Reflections on cloud effects: How much impact does the abundance of cloud condensation nuclei (CCN) aerosols above the oceans have on global temperatures? Rosenfeld et al. analyzed how CCN affect the properties of marine stratocumulus clouds, which reflect much of the solar radiation received by Earth back to space (see the Perspective by Sato and Suzuki). The CCN abundance explained most of the variability in the radiative cooling. Thus, the magnitude of radiative forcing provided by these clouds is much more sensitive to the presence of CCN than current models indicate, which suggests the existence of other compensating warming effects. Science , this issue p. eaav0566 ; see also p. 580

The relationship between aerosol optical depth (AOD) and PM_2.5 is often investigated in order to obtain surface PM_2.5 from satellite observation of AOD with a broad area coverage. However, various factors could affect the AOD–PM_2.5 regressions. Using both ground and satellite observations in Beijing from 2011 to 2015, this study analyzes the influential factors including the aerosol type, relative humidity (RH), planetary boundary layer height (PBLH), wind speed and direction, and the vertical structure of aerosol distribution. The ratio of PM_2.5 to AOD, which is defined as η, and the square of their correlation coefficient (R²) have been examined. It shows that η varies from 54.32 to 183.14, 87.32 to 104.79, 95.13 to 163.52, and 1.23 to 235.08 µg m⁻³ with aerosol type in spring, summer, fall, and winter, respectively. η is smaller for scattering-dominant aerosols than for absorbing-dominant aerosols, and smaller for coarse-mode aerosols than for fine-mode aerosols. Both RH and PBLH affect the η value significantly. The higher the RH, the smaller the η, and the higher the PBLH, the smaller the η. For AOD and PM_2.5 data with the correction of RH and PBLH compared to those without, R² of monthly averaged PM_2.5 and AOD at 14:00 LT increases from 0.63 to 0.76, and R² of multi-year averaged PM_2.5 and AOD by time of day increases from 0.01 to 0.93, 0.24 to 0.84, 0.85 to 0.91, and 0.84 to 0.93 in four seasons respectively. Wind direction is a key factor for the transport and spatial–temporal distribution of aerosols originated from different sources with distinctive physicochemical characteristics. Similar to the variation in AOD and PM_2.5, η also decreases with the increasing surface wind speed, indicating that the contribution of surface PM_2.5 concentrations to AOD decreases with surface wind speed. The vertical structure of aerosol exhibits a remarkable change with seasons, with most particles concentrated within about 500 m in summer and within 150 m in winter. Compared to the AOD of the whole atmosphere, AOD below 500 m has a better correlation with PM_2.5, for which R² is 0.77. This study suggests that all the above influential factors should be considered when we investigate the AOD–PM_2.5 relationships.

[1] Heavy aerosol loads have been observed to suppress warm rain by reducing cloud drop size and slowing drop coalescence. The ice forming nuclei (IFN) activity of the same aerosols glaciate the clouds and create ice precipitation instead of the suppressed warm rain. Satellite observations show that desert dust and heavy air pollution over East Asia have similar ability to glaciate the tops of growing convective clouds at glaciation temperature of Tg < ∼ −20°C, whereas similarly heavy smoke from forest fires in Siberia without dust or industrial pollution glaciated clouds at Tg ≤ −33°C. The observation that both smoke and air pollution have same effect on reducing cloud drop size implies that the difference in Tg is due to the IFN activity. This dependence of Tg on aerosol types appears only for clouds with r_e‐5 < 12 μm (r_e‐5 is the cloud drop effective radius at the −5°C isotherm, above which ice rarely forms in cloud tops). For the rest of the clouds the glaciation temperature increases strongly with r_e‐5 with little relation to the aerosol types, reaching Tg> ∼ −15°C for the largest r_e‐5, which are typical to marine clouds in pristine atmosphere.

In this study, we show how to obtain more reliable satellite‐retrieved cloud drop number concentrations (N_d) from Moderate Resolution Imaging Spectroradiometer (MODIS) standard cloud products. N_d is important as a fundamental cloud property that determines cloud albedo, precipitation‐forming processes, cloud longevity, and fractional cover, all of which determine cloud radiative effects. N_d is determined by cloud base aerosols and updrafts. Satellite retrievals of N_d for marine stratocumulus clouds are performed based on the assumption of a nearly adiabatic cloud column. The retrievals, however, are fraught with problems that cause large biases (e.g., the retrieved N_d for partially filled cloudy pixels are less than one third of the retrieved N_d for the convective cores) and limit the usefulness of N_d, especially in broken cloud fields. The N_d of the brightest 10% of cloudy pixels are selected because the brightest clouds are the convective cores that most closely follow adiabatic parcels, a key assumption of our retrieval. It is shown that this criterion is representative of pixels that are also fully surrounded by cloudy pixels (N_d agreement within 5%).

Fine aerosols, by acting as cloud condensation nuclei, suppress rainfall and enhance the albedo and coverage of marine warm clouds, thereby partly counteracting the greenhouse-induced warming. While this is relatively well documented, the co-existing opposite effects of giant cloud condensation nuclei from coarse sea spray aerosols are poorly quantified. Here, satellite measurements show that the effects of coarse sea spray aerosols have comparable magnitudes with opposite sign to those of fine aerosols. For fixed cloud liquid water path and coarse sea spray aerosols, increasing fine aerosols decreased rainfall flux and cloud drop effective radius by a factor of 1/4 and 40%, respectively. Conversely, for fixed fine aerosols and cloud liquid water path, added coarse sea spray aerosols enhanced rainfall flux and cloud drop effective radius by a factor of 4 and 35%, respectively. These large and contrasting effects are independent on meteorological conditions. These processes must be fully incorporated into climate models to faithfully represent aerosol effects on clouds, precipitation, and radiative forcing.

Operational cloud seeding has been implemented to alleviate local precipitation shortages in China for over half a century. Here, we present quantitative evidence for the effect of AgI seeding on supercooled layer clouds with a top cloud temperature of −15°C in China, as documented for the first time by a combination of radar, satellite, and disdrometer observations. A radar signature appeared 18 min after seeding, shortly followed by a visible glaciated seeding track. The seeding signature expanded horizontally at a rate of ∼1.4 and ∼0.3 m s⁻¹ before and after 04:25 UTC. The radar signature descended to the surface 40 min after seeding. A disdrometer captured the precipitation of the first seeded raindrops that reached maximum diameter of 2.75 mm compared to the maximum diameter of 1 mm of the light background rain. The enhanced surface rainfall was observed within the subsequent 100 min. A conceptual model for the formation and expansion of the seeding track is presented. Although the precipitation was light, it is a promising step toward the goal of quantifying the impact of cloud seeding in China.