Impacts of Long-range Transport of Aerosols on Marine Boundary Layer Clouds in the Eastern North Atlantic

Vertical profiles of aerosols are inadequately observed and poorly represented in climate models, contributing to the current large uncertainty associated with aerosol– cloud interactions. The US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Aerosol and Cloud Experiments in the Eastern North Atlantic (ACEENA) aircraft field campaign near the Azores islands provided ample observations of vertical distributions of aerosol and cloud properties. Here we utilize the in situ aircraft measurements from the ACE-ENA and ground-based remotesensing data along with an aerosol-aware Weather Research and Forecast (WRF) model to characterize the aerosols due to long-range transport over a remote region and to assess their possible influence on marine-boundary-layer (MBL) clouds. The vertical profiles of aerosol and cloud properties measured via aircraft during the ACE-ENA campaign provide detailed information revealing the physical contact between transported aerosols and MBL clouds. The European Centre for Medium-Range Weather Forecasts Copernicus Atmosphere Monitoring Service (ECMWF-CAMS) aerosol reanalysis data can reproduce the key features of aerosol vertical profiles in the remote region. The cloud-resolving WRF sensitivity experiments with distinctive aerosol profiles suggest that the transported aerosols and MBL cloud interactions (ACIs) require not only aerosol plumes to get close to the marine-boundary-layer top but also large cloud top height variations. Based on those criteria, the observations show that the occurrence of ACIs involving the transport of aerosol over the eastern North Atlantic (ENA) is about 62 % in summer. For the case with noticeable long-rangetransport aerosol effects on MBL clouds, the susceptibilities of droplet effective radius and liquid water content are −0.11 and +0.14, respectively. When varying by a similar magnitude, aerosols originating from the boundary layer exert larger microphysical influence on MBL clouds than those entrained from the free troposphere. 1 Motivation and background It has been long hypothesized that increased high concentrations of aerosols serving as cloud condensation nuclei (CCNs) can reduce cloud droplet effective radius, enhance cloud albedo, suppress drizzle formation, and change cloud lifetime and fraction – the so-called aerosol indirect effects (AIEs; Twomey, 1977; Seinfeld et al., 2016). However, current radiative forcing stemming from cloud responses to anthropogenic aerosols remains highly uncertain in the climate system, representing the largest challenge in climate predictions (Fan et al., 2016). Note that the current IPCC assessment mainly considers the warm stratus and stratocumulus responses to aerosols, while aerosol-induced convective cloud response (Wang et al., 2014) and anthropogenic aerosol effects such as ice nuclei (Zhao et al., 2019) have not been fully accounted for yet. Even for warm clouds, the climate significance of whether liquid water content and cloud lifetime are enhanced or reduced by CCNs is still widely debated (Malavelle et al., 2017; Toll et al., 2019; Rosenfeld et al., 2019). Due to the nonlinear nature of cloud responses to CCN perturbations, the largest cloud susceptibility and AIEs Published by Copernicus Publications on behalf of the European Geosciences Union. 14742 Y. Wang et al.: Impacts of long-range transport of aerosols typically occur for the marine-boundary-layer (MBL) clouds over remote regions (Garrett and Hobbs, 1995; Carslaw et al., 2013; Dong et al., 2015). Under pristine conditions with extremely low background CCN concentration (Kristensen et al., 2016), any aerosol intrusion following long-range transport has great potential to alter the local aerosol and CCN budget (Roberts et al., 2006). Hence, in this study, we aim to characterize long-range transport of aerosols and to assess their impacts on MBL clouds by combining in situ aircraft measurements with cloud-resolving model simulations. For those aerosols resulting from long-range transport, one of the most important aspects pertinent to aerosol–cloud interactions (ACIs) is their vertical distribution, or in other words, their position relative to cloud layers. The vertical distribution of aerosols can be affected by a number of complex atmospheric processes, such as emission, transport, and deposition as well as microphysical and chemical processes. Previous studies suggest that aerosols can alter MBL cloud microphysical properties and enhance indirect effects through entrainment into the cloud top either when aerosol particles settle or the cloud deck deepens (Painemal et al., 2014; Lu et al., 2018). In the boundary layer of remote regions like the equatorial Pacific, the majority of CCNs were found to be supplied by long-range transport instead of local emission or formation (Clarke et al., 2013). In the northeast Pacific, where aerosol types are similar to the Azores, biomass-burning aerosols from the episodic wildfire events are found to be less efficient in altering cloud microphysics than the nonbiomass-burning aerosols (Hossein Mardi et al., 2019). Recent aircraft observations from the NASA’s ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) campaign showed distinctive MBL cloud responses to aerosols above and below clouds depending on the history of smoke entrainment (Diamond et al., 2018). Therefore, it is critical to understand aerosol variability as a function of height and its influence on the aerosol indirect forcing assessment over the regions where MBL clouds are abundant. Spaceborne active sensors that possess vertically profiling capabilities have been widely used to characterize aerosol and cloud spatial variations and to detect the aerosol above clouds (Painemal et al., 2014; Jiang et al., 2018). However, satellites likely miss the thin aerosol layers with relatively low concentration (but still higher than maritime background values), and thus overestimate the distance between the aerosol plume base and the cloud top. Also, when plumes are too thick near the aerosol source regions, satellite signals will be saturated, and the retrievals may underestimate the extent of thick layers (Rajapakshe et al., 2017). Therefore, aircraft observations with continuous vertical sampling are the most reliable source that can accurately characterize the vertical relationship between aerosol and cloud. The DOE ARM Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) aircraft field campaign near the Azores islands provided a unique opportunity to study aerosols from different sources and their impacts on MBL clouds (Wang et al., 2019). The eastern North Atlantic (ENA) site is located in the remote northeastern Atlantic Ocean, where MBL clouds are prevalent throughout the year due to the warm sea surface temperature and prevailing subsidence near the edge of the Hadley cell (Wood et al., 2015; Dong et al., 2015). The site also receives complex air mass dictated by different wind patterns. In addition to the local maritime air, the airflows originating from either the North American or the Saharan region complicate the local aerosol types and sources (Logan et al., 2014). This study leverages the airborne measurements of aerosol vertical profiles for different chemical species to understand aerosols and their influence on MBL cloud microphysical properties over the Azores, with the ultimate goal of providing observational constraints on the global climate model simulations. An aerosol reanalysis product is evaluated in the present study as well. Even with the aircraft-measured vertical relationship between aerosol and cloud, it is difficult to estimate whether the aerosol aloft can impact the cloud beneath as the microphysical processes such as entrainment into the cloud top cannot be directly measured. Hence, we employ an aerosolaware cloud-resolving model to simulate the MBL cloud development and aerosol transport in the free troposphere and to quantify the AIEs. Through the sensitivity experiment by imposing different aerosol vertical profiles, we can disentangle aerosol and other confounding meteorological factors in ACIs, which is challenging to do using only short-term observations. Section 2 describes the main observational data and introduces the numerical modeling tools. Section 3 reports the observed aerosols and clouds based on aircraft measurements and reanalysis products. Section 4 presents the analyses of cloud-resolving simulations using the Weather Research and Forecast (WRF) model. Section 5 summarizes the key findings in this study and provides additional discussions for the study’s caveats and future work.