Decades of atmospheric research have focused on the Western North Atlantic Ocean (WNAO) region because of its unique location that offers accessibility for airborne and ship measurements, gradients in important atmospheric parameters, and a range of meteorological regimes leading to diverse conditions that are poorly understood. This work reviews these scientific investigations for the WNAO region, including the East Coast of North America and the island of Bermuda. Over 50 field campaigns and long‐term monitoring programs, in addition to 715 peer‐reviewed publications between 1946 and 2019, have provided a firm foundation of knowledge for these areas. Of particular importance in this region has been extensive work at the island of Bermuda that is host to important time series records of oceanic and atmospheric variables. Our review categorizes WNAO atmospheric research into eight major categories, with some studies fitting into multiple categories (relative %): aerosols (25%); gases (24%); development/validation of techniques, models, and retrievals (18%); meteorology and transport (9%); air‐sea interactions (8%); clouds/storms (8%); atmospheric deposition (7%); and aerosol‐cloud interactions (2%). Recommendations for future research are provided in the categories highlighted above.

Airborne NASA Langley Research Center (LaRC) High Spectral Resolution Lidar-2 (HSRL-2) measurements acquired during the recent NASA Earth Venture Suborbital-3 (EVS-3) Aerosol Cloud Meteorology Interactions over the Western Atlantic Experiment (ACTIVATE) revealed elevated particulate linear depolarization associated with aerosols within the marine boundary layer. These observations were acquired off the east coast of the United States during both winter and summer 2020 and 2021 when the HSRL-2 was deployed on the NASA LaRC King Air aircraft. During 20 of 63 total flight days, particularly on days with cold air outbreaks, linear particulate depolarization at 532 nm exceeded 0.15–0.20 within the lowest several hundred meters of the atmosphere, indicating that these particles were non-spherical. Higher values of linear depolarization typically were measured at 355 nm and lower values were measured at 1,064 nm. Several lines of evidence suggest that these non-spherical particles were sea salt including aerosol extinction/backscatter ratio (“lidar ratio”) values of 20–25 sr measured at both 355 and 532 nm by the HSRL-2, higher values of particulate depolarization measured at low (< 60%) relative humidity, coincident airbornein situsize and composition measurements, and aerosol transport simulations. The elevated aerosol depolarization values were not correlated with wind speed but were correlated with salt mass fraction and effective radius of the aerosol when the relative humidity was below 60%. HSRL-2 measured median particulate extinction values of about 20 Mm⁻¹ at 532 nm associated with these non-spherical sea salt particles and found that the aerosol optical depth (AOD) contributed by these particles remained small (0.03–0.04) but represented on average about 30%–40% of the total column AOD. Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) spaceborne lidar aerosol measurements during several cold air outbreaks and CALIOP retrievals of column aerosol lidar ratio using column AOD constraints suggest that CALIOP operational aerosol algorithms can misclassify these aerosols as dusty marine rather than marine aerosols. Such misclassification leads to ∼40–50% overestimates in the assumed lidar ratio and in subsequent retrievals of aerosol optical depth and aerosol extinction.

The role of the sea/bay breeze in the planetary boundary layer evolution and air quality during a high ozone event day in the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER‐AQ) Texas 2013 campaign was examined. Data from surface air quality monitoring network stations, airborne lidar data, and additional ground‐based lidar instrumentation deployed during the campaign allowed for a unique three‐dimensional spatial and temporal study of the progression of both meteorological and air quality conditions in the Houston‐Galveston regions on 25 September 2013. The Weather Research and Forecasting model coupled with Chemistry model was used to examine the relationship of the land and bay/sea breeze circulations and its influence on air quality during the case study. Comparisons between observations and simulations revealed the largest discrepancies near the Galveston Bay shore areas where the highly localized ozone concentrations were observed and were linked to the strength and timing of the bay/sea breeze progression. Additionally, results indicate vertical downmixing from the remnants of the nighttime residual layer during morning hours into the convective boundary layer and from the lofted offshore return flow into the subjacent bay breeze flow.

Lidar retrievals of aerosol extinction and collocated relative humidity (RH) were acquired during the Department of Energy Combined High Spectral Resolution Lidar (HSRL) and Raman Measurement Study campaign in the summer of 2015 at the Southern Great Plains site in northern Oklahoma. Measurements of the hygroscopic properties of aerosols are crucial for accurately representing their relationship with clouds, which can be a significant source of uncertainty in assessing direct and indirect radiative effects. The ability for lidar to retrieve measurements of the vertically resolved f (RH), that is, the aerosol extinction at some wet RH normalized by the aerosol extinction at a dry reference RH, is investigated here and compared with nephelometer‐measured f (RH) at the surface. We introduce a modified approach to fitting the lidar measurements of aerosol extinction and our comparisons reveal that lidar and nephelometer measurements of f (RH) are consistent, both with each other and with reported values in the literature. The implications for this work present a path forward for global‐scale retrievals of remotely sensed aerosol hygroscopic properties. Most importantly, the efforts in this study could lead to closing the gap on uncertainties associated with the aerosol indirect radiative effect when combined with inversion retrievals of aerosol microphysical properties.

For aerosol retrieval from multi-angle polarimetric (MAP) measurements over the ocean it is important to accurately account for the contribution of the ocean-body to the top-of-atmosphere signal, especially for wavelengths <500 nm. Performing online radiative transfer calculations in the coupled atmosphere ocean system is too time consuming for operational retrieval algorithms. Therefore, mostly lookup-tables of the ocean body reflection matrix are used to represent the lower boundary in an atmospheric radiative transfer model. For hyperspectral measurements such as those from Spectro-Polarimeter for Planetary Exploration (SPEXone) on the NASA Plankton, Aerosol, Cloud and ocean Ecosystem (PACE) mission, also the use of look-up tables is unfeasible because they will become too big. In this paper, we propose a new method for aerosol retrieval over ocean from MAP measurements using a neural network (NN) to model the ocean body reflection matrix. We apply the NN approach to synthetic SPEXone measurements and also to real data collected by SPEX airborne during the Aerosol Characterization from Polarimeter and Lidar (ACEPOL) campaign. We conclude that the NN approach is well capable for aerosol retrievals over ocean, introducing no significant error on the retrieved aerosol properties

The vertical distribution of aerosols and their capability of serving as cloud condensation nuclei (CCN) are important for improving our understanding of aerosol indirect effects. Although ground‐based and airborne CCN measurements have been made, they are generally scarce, especially at cloud base where it is needed most. We have developed an algorithm for profiling CCN number concentrations using backscatter coefficients at 355, 532, and 1,064 nm and extinction coefficients at 355 and 532 nm from multiwavelength lidar systems. The algorithm considers three distinct types of aerosols (urban industrial, biomass burning, and dust) with bimodal size distributions. The algorithm uses look‐up tables, which were developed based on the ranges of aerosol size distributions obtained from the Aerosol Robotic Network, to efficiently find optimal solutions. CCN number concentrations at five supersaturations (0.07–0.80%) are determined from the retrieved particle size distributions. Retrieval simulations were performed with different combinations of systematic and random errors in lidar‐derived extinction and backscatter coefficients: systematic errors range from −20% to 20% and random errors are up to 15%, which fall within the typical error ranges for most current lidar systems. The potential of this algorithm to retrieve CCN concentrations is further evaluated through comparisons with surface‐based CCN measurements with near‐surface lidar retrievals. This retrieval algorithm would be valuable for aerosol‐cloud interaction studies for which virtually none has employed CCN at cloud base because of the lack of such measurements.