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The NASA Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) produced a unique dataset for research into aerosol-cloud-meteorology interactions with applications extending from process-based studies to multi-scale model intercomparison and improvement, and remote sensing algorithm assessments and advancements. ACTIVATE used two NASA Langley Research Center aircraft, a HU-25 Falcon and King Air, to conduct systematic and spatially coordinated flights over the northwest Atlantic Ocean amounting to 162 joint flights and 17 other single-aircraft flights between 2020 and 2022 across all seasons. Data cover 574 and 592 cumulative flights hours for the Falcon and King Air, respectively. The HU-25 Falcon flew conducted profiling at different level legs below, in, and just above boundary layer clouds (< 3 km) and obtained in situ measurements of trace gases, aerosol particles, clouds, and atmospheric state parameters. In cloud-free conditions, the Falcon similarly conducted profiling at different level legs within and immediately above the boundary layer. The King Air (the high-flyer) flew at approximately ~9 km conducting remote sensing with a lidar and polarimeter while also launching dropsondes. Collectively, simultaneous data collected from both aircraft help characterize the same vertical column of the atmosphere. In addition to individual instrument files, data from the Falcon aircraft are combined into “merge files” on the publicly available data archive that are created at different time resolutions of interest (e.g., 1, 5, 10, 15, 30, 60 s, or matching an individual data product start and stop times). This paper describes the ACTIVATE flight strategy, instrument and complementary dataset products, data access and usage details, and data application notes.

Impacts of small-scale surface irregularities, or surface roughness, of atmospheric ice crystals on lidar backscattering properties are quantified. Geometric ice crystal models with various degrees of surface roughness and state-of-the-science light-scattering computational capabilities are used to simulate single-scattering properties across the entire practical size parameter range. The simulated bulk lidar and depolarization ratios of polydisperse ice crystals at 532 nm are strongly sensitive to the degree of surface roughness. Comparisons of these quantities between the theoretical simulations and counterparts inferred from spaceborne lidar observations for cold cirrus clouds suggest a typical surface roughness range of 0.03–0.15, which is most consistent with direct measurements of scanning electron microscopic images. The degree of surface roughness needs to be accounted for to properly interpret lidar backscattering observations of ice clouds.

Using collocated NASA Cloud Physics Lidar (CPL) and Research Scanning Polarimeter (RSP) data from the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) campaign, a new observational-based method was developed which uses aK-means clustering technique to classify ice crystal habit types into seven categories: column, plates, rosettes, spheroids, and three different type of irregulars. Intercompared with the collocated SPEC, Inc., Cloud Particle Imager (CPI) data, the frequency of the detected ice crystal habits from the proposed method presented in the study agrees within 5% with the CPI-reported values for columns, irregulars, rosettes, and spheroids, with more disagreement for plates. This study suggests that a detailed ice crystal habit retrieval could be applied to combined space-based lidar and polarimeter observations such asCALIPSOand POLDER in addition to future missions such as the Aerosols, Clouds, Convection, and Precipitation (A-CCP).

We provide a parameterization of the extinction efficiency, single-scattering albedo, and asymmetry parameter of single ice crystals with any combination of particle volume, projected area, component aspect ratio, and crystal distortion at any wavelength between 0.2 and 100 μm. The parameterization is an extension of the one previously published by van Diedenhoven et al. In addition, the parameterized optical properties are integrated over size distributions yielding bulk extinction efficiencies, single-scattering albedos, and asymmetry parameters for large ranges of effective radii, particle component aspect ratios, and crystal distortion values. The parameterization of single-particle optical properties is evaluated with a reference database. The bulk optical properties are evaluated against the ice model selected for the Moderate Resolution Imaging Spectroradiometer (MODIS) collection 6 products, for which accurate optical properties are available. Mean absolute errors in parameterized extinction efficiency, asymmetry parameter, and single-scattering albedo are shown to be 0.0272, 0.008 90, and 0.004 68, respectively, for shortwave wavelengths, while they are 0.0641, 0.0368, and 0.0200 in the longwave. Shortwave and longwave asymmetry parameters and single-scattering albedos are shown to vary strongly with particle component aspect ratio and distortion, resulting in substantial variation in shortwave fluxes, but relatively small variations in longwave cloud emissivity. The parameterization and bulk optical properties are made publicly available.

The cloud drop effective radius, Re, of the drop size distribution derived from passive satellite sensors is a key variable used in climate research. Validation of these satellite products often took place in stratiform cloud conditions that favored the assumption of cloud horizontal homogeneity used by the retrieval techniques. However, many studies point to concerns of significant biases in retrieved Re arising from cloud heterogeneity, for example, in cumulus cloud fields. Here, we examine data collected during the 2019 Cloud, Aerosol and Monsoon Processes Philippines Experiment (CAMP2Ex), which, in part, targeted the objective of providing the first detailed evaluation of Re retrieved across multiple platforms and techniques in a cumulus and congestus cloud region. Our evaluation consists of cross comparisons of Re between the MODerate resolution Imaging Spectroradiometer (MODIS) onboard the Terra satellite, the Research Scanning Polarimeter (RSP) onboard the NASA P-3 aircraft, and in situ measurements from both the P-3 and Learjet aircrafts that are all taken in close space-time proximity of the same cloud fields. A particular advantage of our approach lies in RSP’s capability to retrieve Re using a bi-spectral MODIS approach and a polarimetric approach, which allows for evaluating bi-spectral and polarimetric Re retrievals from an airborne perspective using the same samples. Averaged over all P-3 flight segments examined here for warm clouds, the RSP-polarimetric, in situ, and the bias-adjusted MODIS method of Fu et al. (2019) show comparable median (mean and standard deviations) of Re samples of 9.6 (10.2 ± 4.0) μm, 11.0 (13.6 ± 11.3) μm, and 10.4 (10.8 ± 3.8) μm, respectively. These values are far lower than 15.1 (16.2 ± 5.5) μm and 17.2 (17.7 ± 5.7) μm from the bi-spectral retrievals of RSP and MODIS, respectively. Similar results are observed when Re is segregated by cloud top height and in detailed case studies. The clouds sampled during CAMP2Ex consist of mostly small (mean transect length ~1.4 km) and low clouds (mean cloud top height ~ 1 km), which are much smaller than the trade wind cumuli sampled in past field campaigns such as Rain in Shallow Cumulus over the Ocean (RICO) and the Indian Ocean Experiment (INDOEX). RSP bi-spectral Re shows larger relative values compared to RSP polarimetric Re for smaller and optically thinner clouds. Drizzle, cloud top bumpiness and solar-zenith angle, however, are not closely correlated with the overestimate of bi-spectral Re. We show that for shallow, non-drizzling clouds that dominate the liquid cloud cover for the CAMP2Ex region and period, 3D radiative pathways appear to be the leading cause for the large positive biases in bi-spectral retrievals. Because this bias varies with the underlying structure of the cloud field, caution continues to be warranted in studies that use bi-spectral Re retrievals in cumulus cloud fields.

This study develops the use of spectral total and diffuse irradiance measurements, made from a prototype hyperspectral total-diffuse Sunshine Pyranometer (SPN-S), to retrieve layer fine-mode aerosol (τaer) and total optical depths from airborne platforms. Additionally, we use spectral analysis in an attempt to partition the total optical depth it into its τaer and cirrus cloud optical depth (τcld) components in the absence of coarse-mode aerosols. Two retrieval methods are developed: one leveraging information in the diffuse irradiance, and the other using spectral characteristics of the transmitted direct beam, with each approach best suited for specific cloud and aerosol conditions. SPN-S has advantages over traditional sun-photometer systems including no moving parts and a low cost. However, a significant drawback of the instrument is that it is unable to measure the direct beam irradiance as accurately as sun-photometers. To compensate for the greater measurement uncertainty of the radiometric irradiances these retrieval techniques employ ratioed inputs or spectral information to reduce output uncertainty. This analysis uses irradiance measurements from SPN-S and the Solar Spectral Flux Radiometer (SSFR) aboard the National Aeronautics and Space Administration’s (NASA) P-3 aircraft during the 2018 deployment of the ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) campaign and the 2019 Cloud, Aerosol and Monsoon Processes Philippines Experiment (CAMP2Ex) mission to quantify above-aircraft cirrus τcld and derive vertical profiles of layer τaer. Validation of the τaer retrieval is accomplished by comparison with collocated measurements of direct solar irradiance made by the Sky-Scanning Sun-Tracking Atmospheric Research (4STAR) and in situ measurements of aerosol optical depth. For the aggregated 2018 ORACLES results, regression between the SPN-S based method and sun-photometer τaer values yield a slope of 0.96 with an R2 of 0.96, while the root-mean-square error (RMSE) is 3.0 × 10−2. When comparing the retrieved τaer to profiles of integrated in situ measurements of optical extinction, the slope, R2, and RMSE values for ORACLES are 0.90, 0.96, 3.4 × 10−2, and for CAMP2Ex are 0.94, 0.97, 3.4 × 10−2 respectively. This paper is a demonstration of methods for deriving cloud and aerosol optical properties in environments where both atmospheric constituents may be present. With improvements to the low-cost SPN-S radiometer instrument, it may be possible to extend these methods to a broader set of sampling applications, such as ground-based settings.

Cloud droplet number concentration (Nd) is an important parameter of liquid clouds and is crucial to understanding aerosol-cloud interactions. It couples boundary layer aerosol composition, size and concentration with cloud reflectivity. It affects cloud evolution, precipitation, radiative forcing, global climate and, through observation, can be used to partially monitor the first indirect effect. With its unique combination of multi-wavelength, multi-angle, total and polarized reflectance measurements, the Research Scanning Polarimeter (RSP) retrieves Nd with relatively few assumptions. The approach involves measuring cloud optical thickness, mean droplet extinction cross-section and cloud physical thickness. Polarimetric observations are capable of measuring the effective variance, or width, of the droplet size distribution. Estimating cloud geometrical thickness is also an important component of the polarimetric Nd retrieval, which is accomplished using polarimetric measurements in a water vapor absorption band to retrieve the amount of in-cloud water vapor and relating this to physical thickness. We highlight the unique abilities and quantify uncertainties of the polarimetric approach. We validate the approach using observational data from the North Atlantic and Marine Ecosystems Study (NAAMES). NAAMES targets specific phases in the seasonal phytoplankton lifecycle and ocean-atmosphere linkages. This study provides an excellent opportunity for the RSP to evaluate its approach of sensing Nd over a range of concentrations and cloud types with in situ measurements from a Cloud Droplet Probe (CDP). The RSP and CDP, along with an array of other instruments, are flown on the NASA C-130 aircraft, which flies in situ and remote sensing legs in sequence. Cloud base heights retrieved by the RSP compare well with those derived in situ (R = 0.83) and by a ceilometer aboard the R.V. Atlantis (R = 0.79). Comparing geometric mean values from 12 science flights throughout the NAAMES-1 and NAAMES-2 campaigns, we find a strong correlation between Nd retrieved by the RSP and CDP (R = 0.96). A linear least squares fit has a slope of 0.92 and an intercept of 0.3 cm−3. Uncertainty in this comparison can be attributed to cloud 3D effects, nonlinear liquid water profiles, multilayered clouds, measurement uncertainty, variation in spatial and temporal sampling, and assumptions used within the method. Radiometric uncertainties of the RSP measurements lead to biases on derived optical thickness and cloud physical thickness, but these biases largely cancel out when deriving Nd for most conditions and geometries. We find that a polarimetric approach to sensing Nd is viable and the RSP is capable of accurately retrieving Nd for a variety of cloud types and meteorological conditions.

This paper describes a neural network algorithm for the estimation of liquid water cloud optical properties from the Polarization and Directionality of Earth's Reflectances-3 (POLDER-3) instrument aboard the Polarization & Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar (PARASOL) satellite. The algorithm has been trained on synthetic multi-angle, multi-wavelength measurements of reflectance and polarization and has been applied to the processing of 1 year of POLDER-3 data. Comparisons of the retrieved cloud properties with Moderate Resolution Imaging Spectroradiometer (MODIS) products show that the neural network algorithm has a low bias of around 2 in cloud optical thickness (COT) and between 1 and 2 µm in the cloud effective radius. Comparisons with existing POLDER-3 datasets suggest that the proposed scheme may have enhanced capabilities for cloud effective radius retrieval, at least over land. An additional feature of the presented algorithm is that it provides COT and effective radius retrievals at the native POLDER-3 Level 1B pixel level.

We quantify the performance of aerosol and ocean remote sensing products from the PolCube instrument using a previously developed polarimeter retrieval algorithm based on optimal estimation. PolCube is a modified version of the PolCam lunar instrument on the Korea Pathfinder Lunar Orbiter that has been optimized for Earth-Science observations of aerosol, ocean, and thin cloud optical properties. The objective of the PolCube instrument is to retrieve detailed fine-mode (pollution and smoke) and coarse-mode (sea-salt and dust) aerosol properties over the ocean for a range of light to heavy aerosol loadings using its polarimetric-imaging capability at multiple angles and wavelengths from 410−865 nm. An additional objective is to discriminate aerosols from thin clouds. PolCube’s retrieval performance of aerosol optical and microphysical properties and ocean products is quantitatively assessed. We estimate that PolCube can retrieve total aerosol optical depth at 555 nm (AOD555) within ±0.068, fine-mode AOD555 within ±0.078, and fine-mode single-scattering albedo within ±0.036, where all uncertainties are expressed as one standard deviation (1σ). PolCube’s accurate and high-resolution aerosol-retrieval products will provide unique spatial and temporal coverage of the Earth that can be used synergistically with other instruments, such as the Geostationary Environmental Monitoring Spectrometer to improve air-quality forecasting.

The Western North Atlantic Ocean (WNAO) and adjoining East Coast of North America are of great importance for atmospheric research and have been extensively studied for several decades. This broad region exhibits complex meteorological features and a wide range of conditions associated with gas and particulate species from many sources regionally and other continents. As Part 1 of a 2-part paper series, this work characterizes quantities associated with atmospheric chemistry, including gases, aerosols, and wet deposition, by analyzing available satellite observations, ground-based data, model simulations, and reanalysis products. Part 2 provides insight into the atmospheric circulation, boundary layer variability, three-dimensional cloud structure, properties, and precipitation over the WNAO domain. Key results include spatial and seasonal differences in composition along the North American East Coast and over the WNAO associated with varying sources of smoke and dust and meteorological drivers such as temperature, moisture, and precipitation. Spatial and seasonal variations of tropospheric carbon monoxide and ozone highlight different pathways toward the accumulation of these species in the troposphere. Spatial distributions of speciated aerosol optical depth and vertical profiles of aerosol mass mixing ratios show a clear seasonal cycle highlighting the influence of different sources in addition to the impact of intercontinental transport. Analysis of long-term climate model simulations of aerosol species and satellite observations of carbon monoxide confirm that there has been a significant decline in recent decades among anthropogenic constituents owing to regulatory activities.

This study presents a new algorithm that combines W-band reflectivity measurements from the Airborne Precipitation Radar-3rd generation (APR-3), passive radiometric cloud optical depth and effective radius retrievals from the Research Scanning Polarimeter (RSP) to estimate total liquid water path in warm clouds and identify the contributions from cloud water path (CWP) and rainwater path (RWP). The resulting CWP estimates are primarily determined by the optical depth input, although reflectivity measurements contribute ~ 10–50 % of the uncertainty due to attenuation through the profile. Uncertainties in CWP estimates across all conditions are 25 % to 35 %, while RWP uncertainty estimates frequently exceed 100 %. Two thirds of all radar-detected clouds observed during the ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) campaign that took place from 2016–2018 over the southeast Atlantic Ocean have CWP between 41 and 168 g m−2 and almost all CWPs (99 %) between 6 to 445 g m−2. RWP, by contrast, typically makes up a much smaller fraction of total liquid water path (LWP) with more than 70 % of raining clouds having less than 10 g m−2 of rainwater. In heavier warm rain (i.e. rain rate exceeding 40 mm h−1 or 1000 mm d−1), however, RWP is observed to exceed 2500 g m−2. CWP (RWP) is found to be approximately 30 g m−2 (7 g m−2) larger in unstable environments compared to stable environments. Surface precipitation is also more than twice as likely in unstable environments. Comparisons against in-situ cloud microphysical probe data spanning the range of thermodynamic stability and meteorological conditions encountered across the southeast Atlantic basin demonstrate that the combined APR-3 and RSP dataset enable a robust joint cloud-precipitation retrieval algorithm to support future ORACLES precipitation susceptibility and cloud–aerosol–precipitation interaction studies.

The Research Scanning Polarimeter (RSP) is an airborne along-track scanner measuring the polarized and total reflectances with high angular resolution. It allows for accurate characterization of liquid water cloud droplet sizes using the rainbow structure in the polarized reflectance. RSP’s observations also provide constraints on the cumulus cloud’s 2D cross section, yielding estimates of its geometric shape. In this study for the first time we evaluate the possibility to retrieve vertical profiles of microphysical characteristics along the cloud side by combining these micro- and macrophysical retrieval methods. First we constrain cloud’s geometric shape, then for each point on the bright side of its surface we collect data from different scans to obtain the multi-angle polarized reflectance at that point. The rainbow structures of the reflectances from multiple points yield the corresponding droplet size distributions (DSDs), which are then combined into vertical profiles. We present the results of testing the proposed profiling algorithm on simulated data obtained using large eddy simulations and 3D radiative transfer computations. The virtual RSP measurements were used for retrieval of DSD profiles, which then were compared to the actual data from the LES-model output. A cumulus congestus cloud was selected for these tests in preparation for analysis of real measurements made during the Cloud, Aerosol and Monsoon Processes Philippines Experiment (CAMP(2)Ex). We demonstrate that the use of the non-parametric Rainbow Fourier Transform (RFT) allows for adequate retrieval of the complex altitude-dependent bimodal structure of cloud DSDs.

Cloud top height (CTH) affects the radiative properties of clouds. Improved CTH observations will allow for improved parameterizations in large-scale models and accurate information on CTH is also important when studying variations in freezing point and cloud microphysics. NASA's airborne Research Scanning Polarimeter (RSP) is able to measure cloud top height using a novel multi-angular contrast approach. For the determination of CTH, a set of consecutive nadir reflectances is selected and the cross correlations between this set and collocated sets at other viewing angles are calculated for a range of assumed cloud top heights, yielding a correlation profile. Under the assumption that cloud reflectances are isotropic, local peaks in the correlation profile indicate cloud layers. This technique can be applied to every RSP footprint and we demonstrate that detection of multiple peaks in the correlation profile allows retrieval of heights of multiple cloud layers within single RSP footprints. This paper provides an in-depth description of the architecture and performance of the RSP's CTH retrieval technique using data obtained during the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) campaign. RSP-retrieved cloud heights are evaluated using collocated data from the Cloud Physics Lidar (CPL). The method's accuracy associated with the magnitude of correlation, optical thickness, cloud thickness and cloud height are explored. The technique is applied to measurements at a wavelength of 670 and 1880 nm and their combination. The 1880 nm band is virtually insensitive to the lower troposphere due to strong water vapor absorption. It is found that each band is well suitable for retrieving heights of cloud layers with optical thicknesses above about 0.1 and that RSP cloud layer height retrievals more accurately correspond to CPL cloud middle than cloud top. It is also found that the 1880 nm band yields the most accurate results for clouds at middle and high altitudes (4.0 to 17 km), while the 670 nm band is most accurate at low and middle altitudes (1.0–13.0 km). The dual band performs best over the broadest range and is suitable for accurately retrieving cloud layer heights between 1.0 and 16.0 km. Generally, the accuracy of the retrieved cloud top heights increases with increasing correlation value. Improved accuracy is achieved by using customized filtering techniques for each band with the most significant improvements occurring in the primary layer retrievals. RSP is able to measure a primary layer CTH with a median error of about 0.5 km when compared to CPL. For multilayered scenes, the second and third layer heights are determined median errors of about 1.5 and 2.0–2.5 km, respectively.

International audience; The sizes and shapes of ice crystals in clouds affect fundamental microphysical processes, such as sedimentation and aggregation, as well as their optical properties. The evolution of ice crystal size and shape depends on temperature and supersaturation, as well as on other processes that may lead to various coexisting complex shapes. Here we present a global assessment of collocated size and shape characteristics and shortwave scattering properties of ice crystals at the tops of optically thick clouds inferred from space-borne multiwavelength reflectance measurements and multiangle polarimetry. The results indicate systematic covariations of ice size, shape, and distortion, as well as variations with temperature that can be plausibly related to simplified ice crystal growth theory and in situ and laboratory data. This simplicity may be attributable to the temperature dependence of cloud top ice size and shapes commonly being dominated by vapor growth at conditions similar to those at cloud top. Such a conclusion may be viewed as somewhat surprising given the expectation that ice properties at cloud top will be an integral manifestation of processes occurring at lower levels within updrafts. We also find that, contrary to commonly used models, ice scattering asymmetry parameters decrease with increasing effective radius, reducing sensitivity of cloud reflectance to particle size.

High accuracy multi-angle polarimetry is of crucial importance for remote sensing of aerosol and cloud properties with accuracies demanded by climate and air quality studies. In this contribution, we provide an detailed description of the multi-angle spectro-polarimetric instrument “SPEX airborne” that was developed to operate from NASA’s high altitude research aircraft ER-2. SPEX airborne delivers measurements of radiance and linear polarization at nine fixed viewports with angles equally distributed over at total angular range of 112°, at visual wavelength in the range 400-760nm. Each viewport acts as a pushbroom spectrometer with a swath of 6°. SPEX airborne participated in the recent the ACEPOL campaign in October-November 2017 when it flew together with NASA’s Research Scanning Polarimeter (RSP), the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI), and the Airborne Hyper-Angular Rainbow Polarimeter (AirHARP). We compare polarimetric and radiometric measurements from SPEX airborne with those collected by RSP at four visible wavelength bands. Simultaneous measurements were made while flying over widely different scenes, under different illumination and meteorological conditions. This provided a large dynamic range in radiometric and polarimetric values. We find that the Degree of Linear Polarization (DoLP) measured by both instruments agrees well with a RMS differences of ~0.005 as the best result for 555nm. For radiance measurements excellent agreement is obtained with a RMS difference of ~4%. The in-flight comparison results provide verification of SPEX airborne’s capability to deliver high-quality data.

Supercooled liquid water (SLW) clouds, where liquid droplets exist at temperatures below 0°C present a well-known aviation hazard through aircraft icing, in which SLW accretes on the airframe. SLW clouds are common over the Southern Ocean, and climate-induced changes in their occurrence is thought to constitute a strong cloud feedback on global climate. The two recent NASA field campaigns POlarimeter Definition EXperiment (PODEX, based in Palmdale, California, January–February 2013) and Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS, based in Houston, Texas in August–September 2013) provided a unique opportunity to observe SLW clouds from the high-altitude airborne platform of NASA's ER-2 aircraft. We present an analysis of measurements made by the Research Scanning Polarimeter (RSP) during these experiments accompanied by correlative retrievals from other sensors. The RSP measures both polarized and total reflectance in 9 spectral channels with wavelengths ranging from 410 to 2250 nm. It is a scanning sensor taking samples at 0.8° intervals within 60° from nadir in both forward and backward directions. This unique angular resolution allows for characterization of liquid water droplet size using the rainbow structure observed in the polarized reflectances in the scattering angle range between 135° and 165°. Simple parametric fitting algorithms applied to the polarized reflectance provide retrievals of the droplet effective radius and variance assuming a prescribed size distribution shape (gamma distribution). In addition to this, we use a non-parametric method, Rainbow Fourier Transform (RFT), which allows retrieval of the droplet size distribution without assuming a size distribution shape. We present an overview of the RSP campaign datasets available from the NASA GISS website, as well as two detailed examples of the retrievals. In these case studies we focus on cloud fields with spatial features varying between glaciated and liquid phases at altitudes as high as 10 km, which correspond to temperatures close to the homogeneous freezing temperature of pure water drops (about -35°C or colder). The multimodal droplet size distributions retrieved from RSP data in these cases are consistent with the multi-layer cloud structure observed by correlative Cloud Physics Lidar (CPL) measurements.

Single-crystal images collected in mid-latitude cirrus are analyzed to provide internally consistent ice physical and optical properties for a size-resolved cloud microphysics model, including single-particle mass, projected area, fall speed, capacitance, single-scattering albedo, and asymmetry parameter. Using measurements gathered during two flights through a widespread synoptic cirrus shield, bullet rosettes are found to be the dominant identifiable habit among ice crystals with maximum dimension (Dmax) greater than 100 µm. Properties are therefore first derived for bullet rosettes based on measurements of arm lengths and widths, then for aggregates of bullet rosettes and for unclassified (irregular) crystals. Derived bullet rosette masses are substantially greater than reported in existing literature, whereas measured projected areas are similar or lesser, resulting in factors of 1.5–2 greater fall speeds, and, in the limit of large Dmax, near-infrared single-scattering albedo and asymmetry parameter (g) greater by ∼ 0.2 and 0.05, respectively. A model that includes commonly imaged side plane growth on bullet rosettes exhibits relatively little difference in microphysical and optical properties aside from ∼ 0.05 increase in mid-visible g primarily attributable to plate aspect ratio. In parcel simulations, ice size distribution, and g are sensitive to assumed ice properties.

A novel technique is used to estimate derivatives of ice effective radius with respect to height near convective cloud tops (dre /dz) from airborne shortwave reflectance measurements and lidar. Values of dre /dz are about -6 μm/km for cloud tops below the homogeneous freezing level, increasing to near 0 μm/km above the estimated level of neutral buoyancy. Retrieved dre /dz compares well with previously documented remote sensing and in situ estimates. Effective radii decrease with increasing cloud top height, while cloud top extinction increases. This is consistent with weaker size sorting in high, dense cloud tops above the level of neutral buoyancy where fewer large particles are present, and with stronger size sorting in lower cloud tops that are less dense. The results also confirm that cloud-top trends of effective radius can generally be used as surrogates for trends with height within convective cloud tops. These results provide valuable observational targets for model evaluation.

This paper describes a neural network algorithm for the estimation of liquid water cloud optical properties from the Polarization and Directionality of Earth's Reflectances-3 (POLDER-3) instrument, on board the Polarization & Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar (PARASOL) satellite. The algorithm has been trained on synthetic multi-angle, multi-wavelength measurements of reflectance and polarization, and has been applied to the processing of one year of POLDER-3 data. Comparisons of the retrieved cloud properties with Moderate resolution Imaging Spectroradiometer (MODIS) products show negative biases around −2 in retrieved cloud optical thicknesses (COTs) and between −1 and −2 μm in retrieved cloud effective radii. Comparisons with existing POLDER-3 datasets suggest that the proposed scheme may have enhanced capabilities for cloud effective radius retrieval at least over land. An additional feature of the presented algorithm is that it provides COT and effective radius retrievals at the native POLDER-3 Level 1B pixel level.