Phytoplankton Impact on Marine Cloud Microphysical Properties Over the Northeast Atlantic Ocean

The current understanding of the impact of natural cloud condensation nuclei (CCN) variability on cloud properties in marine air is low, thus contributing to climate prediction uncertainty. By analyzing cloud remote sensing observations (2009-2015) at Mace Head (west coast of Ireland), we show the oceanic biota impact on the microphysical properties of stratiform clouds over the Northeast Atlantic Ocean. During spring to summer (seasons of enhanced oceanic biological activity), clouds typically host a higher number of smaller droplets resulting from increased aerosol number concentration in the CCN relevant-size range. The induced increase in cloud droplet number concentration (+100%) and decrease in their radius (-14%) are comparable in magnitude to that generated by the advection of anthropogenically influenced air masses over the background marine boundary layer. Cloud water content and albedo respond to marine CCN perturbations with positive adjustments, making clouds brighter as the number of droplets increases. Cloud susceptibility to marine aerosols overlaps with a large variability of cloud macrophysical and optical properties primarily affected by the meteorological conditions. The above findings suggest the existence of a potential feedback mechanism between marine biota and the marine cloud-climate system.

Dual-field-of-view high-spectral-resolution lidar: Simultaneous profiling of aerosol and water cloud to study aerosol-cloud interaction

Aerosol–cloud interaction affects the cooling of Earth’s climate, mostly by activation of aerosols as cloud condensation nuclei that can increase the amount of sunlight reflected back to space. But the controlling physical processes remain uncertain in current climate models. We present a lidar-based technique as a unique remote-sensing tool without thermodynamic assumptions for simultaneously profiling diurnal aerosol and water cloud properties with high resolution. Direct lateral observations of cloud properties show that the vertical structure of low-level water clouds can be far from being perfectly adiabatic. Furthermore, our analysis reveals that, instead of an increase of liquid water path (LWP) as proposed by most general circulation models, elevated aerosol loading can cause a net decrease in LWP.

Aerosol–cloud interaction (ACI) is complex and difficult to be well represented in current climate models. Progress on understanding ACI processes, such as the influence of aerosols on water cloud droplet formation, is hampered by inadequate observational capability. Hitherto, high-resolution and simultaneous observations of diurnal aerosol loading and cloud microphysical properties are challenging for current remote-sensing techniques. To overcome this conundrum, we introduce the dual-field-of-view (FOV) high-spectral-resolution lidar (HSRL) for simultaneously profiling aerosol and water cloud properties, especially water cloud microphysical properties. Continuous observations of aerosols and clouds using this instrument, verified by the Monte Carlo simulation and coincident observations of other techniques, were conducted to investigate the interactions between aerosol loading and water cloud microphysical properties. A case study over Beijing highlights the scientific potential of dual-FOV HSRL to become a significant contributor to the ACI investigations. The observed water cloud profiles identify that due to air entrainment its vertical structure is not perfectly adiabatic, as assumed by many current retrieval methods. Our ACI analysis shows increased aerosol loading led to increased droplet number concentration and decreased droplet effective radius—consistent with expectations—but had no discernible increase on liquid water path. This finding supports the hypothesis that aerosol-induced cloud water increase caused by suppressed rain formation can be canceled out by enhanced evaporation. Thus, these observations obtained from the dual-FOV HSRL constitute substantial and significant additions to understanding ACI process. This technique is expected to represent a significant step forward in characterizing ACI.

Assessment of Aerosol Mechanisms and Aerosol Meteorology Feedback over an Urban Airshed in India Using a Chemical Transport Model

The direct aerosol-radiative effects in the WRF-Chem model account for scattering/absorption of solar radiation due to aerosols, while aerosol–cloud interactions result in modifying wet scavenging of the ambient concentrations as an indirect aerosol effect. In this study, impact of aerosol on meteorological parameters, PM10 and ozone concentrations are analysed which revealed (i) that a net decrease in shortwave and longwave radiation by direct feedback results in decrease in temperature up to 0.05 K, (ii) that a net increase due to longwave and shortwave radiation when both direct and indirect effects are taken together results in an increase in temperature up to 0.25 K (where the mean of temperature is 33.5 °C and standard deviation 2.13 °C), (iii) a marginal increase in boundary layer height of 50 m with increase in temperature with feedbacks, (iv) overall net increase in radiation by direct and indirect effect together result in an increase in PM10 concentration up to 12 μg m−3 (with PM10 mean as 84.5 μg m−3 and standard deviation 28 μg m−3) and an increase in ozone concentration up to 3 μg m−3 (with ozone mean as 29.65 μg m−3 and standard deviation 5.2 μg m−3) mainly due to net increase in temperature. Furthermore, impact of sensitivity of different aerosol mechanisms on PM10 concentrations was scrutinized for two different mechanisms that revealed underestimation by both of the mechanisms with MOSAIC scheme, showing less fractional bias than MADE/SORGAM. For the dust storm period, MOSAIC scheme simulated higher mass concentrations than MADE/SORGAM scheme and performed well for dust-storm days while closely capturing the peaks of high dust concentrations. This study is one of the first few to demonstrate the impact of both direct and indirect aerosol feedback on local meteorology and air quality using a meteorology–chemistry modelling framework; the WRF-Chem model in a tropical urban airshed in India located in semi-arid climatic zone. It is inferred that semi-arid climatic conditions behave in a vastly different manner than other climatic zones for direct and indirect radiative feedback effects.

Cloud drop number concentrations over the western North Atlantic Ocean: seasonal cycle, aerosol interrelationships, and other influential factors

Cloud drop number concentrations (N _d) over the western North Atlantic Ocean (WNAO) are generally highest during the winter (DJF) and lowest in summer (JJA), in contrast to aerosol proxy variables (aerosol optical depth, aerosol index, surface aerosol mass concentrations, surface cloud condensation nuclei (CCN) concentrations) that generally peak in spring (MAM) and JJA with minima in DJF. Using aircraft, satellite remote sensing, ground-based in situ measurement data, and reanalysis data, we characterize factors explaining the divergent seasonal cycles and furthermore probe into factors influencing N _d on seasonal timescales. The results can be summarized well by features most pronounced in DJF, including features associated with cold-air outbreak (CAO) conditions such as enhanced values of CAO index, planetary boundary layer height (PBLH), low-level liquid cloud fraction, and cloud-top height, in addition to winds aligned with continental outflow. Data sorted into high- and low-N _d days in each season, especially in DJF, revealed that all of these conditions were enhanced on the high-N _d days, including reduced sea level pressure and stronger wind speeds. Although aerosols may be more abundant in MAM and JJA, the conditions needed to activate those particles into cloud droplets are weaker than in colder months, which is demonstrated by calculations of the strongest (weakest) aerosol indirect effects in DJF (JJA) based on comparing N _d to perturbations in four different aerosol proxy variables (total and sulfate aerosol optical depth, aerosol index, surface mass concentration of sulfate). We used three machine learning models and up to 14 input variables to infer about most influential factors related to N _d for DJF and JJA, with the best performance obtained with gradient-boosted regression tree (GBRT) analysis. The model results indicated that cloud fraction was the most important input variable, followed by some combination (depending on season) of CAO index and surface mass concentrations of sulfate and organic carbon. Future work is recommended to further understand aspects uncovered here such as impacts of free tropospheric aerosol entrainment on clouds, degree of boundary layer coupling, wet scavenging, and giant CCN effects on aerosol-N _d relationships, updraft velocity, and vertical structure of cloud properties such as adiabaticity that impact the satellite estimation of N _d.

Bounding Global Aerosol Radiative Forcing of Climate Change

Aerosols interact with radiation and clouds. Substantial progress made over the past 40 years in observing, understanding, and modeling these processes helped quantify the imbalance in the Earth's radiation budget caused by anthropogenic aerosols, called aerosol radiative forcing, but uncertainties remain large. This review provides a new range of aerosol radiative forcing over the industrial era based on multiple, traceable, and arguable lines of evidence, including modeling approaches, theoretical considerations, and observations. Improved understanding of aerosol absorption and the causes of trends in surface radiative fluxes constrain the forcing from aerosol-radiation interactions. A robust theoretical foundation and convincing evidence constrain the forcing caused by aerosol-driven increases in liquid cloud droplet number concentration. However, the influence of anthropogenic aerosols on cloud liquid water content and cloud fraction is less clear, and the influence on mixed-phase and ice clouds remains poorly constrained. Observed changes in surface temperature and radiative fluxes provide additional constraints. These multiple lines of evidence lead to a 68% confidence interval for the total aerosol effective radiative forcing of -1.6 to -0.6 W m-2, or -2.0 to -0.4 W m-2 with a 90% likelihood. Those intervals are of similar width to the last Intergovernmental Panel on Climate Change assessment but shifted toward more negative values. The uncertainty will narrow in the future by continuing to critically combine multiple lines of evidence, especially those addressing industrial-era changes in aerosol sources and aerosol effects on liquid cloud amount and on ice clouds.

Effects of Biomass Burning on Stratocumulus Droplet Characteristics, Drizzle Rate, and Composition

This study reports on airborne measurements of stratocumulus cloud properties under varying degrees of influence from biomass burning (BB) plumes off the California coast. Data are reported from five total airborne campaigns based in Marina, California, with two of them including influence from wildfires in different areas along the coast of the western United States. The results indicate that subcloud cloud condensation nuclei number concentration and mass concentrations of important aerosol species (organics, sulfate, nitrate) were better correlated with cloud droplet number concentration (N d) as compared to respective above-cloud aerosol data. Given that the majority of BB particles resided above cloud tops, this is an important consideration for future work in the region as the data indicate that the subcloud BB particles likely were entrained from the free troposphere. Lower cloud condensation nuclei activation fractions were observed for BB-impacted clouds as compared to non-BB clouds due, at least partly, to less hygroscopic aerosols. Relationships between N d and either droplet effective radius or drizzle rate are preserved regardless of BB influence, indicative of how parameterizations can exhibit consistent skill for varying degrees of BB influence as long as N d is known. Lastly, the composition of both droplet residual particles and cloud water changed significantly when clouds were impacted by BB plumes, with differences observed for different fire sources stemming largely from effects of plume aging time and dust influence.

AEROSOL-CLOUD-METEOROLOGY INTERACTION AIRBORNE FIELD INVESTIGATIONS: Using Lessons Learned from the U.S. West Coast in the Design of ACTIVATE off the U.S. East Coast

We report on a multiyear set of airborne field campaigns (2005–16) off the California coast to examine aerosols, clouds, and meteorology, and how lessons learned tie into the upcoming NASA Earth Venture Suborbital (EVS-3) campaign: Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE; 2019–23). The largest uncertainty in estimating global anthropogenic radiative forcing is associated with the interactions of aerosol particles with clouds, which stems from the variability of cloud systems and the multiple feedbacks that affect and hamper efforts to ascribe changes in cloud properties to aerosol perturbations. While past campaigns have been limited in flight hours and the ability to fly in and around clouds, efforts sponsored by the Office of Naval Research have resulted in 113 single aircraft flights (>500 flight hours) in a fixed region with warm marine boundary layer clouds. All flights used nearly the same payload of instruments on a Twin Otter to fly below, in, and above clouds, producing an unprecedented dataset. We provide here i) an overview of statistics of aerosol, cloud, and meteorological conditions encountered in those campaigns and ii) quantification of model-relevant metrics associated with aerosol–cloud interactions leveraging the high data volume and statistics. Based on lessons learned from those flights, we describe the pragmatic innovation in sampling strategy (dual-aircraft approach with combined in situ and remote sensing) that will be used in ACTIVATE to generate a dataset that can advance scientific understanding and improve physical parameterizations for Earth system and weather forecasting models, and for assessing next-generation remote sensing retrieval algorithms.

A multi-year data set on aerosol-cloud-precipitation-meteorology interactions for marine stratocumulus clouds

Airborne measurements of meteorological, aerosol, and stratocumulus cloud properties have been harmonized from six field campaigns during July-August months between 2005 and 2016 off the California coast. A consistent set of core instruments was deployed on the Center for Interdisciplinary Remotely-Piloted Aircraft Studies Twin Otter for 113 flight days, amounting to 514 flight hours. A unique aspect of the compiled data set is detailed measurements of aerosol microphysical properties (size distribution, composition, bioaerosol detection, hygroscopicity, optical), cloud water composition, and different sampling inlets to distinguish between clear air aerosol, interstitial in-cloud aerosol, and droplet residual particles in cloud. Measurements and data analysis follow documented methods for quality assurance. The data set is suitable for studies associated with aerosol-cloud-precipitation-meteorology-radiation interactions, especially owing to sharp aerosol perturbations from ship traffic and biomass burning. The data set can be used for model initialization and synergistic application with meteorological models and remote sensing data to improve understanding of the very interactions that comprise the largest uncertainty in the effect of anthropogenic emissions on radiative forcing.

Untangling aerosol effects on clouds and precipitation in a buffered system

It is thought that changes in the concentration of cloud-active aerosol can alter the precipitation efficiency of clouds, thereby changing cloud amount and, hence, the radiative forcing of the climate system. Despite decades of research, it has proved frustratingly difficult to establish climatically meaningful relationships among the aerosol, clouds and precipitation. As a result, the climatic effect of the aerosol remains controversial. We propose that the difficulty in untangling relationships among the aerosol, clouds and precipitation reflects the inadequacy of existing tools and methodologies and a failure to account for processes that buffer cloud and precipitation responses to aerosol perturbations.