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In-situ marine cloud droplet number concentrations (CDNCs), cloud condensation nuclei (CCN), and CCN proxies, based on particle sizes and optical properties, are accumulated from seven field campaigns: ACTIVATE; NAAMES; CAMP2EX; ORACLES; SOCRATES; MARCUS; and CAPRICORN2. Each campaign involves aircraft measurements, ship-based measurements, or both. Measurements collected over the North and Central Atlantic, Indo-Pacific, and Southern Oceans, represent a range of clean to polluted conditions in various climate regimes. With the extensive range of environmental conditions sampled, this data collection is ideal for testing satellite remote detection methods of CDNC and CCN in marine environments. Remote measurement methods are vital to expanding the available data in these difficult-to-reach regions of the Earth and improving our understanding of aerosol-cloud interactions. The data collection includes particle composition and continental tracers to identify potential contributing CCN sources. Several of these campaigns include High Spectral Resolution Lidar (HSRL) and polarimetric imaging measurements and retrievals that will be the basis for the next generation of space-based remote sensors and, thus, can be utilized as satellite surrogates.

Atmospheric marine particle concentrations impact cloud properties, which strongly impact the amount of solar radiation reflected back into space or absorbed by the ocean surface. While satellites can provide a snapshot of current conditions at the overpass time, models are necessary to simulate temporal variations in both particle and cloud properties. However, poor model accuracy limits the reliability with which these tools can be used to predict future climate. Here, we leverage the comprehensive ocean ecosystem and atmospheric aerosol–cloud dataset obtained during the third deployment of the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES3). Airborne and ship-based measurements were collected in and around a cold-air outbreak during a 3 d (where d stands for day) intensive operations period from 17–19 September 2017. Cold-air outbreaks are of keen interest for model validation because they are challenging to accurately simulate, which is due, in part, to the numerous feedbacks and sub-grid-scale processes that influence aerosol and cloud evolution. The NAAMES observations are particularly valuable because the flight plans were tailored to lie along Lagrangian trajectories, making it possible to spatiotemporally connect upwind and downwind measurements with the state-of-the-art FLEXible PARTicle (FLEXPART) Lagrangian particle dispersion model and then calculate a rate of change in particle properties. Initial aerosol conditions spanning an east–west, closed-cell-to-clear-air transition region of the cold-air outbreak indicate similar particle concentrations and properties. However, despite the similarities in the aerosol fields, the cloud properties downwind of each region evolved quite differently. One trajectory carried particles through a cold-air outbreak, resulting in a decrease in accumulation mode particle concentration (−42 %) and cloud droplet concentrations, while the other remained outside of the cold-air outbreak and experienced an increase in accumulation mode particle concentrations (+62 %). The variable meteorological conditions between these two adjacent trajectories result from differences in the local sea surface temperature in the Labrador Current and surrounding waters, altering the stability of the marine atmospheric boundary layer. Further comparisons of historical satellite observations indicate that the observed pattern occurs annually in the region, making it an ideal location for future airborne Lagrangian studies tracking the evolution of aerosols and clouds over time under cold-air outbreak conditions.

Abstract: 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.

The North Atlantic Aerosols and Marine Ecosystems Study (NAAMES) is an interdisciplinary investigation to improve understanding of Earth's ocean ecosystem-aerosol-cloud system. Specific overarching science objectives for NAAMES are to (1) characterize plankton ecosystem properties during primary phases of the annual cycle and their dependence on environmental forcings, (2) determine how these phases interact to recreate each year the conditions for an annual plankton bloom, and (3) resolve how remote marine aerosols and boundary layer clouds are influenced by plankton ecosystems. Four NAAMES field campaigns were conducted in the western subarctic Atlantic between November 2015 and April 2018, with each campaign targeting specific seasonal events in the annual plankton cycle. A broad diversity of measurements were collected during each campaign, including ship, aircraft, autonomous float and drifter, and satellite observations. Here, we present an overview of NAAMES science motives, experimental design, and measurements. We then briefly describe conditions and accomplishments during each of the four field campaigns and provide information on how to access NAAMES data. The intent of this manuscript is to familiarize the broad scientific community with NAAMES and to provide a common reference overview of the project for upcoming publications.

Remote marine regions comprise a high fraction of Earth's surface, but in situ vertically resolved measurements over these locations remain scarce. Here we use airborne data during 15 vertical spiral soundings (0.15–8.5 km) over Bermuda during the NASA Aerosol Cloud meTeorology Interactions over the western ATlantic Experiment (ACTIVATE) to investigate the impact of different source regions on the vertical structure of trace gases, aerosol particles, and meteorological variables over 1000 km offshore of the US East Coast. Results reveal significant differences in vertical profiles of variables between three different air mass source categories (North America, Ocean, Caribbean/North Africa) identified using the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model: (i) the strongest pollution signature is from air masses from the North America category, while the weakest one is from the Ocean category; (ii) North America air has the highest levels of CO, CH 4 , submicron particle number concentration, aerosol mass spectrometer (AMS) mass, and organic mass fraction along with smoke layers in the free troposphere (FT); (iii) Ocean air has the highest relative amount of nitrate, non-sea-salt sulfate, and oxalate, which are key acidic species participating in chloride depletion; (iv) air masses from the Caribbean/North Africa showed a pronounced coarse aerosol signature in the FT and reduced aerosol hygroscopicity, which is associated with dust transport; and (v) there is considerable vertical heterogeneity for almost all variables examined, including higher O 3 and submicron particle concentrations with altitude, suggesting that the FT is a potential contributor of both constituents in the marine boundary layer. This study highlights the importance of considering air mass source origin and vertical resolution to capture aerosol and trace gas properties over remote marine areas. [ABSTRACT FROM AUTHOR]

With the ongoing expansion of global observation networks, it is expected that we shall routinely analyze records of geophysical variables such as temperature from multiple collocated instruments. Validating datasets in this situation is not a trivial task because every observing system has its own bias and noise. Triple collocation is a general statistical framework to estimate the error characteristics in three or more observational-based datasets. In a triple colocation analysis, several metrics are routinely reported but traditional multiple-panel plots are not the most effective way to display information. A new formula of error variance is derived for connecting the key terms in the triple collocation theory. A diagram based on this formula is devised to facilitate triple collocation analysis of any data from observations, as illustrated using three aerosol optical depth datasets from the recent Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE). An observational-based skill score is also derived to evaluate the quality of three datasets by taking into account both error variance and correlation coefficient. Several applications are discussed and sample plotting routines are provided. [ABSTRACT FROM AUTHOR]

Ocean surface wind speed (i.e., wind speed 10 m above sea level) is a critical parameter used by atmospheric models to estimate the state of the marine atmospheric boundary layer (MABL). Accurate surface wind speed measurements in diverse locations are required to improve characterization of MABL dynamics and assess how models simulate large-scale phenomena related to climate change and global weather patterns. To provide these measurements, this study introduces and evaluates a new surface wind speed data product from the NASA Langley Research Center nadir-viewing High Spectral Resolution Lidar – generation 2 (HSRL-2) using data collected as part of the NASA Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) mission. The HSRL-2 can directly measure vertically resolved aerosol backscatter and extinction profiles without additional constraints or assumptions, enabling the instrument to accurately derive atmospheric attenuation and directly determine surface reflectance (i.e., surface backscatter). Also, the high horizontal spatial resolution of the HSRL-2 retrievals (0.5 s or ∼ 75 m along track) allows the instrument to probe the fine-scale spatial variability in surface wind speeds over time along the flight track and over breaks in broken cloud fields. A rigorous evaluation of these retrievals is performed by comparing coincident HSRL-2 and National Center for Atmospheric Research (NCAR) Airborne Vertical Atmosphere Profiling System (AVAPS) dropsonde data, owing to the joint deployment of these two instruments on the ACTIVATE King Air aircraft. These comparisons show correlations of 0.89, slopes of 1.04 and 1.17, and y intercepts of - 0.13 and - 1.05 ms-1 for linear and bisector regressions, respectively, and the overall accuracy is calculated to be 0.15 ± 1.80 ms-1. It is also shown that the dropsonde surface wind speed data most closely follow the HSRL-2 distribution of wave slope variance using the distribution proposed by Hu et al. (2008) rather than the ones proposed by Cox and Munk (1954) and Wu (1990) for surface wind speeds below 7 ms-1 , with this category comprising most of the ACTIVATE data set. The retrievals are then evaluated separately for surface wind speeds below 7 ms-1 and between 7 and 13.3 ms-1 and show that the HSRL-2 retrieves surface wind speeds with a bias of ∼ 0.5 ms-1 and an error of ∼ 1.5 ms-1 , a finding not apparent in the cumulative comparisons. Also, it is shown that the HSRL-2 retrievals are more accurate in the summer (- 0.18 ± 1.52 ms-1) than in the winter (0.63 ± 2.07 ms-1), but the HSRL-2 is still able to make numerous (N=236) accurate retrievals in the winter. Overall, this study highlights the abilities and assesses the performance of the HSRL-2 surface wind speed retrievals, and it is hoped that further evaluation of these retrievals will be performed using other airborne and satellite data sets. [ABSTRACT FROM AUTHOR]

Mesoscale organization of marine convective clouds into linear or clustered states is prevalent across the tropical and subtropical oceans, and its investigation served as a guiding focus for a series of process study flights conducted as part of the Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) during summer 2020, 2021, and 2022. These select ACTIVATE flights involved a novel strategy for coordinating two aircraft, with respective remote sensing and in situ sampling payloads, to probe regions of organized shallow convection for several hours. The main purpose of this measurement report is to summarize the aircraft sampling approach, describe the characteristics and evolution of the cases, and provide an overview of the datasets that can serve as a starting point for more detailed modeling and analysis studies. Six flights are described, involving a total of 80 dropsonde profiles that capture the environment surrounding clustered shallow convection. The flights include detailed observations of the vertical structure of cloud systems, comprising up to 20 in situ sampling levels. Four cases involved deepening convection rooted in the marine boundary layer that developed vertically to 2–5 km with varying precipitation amounts, while two cases captured more complex and developed cumulus congestus systems extending above 5 km. In addition to the thermodynamic and dynamic characterization afforded by dropsonde and in situ measurements, the datasets include cloud and aerosol microphysics, trace gas concentrations, aerosol and droplet composition, and cloud and aerosol remote sensing from high-spectral-resolution lidar and polarimetry. [ABSTRACT FROM AUTHOR]

The Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) is a six-year (2019-2024) NASA Earth-Venture Suborbital-3 (EVS-3) mission to robustly characterize aerosol-cloud-meteorology interactions over the western North Atlantic Ocean (WNAO) during winter and summer seasons, with a focus on marine boundary layer clouds. This characterization requires understanding the aerosol life cycle (sources and sinks), composition, transport pathways, and distribution in the WNAO region. We use the GEOS-Chem chemical transport model driven by the MERRA-2 reanalysis to simulate tropospheric aerosols that are evaluated against in situ and remote sensing measurements from Falcon and King Air aircraft, respectively, as well as ground-based and satellite observations over the WNAO during the winter (Feb. 14 - Mar. 12) and summer (Aug. 13 - Sep. 30) field deployments of ACTIVATE 2020. Transport of pollution in the boundary layer behind cold fronts is a major mechanism for the North American continental outflow to the WNAO during Feb.-Mar. 2020. While large-scale frontal lifting is a dominant mechanism in winter, convective lifting significantly increases the vertical extent of major continental outflow aerosols in summer. Turbulent mixing is found to be the dominant process responsible for the vertical transport of sea salt within and ventilation out of the boundary layer in winter. The simulated boundary layer aerosol composition and optical depth (AOD) in the ACTIVATE flight domain are dominated by sea salt, followed by organic aerosol and sulfate. Compared to winter, boundary layer sea salt concentrations increased in summer over the WNAO, especially from the ACTIVATE flight areas to Bermuda, because of enhanced surface winds and emissions. Dust concentrations also significantly increased in summer because of long-range transport from North Africa. Comparisons of model and aircraft submicron non-refractory aerosol species (measured by an HR-ToF-AMS) vertical profiles show that intensive measurements of sulfate, nitrate, ammonium, and organic aerosols in the lower troposphere over the WNAO in winter provide useful constraints on model aerosol wet removal by precipitation scavenging. Comparisons of model aerosol extinction (at 550 nm) with the King Air High Spectral Resolution Lidar-2 (HSRL-2) measurements (at 532 nm) and CALIOP/CALIPSO satellite retrievals (at 532 nm) indicate that the model generally captures the continental outflow of aerosols, the land-ocean aerosol extinction gradient, and the mixing of anthropogenic aerosols with sea salt. Large enhancements of aerosol extinction at ~1.5-6.0 km altitudes from long-range transport of the western U.S. fire smoke were observed by HSRL-2 and CALIOP during Aug.-Sep. 2020. Model simulations with biomass burning (BB) emissions injected up to the mid-troposphere (vs. within the BL) better reproduce these remote-sensing observations, Falcon aircraft organic aerosol vertical profiles, as well as AERONET AOD measurements over eastern U.S. coast and Tudor Hill, Bermuda. High aerosol (mostly coarse-mode sea salt) extinction near the top (~1.5-2.0 km) of the marine BL along with high relative humidity and cloud extinction were typically seen over the WNAO (< 35°N) in the CALIOP aerosol extinction profiles and GEOS-Chem simulations, suggesting strong hygroscopic growth of sea salt particles and sea salt seeding of marine boundary layer clouds. Contributions of different emission types (anthropogenic, BB, biogenic, marine, and dust) to the total AOD over the WNAO in the model are also quantified. Future modeling efforts should focus on improving parameterizations for aerosol wet scavenging and sea salt emissions, implementing realistic BB emission injection height, and applying high-resolution models that better resolve vertical transport. [ABSTRACT FROM AUTHOR]

Inadequate knowledge about the complex microphysical and optical processes of the aerosol–cloud system severely restricts our ability to quantify the resultant impact on climate. Contrary to the negative radiative forcing (cooling) exerted by aerosols in cloud-free skies over dark surfaces, the absorbing aerosols, when lofted over the clouds, can potentially lead to significant warming of the atmosphere. The sign and magnitude of the aerosol radiative forcing over clouds are determined mainly by the amount of aerosol loading, the absorption capacity of aerosols or single-scattering albedo (SSA), and the brightness of the underlying cloud cover. In satellite-based algorithms that use measurements from passive sensors, the assumption of aerosol SSA is known to be the largest source of uncertainty in quantifying above-cloud aerosol optical depth (ACAOD). In this paper, we introduce a novel synergy algorithm that combines direct airborne measurements of ACAOD and the top-of-atmosphere (TOA) spectral reflectance from Ozone Monitoring Instrument (OMI) and Moderate Resolution Imaging Spectroradiometer (MODIS) sensors of NASA's A-train satellites to retrieve (1) SSA of light-absorbing aerosols lofted over the clouds and (2) aerosol-corrected cloud optical depth (COD). Radiative transfer calculations show a marked sensitivity of the TOA measurements to ACAOD, SSA, and COD, further suggesting that the availability of accurate ACAOD allows retrieval of SSA for above-cloud aerosol scenes using the "color ratio" algorithm developed for satellite sensors carrying ultraviolet (UV) and visible-near-IR (VNIR) wavelength bands. The proposed algorithm takes advantage of airborne measurements of ACAOD acquired from the High Spectral Resolution Lidar-2 (HSRL-2) and Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) sun photometer operated during the ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) field campaign (September 2016, August 2017, and October 2018) over the southeastern Atlantic Ocean and synergizes them with TOA reflectance from OMI and MODIS to derive spectral SSA in the near-UV (354–388 nm) and VNIR (470–860 nm), respectively. When compared against the ORACLES airborne remote sensing and in situ measurements and the inversion dataset of the ground-based Aerosol Robotic Network (AERONET) over land, the retrieved spectral SSAs from the satellites, on average, were found to be within agreement of ∼ 0.01 – the difference well within the uncertainties involved in all these inversion datasets. The retrieved SSA above the clouds at UV–Vis-NIR wavelengths shows a distinct increasing trend from August to October, which is consistent with the ORACLES in situ measurements, AERONET inversions, and previous findings. The sensitivity analysis quantifying theoretical uncertainties in the retrieved SSA shows that errors in the measured ACAOD, aerosol layer height, and the ratio of the imaginary part of the refractive index (spectral dependence) of aerosols by 20 %, 1 km, and 10 %, respectively, produce an error in the retrieved SSA at 388 nm (470 nm) by 0.017 (0.015), 0.008 (0.002), and 0.03 (0.005). The development of the proposed aerosol–cloud algorithm implies a possible synergy of Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) and OMI–MODIS passive sensors to deduce a global product of ACAOD and SSA. Furthermore, the presented synergy algorithm assumes implications for future missions, such as the Atmosphere Observing System (AOS) and the Earth Cloud Aerosol and Radiation Explorer (EarthCARE). The availability of the intended global dataset can help constrain climate models with the much-needed observational estimates of the radiative effects of aerosols in cloudy regions and expand our ability to study aerosol effects on clouds. [ABSTRACT FROM AUTHOR]

The year 2023 marked the tenth anniversary of the first published description of global ocean plankton stocks based on measurements from a satellite lidar. Diverse studies have since been conducted to further refine and validate the lidar retrievals and use them to discover new characteristics of plankton seasonal dynamics and marine animal migrations, as well as evaluate geophysical products from traditional passive ocean color sensors. Surprisingly, all of these developments have been achieved with lidar instruments not designed for ocean applications. Over this same decade, we have witnessed unprecedented changes in ocean ecosystems at unexpected rates and driven by a multitude of environmental stressors, with a dominant factor being climate warming. Understanding, predicting, and responding to these ecosystem changes requires a global ocean observing network linking satellite, in situ, and modeling approaches. Inspired by recent successes, we promote here the creation of a lidar global ocean climate record as a key element in this envisioned advanced observing system. Contributing to this record, we announce the development of a new satellite lidar mission with ocean-observing capabilities and then discuss additional technological advances that can be envisioned for subsequent missions. Finally, we discuss how a potential near-term gap in global ocean lidar data might, at least partially, be filled using on-orbit or soon-to-be-launched lidars designed for other disciplinary purposes, and we identify upcoming needs for in situ support systems and science community development. [ABSTRACT FROM AUTHOR]

Aerosol optical depth was retrieved from two airborne remote sensing instruments, the Research Scanning Polarimeter (RSP) and Second Generation High Spectral Resolution Lidar (HSRL-2), during the NASA Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE). The field campaign offers a unique opportunity to evaluate an extensive 3-year dataset under a wide range of meteorological conditions from two instruments on the same platform. However, a longstanding issue in atmospheric field studies is that there is a lack of reference datasets for properly validating field measurements and estimating their uncertainties. Here we address this issue by using the triple collocation method, in which a third collocated satellite dataset from the Moderate Resolution Imaging Spectroradiometer (MODIS) is introduced for comparison. HSRL-2 is found to provide a more accurate retrieval than RSP over the study region. The error standard deviation of HSRL-2 with respect to the ground truth is 0.027. Moreover, this approach enables us to develop a simple, yet efficient, quality control criterion for RSP data. The physical reasons for the differences in two retrievals are determined to be cloud contamination, aerosols near surface, multiple aerosol layers, absorbing aerosols, non-spherical aerosols, and simplified retrieval assumptions. These results demonstrate the pathway for optimal aerosol retrievals by combining information from both lidar and polarimeter for future airborne and satellite missions. [ABSTRACT FROM AUTHOR]

This study introduces and evaluates ocean surface wind speed retrieval capabilities of the High Spectral Resolution Lidar – generation 2 (HSRL-2) instrument through comparison with wind speed data collected by National Center for Atmospheric Research (NCAR) Airborne Vertical Atmospheric Profiling System (AVAPS) dropsondes. Wind speed is derived from HSRL-2 measurements of the transmitted laser's specular reflection off the ocean surface. The magnitude of the surface reflectivity is determined by the surface's wave-slope variance, which is driven by surface winds. The assessment relies on the multi-year airborne data set collected as part of NASA's Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) campaign, where HSRL-2 retrievals and AVAPS dropsonde measurements of surface wind speeds were horizontally synchronized owing to their joint deployment on one of two aircraft used during the mission. A total of 577 collocated HSRL-2 - dropsonde surface wind speed data points over the northwest Atlantic Ocean are used for this study. Treating the dropsonde wind speeds as truth, it is found that, through two established wind speed – wave-slope parameterizations, the HSRL-2 wind speed retrievals have small errors (0.15 m s−1 ± 1.80 m s−1 and 0.62 m s−1 ± 1.70 m s−1) and high correlation coefficients (0.89 and 0.88) with dropsonde wind speed measurements. Also, HSRL-2 wind speed error is higher in winter than in summer due at least partly to the higher frequency of low wind speeds and reduced cloud fraction in summer. Two research flights from 28 August 2020 and 1 March 2020 serve as detailed case studies to show the success of the collocation method based on ACTIVATE's spatial-coordination strategy and how HSRL-2 wind speed retrievals can enhance science-oriented studies such as those related to cloud evolution and general air-sea interaction. Another case flight examined from 11 January 2022 demonstrates the challenge of conducting HSRL-2 wind speed retrievals in high cloud fraction conditions. Overall, this study highlights the airborne HSRL-2's ability to retrieve surface wind speeds with accuracy as well as the potential of using dropsondes to validate aircraft instrument data sets within a field campaign. [ABSTRACT FROM AUTHOR]

Inadequate knowledge about the complex microphysical and optical processes of the aerosol-cloud system severely restricts our ability to quantify the resultant impact on climate. Contrary to the negative radiative forcing (cooling) exerted by aerosols in cloud-free skies over dark surfaces, the absorbing aerosols, when lofted over the clouds, can potentially lead to significant warming of the atmosphere. The sign and magnitude of the aerosol radiative forcing over clouds are determined mainly by the amount of aerosol loading, the absorption capacity of aerosols or single-scattering albedo (SSA), and the brightness of the underlying cloud cover. In the satellite-based algorithms that use measurements from passive sensors, the assumption of aerosol SSA is known to be the largest source of uncertainty in quantifying above-cloud aerosol optical depth (ACAOD). In this paper, we introduce a novel synergy algorithm that combines direct airborne measurements of ACAOD and the top-of-atmosphere (TOA) spectral reflectance from OMI and MODIS sensors of NASA's A-train satellites to retrieve 1) SSA of light-absorbing aerosols lofted over the clouds, and 2) aerosol-corrected cloud optical depth (COD). Radiative transfer calculations show a marked sensitivity of the TOA measurements to ACAOD, SSA, and COD, further suggesting that the availability of accurate ACAOD allows retrieval of SSA for above-cloud aerosols scenes using the 'color ratio' algorithm developed for satellite sensors carrying ultraviolet (UV) and visible-near-IR (VNIR) wavelength bands. The proposed algorithm takes advantage of airborne measurements of ACAOD acquired from the High-spectral Resolution Lidar-2 (HSRL-2) and Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) Sunphotometer operated during the ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) field campaign (September 2016, August 2017, and October 2018) over the southeastern Atlantic Ocean, and synergize them with TOA reflectance from OMI and MODIS to derive spectral SSA in the near-UV (354–388 nm) and VIS-near-IR (470–860 nm), respectively. When compared against the ORACLES airborne remote sensing and in situ measurements and the inversion dataset of ground-based AERONET over land, the retrieved spectral SSAs from the satellites, on average, were found to be higher overall by ~0.01–0.02—a positive bias still within the uncertainties involved in all these inversion datasets. The sensitivity analysis quantifying theoretical uncertainties in the retrieved SSA shows that errors in the measured ACAOD, aerosol layer height, and the ratio of the imaginary part of the refractive index (spectral dependence) of aerosols by 20 %, 1 km, and 10 %, respectively, produce an error in the retrieved SSA by 0.017 (0.01), 0.008 (0.001), and 0.03 (0.005) at 388 (470) nm. The development of the proposed aerosol-cloud algorithm implies a possible synergy of CALIOP lidar and OMI-MODIS passive sensors to deduce a global product of ACAOD and SSA. The availability of such global dataset can help constrain the climate models with the much-needed observational estimates of the radiative effects of aerosols in cloudy regions and expand our ability to study aerosol effects on clouds. [ABSTRACT FROM AUTHOR]

Inadequate knowledge about the complex microphysical and optical processes of the aerosol-cloud system severely restricts our ability to quantify the resultant impact on climate. Contrary to the negative radiative forcing (cooling) exerted by aerosols in cloud-free skies over dark surfaces, the absorbing aerosols, when lofted over the clouds, can potentially lead to significant warming of the atmosphere. The sign and magnitude of the aerosol radiative forcing over clouds are determined mainly by the amount of aerosol loading, the absorption capacity of aerosols or single-scattering albedo (SSA), and the brightness of the underlying cloud cover. In the satellite-based algorithms that use measurements from passive sensors, the assumption of aerosol SSA is known to be the largest source of uncertainty in quantifying above-cloud aerosol optical depth (ACAOD). In this paper, we introduce a novel synergy algorithm that combines direct airborne measurements of ACAOD and the top-of-atmosphere (TOA) spectral reflectance from OMI and MODIS sensors of NASA's A-train satellites to retrieve 1) SSA of light-absorbing aerosols lofted over the clouds, and 2) aerosol-corrected cloud optical depth (COD). Radiative transfer calculations show a marked sensitivity of the TOA measurements to ACAOD, SSA, and COD, further suggesting that the availability of accurate ACAOD allows retrieval of SSA for above-cloud aerosols scenes using the 'color ratio' algorithm developed for satellite sensors carrying ultraviolet (UV) and visible-near-IR (VNIR) wavelength bands. The proposed algorithm takes advantage of airborne measurements of ACAOD acquired from the High-spectral Resolution Lidar-2 (HSRL-2) and Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) Sunphotometer operated during the ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) field campaign (September 2016, August 2017, and October 2018) over the southeastern Atlantic Ocean, and synergize them with TOA reflectance from OMI and MODIS to derive spectral SSA in the near-UV (354-388 nm) and VIS-near-IR (470-860 nm), respectively. When compared against the ORACLES airborne remote sensing and in situ measurements and the inversion dataset of ground-based AERONET over land, the retrieved spectral SSAs from the satellites, on average, were found to be higher overall by ~0.01-0.02--a positive bias still within the uncertainties involved in all these inversion datasets. The sensitivity analysis quantifying theoretical uncertainties in the retrieved SSA shows that errors in the measured ACAOD, aerosol layer height, and the ratio of the imaginary part of the refractive index (spectral dependence) of aerosols by 20%, 1 km, and 10%, respectively, produce an error in the retrieved SSA by 0.017 (0.01), 0.008 (0.001), and 0.03 (0.005) at 388 (470) nm. The development of the proposed aerosol-cloud algorithm implies a possible synergy of CALIOP lidar and OMI-MODIS passive sensors to deduce a global product of ACAOD and SSA. The availability of such global dataset can help constrain the climate models with the much-needed observational estimates of the radiative effects of aerosols in cloudy regions and expand our ability to study aerosol effects on clouds. [ABSTRACT FROM AUTHOR]