A key uncertainty in Aerosol-cloud interactions is the cloud liquid water path (LWP) response to increased aerosols (λ). LWP can either increase due to precipitation suppression or decrease due to entrainment-drying. Previous research suggests that precipitation suppression dominates in thick clouds, while entrainment-drying prevails in thin clouds. The time scales of the two competing effects are vastly different, requiring temporally resolved observations. We analyze 3-day Lagrangian trajectories of stratocumulus clouds over the southeast Pacific using geostationary data. We find that clouds with a LWP exceeding 200 g m-2 exhibit a positive response, while clouds with lower LWP show a negative response. We observe a significant diurnal cycle in λ, indicating a more strongly negative daytime adjustment driven by entrainment-drying. In contrast, at night, precipitation suppression can occasionally fully counteract the entrainment-drying mechanism. The time-integrated adjustment appears weaker than previously suggested in studies that do not account for the diurnal cycle.

Low marine clouds are a major source of uncertainty in cloud feedbacks across climate models and in forcing by aerosol-cloud interactions. The evolution of these clouds and their response to aerosol are sensitive to the ambient environmental conditions, so it is important to be able to determine different responses over a representative set of conditions. Here, we propose a novel approach to encompassing the broad range of conditions present in low marine cloud regions, by building a library of observed environmental conditions. This approach can be used, for example, to more systematically test the fidelity of Large Eddy Simulations (LES) in representing these clouds. ERA5 reanalysis and various satellite observations are used to extract and derive macrophysical and microphysical cloud-controlling variables (CCVs) such as SST, estimated inversion strength (EIS), subsidence, and cloud droplet number concentrations. A few locations in the stratocumulus (Sc) deck region of the Northeast Pacific during summer are selected to fill out a phase space of CCVs. Thereafter, Principal Component Analysis (PCA) is applied to reduce the dimensionality and to select a reduced set of components that explain most of the variability among CCVs in order to efficiently select cases for LES simulations that encompass the observed CCV phase space. From this phase space, 75-100 cases with distinct environmental conditions will be selected and used to initialize 2-day LES modeling to provide a spectrum of aerosol-cloud interactions and Sc-to-Cumulus transition under observed ambient conditions. Such a large number of simulations will help create statistics to assess how well the LES can simulate the cloud lifecycle when constrained by the ‘best estimate’ of the environmental conditions, and how sensitive the modeled clouds are to changes in these driving fields.

A convolutional neural network was used to detect occurrences of pockets of open cells (POCs). Trained on a small hand-logged dataset and applied to 13 years of satellite imagery the neural network is able to classify 8,491 POCs. This extensive database allows the first robust analysis of the spatial and temporal prevalence of these phenomena, as well as a detailed analysis of their micro-physical properties. We find a large (30%) increase in cloud effective radius inside POCs as compared to their surroundings and similarly large (20%) decrease in cloud fraction. This also allows their global radiative effect to be determined. Using simple radiative approximations we find that the instantaneous global mean top-of-atmosphere perturbation by all POCs is only 0.01Wm-2.

Four previously identified patterns of meso-scale cloud organization in the trades -- called Sugar, Gravel, Flowers and Fish -- are studied using long-term records of ground-based measurements, satellite observations and reanalyses. A neural network trained to detect these patterns is applied to satellite imagery to identify periods during which a particular pattern is over the Barbados Cloud Observatory. Surface based remote sensing at the observatory is composited and shows that the patterns can be distinguished by differences in cloud macro-physical structures. Variations in total cloudiness among the patterns are dominated by variations in cloud-top cloudiness. Cloud amount near cloud base varies little. Each pattern is associated with a distinct atmospheric environment whose characteristics are traced back to origins that are not solely within the trades. Sugar air-masses are characterized by weak winds and of tropical origin. Fish are driven by convergence lines originating from synoptical disturbances. Gravel and Flowers are most native to the trades, but distinguish themselves with slightly stronger winds and stronger subsidence in the first case and greater stability in the latter. These results suggest that due to the tight bound of the patterns to wind and air-mass origin, the patterns with the higher cloud fraction, Flowers and Fish, will be disfavoured in a warming climate with more equable sea-surface temperatures and fewer mid-latitudinal disturbances.

Marine boundary layer clouds tend to organize into closed or open mesoscale cellular convection (MCC). Here, two-dimensional wavelet analysis is applied for the first time to passive microwave retrievals of cloud water path (CWP), water vapor path (WVP), and rain rate from AMSR-E in 2008 over the Northeast and Southeast Pacific, and the Southeast Atlantic subtropical stratocumulus to cumulus transition regions. The (co-)variability between CWP, WVP, and rain rate in 160x160 km2 analysis boxes is partitioned between four mesoscale wavelength octaves (20, 40, 80, and 160 km). The cell scale is identified as the wavelength of the peak CWP variance. Together with a machine-learning classification of cell type, this allows the statistical characteristics of open and closed MCC of various scales, and its relation to WVP, rain rate and potential environmental controlling factors to be analyzed across a very large set of cases. The results show that the cell wavelength is most commonly 40-80 km. Cell-scale CWP perturbations are good predictors of the WVP and rain rate perturbations. A universal cubic dependence of rain rate on CWP is found in closed and open cells of all scales. This suggests that aerosol control on precipitation susceptibility is not as important for open cell formation as are processes that cause increases in cloud water. For cells larger than 20 km, there is no obvious dependence of cell scale on the environmental controlling factors tested, suggesting that the cell scale may depend more on its historical evolution than the current environmental conditions.

The influence of aerosol particles on cloud reflectivity remains one of the largest sources of uncertainty in our understanding anthropogenic climate change. Commercial shipping constitutes a large and concentrated aerosol perturbation in a meteorological regime where clouds have a disproportionally large effect on climate. Yet, to date, studies have been unable to detect climatologically-relevant cloud radiative effects from shipping, despite models indicating that the cloud response should produce a sizable negative radiative forcing (perturbation to Earth’s energy balance). We attribute a significant increase in cloud reflectivity to enhanced cloud droplet number concentrations within a major shipping corridor in the southeast Atlantic. Prevailing winds constrain emissions around the corridor, which cuts through a climatically-important region of expansive low-cloud cover. We use universal kriging, a classic geostatistical method, to estimate what cloud properties would have been in the absence of shipping. In the morning, cloud brightening is consistent with changes in microphysics alone, whereas in the afternoon, increases in cloud brightness from microphysical changes are offset by decreases in the total amount of cloud water. We find a radiative forcing in the southeast Atlantic shipping corridor two orders of magnitude greater than previous observational estimates. Approximately five years of data are required to identify a clear signal. Extrapolating our results globally, we calculate an effective radiative forcing due to aerosol-cloud interactions in low clouds of -0.62 W/m2 (-1.23 to -0.08 W/m2). The unique setup in the southeast Atlantic could be an ideal test for the representation of aerosol-cloud interactions in climate models.