaled to the global level, thus demonstrating a need for deeper investigation in order to improve assessments of aerosol radiative forcing and climate change.

The aerosol impact on liquid water path (LWP) is a key uncertainty in the overall climate impact of aerosol. However, despite a significant effort in this area, the size of the effect remains poorly constrained, and even the sign is unclear. Recent studies have shown that the relationship between droplet number concentration (Nd) and LWP is an unreliable measure of the impact of Nd variations on LWP due to the difficulty in establishing causality. In this work, we use satellite observations of the short-term development of clouds to examine the role of Nd perturbations in LWP variations. Similar to previous studies, an increase followed by a general decrease in LWP with increasing Nd is observed, suggesting an overall negative LWP response to Nd and a warming LWP adjustment to aerosol. However, the Nd also responds to the local environment, with aerosol production, entrainment from the free troposphere and wet scavenging all acting to modify the Nd. Many of these effects act to further steepen the Nd-LWP relationship and obscure the causal Nd impact on LWP. Using the temporal development of clouds to account for these feedbacks in the Nd-LWP system, a weaker negative Nd-LWP relationship is observed over most of the globe. This relationship is highly sensitive to the initial cloud state, illuminating the roles of different processes in shaping the Nd-LWP relationship. The nature of the current observing system limits this work to a single time period for observations, highlighting the need for more frequent observations of key cloud properties to constrain cloud behaviour at process timescales.

The effect of anthropogenic aerosol on the reflectivity of stratocumulus cloud decks through changes in cloud amount is a major uncertainty in climate projections. In frequently occurring nonprecipitating stratocumulus, cloud amount can decrease through aerosol-enhanced cloud-top mixing. The climatological relevance of this effect is debated because ship exhaust only marginally reduces stratocumulus amount. By comparing detailed numerical simulations with satellite analyses, we show that ship-track studies cannot be generalized to estimate the climatological forcing of anthropogenic aerosol. The ship track-derived sensitivity of the radiative effect of nonprecipitating stratocumulus to aerosol overestimates their cooling effect by up to 200%. The offsetting warming effect of decreasing stratocumulus amount needs to be taken into account if we are to constrain the cloud-mediated radiative forcing of anthropogenic aerosol.

Predator–prey dynamics have been suggested as simplified models of stratocumulus clouds, with rain acting as a predator of the clouds. We describe a mathematical and computational framework for estimating the parameters of a simplified model from a large eddy simulation (LES). In our method, we extract cycles of cloud growth and decay from the LES and then search for parameters of the simplified model that lead to similar cycles. We implement our method via Markov chain Monte Carlo. Required error models are constructed based on variations of the LES cloud cycles. This computational framework allows us to test the robustness of our overall approach and various assumptions, which is essential for the simplified model to be useful. Our main conclusion is that it is indeed possible to calibrate a predator–prey model so that it becomes a reliable, robust, but simplified representation of selected aspects of a LES. In the future, such models may then be used as a quantitative tool for investigating important questions in cloud microphysics.