Susceptibility of East Asian Marine Warm Clouds to Aerosols in Winter and Spring from Co-Located A-Train Satellite Observations

We constructed the A-Train co-located aerosol and marine warm cloud data from 2006 to 2010 winter and spring over East Asia and investigated the sensitivities of single-layer warm cloud properties to aerosols under different precipitation statuses and environmental regimes. The near-surface stability (NSS), modulated by cold air on top of a warm surface, and the estimated inversion strength (EIS) controlled by the subsidence are critical environmental parameters affecting the marine warm cloud structure over East Asia and, thus, the aerosols–cloud interactions. Based on our analysis, precipitating clouds revealed higher cloud susceptibility to aerosols as compared to non-precipitating clouds. The cloud liquid water path (LWP) increased with aerosols for precipitating clouds, yet decreased with aerosols for non-precipitating clouds, consistent with previous studies. For precipitating clouds, the cloud LWP and albedo increased more under higher NSS as unstable air promotes more moisture flux from the ocean. Under stronger EIS, the cloud albedo response to aerosols was lower than that under weaker EIS, indicating that stronger subsidence weakens the cloud susceptibility due to more entrainment drying. Our study suggests that the critical environmental factors governing the aerosol–cloud interactions may vary for different oceanic regions, depending on the thermodynamic conditions.

Global estimates of changes in shortwave low-cloud albedo and fluxes due to variations in cloud droplet number concentration derived from CERES-MODIS satellite sensors

15 years of Aqua CERES and MODIS observations are combined to derive nearly global maps of shortwave albedo (A) and flux (F) response to changes in cloud droplet number concentration (N_d ). Absolute ( S a = ∂ A ∂ N d ) and relative ( S r = ∂ A ∂ ln ( N d ) ) albedo susceptibilities are computed seasonally by exploiting the linear relationship between A and ln(N_d ) for shallow liquid clouds. Subtropical stratiform clouds (eastern Pacific, eastern Atlantic, and Australia) yield the highest S_r , followed by the extratropical oceans during their hemispheric summer. When S_r is cast in terms of F, the eastern Pacific clouds dominate S_r , with a secondary maximum offshore eastern Asia. S_a is mainly governed by N_d , with more pristine environments being more susceptible to change their albedo. While both S_a and S_r are advantageous for understanding radiative aspects of the aerosol indirect effect, S_r is more suitable for calculating changes in A and F due to the linear relationship between A and ln(N_d ).

A key process controlling the wet removal of aerosols: new observational evidence

The lifetime and spatial distributions of accumulation-mode aerosols in a size range of approximately 0.05–1 μm, and thus their global and regional climate impacts, are primarily constrained by their removal via cloud and precipitation (wet removal). However, the microphysical process that predominantly controls the removal efficiency remains unidentified because of observational difficulties. Here, we demonstrate that the activation of aerosols to cloud droplets (nucleation scavenging) predominantly controls the wet removal efficiency of accumulation-mode aerosols, using water-insoluble black carbon as an observable particle tracer during the removal process. From simultaneous ground-based observations of black carbon in air (prior to removal) and in rainwater (after removal) in Tokyo, Japan, we found that the wet removal efficiency depends strongly on particle size, and the size dependence can be explained quantitatively by the observed size-dependent cloud-nucleating ability. Furthermore, our observational method provides an estimate of the effective supersaturation of water vapour in precipitating cloud clusters, a key parameter controlling nucleation scavenging. These novel data firmly indicate the importance of quantitative numerical simulations of the nucleation scavenging process to improve the model’s ability to predict the atmospheric aerosol burden and the resultant climate forcings, and enable a new validation of such simulations.