Ozone profile measurements at high temporal and vertical resolution are needed to better understand physical processes driving tropospheric ozone variability and to validate the tropospheric ozone measurements from spaceborne missions such as TEMPO (Tropospheric Emissions: Monitoring Pollution). As part of the Tropospheric Ozone Lidar Network (TOLNet) efforts allocated to provide such measurements, and leveraging on the experience of more than 20 years of ozone lidar measurements at Table Mountain Facility, the JPL lidar group developed the SMOL (Small Mobile Ozone Lidar), an affordable differential absorption lidar (DIAL) system covering all altitudes from 150 m to 10 km a.g.l. In this abstract, we will review the main characteristics of SMOL, the preliminary results of its first field deployment during the Synergistic TEMPO Air Quality Science (STAQS) and Atmospheric Emissions and Reactions Observed from Megacities to Marine Areas (AEROMMA) campaigns in summer 2023, as well as discuss upcoming deployments and collaborations.

NASA Langley Research Center has developed the High-Altitude Lidar Observatory (HALO), a water vapor and methane Differential Absorption Lidar (DIAL) and High Spectral Resolution Lidar (HSRL) system to address the observational needs of weather, climate, carbon cycle, and atmospheric composition communities, but also serve as a technology testbed to mature and demonstrate requisite technologies need to enable future space-based water vapor and methane DIAL missions. We will present on the HALO airborne architecture, enabling technologies, and representative water vapor and methane measurements. We will also present on technologies adapted from HALO to enable a cross-cutting water vapor and methane DIAL space-based mission being advanced through the Atmospheric Boundary Layer Lidar Pathfinder (ABLE) project.

The NASA Aerosol Cloud Meteorology Interactions over the Western Atlantic Experiment (ACTIVATE) conducted 162 joint flights with two aircraft over the northwest Atlantic to study aerosol-cloud interactions (ACIs), which represent the largest uncertainty in estimating total anthropogenic radiative forcing. The combination of a high-flying King Air and low-flying HU-25 Falcon, equipped with remote sensing and in situ instruments, characterized trace gases, aerosol particles, clouds, and meteorological variables with data collected nearly simultaneously below, within, and above marine boundary layer (MBL) clouds. Flights spanning warm and cold seasons across 3 years (2020-22) provided a broad range of conditions associated with aerosol particles, cloud properties (including particle size and phase), and meteorology, ideally suited for robust ACI calculations and assessing how well models simulate a wide range of MBL clouds from stratiform to cumulus. ACTIVATE data suggest that drivers of cloud droplet number concentration Nd, including aerosol particles and MBL dynamics, vary between winter and summer months with a stronger potential to convert aerosol particles into cloud droplets in winter. Models of varying complexity not only highlight some skills in simulating winter and summer cloud types but also identify challenges that still need to be addressed such as treatment of turbulence, wet scaveng-ing, and mesoscale organization. Remote sensing advances range from new retrieval methods for Nd, cloud phase classification, vertically resolved aerosol and cloud condensation nuclei number concentration, and ocean surface wind speed. This work describes these scientific and technologi-cal advances along with efforts in outreach and open data science. SIGNIFICANCE STATEMENT: Depending on the number and type of aerosol particles there are in the air, the properties of cloud droplets can vary in number concentration, size, and lifetime, and this leads to varying effects of clouds on climate and weather. We took an ambitious approach to investigate aerosol-cloud interactions, which represent the largest uncertainty in estimating human impacts on climate change. The NASA ACTIVATE mission conducted 162 joint airborne flights over the northwest Atlantic with two spatially coordinated planes making measurements relevant to understanding clouds spanning the continuum from stratiform to cumulus clouds. Along with newfound knowledge of how clouds evolve and interact with aerosol particles, extensive technological advancements were made assisted by the carefully designed sampling strategy.

Biomass burning (BB) affects air quality and climate by releasing large quantities of gaseous and particulate pollutants into the atmosphere. Photochemical processing during daylight transforms these emissions, influencing their overall environmental impact. Accurately quantifying the photochemical drivers, namely actinic flux and photolysis frequencies, is crucial to constraining this chemistry. However, the complex radiative transfer within BB plumes presents a significant challenge for both direct observations and numerical models. This study introduces an expanded version of the 1D VLIDORT-QS radiative transfer (RT) model, named VLIDORT for photochemistry (VPC). VPC is designed for photochemical and remote sensing applications, particularly in BB plumes and other complex scenarios. To validate VPC and investigate photochemical conditions within BB plumes, the model was used to simulate spatial distributions of actinic fluxes and photolysis frequencies for the Shady wildfire (Idaho, US, 2019) based on plume composition data from the NOAA/NASA FIREX-AQ (Fire Influence on Regional to Global Environments and Air Quality) campaign. Comparison between modeling results and observations by the CAFS (charged-coupled device actinic flux spectroradiometer) yields a modeling accuracy of 10 %–20 %. Systematic biases between the model and observations are within 2 %, indicating that the uncertainties are most likely due to variability in the input data caused by the inhomogeneity of the plume as well as 3D RT effects not captured in the model. Random uncertainties are largest in the ultraviolet (UV) spectral range, where they are dominated by uncertainties in the plume particle size distribution and brown carbon (BrC) absorptive properties. The modeled actinic fluxes show a decrease from the plume top to the bottom of the plume with a strong spectral dependence caused by BrC absorption, which darkens the plume towards shorter wavelengths. In the visible (Vis) spectral range, actinic fluxes above the plume are enhanced by up to 60 %. In contrast, in the UV, actinic fluxes above the plume are not affected or even reduced by up to 10 %. Strong reductions exceeding an order of magnitude in and below the plume occur for both spectral ranges but are more pronounced in the UV.

A technique was developed to provide cloud phase information using data collected by the NASA Langley airborne High Spectral Resolution Lidar systems with a particular emphasis on mixed-phase cloud conditions, where boundaries and gradients in the distribution of ice and liquid water are critically important for microphysical and radiative processes. The method is based on the established use of depolarization to identify ice particles but incorporates a new method to separate the ice depolarization from the depolarization produced by multiple scattering in dense liquid clouds. Clouds known to be liquid-only based on ambient temperature were used to train an empirical model of the multiple-scattering depolarization that results at different ranges from the lidar. The method classifies lidar observations as liquid-dominant, mixed-phase, and ice-dominant and has an additional categorization for oriented ice. For evaluation of the retrieval, a two-aircraft approach was used with the lidar observing the same clouds that were concurrently being sampled with in situ microphysical probes. Aircraft matchups were able to track the individual cloud elements and capture marked changes in the distribution of liquid and ice across flight segments of typically 20-100 km. Qualitative features relating to localized changes in the cloud-top temperature, cloud morphology, and convective circulations were generally replicated between the lidar phase classification and the in situ microphysical data. Quantitative evaluation of the phase classification was carried out using a subset of 15 cloud scenes that satisfied strict aircraft collocation and microphysical requirements. Using the in situ microphysical data, it was found that ice extinction fractions of 14 % and 76 % most closely matched the upper and lower bounds of the lidar mixed-phase classification.

Abstract. Improved satellite-derived observations of the Direct Aerosol Radiative Effects (DARE) remain essential to reduce the uncertainty in the impact of aerosol on solar radiation. We develop a framework to compute DARE at the top of the Earth’s atmosphere, in the short-wave part of the electromagnetic spectrum and in all-sky conditions along the track of the A-Train constellation of satellites. We use combined state-of-the-art aerosol and cloud properties from satellite sensors Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and Moderate Resolution Imaging Spectroradiometer (MODIS). We also use a global reanalysis from the Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) to provide vertical distribution of aerosol properties and atmospheric conditions. Diurnal mean satellite DARE values range from -25 (cooling) to 40 W⋅m-2 (warming) over the Southeast Atlantic during three days from the NASA ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) aircraft campaign. These three days also show agreement between our satellite DARE and co-located airborne Solar Spectral Flux Radiometer (SSFR) measurements. This paper constitutes the first step before applying our algorithm to many more years of combined satellite and model data over many regions of the world. The goal is to ultimately assess the order of importance of atmospheric parameters in the calculation of DARE for specific aerosol and cloud regimes. This will inform future missions where, when and how accurately the retrievals should be performed to reduce all-sky DARE uncertainties.

Ozone profile measurements at high temporal and vertical resolution are needed to better understand physical and chemical processes driving tropospheric ozone variability and to validate the tropospheric ozone measurements from spaceborne missions such as TEMPO (Tropospheric Emissions: Monitoring Pollution). As part of the Tropospheric Ozone Lidar Network (TOLNet) efforts allocated to provide such measurements and leveraging on the experience of more than 20 years of ozone lidar measurements at Table Mountain Facility, the JPL lidar group developed the SMOL (Small Mobile Ozone Lidar), an affordable differential absorption lidar (DIAL) system covering all altitudes from 200 to 10 km above ground level (a.g.l.). The transmitter is based on a quadrupled Nd:YAG laser, which is further converted into a 289/299 nm wavelength pair using Raman shifting cells, and the receiver consists of three ozone DIAL pairs, including one that is 266/289 nm and two that are 289/299 nm. Two units were deployed in the Los Angeles basin area during the Synergistic TEMPO Air Quality Science (STAQS) and Atmospheric Emissions and Reactions Observed from Megacities to Marine Areas (AEROMMA) campaigns in summer 2023. The comparison with airborne in situ and lidar measurements shows very good agreement, with systematic differences below 10 % throughout most of the measurement range. An additional comparison with nearby surface ozone measuring instruments indicates unbiased measurements by the SMOL lidars down to 200 m a.g.l. Further comparison with the Goddard Earth Observing System Composition Forecast (GEOS-CF) model suggests that such lidars are a critical tool to perform model validation and can potentially be used for assimilation to air quality forecasts.

Surface‐level ozone is a trace gas regulated by the Environmental Protection Agency as its oxidizing properties are detrimental to air quality, impacting human and environmental health. Satellite observations provide spatially continuous intraurban ozone distributions, potentially filling in gaps within monitoring networks. However, near‐surface ozone is difficult to retrieve from columns due to the large signal in the stratosphere and lack of sensitivity to the lower troposphere in the ultraviolet wavelengths. Airborne lidar measurements of ozone profiles present the opportunity to assess vertical, geospatial, and temporal variability of lower tropospheric (0–2 km) near‐surface ozone subcolumn products for air quality analyses. This study uses the first city‐wide airborne‐lidar measurements collected by the National Aeronautics and Space Administration High‐Spectral Resolution Lidar‐2 instrument over Houston, Texas during the September 2021 Tracking Aerosol Convection ExpeRiment–Air Quality campaign alongside surface‐monitoring and ozone‐sonde measurements to examine ozone diurnal variability within a city. In situ ground measurements and lidar subcolumns were well correlated ( r = 0.87) with 2× larger differences observed in the morning than afternoon reflecting the impacts of chemical titration at the surface. Matched ozone‐sonde and airborne‐lidar subcolumns are also well correlated ( r = 0.96, bias = 1.3 ppb) suggesting biases between surface and subcolumn ozone reflect vertical distribution variability not instrument biases. Finally, if the Tropospheric Emissions: Monitoring of Pollution instrument achieves its precision requirement, we find this product may be able to detect enhanced ozone over a city like Houston with up to 55% of near‐surface subcolumns capturing ozone variability, particularly during exceedance events.

The height of the planetary boundary layer (PBLH) influences processes such as pollutant distributions, convection, and cloud formation within the troposphere. Aerosol observables play a critical role in deriving the mixed layer height (MLH) using retrieval techniques like the Haar wavelet covariance transform (WCT), which employs gradients in aerosol backscatter to estimate MLH. Currently, backscatter‐only approaches struggle with identifying very shallow stable boundary layers, distinguishing PBL from lofted residual or other aerosol layers, and profiles with very low aerosol loading. Here, we reflect on the WCT method's performance and evaluate different approaches to improve PBLH estimations. We aggregate lidar observables from recent NASA airborne field campaigns and compute MLHs based on the WCT method. Machine learning (ML) approaches are explored to produce PBLH estimates by training lidar information on thermodynamically derived PBLHs over marine and land settings. A linear model is found suitable for producing PBLH estimates in marine settings (improving mean bias by 71 m), while an ensemble tree method proves more suitable for PBLH types over land, as indicated by improved biases (13 m mean bias), errors (179 m mean error and 391 m RMSE), and correlations (+0.3) for the models explored. The algorithms are additionally tested on “unseen” data to gauge differences between MLH and PBLH estimates produced from each of the models. The PBLH estimates, composed of information from lidar and thermodynamic profiles, further support the use of ML for an automated method of PBLH prediction. Overall, these improved predictions will help evaluate models and deepen our understanding of PBL‐aerosol interactions.

The vertical distribution of wildfire smoke aerosols is important in determining its environmental impacts but existing observations of smoke heights generally do not possess the temporal resolution required to fully resolve the diurnal behavior of wildfire smoke injection. We use Weather Surveillance Radar-1988 Doppler (WSR-88D) dual polarization data to estimate injection heights of Biomass Burning Debris (BBD) generated by fires. We detect BBD as a surrogate for smoke aerosols, which are often collocated with BBD near the fire but are not within the size range detectable by these radars. Injection heights of BBD are derived for 2-10 August 2019, using WSR-88D reflectivity (Z >= 10 dBZ) and dual polarization correlation coefficients (0.2 < C.C < 0.9) to study the Williams Flats fire. Results show the expected diurnal cycles with maximum injection heights present during the late afternoon period when the fire's intensity and convective mixing are maximized. WSR-88D and airborne lidar injection height comparisons reveal that this method is sensitive to outliers and generally overpredicts maximum heights by 40%, though mean and median heights are better captured (<20% mean error). WSR-88D heights between the 75th and 90th percentile seem to accurately represent the maximum heights, with the exception of heights estimated during the occurrence of a pyro-cumulonimbus. Location specific mapping of WSR-88D and lidar injection heights reveal that they diverge further away from the fire as expected due to BBD settling. Most importantly, WSR-88D-derived injection height estimates provide near continuous smoke height information, allowing for the study of diurnal variability of smoke injections.

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 m s−1 for linear and bisector regressions, respectively, and the overall accuracy is calculated to be 0.15 ± 1.80 m s−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 m s−1, with this category comprising most of the ACTIVATE data set. The retrievals are then evaluated separately for surface wind speeds below 7 m s−1 and between 7 and 13.3 m s−1 and show that the HSRL-2 retrieves surface wind speeds with a bias of ∼ 0.5 m s−1 and an error of ∼ 1.5 m s−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 m s−1) than in the winter (0.63 ± 2.07 m s−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. 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.

Suborbital (e.g., airborne) campaigns that carry advanced remote sensing and in situ payloads provide detailed observations of atmospheric processes, but can be challenging to use when it is necessary to geographically collocate data from multiple platforms that make repeated observations of a given geographic location at different altitudes. This study reports on a data collocation algorithm that maximizes the volume of collocated data from two coordinated suborbital platforms and demonstrates its value using data from the NASA Aerosol Cloud Meteorology Interactions Over the western Atlantic Experiment (ACTIVATE) suborbital mission. A robust data collocation algorithm is critical for the success of the ACTIVATE mission goal to develop new and improved remote sensing algorithms, and quantify their performance. We demonstrate the value of these collocated data to quantify the performance of a recently developed vertically resolved lidar 1 polarimeter-derived aerosol particle number concentration (Na) product, resulting in a range -normalized mean absolute deviation (NMAD) of 9% compared to in situ measurements. We also show that this collocation algorithm increases the volume of collocated ACTIVATE data by 21% compared to using only nearest -neighbor finding algorithms alone. Additional to the benefits demonstrated within this study, the data files and routines produced by this algorithm have solved both the critical collocation and the collocation application steps for researchers who require collocated data for their own studies. This freely available and open -source collocation algorithm can be applied to future suborbital campaigns that, like ACTIVATE, use multiple platforms to conduct coordinated observations, e.g., a remote sensing aircraft together with in situ data collected from suborbital platforms.

Table S1: Two-mode, lognormal model results for aerosol number concentration (N) for different bins of distance relative to LaRC.N1 represents the mode corresponding to the smaller Dp,g while N2 corresponds to the larger Dp,g.The bolded values represent the measurements made within the smoke layer, which correspond to the FT measurements made on 22 March 2022 in the 550 -800 km range.Blank cells indicate unavailable data or when the data can be better represented by a single mode.

Extensive airborne measurements of non-methane organic gases (NMOGs), methane, nitrogen oxides, reduced nitrogen species, and aerosol emissions from US wild and prescribed fires were conducted during the 2019 NOAA/NASA Fire Influence on Regional to Global Environments and Air Quality campaign (FIREX-AQ). Here, we report the atmospheric enhancement ratios (ERs) and inferred emission factors (EFs) for compounds measured on board the NASA DC-8 research aircraft for nine wildfires and one prescribed fire, which encompass a range of vegetation types. We use photochemical proxies to identify young smoke and reduce the effects of chemical degradation on our emissions calculations. ERs and EFs calculated from FIREX-AQ observations agree within a factor of 2, with values reported from previous laboratory and field studies for more than 80 % of the carbon- and nitrogen-containing species. Wildfire emissions are parameterized based on correlations of the sum of NMOGs with reactive nitrogen oxides (NOy) to modified combustion efficiency (MCE) as well as other chemical signatures indicative of flaming/smoldering combustion, including carbon monoxide (CO), nitrogen dioxide (NO2), and black carbon aerosol. The sum of primary NMOG EFs correlates to MCE with an R2 of 0.68 and a slope of −296 ± 51 g kg−1, consistent with previous studies. The sum of the NMOG mixing ratios correlates well with CO with an R2 of 0.98 and a slope of 137 ± 4 ppbv of NMOGs per parts per million by volume (ppmv) of CO, demonstrating that primary NMOG emissions can be estimated from CO. Individual nitrogen-containing species correlate better with NO2, NOy, and black carbon than with CO. More than half of the NOy in fresh plumes is NO2 with an R2 of 0.95 and a ratio of NO2 to NOy of 0.55 ± 0.05 ppbv ppbv−1, highlighting that fast photochemistry had already occurred in the sampled fire plumes. The ratio of NOy to the sum of NMOGs follows trends observed in laboratory experiments and increases exponentially with MCE, due to increased emission of key nitrogen species and reduced emission of NMOGs at higher MCE during flaming combustion. These parameterizations will provide more accurate boundary conditions for modeling and satellite studies of fire plume chemistry and evolution to predict the downwind formation of secondary pollutants, including ozone and secondary organic aerosol.

Coupled atmosphere and ocean remote sensing retrievals of aerosol, cloud, and oceanic phytoplankton microphysical properties, such as those carried out by the NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission, involve single -scattering calculations that are time consuming. Lookup tables (LUTs) exist to speed up these calculations for aerosol and water droplets in the atmosphere. In our new Lorenz-Mie lookup table, we tabulate single scattering by an ensemble of coated isotropic spheres representing oceanic phytoplankton at wavelengths from 0.355 mu m. The lookup table covers phytoplankton particles with radii in the range of 0.15-100 mu m at an increase of up to 10 4 in computational speed compared to single -scattering calculations. The allowed complex refractive indices range from 1.05 to 1.24 for the shell's real part, from 10 (-7) to 0.3 for the shell's imaginary part, from 0 to 0.001 for the core's imaginary part, and equal to 1.02 for the core's real part. We show that we precisely compute inherent optical properties for the phytoplankton size distributions ranging up to 5 mu m for the effective radius and up to 0.6 for the effective variance. We test wavelengths from 0.355 to 1.065 mu m and find that all the inherent optical properties of interest agree with the single -scattering calculations to within 1% for 99.9% of cases. We also provide an example of using the lookup table to reproduce the phytoplankton optical datasets listed in the PANGAEA database for synthetic hyperspectral algorithm development. The table together with C ++, Fortran, MATLAB, and Python codes to apply different complex refractive indices and phytoplankton size distributions is freely available online.

Process modeling of Aerosol-cloud interaction (ACI) is essential to bridging gaps between observational analysis and climate modeling of aerosol effects in the Earth system and eventually reducing climate projection uncertainties. In this study, we examine ACI in summertime precipitating shallow cumuli observed during the Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE). Aerosols and precipitating shallow cumuli were extensively observed with in-situ and remote-sensing instruments during two research flight cases on 02 June and 07 June, respectively, during the ACTIVATE summer 2021 deployment phase. We perform observational analysis and large-eddy simulation (LES) of aerosol effect on precipitating cumulus in these two cases. Given the measured aerosol size distributions and meteorological conditions, LES is able to reproduce the observed cloud properties by aircraft such as liquid water content (LWC), cloud droplet number concentration (Nc) and effective radius reff. However, it produces smaller liquid water path (LWP) and larger Nc compared to the satellite retrievals. Both 02 and 07 June cases are over warm waters of the Gulf Stream and have a cloud top height over 3 km, but the 07 June case is more polluted and has larger LWC. We find that the Na-induced LWP adjustment is dominated by precipitation feedback for the 2 June precipitating case and there is no clear entrainment feedback in both cases. An increase of cloud fraction due to a decrease of aerosol number concentration is also shown in the simulations for the 02 June case. Aerosol-cloud-interaction (ACI) regulates the energy budget of the Earth and poses the largest uncertainty in climate projection. Particularly, ACI of low clouds is poorly understood and causes the spread of Earth System Models (ESMs) in predicting cloud and climate responses to aerosol changes. Process studies have shown a nonlinear cloud water amount and cloud fraction adjustments due to aerosol changes via precipitation and cloud top entrainment, which are not often captured correctly in ESMs. This study explores the physical mechanisms of ACI in marine low clouds with a focus on precipitating low clouds using a cloud process model and unprecedented field campaign measurements of meteorology states, cloud properties, and aerosols collected during the Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment. We show that the aerosol-induced cloud water amount adjustment is dominated by changes in precipitation and there is no clear entrainment feedback in both cases. Our findings can help improve the representation of ACI within precipitating marine low clouds in ESMs. Aerosol-cloud interactions in precipitating shallow cumuli are investigated using large-eddy simulations (LES) and observations LES show that aerosol-induced cumulus cloud water adjustment is dominated by precipitation with no clear entrainment feedback An increase in cloud fraction in response to aerosol number concentration decrease is shown in the precipitating cumuli

The western North Atlantic Ocean is strongly influenced by continental outflow, making it an ideal region to study the atmospheric transition from a polluted coastline to the marine environment. Utilizing eight transit flights between the NASA Langley Research Center (LaRC) in Hampton, Virginia, and the remote island of Bermuda from NASA's Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE), we examine the evolution of trace gas and aerosol properties off the US East Coast. The first pair of flights flew along the wind trajectory of continental outflow, while the other flights captured a mix of marine and continental air mass sources. For measurements within the boundary layer (BL), there was an offshore decline in particle N<100 nm, N>100 nm, CH4, CO, and CO2 concentrations, all leveling off around ∼900 km offshore from the LaRC. These trends are strongest for the first pair of flights. In the BL, offshore declines in organic mass fraction and increases in sulfate mass fraction coincide with increasing hygroscopicity based on f(RH) measurements. Free troposphere measurements show a decline in N<100 nm, but other measured parameters are more variable when compared to the prominent offshore gradients seen in the BL. Pollution layers exist in the free troposphere, such as smoke plumes, that can potentially entrain into the BL. This work provides detailed case studies with a broad set of high-resolution measurements to further our understanding of the transition between continental and marine environments.

Airborne high spectral resolution lidar (HSRL) measurements of ocean particulate backscatter (bbp) offer dramatic improvements in spatiotemporal coverage over in situ techniques, filling observational “blind spots” that limit our ability to study ocean processes. However, the technique has been assessed in only a few limited cases, and uncertainties remain regarding its applicability across a diversity of optical domains. In this study, we present the first comprehensive comparison of bbp derived from airborne HSRL, satellite ocean color, and in situ measurements to increase confidence in HSRL bbp retrievals and to demonstrate the value of airborne HSRL for assessing/improving satellite ocean color algorithms. Retrievals of bbp performed using the NASA Langley HSRL-1 instrument agreed with in situ measurements performed across a diversity of optical and ecological domains. Comparisons across multiple campaigns revealed regional and seasonal dependencies in the ocean color retrievals that likely resulted from applying a single configuration of the ocean color retrieval across multiple distinct domains. In two case studies, atmospheric measurements from HSRL-1 and systematic differences in bbp between HSRL and the 2018 NASA ocean color distribution provided evidence of insufficient atmospheric correction of the ocean color retrieval. These differences in bbp were absent from comparisons against the 2022 ocean color distribution, suggesting that changes made to the algorithm resulted in improved retrievals. These cases highlight the advantages of airborne HSRL for assessing and improving ocean color retrievals, namely its ability to provide simultaneous, independent profiles of atmosphere and ocean optical properties, and improvements in the spatiotemporal coverage of satellite matchups.

The High-Spectral-Resolution Lidar (HSRL) Pathfinder Mission concept is designed to provide HSRL measurements at 532 nm and elastic backscatter lidar measurements at 1064 nm. The instrument is based on Clio, the HSRL that was descoped from NASA's Atmosphere Observing System (AOS) mission due to cost constraints. The NASA Langley Research Center (LaRC) developed the HSRL Pathfinder concept as an example of a lower-cost mission to advance the technology and demonstrate the measurement capability originally planned for AOS. Cost savings are achieved via a Class-D instrument development approach and some reductions in performance from the original Clio design. Despite these changes, the HSRL Pathfinder Mission promises to provide valuable observations for advancing studies of aerosol and cloud radiative effects, cloud microphysics, aerosol-cloud interaction, aerosol transport and speciation, and air quality. The design also enables scientifically important observations of depth-resolved ocean subsurface optical properties, snow water equivalent, and seasonal sea ice, making HSRL Pathfinder a truly multifunctional lidar mission.