We present for the first time within the cloud physics context, the application of wavelet phase coherence analysis to disentangle counteracting physical processes associated with the lead-lag phase difference between liquid water path (LWP) and cloud droplet number concentration (Nd) in an Eulerian framework using satellite-based observations and climate model outputs. This approach allows us to identify the causality and typical adjustment timescales governing the correlation between LWP and Nd. Satellite observations indicate a more prevalent positive correlation between daytime LWP and Nd regardless of whether LWP leads or lags Nd. The positive cloud water response, associated with precipitation processes, typically occurs within 1 hour, while the negative response resulting from entrainment drying, usually takes 2-4 hours. CAM6 displays excessively rapid negative responses along with overly strong negative cloud water response and insufficient positive response, leading to a more negative correlation between LWP and Nd compared to observations.

Process modeling of aerosol-cloud interaction is essential to bridging gaps between observational analysis and climate modeling of aerosol effects in the Earth system and eventually reducing climate projection uncertainties. In this study, we examine aerosol-cloud interaction in summertime precipitating shallow cumuli observed during the Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE). Aerosols and precipitating shallow cumuli were extensively observed with in-situ and remote-sensing instruments during two research flight cases on 02 June and 07 June, respectively, during the ACTIVATE summer 2021 deployment phase. We perform observational analysis and large-eddy simulation (LES) of aerosol effect on precipitating cumulus in these two cases. Given the measured aerosol size distributions and meteorological conditions, LES is able to reproduce the observed cloud properties by aircraft such as liquid water content (LWC), cloud droplet number concentration (Nc) and effective radius reff. However, it produces smaller liquid water path (LWP) and larger Nc compared to the satellite retrievals. Both 02 and 07 June cases are over warm waters of the Gulf Stream and have a cloud top height over 3 km, but the 07 June case is more polluted and has larger LWC. We find that the aerosol-induced LWP adjustment is dominated by precipitation and is anticorrelated with cloud-top entrainment for both cases. A negative cloud fraction adjustment due to an increase of aerosol number concentration is also shown in the simulations.

Aerosol-cloud interactions are the most uncertain component of the Earth system, due to their major influence on cloud properties, and as a result, Earth’s energy budget. We need to better characterize these interactions, which requires constraining the cloud condensation nuclei (CCN) budget and disentangling the influences of aerosol microphysics from meteorology. Observational data are essential for evaluating and improving climate models, but airborne field campaigns have, until recently, been limited to a few (mostly continental) regions worldwide. CCN measurements over the remote ocean are scarce and only occur during extensive field missions involving airborne or ship-based measurements of limited spatial and temporal extent. Polar-orbiting satellite observations hold great promise for expanding the spatial coverage of observations to remote regions, however, it is currently not well understood to what extent these active and passive remote sensing observations can be considered adequate proxies for CCN. Recent literature make use of column integrated retrievals, such as aerosol optical depth or aerosol index, to characterize aerosol concentration and CCN, and the utility of vertically resolved optical properties from active sensors is only now becoming more fully understood. The NASA ACTIVATE, NAAMES, CAMP2EX and ORACLES field campaigns are particularly well suited for evaluating the skill of advanced satellite aerosol and cloud microphysical retrievals, given the comprehensive suite of airborne aerosol, cloud, and trace gas measurements, combined with airborne High Spectral Resolution Lidar (HSRL) and polarimetric imaging instruments that will be the basis for the next generation of space-based remote sensors. Here, we characterize the properties of aerosol and CCN from these NASA field campaigns and critically assess methods for deriving CCN and CCN proxies using visible and infrared satellite remote sensing retrievals.

The warm Gulf Stream sea surface temperatures (SSTs) strongly impact the evolution of winter clouds behind atmospheric cold fronts. Such cloud evolution remains challenging to model. The Gulf Stream is too wide within the ERA5 and MERRA2 reanalyses, affecting the turbulent surface fluxes. Known problems within the ERA5 boundary layer (too-dry and too-cool with too strong westerlies), ascertained primarily from ACTIVATE 2020 campaign aircraft dropsondes and secondarily from older buoy measurements, reinforce surface flux biases. In contrast, MERRA2 winter surface winds and air-sea temperature/humidity differences are slightly too weak, producing surface fluxes that are too low. Reanalyses boundary layer heights in the strongly-forced winter cold-air-outbreak regime are realistic, whereas late-summer quiescent stable boundary layers are too shallow. Nevertheless, the reanalysis biases are small, and reanalyses adequately support their use for initializing higher-resolution cloud process modeling studies of cold-air outbreaks.