Saharan dust is frequently transported across the Atlantic, yet the chemical, physical, and morphological transformations dust undergoes within the marine atmospheric boundary layer (MABL) remain poorly understood. These transformations are critical for understanding dust's radiative and geochemical impacts, it's representation in atmospheric models, and detection via remote sensing. Here, we present coordinated observations from the Office of Naval Research's Moisture and Aerosol Gradients/Physics of Inversion Evolution (MAGPIE) August 2023 campaign at Ragged Point, Barbados. These include vertically resolved single-particle analyses, mass concentrations of dust and sea spray, and High Spectral Resolution Lidar (HSRL) retrievals. Single-particle data show that dust within the Saharan Air Layer (SAL) remains externally mixed, with a corresponding high HSRL-derived linear depolarization ratio (LDR) at 532 nm of similar to 0.3. However, at lower altitudes, dust becomes internally mixed with sea spray, and under the high humidity ( > 80 %) of the MABL undergoes hygroscopic growth, yielding more spherical particles, suppressing the LDR to < 0.1 ; even in the presence of high dust loadings (e.g., similar to 120 g m(-3)). This low depolarization in the MABL is likely due to a combination of the differences between the single scattering properties of dust and spherical particles, and the potential modification of the dust optical properties from an increased hygroscopicity of dust caused by the mixing with sea salt in the humid MABL. These results highlight the importance of the aerosol particle mixing state when interpreting LDR-derived dust retrievals and estimating surface dust concentrations in satellite products and atmospheric models.

The NASA Cloud, Aerosol and Monsoon Processes Philippines Experiment (CAMP 2 Ex) field campaign from 24 August to 05 October 2019 observed a complex mixture of aerosols – biomass burning smoke transported from Maritime Continent (MC)/Indonesia fires to the Philippines and Metro Manila’s urban pollution. The in-situ and remote sensing aerosol measurements from CAMP 2 Ex plus aerosol retrievals from the Advanced Himawari Imager (AHI) provide a unique dataset for characterizing the complex aerosol regimes and their regional air quality (AQ) impacts. We conducted two Multi-Scale Infrastructure for Chemistry and Aerosols (MUSICAv0) simulations using specified oxidants during the CAMP 2 Ex period: a Control experiment including only open burning emissions and Exp01 adding below-ground peat burning emissions. Both simulations employ variable resolution grids (~14 km over the MC fires, ~7 km over Luzon, Philippines). Here, we evaluate MUSICAv0’s ability to represent transported smoke and local pollution and quantify the contribution of peat burning emissions to the observed aerosol burden. MUSICAv0 Control underestimates AOD across the region, with the largest biases over peat burning areas. Adding peat emissions improves regional AOD mean by 26%. However, both simulations underpredict oceanic and downwind aerosol burden. Case studies of dense Borneo burning (16 September) and the Metro Manila urban plume (04 October) show that MUSICAv0 represents key transport and vertical structures of smoke and urban pollution but overestimates black carbon and secondary organic aerosol production. These findings highlight MUSICAv0’s capability in multi-scale modeling of aerosols in the tropics, and motivate future improvements to emissions, plume rise, and aerosol representation.

Abstract. While most large-scale smoke advection occurs within the free troposphere, Maritime Continent smoke transport is suspected to be unique in its long-range, near-surface transport. Such a pathway likely creates strong gradients and uncertainties in interpreting satellite and model data on light extinction, air pollution, and cloud condensation nuclei. This paper documents High Spectral Resolution Lidar (HSRL) data from the 2019 ONR PISTON cruise and NASA CAMP2Ex flights that revealed Maritime Continent smoke and pollution transport pathways and heterogeneity around the Marine Atmospheric Boundary Layer (MABL) over thousands of kilometers. Observations showed that 95 % of integrated aerosol backscatter occurred below 2500 m altitude. The R/V Sally Ride observed 50th and 84th percentile aerosol backscatter altitudes at ~600 and ~1500 m respectively, regardless of aerosol loading. Peak backscatter values occurred within or near the MABL top, diminishing as we approached 2–3 km altitude, but with occasional plumes reaching the melting level at 4800 m. At monsoonal scales, aerosol models largely account for the observed directional wind shear that causes altitude-dependent particle transport: near-surface particles remain in the core monsoon flow around the MABL, while at lower latitudes, aerosol layers aloft advect more eastwardly. Around the MABL, however, significant cloud-scale variability exists due to fine-scale flow, halo-entrainment-detrainment, and cold pool phenomena. Backscatter enhancements beneath individual clouds, extending to the ocean surface, likely relate to MABL-free troposphere exchange and air-sea interaction. So while aerosol transport occurs near the surface, particle extinction heterogeneity must still be considered for in situ observations and satellite retrievals.

While most large-scale smoke advection occurs within the free troposphere, Maritime Continent smoke is suspected to be unique in its long-range, near-surface transport. Such a pathway likely creates strong gradients and uncertainties in interpreting satellite and model data on light extinction, air pollution, and cloud condensation nuclei. This paper documents High Spectral Resolution Lidar (HSRL) data from the 2019 ONR PISTON cruise and NASA CAMP2Ex flights that revealed Maritime Continent smoke and pollution transport pathways and heterogeneity around the Marine Atmospheric Boundary Layer (MABL) over thousands of kilometers. Observations showed that 95 % of integrated aerosol backscatter occurred below 2500 m altitude. The R/V Sally Ride observed 50th and 84th percentile aerosol backscatter altitudes at ∼600 and ∼1500 m respectively, regardless of aerosol loading. Peak backscatter values occurred within or near the MABL top, diminishing as we approached 2–3 km altitude, but with occasional plumes reaching the melting level at 4800 m. At monsoonal scales, aerosol models largely account for the observed directional wind shear that causes altitude-dependent particle transport: near-surface particles remain in the core monsoon flow around the MABL, while at lower latitudes, aerosol layers aloft advect more eastwardly. Around the MABL, however, significant cloud-scale variability exists due to fine-scale flow, halo-entrainment-detrainment, and cold pool phenomena. Backscatter enhancements beneath individual clouds, extending to the ocean surface, likely relate to MABL-free troposphere exchange and air-sea interaction. So while aerosol transport occurs near the surface, particle extinction heterogeneity must still be considered for in situ observations and satellite retrievals.

Biomass burning smoke particles, due to their submicron particle size in relation to the average thermal infrared (TIR) wavelength, theoretically have negligible signals at the TIR channels. However, nearly instantaneous longwave (LW) signatures of thick smoke plumes can be frequently observed at the TIR channels from remotely sensed data, including at 10.6 µm (IR window), as well as in water-vapor-sensitive wavelengths at 7.3, 6.8, and 6.3 µm (e.g., lower, middle, and upper troposphere). We systematically evaluated multiple hypotheses as to causal factors of these IR signatures of biomass burning smoke using a combination of data from the Aqua MODerate resolution Imaging Spectroradiometer (MODIS), Aqua Cloud and the Earth Radiant Energy System (CERES), Geostationary Operational Environmental Satellite 16/17 (GOES-16/17) Advanced Baseline Imager, and Suomi-NPP Visible Infrared Imaging Radiometer Suite (VIIRS) and Cross-track Infrared Sounder (CrIS). The largely clear transmission of light through wildfire smoke in the near infrared indicates that coarse or giant ash particles are unlikely to be the dominant cause. Rather, clear signals in water vapor and TIR channels suggest that both co-transported water vapor injected to the middle to upper troposphere and surface cooling by the reduction of surface radiation by the plume are more significant, with the surface cooling effect of smoke aloft being the most dominant. Giving consideration of the smoke impacts on TIR and longwave, CERES indicates that large wildfire aerosol plumes are more radiatively neutral. Further, this smoke-induced TIR signal may be used to map very optically thick smoke plumes, where traditional aerosol retrieval methods have difficulties.

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.

Accurate long-term sensor calibration and periodic re-processing to ensure consistency and continuity of atmospheric, land and ocean geophysical retrievals from space within the mission period and across different missions is a major requirement of climate data records. In this work, we applied the Multi-Angle Implementation of Atmospheric Correction (MAIAC)-based vicarious calibration technique over Libya-4 desert site to perform calibration analysis of Visible Infrared Imaging Radiometer Suite (VIIRS) on Suomi National Polarorbiting Partnership (SNPP) and NOAA-20 satellites. For both VIIRS sensors we characterized residual linear calibration trends and cross-calibrated both sensors to MODerate resolution Imaging Spectroradiometer (MODIS) Aqua regarded as a calibration standard. The relative spectral response (RSR) differences were accounted for using the German Aerospace Center (DLR) Earth Sensing Imaging Spectrometer (DESIS) hyperspectral surface reflectance data. Our results agree with independent vicarious calibration results of both the MODIS/VIIRS Characterization Support Team as well as the CERES Imager and Geostationary Calibration Group within estimated uncertainty of 1-2%. Analysis of MAIAC geophysical products with the new calibration shows a high level of agreement of MAIAC aerosol, surface reflectance and NDVI records between MODIS and VIIRS. Excluding high aerosol optical depth (AOD), all three sensors agree in AOD with mean difference (MD) less than 0.01 and residual mean squared difference rmsd - 0.04. Spectral geometrically normalized surface reflectance agrees within rmsd of 0.003-0.005 in the visible and 0.01-0.012 at longer wavelengths. The residual surface reflectance differences are fully explained by differences in spectral filter functions. Finally, difference in NDVI is characterized by rmsd 0.02 and MD less than 0.003 for NDVI based on VIIRS imagery bands I1/I2 and less than 0.01 for NDVI based on VIIRS radiometric bands M5/M7. In practical sense, these numbers indicate consistency and continuity in MAIAC records ensuring the smooth transition from MODIS to VIIRS.

Yori is a highly customizable, sensor-agnostic software, developed to support the NASA Atmosphere Science Teams, to spatially/temporally resample geophysical variables from satellite measurements. Out of the box this software outputs common statistics, such as mean, standard deviation and pixel count, of each geophysical variable read, for every grid cell. Additionally, Yori allows users to easily produce additional statistics (e.g. histograms, min/max, median) and filter data to create custom outputs while maintaining a CF-compliant format. Yori has been designed to be easily scalable on a distributed computing environment.

Fine particulate matter (PM2.5) concentrations in Metro Manila, Philippines have consistently exceeded the guideline values set by the World Health Organization (WHO). Although there has been much progress in understanding the components and sources of PM2.5, limited research has been done on the influence of meteorological factors. In particular, the influence of the planetary boundary layer height (PBLH) on PM2.5 concentration has not been studied due to inadequate observations. From January 2019–June 2020, measurements from a High Spectral Resolution Lidar (HSRL) filled this gap and allowed for PBLH estimation and aerosol typing. This paper investigates the roles of PBLH and regional and local wind circulations on the temporal evolution of aerosol pollution. Results show that daytime and nighttime PBLH variability is associated with solar heating and radiative cooling, respectively. Cloud-free conditions during the dry season yield a higher PBL growth rate than during the wet season when lower daytime and elevated nighttime PBLH are observed. Lower PM2.5 levels are generally observed during daytime when PBLH is at its maximum. However, the PBLH has a significant inverse correlation with PM2.5 only in the months of December-January-February. We find that horizontal directional wind shear between synoptic and mesoscale circulations confounds the PM2.5 - PBLH relationship by creating stagnant conditions conducive to aerosol accumulation. The lower 20% of PM2.5 concentrations occur during the prevalence of strong monsoon winds. On the other hand, the upper 80% are found during the occurrence of compound mesoscale winds (i.e., sea/land/lake/valley/mountain breezes and channeling monsoon winds). In addition, mountain breeze is found to be associated with lifting of aerosols, resulting in multi-layering within the PBL. The findings in the present study emphasize the role of complex topography and mesoscale scale winds arising from the landscape on aerosol pollution variability.

This paper describes a new global dataset of cloud properties observed by MODIS relying on the current (collection 6.1) processing of MODIS data and produced to facilitate comparison with results from the MODIS observational proxy used in climate models. The dataset merges observations from the two MODIS instruments into a single netCDF file. Statistics (mean, standard deviation, and number of observations) are ac-cumulated over daily and monthly timescales on an equal-angle grid for viewing and illumination geometry, cloud detection, cloud-top pressure, and cloud properties (optical thickness, effective particle size, and water path) partitioned by thermodynamic phase and an assessment as to whether the underlying observations come from fully or partly cloudy pixels. Similarly partitioned joint histograms are available for (1) optical thickness and cloud-top pressure, (2) optical thickness and particle size, and (3) cloud water path and particle size. Differences with standard data products, caveats for data use, and guidelines for comparison to the MODIS simulator are described.

In this study, we describe the chemical and physical characteristics of two air pollution events in the first half of January 2020 in Metro Manila, Philippines, namely the New Year's eve fireworks and the Taal volcano ashfall. During the New Year's eve fireworks, PM2.5 concentration and most of the chemical components increased three-fold. However, we found disproportionately higher increases for certain metallic components typically used as pyrotechnic propellant and/or colorant for blue, white, and green light: Fe(5-fold), Cr(5-fold), Cu(8-fold), Ni(9-fold), V(10-fold), Ti(11-fold), and Ba(34-fold). These results provide insights for health assessments and legislation related to fireworks emissions. On January 12, 2020, the Taal volcano eruption caused much concern in Metro Manila as visible tephra deposits were observed. There was only a slight in-crease (8%) in PM2.5 concentration and its components related to basaltic ash. The low PM2.5 concentration was mainly due to the inhibited intrusion of ash into the stable nocturnal boundary layer. In addition, the detection of lightning in the plume and umbrella region showed size segregation of ash particles. The WRF-Chem model was able to capture the distribution of both tephra advection and fallout, a first for Taal volcano, making it possible for use in the future ashfall forecasting.

We introduce the Education and Research 3D Radiative Transfer Toolbox (EaR3T, pronounced []) for quantifying and mitigating artifacts in atmospheric radiation science algorithms due to spatially inhomogeneous clouds and surfaces and show the benefits of automated, realistic radiance and irradiance generation along extended satellite orbits, flight tracks from entire aircraft field missions, and synthetic data generation from model data. EaR3T is a modularized Python package that provides high-level interfaces to automate the process of 3D radiative transfer (3D-RT) calculations. After introducing the package, we present initial findings from four applications, which are intended as blueprints to future in-depth scientific studies. The first two applications use EaR3T as a satellite radiance simulator for the NASA Orbiting Carbon Observatory 2 (OCO-2) and Moderate Resolution Imaging Spectroradiometer (MODIS) missions, which generate synthetic satellite observations with 3D-RT on the basis of cloud field properties from imagery-based retrievals and other input data. In the case of inhomogeneous cloud fields, we show that the synthetic radiances are often inconsistent with the original radiance measurements. This lack of radiance consistency points to biases in heritage imagery cloud retrievals due to sub-pixel resolution clouds and 3D-RT effects. They come to light because the simulator's 3D-RT engine replicates processes in nature that conventional 1D-RT retrievals do not capture. We argue that 3D radiance consistency (closure) can serve as a metric for assessing the performance of a cloud retrieval in presence of spatial cloud inhomogeneity even with limited independent validation data. The other two applications show how airborne measured irradiance data can be used to independently validate imagery-derived cloud products via radiative closure in irradiance. This is accomplished by simulating downwelling irradiance from geostationary cloud retrievals of Advanced Himawari Imager (AHI) along all the below-cloud aircraft flight tracks of the Cloud, Aerosol and Monsoon Processes Philippines Experiment (CAMP2Ex, NASA 2019) and comparing the irradiances with the colocated airborne measurements. In contrast to case studies in the past, EaR3T facilitates the use of observations from entire field campaigns for the statistical validation of satellite-derived irradiance. From the CAMP2Ex mission, we find a low bias of 10 % in the satellite-derived cloud transmittance, which we are able to attribute to a combination of the coarse resolution of the geostationary imager and 3D-RT biases. Finally, we apply a recently developed context-aware Convolutional Neural Network (CNN) cloud retrieval framework to high-resolution airborne imagery from CAMP2Ex and show that the retrieved cloud optical thickness fields lead to better 3D radiance consistency than the heritage independent pixel algorithm, opening the door to future mitigation of 3D-RT cloud retrieval biases.

The NASA Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2Ex) employed the NASA P-3, Stratton Park Engineering Company (SPEC) Learjet 35, and a host of satellites and surface sensors to characterize the coupling of aerosol processes, cloud physics, and atmospheric radiation within the Maritime Continent's complex southwest monsoonal environment. Conducted in the late summer of 2019 from Luzon, Philippines, in conjunction with the Office of Naval Research Propagation of Intraseasonal Tropical Oscillations (PISTON) experiment with its R/V Sally Ride stationed in the northwestern tropical Pacific, CAMP2Ex documented diverse biomass burning, industrial and natural aerosol populations, and their interactions with small to congestus convection. The 2019 season exhibited El Nino conditions and associated drought, high biomass burning emissions, and an early monsoon transition allowing for observation of pristine to massively polluted environments as they advected through intricate diurnal mesoscale and radiative environments into the monsoonal trough. CAMP2Ex's preliminary results indicate 1) increasing aerosol loadings tend to invigorate congestus convection in height and increase liquid water paths; 2) lidar, polarimetry, and geostationary Advanced Himawari Imager remote sensing sensors have skill in quantifying diverse aerosol and cloud properties and their interaction; and 3) high-resolution remote sensing technologies are able to greatly improve our ability to evaluate the radiation budget in complex cloud systems. Through the development of innovative informatics technologies, CAMP2Ex provides a benchmark dataset of an environment of extremes for the study of aerosol, cloud, and radiation processes as well as a crucible for the design of future observing systems.

While the use and data assimilation (DA) of operational Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol data is commonplace, MODIS is scheduled to sunset in the next year. For data continuity, focus has turned to the development of next-generation aerosol products and sensors such as those associated with the Visible Infrared Imaging Radiometer Suite (VIIRS) on Suomi NPOESS Preparation Project (S-NPP) and NOAA-20. Like MODIS algorithms, products from these sensors require their own set of extensive error characterization and correction exercises. This is particularly true in the context of monitoring significant aerosol events that tax an algorithm's ability to separate cloud from aerosol and account for multiple scattering related errors exacerbated by uncertainties in aerosol optical properties. To investigate the performance of polar-orbiting satellite algorithms to monitor and characterize significant events, a level 3 (L3) product has been developed using a consistent aggregation methodology for 4 years of observations (2016-2019) that is referred to as the SSEC/NRL L3 product. Included in this product are the AErosol RObotic NETwork (AERONET), MODIS Dark Target, Deep Blue, and Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithms. These MODIS "baseline algorithms" are compared to NASA's recently released NASA Deep Blue algorithm for use with VIIRS. Using this new dataset, the relative performance of the algorithms for both land and ocean were investigated with a focus on the relative skill of detecting severe events and accuracy of the retrievals using AERONET. Maps of higher-percentile aerosol optical depth (AOD) regions of the world by product identified those with the highest measured AODs and determined what is high by local standards. While patterns in AOD match across products and median to moderate AOD values match well, there are regionally correlated biases between products based on sampling, algorithm differences, and AOD range - in particular for higher AOD events. Most notable are differences in boreal biomass burning and Saharan dust. Significant percentile biases must be accounted for when data are used in trend studies, data assimilation, or inverse modeling. These biases vary by aerosol regime and are likely due to retrieval assumptions in lower boundary conditions and aerosol optical models.

Continuous measurements of aerosol extinction coefficient ( σ ext ) from the High Spectral Resolution Lidar (HSRL) in Seoul from 2016 to 2018 were used to investigate the diurnal variation of the aerosol optical depth (AOD). Nighttime AOD displayed a larger mean and standard deviation (0.45 ± 0.47) than daytime (0.40 ± 0.29). Hygroscopic growth of aerosols under humid conditions was a key factor in the relative enhancement of nighttime AOD. Taking advantage of the HSRL's vertically resolved measurements, the contribution of aerosols within the boundary layer (BL) and free troposphere (FT) to AOD and its temporal variation were investigated. Unlike the diurnal AOD variation, AOD within the BL (AOD BL ) showed similar diurnal variations with the mixing layer height (MLH), displaying lower nighttime values with a peak around 14–15 local standard time. However, the low correlation between MLH and AOD BL ( R 2 = 0.06) implied that MLH was not the sole deterministic factor of AOD BL . A larger AOD of FT aerosols (AOD FT ) was observed during spring due to frequent elevated dust layers. Using mean σ ext within the BL and surface PM 10 concentrations, the mass extinction efficiency (MEE) of aerosols in Seoul was estimated. The PM 10 MEE showed a mean of 5.40 g m −2 and displayed significant variability by PM 2.5 to PM 10 ratio, season, and ambient relative humidity. The uncertainty of estimated surface PM 10 concentrations was minimized when the seasonality and humidity factor in MEE were taken into account (the normalized mean bias decreased from 10.6%, using a single MEE value, to 6.2%).

Although satellite retrievals and data assimilation have progressed to where there is a good skill for monitoring maritime Aerosol Optical Depth (AOD), there remains uncertainty in achieving further degrees of freedom, such as distinguishing fine and coarse mode dominated species in maritime environments (e.g., coarse mode sea salt and dust versus fine mode terrestrial anthropogenic emissions, biomass burning, and maritime secondary production). For the years 2016 through 2019, we performed an analysis of 550 nm total AOD550, fine mode AOD (FAOD550; also known as FM AOD in the literature), coarse mode AOD (CAOD550), and fine mode fraction (η550) between Moderate Resolution Spectral Imaging Radiometer (MODIS) V6.1 MOD/MYD04 dark target aerosol retrievals and the International Cooperative for Aerosol Prediction (ICAP) core four multi-model consensus (C4C) of analyses/short term forecasts that assimilate total MODIS AOD550. Differences were adjudicated by the global shipboard Maritime Aerosol Network (MAN) and selected island AERONET sun photometer observations with the application of the spectral deconvolution algorithm (SDA). Through a series of conditional and regional analyses, we found divergence included regions of terrestrial influence and latitudinal dependencies in the remote oceans. Notably, MODIS and the C4C and its members, while having good correlations overall, have a persistent +0.04 to +0.02 biases relative to MAN and AERONET for typical AOD550 values (84th% < 0.28), with the C4C underestimating significant events thereafter. Second, high biases in AOD550 are largely associated with the attribution of the fine mode in satellites and models alike. Thus, both MODIS and C4C members are systematically overestimating AOD550 and FAOD550 but perform better in characterizing the CAOD550. Third, for MODIS, findings are consistent with previous reports of a high bias in the retrieved Ångström Exponent, and we diagnosed both the optical model and cloud masking as likely causal factors for the AOD550 and FAOD550 high bias, whereas for the C4C, it is likely from secondary overproduction and perhaps numerical diffusion. Fourth, while there is no wind-speed-dependent bias for surface winds <12 m s−1, the C4C and MODIS AOD550s also overestimate CAOD550 and FAOD550, respectively, for wind speeds above 12 m/s. Finally, sampling bias inherent in MAN, as well as other circumstantial evidence, suggests biases in MODIS are likely even larger than what was diagnosed here. We conclude with a discussion on how MODIS and the C4C products have their own strengths and challenges for a given climate application and discuss needed research.

The NASA Aqua MODIS and Suomi National Polar-Orbiting Partnership (SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS) climate data record continuity cloud properties products (CLDPROP) were publicly released in April 2019 with an update later that year (Version 1.1). These cloud products, having heritage with the NASA Moderate-resolution Imaging Spectroradiometer (MODIS) MOD06 cloud optical properties product and the NOAA GOES-R Algorithm Working Group (AWG) Cloud Height Algorithm (ACHA), represent an effort to bridge the multispectral imager records of NASA’s Earth Observing System (EOS) and NOAA’s current generation of operational weather satellites to achieve a continuous, multi-decadal climate data record for clouds that can extend well into the 2030s. CLDPROP offers a “continuity of approach,” applying common algorithms and ancillary datasets to both MODIS and VIIRS, including utilizing only a subset of spectral channels available on both sensors to help mitigate instrument differences. The initial release of the CLDPROP_MODIS and CLDPROP_VIIRS data records spans the SNPP observational record (2012-present). Here, we present an overview of the algorithms and an evaluation of the intersensor continuity of the core CLDPROP_MODIS and CLDPROP_VIIRS cloud optical property datasets, i.e., cloud thermodynamic phase, optical thickness, effective particle size, and derived water path. The evaluation includes analyses of pixel-level MODIS/VIIRS co-locations as well as spatial and temporal aggregated statistics, with a focus on identifying and understanding the root causes of individual dataset discontinuities. The results of this evaluation will inform future updates to the CLDPROP products and help scientific users determine the appropriate use of the product datasets for their specific needs.

Fireworks degrade air quality, reduce visibility, alter atmospheric chemistry, and cause short-term adverse health effects. However, there have not been any comprehensive physicochemical and optical measurements of fireworks and their associated impacts in a Southeast Asia megacity, where fireworks are a regular part of the culture. Size-resolved particulate matter (PM) measurements were made before, during, and after New Year 2019 at the Manila Observatory in Quezon City, Philippines, as part of the Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2Ex). A high-spectral-resolution lidar (HSRL) recorded a substantial increase in backscattered signal associated with high aerosol loading ∼440 m above the surface during the peak of firework activities around 00:00 (local time). This was accompanied by PM2.5 concentrations peaking at 383.9 µg m−3. During the firework event, water-soluble ions and elements, which affect particle formation, growth, and fate, were mostly in the submicrometer diameter range. Total (>0.056 µm) water-soluble bulk particle mass concentrations were enriched by 5.7 times during the fireworks relative to the background (i.e., average of before and after the firework). The water-soluble mass fraction of PM2.5 increased by 18.5 % above that of background values. This corresponded to increased volume fractions of inorganics which increased bulk particle hygroscopicity, kappa (κ), from 0.11 (background) to 0.18 (fireworks). Potassium and non-sea-salt (nss) SO42- contributed the most (70.9 %) to the water-soluble mass, with their mass size distributions shifting from a smaller to a larger submicrometer mode during the firework event. On the other hand, mass size distributions for NO3-, Cl−, and Mg2+ (21.1 % mass contribution) shifted from a supermicrometer mode to a submicrometer mode. Being both uninfluenced by secondary aerosol formation and constituents of firework materials, a subset of species were identified as the best firework tracer species (Cu, Ba, Sr, K+, Al, and Pb). Although these species (excluding K+) only contributed 2.1 % of the total mass concentration of water-soluble ions and elements, they exhibited the highest enrichments (6.1 to 65.2) during the fireworks. Surface microscopy analysis confirmed the presence of potassium/chloride-rich cubic particles along with capsule-shaped particles in firework samples. The results of this study highlight how firework emissions change the physicochemical and optical properties of water-soluble particles (e.g., mass size distribution, composition, hygroscopicity, and aerosol backscatter), which subsequently alters the background aerosol's respirability, influence on surroundings, ability to uptake gases, and viability as cloud condensation nuclei (CCN).