Deposition of mineral dust into ocean fertilizes ecosystems and influences biogeochemical cycles and climate. In situ observations of dust deposition are scarce, and model simulations depend on the highly parameterized representations of dust processes with few constraints. By taking advantage of satellites' routine sampling on global and decadal scales, we estimate African dust deposition flux and loss frequency (a ratio of deposition flux to mass loading) along the trans‐Atlantic transit using the three‐dimensional distributions of aerosol retrieved by spaceborne lidar (Cloud‐Aerosol Lidar with Orthogonal Polarization [CALIOP]) and radiometers (Moderate Resolution Imaging Spectroradiometer [MODIS], Multiangle Imaging Spectroradiometer [MISR], and Infrared Atmospheric Sounding Interferometer [IASI]). On the basis of a 10‐year (2007‐2016) and basin‐scale average, the amount of dust deposition into the tropical Atlantic Ocean is estimated at 136‐222 Tg/year. The 65‐83% of satellite‐based estimates agree with the in situ climatology within a factor of 2. The magnitudes of dust deposition are highest in boreal summer and lowest in fall, whereas the interannual variability as measured by the normalized standard deviation with mean is largest in spring (28‐41%) and smallest (7‐15%) in summer. The dust deposition displays high spatial heterogeneity, revealing that the meridional shifts of major dust deposition belts are modulated by the seasonal migration of the intertropical convergence zone. On the basis of the annual and basin mean, the dust loss frequency derived from the satellite observations ranges from 0.078 to 0.100 day‐1, which is lower than model simulations by up to factors of 2 to 5. The most efficient loss of dust occurs in winter, consistent with the higher possibility of low‐altitude transported dust in southern trajectories being intercepted by rainfall associated with the intertropical convergence zone. The satellite‐based estimates of dust deposition can be used to fill the geographical gaps and extend time span of in situ measurements, study the dust‐ocean interactions, and evaluate model simulations of dust processes.

Abstract. One of the challenges in representing warm rain processes in global climate models (GCMs) is related to the representation of the subgrid variability of cloud properties, such as cloud water and cloud droplet number concentration (CDNC), and the effect thereof on individual precipitation processes such as autoconversion. This effect is conventionally treated by multiplying the resolved-scale warm rain process rates by an enhancement factor (Eq) which is derived from integrating over an assumed subgrid cloud water distribution. The assumed subgrid cloud distribution remains highly uncertain. In this study, we derive the subgrid variations of liquid-phase cloud properties over the tropical ocean using the satellite remote sensing products from Moderate Resolution Imaging Spectroradiometer (MODIS) and investigate the corresponding enhancement factors for the GCM parameterization of autoconversion rate. We find that the conventional approach of using only subgrid variability of cloud water is insufficient and that the subgrid variability of CDNC, as well as the correlation between the two, is also important for correctly simulating the autoconversion process in GCMs. Using the MODIS data which have near-global data coverage, we find that Eq shows a strong dependence on cloud regimes due to the fact that the subgrid variability of cloud water and CDNC is regime dependent. Our analysis shows a significant increase of Eq from the stratocumulus (Sc) to cumulus (Cu) regions. Furthermore, the enhancement factor EN due to the subgrid variation of CDNC is derived from satellite observation for the first time, and results reveal several regions downwind of biomass burning aerosols (e.g., Gulf of Guinea, east coast of South Africa), air pollution (i.e., East China Sea), and active volcanos (e.g., Kilauea, Hawaii, and Ambae, Vanuatu), where the EN is comparable to or even larger than Eq, suggesting an important role of aerosol in influencing the EN. MODIS observations suggest that the subgrid variations of cloud liquid water path (LWP) and CDNC are generally positively correlated. As a result, the combined enhancement factor, including the effect of LWP and CDNC correlation, is significantly smaller than the simple product of Eq⋅EN. Given the importance of warm rain processes in understanding the Earth's system dynamics and water cycle, we conclude that more observational studies are needed to provide a better constraint on the warm rain processes in GCMs.

In this study, we integrate recent in situ measurements with satellite retrievals of dust physical and radiative properties to quantify dust direct radiative effects on shortwave (SW) and longwave (LW) radiation (denoted as DRE SW and DRE LW , respectively) in the tropical North Atlantic during the summer months from 2007 to 2010. Through linear regression of the CERES-measured top-ofatmosphere (TOA) flux versus satellite aerosol optical depth (AOD) retrievals, we estimate the instantaneous DRE SW efficiency at the TOA to be −49.7 ± 7.1 W m −2 AOD −1 and −36.5±4.8 W m −2 AOD −1 based on AOD from MODIS and CALIOP, respectively. We then perform various sensitivity studies based on recent measurements of dust particle size distribution (PSD), refractive index, and particle shape distribution to determine how the dust microphysical and optical properties affect DRE estimates and its agreement with the above-mentioned satellite-derived DREs. Our analysis shows that a good agreement with the observation-based estimates of instantaneous DRE SW and DRE LW can be achieved through a combination of recently observed PSD with substantial presence of coarse particles, a less absorptive SW refractive index, and spheroid shapes. Based on this optimal combination of dust physical properties we further estimate the diurnal mean dust DRE SW in the region of −10 W m −2 at TOA and −26 W m −2 at the surface, respectively, of which ∼ 30 % is canceled out by the positive DRE LW . This yields a net DRE of about −6.9 and −18.3 W m −2 at TOA and the surface, respectively. Our study suggests that the LW flux contains useful information on dust particle size, which could be used together with SW observations to achieve a more holistic understanding of the dust radiative effect.Published by Copernicus Publications on behalf of the European Geosciences Union.