Aerosol Microphysical Properties Research Articles

Parameterization of Dust Emissions from Heaps and Excavations Based on Measurement Results and Mathematical Modelling

Assessment of the concentrations of dust pollution resulting from both measurements at reference stations and those determined using mathematical modelling requires accurate identification of the sources of emission. Although the concentration of dust results from several complex transport processes, as well as chemical and microphysical transformations of aerosols, sources of emissions may have a significant impact on the local level of pollution. This pilot study aimed to use measurements of the concentrations of dust (with the specification of the PM10 and PM2.5 fractions) made over a heap/excavation and its surroundings using an airship equipped with equipment for testing the optical and microphysical properties of atmospheric aerosols, and a ground station located at the facility. On the basis of the measurements, the function of the source of emissions of dust was estimated. According to our study, the yearly emission of dust varies between 42 470 and 886 289 kg for PM10, and between 42 470 and 803 893 for PM2.5 (minimum and maximum values). A model of local air quality was also used, which allowed us to verify the parameterization of emissions of dust pollutants for the PM10 and PM2.5 fractions from heaps and excavations based on the modelling results.

Effects of aerosol on downward diffuse radiation under blowing dust and haze conditions

Aerosols are not only an important component of the atmosphere, but also an indispensable medium for the generation of diffuse radiation (DR) in the atmosphere. This study analyzed the variation of diffuse radiation using ground-based observation under clear sky conditions at Wuhan, and quantifies the effects of aerosol optical and microphysical properties on diffuse radiation under blowing dust and haze conditions. The results are as follows: DR showed a decreasing trend from 2010 to 2014, and an increasing trend with rate of 4.076 Wm-2 year-1 from 2014 to 2018. From 2011-2016, the diffuse radiation fraction (DRF) showed a trend of first decreasing and then increasing. During the study period, the relationship between aerosol optical depth (AOD) and DRF showed a significant and solid relationship with an R2 of 0.874. DR increased from 159.592 W m-2 in clean air to 195.420 W m-2 during the haze period, and AOD also increased from 0.607 in clean air to 0.914 during the haze period, which demonstrated the increase in diffuse radiation with the increase in aerosol loading. During the haze period, the sensitivity of fine-mode aerosol effective particle size (REFFF) and asymmetry (ASY) to DR was higher, with determination coefficients of 0.541 and 0.317, respectively, which were attributed to the hygroscopic growth of the aerosol resulting in larger particle size, increased ASY, and scattering of more solar radiation. The absorption properties of aerosols affect the DR during blowing dust, with a coefficient of determination between single scattering albedo (SSA) and DR of 0.40. The aerosol diffuse radiation effect (ADRE) was 111.688 W m-2 during the clean air period, ADRE increased by 31.839, 13.312 W m-2 during the haze and blowing dust periods, respectively, compared to that during the clean air period. The study of aerosols and radiation under different pollution conditions helps to understand the mechanisms behind local climate change and pollution phenomena, and deepens our understanding of the impact of pollution on the environment.

Atmospheric Aerosols and Air Quality in the 2022 Dry Season in Huancayo-Perú

This work presents results of Aerosol Optical Depth (AOD) and Direct Radiative Force (DRF) at the top of the atmosphere (TOA), obtained during monitoring campaigns carried out at the Huancayo Observatory of the Geophysical Institute of Peru (OH-IGP ) in April and August 2022. In these campaigns, a Sun CIMEL photometer was used to measure the microphysical and optical properties of aerosols at wavelengths ranging from 340 to 1020 nm, and a low-cost Purple-air sensor to quantify the concentration of material particulate (PM), in fine and coarse modes. The AOD results indicated values in the range 0.06-0.22. The daily averages of PM2.5 and PM10 did not exceed Peru's current Environmental Quality Standards (50 μg/m3 and 100 μg/m3). The air quality index (AQI) calculated for PM2.5 and PM10 was classified as good. On some days during the campaigns, the air quality was classified as moderate. These results contribute to a better understanding of the current climatic conditions of the Peruvian Altiplano.

Efficient single-scattering lookup table for lidar and polarimeter phytoplankton studies.

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 µm. The lookup table covers phytoplankton particles with radii in the range of 0.15-100 µm at an increase of up to 104 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 µm for the effective radius and up to 0.6 for the effective variance. We test wavelengths from 0.355 to 1.065 µm 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.

Construction of Aerosol Model and Atmospheric Correction in the Coastal Area of Shandong Peninsula

Applying standard aerosol models for atmospheric correction in nearshore coastal waters introduces significant uncertainties due to their inability to accurately represent aerosol characteristics in these regions. To improve the accuracy of remote sensing reflectance (Rrs) products in the nearshore waters of the Shandong Peninsula, this study develops an aerosol model based on aerosol data collected from the Mu Ping site in the coastal area of the Shandong Peninsula, enabling tailored atmospheric correction for this specific region. Given the pronounced seasonal variations in aerosol optical properties, monthly aerosol models were developed. The monthly aerosol model is derived using the average values of aerosol microphysical properties. Compared to the standard aerosol model, this model is more effective in characterizing the absorption and scattering characteristics of aerosols in the study area. Corresponding lookup tables for the aerosol model were created and integrated into the NIR-SWIR atmospheric correction algorithm. According to the accuracy evaluation indexes of RMSD, MAE, and UPD, it can be found that the atmospheric correction results of the aerosol model established in this paper are better than those of the standard aerosol model, especially in the 547 nm band. It demonstrates that the new aerosol model outperforms the standard model in atmospheric correction performance. With the increasing availability of aerosol observational data, the aerosol model is expected to become more accurate and applicable to other satellite missions.

Upgraded Three-Wavelength Lidar for Real-Time Observations of Volcanic Aerosol Optical and Microphysical Properties at Etna (Italy): Calibration Procedures and Measurement Tests.

An innovative mobile lidar device, developed to monitor volcanic plumes during explosive eruptions at Mt. Etna (Italy) and to analyse the optical properties of volcanic particles, was upgraded in October 2023 with the aim of improving volcanic plume retrievals. The new configuration of the lidar allows it to obtain new data on both the optical and the microphysical properties of the atmospheric aerosol. In fact, after the upgrade, the lidar is able to measure three backscattering coefficients, two extinction coefficients and two depolarisation ratios in a configuration defined as "state-of-the-art lidar", where properties such as particle size distribution and the refractive index can be derived. During the lidar implementation, we were able to test the system's performance through specific calibration measurements. A comparison in an aerosol-free region (7.2-12 km) between lidar signals at 1064 nm, 532 nm and 355 nm and the corresponding pure molecular profiles showed a relative difference of <1% between them for all the wavelengths, highlighting the good dynamic of the signals. The overlap correction allowed us to reduce the underestimation of the backscattering coefficient from 50% to 10% below 450 m and 750 m at both 355 and 532 nm, respectively. The correct alignment between the laser beam and the receiver optical chain was tested using the signal received from the different quadrants of the telescope, and the relative differences between the four directions were comparable to zero, within the margin of error. Finally, the first measurement results are shown and compared with results obtained by other instruments, with the aim of proving the ability of the upgraded system to more precisely characterise aerosol optical and microphysical properties.

Bridging New Observational Capabilities and Process-Level Simulation: Insights into Aerosol Roles in the Earth System

Abstract The spatial distribution of ambient aerosol particles significantly impacts aerosol–radiation–cloud interactions, which contribute to the largest uncertainty in global anthropogenic radiative forcing estimations. However, the atmospheric boundary layer and lower free troposphere have not been adequately sampled in terms of spatiotemporal resolution, hindering a comprehensive characterization of various atmospheric processes and impeding our understanding of the Earth system. To address this research data gap, we have leveraged the development of uncrewed aerial systems (UAS) and advanced measurement techniques to obtain mesoscale spatial data on aerosol microphysical and optical properties around the U.S. Southern Great Plains (SGP) atmospheric observatory. Our study also benefits from state-of-the-art laboratory facilities that include three-dimensional molecular imaging techniques enabled by secondary ion mass spectrometry and nanogram-level chemical composition analysis via micronebulization aerosol mass spectrometry. Through our study, we have developed a framework for observation–modeling integration, enabling an examination of how various assumptions about the organic–inorganic components mixing state, inferred from chemical analysis, affect clouds and radiation in observation-constrained model simulations. By integrating observational constraints (derived from offline chemical analysis of the aerosol surface using collected samples) with in situ UAS observations, we have identified a prominent role of organic-enriched nanometer layers located at the surface of aerosol particles in determining profiles of aerosol optical and hygroscopic properties over the SGP observatory. Furthermore, we have improved the agreement between predicted clouds and ground-based cloud lidar measurements. This UAS–model–laboratory integration exemplifies how these new advanced capabilities can significantly enhance our understanding of aerosol–radiation–cloud interactions.

Optical and Microphysical Properties of the Aerosols during a Rare Event of Biomass-Burning Mixed with Polluted Dust

A rare event of mixed biomass-burning and polluted dust aerosols was observed over Athens, Greece (37.9° N, 23.6° E), during 21–26 May 2014. This event was studied using a synergy of a 6-wavelength elastic-Raman-depolarization lidar measurements, a CIMEL sun photometer, and in situ instrumentation. The FLEXPART dispersion model was used to identify the aerosol sources and quantify the contribution of dust and black carbon particles to the mass concentration. The identified air masses were found to originate from Kazakhstan and Saharan deserts, under a rare atmospheric pressure system. The lidar ratio (LR) values retrieved from the Raman lidar ranged within 25–89 sr (355 nm) and 35–70 sr (532 nm). The particle linear depolarization ratio (δaer) ranged from 7 to 28% (532 nm), indicating mixing of dust with biomass-burning particles. The aerosol optical depth (AOD) values derived from the lidar ranged from 0.09–0.43 (355 nm) to 0.07–0.25 (532 nm). An inversion algorithm was used to derive the mean aerosol microphysical properties (mean effective radius (reff), single scattering albedo (SSA), and mean complex refractive index (m)) inside selected atmospheric layers. We found that reff was 0.12–0.51 (±0.04) µm, SSA was 0.94–0.98 (±0.19) (at 532 nm), while m ranged between 1.39 (±0.05) + 0.002 (±0.001)i and 1.63 (±0.05) + 0.008 (±0.004)i. The polarization lidar photometer networking (POLIPHON) algorithm was used to estimate the vertical profile of the mass concentration for the dust and non-dust components. A mean mass concentration of 15 ± 5 μg m−3 and 80 ± 29 μg m−3 for smoke and dust was estimated for selected days, respectively. Finally, the retrieved aerosol microphysical properties were compared with column-integrated sun photometer CIMEL data with good agreement.

Relationship between El Niño-Southern Oscillation and Atmospheric Aerosols in the Legal Amazon

The El Niño-Southern Oscillation (ENSO) stands out as the most significant tropical phenomenon in terms of climatic magnitude resulting from ocean–atmosphere interaction. Due to its atmospheric teleconnection mechanism, ENSO influences various environmental variables across distinct atmospheric scales, potentially impacting the spatiotemporal distribution of atmospheric aerosols. Within this context, this study aims to evaluate the relationship between ENSO and atmospheric aerosols across the entire Legal Amazon during the period from 2006 to 2011. Over this five-year span, four ENSO events were identified. Concurrently, an analysis of the spatiotemporal variability of aerosol optical depth (AOD) and Black Carbon radiation extinction (EAOD-BC) was conducted alongside these ENSO events, utilizing data derived from the Aerosol Robotic Network (AERONET), MERRA-2 model, and ERSSTV5. Employing the Windowed Cross-Correlation (WCC) approach, statistically significant phase lags of up to 4 to 6 months between ENSO indicators and atmospheric aerosols were observed. There was an approximate 100% increase in AOD immediately after El Niño periods, particularly during intervals encompassing the La Niña phase. The analysis of specific humidity anomaly (QA) revealed that, contrary to expectations, positive values were observed throughout most of the El Niño period. This result suggests that while there is a suppression of precipitation events during El Niño due to the subsidence of drier air masses in the Amazon, the region still exhibits positive specific humidity (Q) conditions. The interaction between aerosols and humidity is intricate. However, Q can exert influence over the microphysical and optical properties of aerosols, in addition to affecting their chemical composition and aerosol load. This influence primarily occurs through water absorption, leading to substantial alterations in radiation scattering characteristics, and thus affecting the extinction of solar radiation.

Characteristics of Absorbing Aerosols in Mexico City: A Study of Morphology and Columnar Microphysical Properties

This paper presents an analysis of the morphology and columnar microphysical properties of atmospheric aerosols in Mexico City (MC) for the period 2022–2023. The morphological study focused on the structure description of soot particles and tar balls (TB). By transmission electron microscope (TEM) and scanning electrode microscope (SEM), voluminous soot aggregates mixed with TBs were observed. The chemistry shows that both soot and TBs are mostly carbonaceous species with well-defined morphologies. On the other hand, the columnar aerosol microphysical properties recovered from AERONET show that the particles have a bimodal aerosol size distribution (ASD) with two modes: fine and coarse. The ASD remains constant without showing significant seasonal changes, only with some variability for coarse particles. The aerosol optical depth (AOD) value is significantly high, typical of urban areas. The real (n) and imaginary (k) parts of the complex refractive index (CRI) were obtained from the photometric measurements. The CRI values show seasonal variations, with spring being the season with the highest values for n, while the highest values for k were measured in winter.

Simultaneous retrieval of aerosol and ocean properties from PACE HARP2 with uncertainty assessment using cascading neural network radiative transfer models

Abstract. The University of Maryland, Baltimore County (UMBC) Hyper-Angular Rainbow Polarimeter (HARP2) will be on board NASA's Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission, scheduled for launch in January 2024. In this study we systematically evaluate the retrievability and uncertainty of aerosol and ocean parameters from HARP2 multi-angle polarimeter (MAP) measurements. To reduce the computational demand of MAP-based retrievals and maximize data processing throughput, we developed improved neural network (NN) forward models for spaceborne HARP2 measurements over a coupled atmosphere and ocean system within the FastMAPOL retrieval algorithm. To this end, a cascading retrieval scheme is implemented in FastMAPOL, which leverages a series of NN models of varying size, speed, and accuracy to optimize performance. Two sets of NN models are used for reflectance and polarization, respectively. A full day of global synthetic HARP2 data was generated and used to test various retrieval parameters including aerosol microphysical and optical properties, aerosol layer height, ocean surface wind speed, and ocean chlorophyll a concentration. To assess retrieval quality, pixel-wise retrieval uncertainties were derived from error propagation and evaluated against the difference between the retrieval parameters and truth based on a Monte Carlo method. We found that the fine-mode aerosol properties can be retrieved well from the HARP2 data, though the coarse-mode aerosol properties are more uncertain. Larger uncertainties are associated with a reduced number of available viewing angles, which typically occur near the scan edge of the HARP2 instrument. Results of the performance assessment demonstrate that the algorithm is a viable approach for operational application to HARP2 data after the PACE launch.

Aerosol and dynamical contributions to cloud droplet formation in Arctic low-level clouds

Abstract. The Arctic is one of the most rapidly warming regions of the globe. Low-level clouds and fog modify the energy transfer from and to space and play a key role in the observed strong Arctic surface warming, a phenomenon commonly termed “Arctic amplification”. The response of low-level clouds to changing aerosol characteristics throughout the year is therefore an important driver of Arctic change that currently lacks sufficient constraints. As such, during the NASCENT campaign (Ny-Ålesund AeroSol Cloud ExperimeNT) extending over a full year from October 2019 to October 2020, microphysical properties of aerosols and clouds were studied at the Zeppelin station (475 m a.s.l.), Ny-Ålesund, Svalbard, Norway. Particle number size distributions obtained from differential mobility particle sizers as well as chemical composition derived from filter samples and an aerosol chemical speciation monitor were analyzed together with meteorological data, in particular vertical wind velocity. The results were used as input to a state-of-the-art cloud droplet formation parameterization to investigate the particle sizes that can activate to cloud droplets, the levels of supersaturation that can develop, the droplet susceptibility to aerosol and the role of vertical velocity. We evaluate the parameterization and the droplet numbers calculated through a droplet closure with in-cloud in situ measurements taken during nine flights over 4 d. A remarkable finding is that, for the clouds sampled in situ, closure is successful in mixed-phase cloud conditions regardless of the cloud glaciation fraction. This suggests that ice production through ice–ice collisions or droplet shattering may have explained the high ice fraction, as opposed to rime splintering that would have significantly reduced the cloud droplet number below levels predicted by warm-cloud activation theory. We also show that pristine-like conditions during fall led to clouds that formed over an aerosol-limited regime, with high levels of supersaturation (generally around 1 %, although highly variable) that activate particles smaller than 20 nm in diameter. Clouds formed in the same regime in late spring and summer, but aerosol activation diameters were much larger due to lower cloud supersaturations (ca. 0.5 %) that develop because of higher aerosol concentrations and lower vertical velocities. The contribution of new particle formation to cloud formation was therefore strongly limited, at least until these newly formed particles started growing. However, clouds forming during the Arctic haze period (winter and early spring) can be limited by updraft velocity, although rarely, with supersaturation levels dropping below 0.1 % and generally activating larger particles (20 to 200 nm), including pollution transported over a long range. The relationship between updraft velocity and the limiting cloud droplet number agrees with previous observations of various types of clouds worldwide, which supports the universality of this relationship.

Evaluation of the Accuracy of the Aerosol Optical and Microphysical Retrievals by the GRASP Algorithm from Combined Measurements of a Polarized Sun-Sky-Lunar Photometer and a Three-Wavelength Elastic Lidar

The versatile Generalized Retrieval of Aerosol and Surface Properties (GRASP) algorithm exploits the advantages of synergic ground-based aerosol observations such as radiometric (sensitive to columnar aerosol optical and microphysical properties) and lidar (sensitive to vertical distribution of the optical properties) observations. The synergy is possible when the complementary data is mutually constrained by GRASP parametrization that includes, for the first time ever, the degree of linear polarization (DoLP) parameter measured by a polarized sun-sky-lunar AERONET photometer (380, 440, 500, 675, 870, 1020, and 1640 nm) in synergy with the vertical profiles from an elastic lidar (355, 532, and 1064 nm). First, a series of numerical tests is performed using simulated data generated using a climatology of data and ground-based measurements. The inversions are performed with and without random noise for five different combinations of input data, starting from the AERONET-like dataset and increasing to the complex one by adding more information for three aerosol scenarios: I—high aerosol optical depth (AOD) with dominant coarse mode; II—low AOD with dominant coarse mode; III—high AOD with dominant fine mode. The inclusion of DoLP improves (i) the retrieval accuracy of the fine-mode properties when it is not dominant; (ii) the retrieval accuracy of the coarse-mode properties at longer wavelengths and that of the fine-mode properties at shorter wavelengths; (iii) the retrieval accuracy of the coarse-mode real part of the refractive index (up to 36% reduction), but has no effect on the retrieval of the imaginary part; (iv) reduces up to 83% the bias of the sphere fraction (SF) retrieval in coarse-mode dominated regimes; and (v) the root mean square error (RMSE) of the retrieval for most of the parameters in all scenarios. In addition, the addition of more photometer channels in synergy with a three-wavelength elastic lidar reduces the RMSE for the real part (67% in the coarse mode) and the imaginary part (35% in the fine mode) of the refractive index, the single scattering albedo (38% in the fine mode), the lidar ratio (20% in the coarse mode), and the SF (43%).

Climatological assessment of the vertically resolved optical and microphysical aerosol properties by lidar measurements, sun photometer, and in situ observations over 17 years at Universitat Politècnica de Catalunya (UPC) Barcelona

Abstract. Aerosols are one of the most important pollutants in the atmosphere and have been monitored for the past few decades by remote sensing and in situ observation platforms to assess the effectiveness of government-managed reduction emission policies and assess their impact on the radiative budget of the Earth's atmosphere. In fact, aerosols can directly modulate incoming short-wave solar radiation and outgoing long-wave radiation and indirectly influence cloud formation, lifetime, and precipitation. In this study, we quantitatively evaluated long-term temporal trends and seasonal variability from a climatological point of view of the optical and microphysical properties of atmospheric particulate matter at the Universitat Politècnica de Catalunya (UPC), Barcelona, Spain, over the past 17 years, through a synergy of lidar, sun photometer, and in situ concentration measurements. Interannual temporal changes in aerosol optical and microphysical properties are evaluated through the seasonal Mann–Kendall test. Long-term trends in the optical depth of the recovered aerosol; the Ångström exponent (AE); and the concentrations of PM10, PM2.5, and PM1 reveal that emission reduction policies implemented in the past decades were effective in improving air quality, with consistent drops in PM concentrations and optical depth of aerosols. The seasonal analysis of the 17-year average vertically resolved aerosol profiles obtained from lidar observations shows that during summer the aerosol layer can be found up to an altitude of 5 km, after a sharp decay in the first kilometer. In contrast, during the other seasons, the backscatter profiles fit a pronounced exponential decay well with a well-defined scale height. Long-range transport, especially dust outbreaks from the Sahara, is likely to occur throughout the year. During winter, the dust aerosol layers are floating above the boundary layer, while during the other seasons they can penetrate the layer. The analysis also revealed that intense, short-duration pollution events during winter, associated with dust outbreaks, have become more frequent and intense since 2016. This study sheds some light on the meteorological processes and conditions that can lead to the formation of haze and helps decision makers adopt mitigation strategies to preserve large metropolitan areas in the Mediterranean basin.

Measurements of aerosol microphysical and chemical properties in the central Arctic atmosphere during MOSAiC

The Arctic environment is transforming rapidly due to climate change. Aerosols’ abundance and physicochemical characteristics play a crucial, yet uncertain, role in these changes due to their influence on the surface energy budget through direct interaction with solar radiation and indirectly via cloud formation. Importantly, Arctic aerosol properties are also changing in response to climate change. Despite their importance, year-round measurements of their characteristics are sparse in the Arctic and often confined to lower latitudes at Arctic land-based stations and/or short high-latitude summertime campaigns. Here, we present unique aerosol microphysics and chemical composition datasets collected during the year-long Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, in the central Arctic. These datasets, which include aerosol particle number concentrations, size distributions, cloud condensation nuclei concentrations, fluorescent aerosol concentrations and properties, and aerosol bulk chemical composition (black carbon, sulfate, nitrate, ammonium, chloride, and organics) will serve to improve our understanding of high-Arctic aerosol processes, with relevance towards improved modelling of the future Arctic (and global) climate.

Synergic use of in-situ and remote sensing techniques for comprehensive characterization of aerosol optical and microphysical properties

We report on importance of conducting comprehensive studies of atmospheric aerosol particles, which cannot be done if information from various complementary sensors is unavailable. We present an example for such application and recommend on the types of sensors that should be used in view of the ACTRIS and RI-URBANS new strategies for monitoring at supersites. Although active and passive remote sensing data was not available in continuous mode, we show that synergic use of them with in-situ observations allows for comprehensive study of temporal and height-resolved distribution of aerosol in the lower troposphere and it can be successfully combined to assess biomass burning impact on air quality and optical properties.The analysed period was divided into three episodes based on the measured black carbon (BC) concentration and the prevailing wind direction. The dominant 72-h backward trajectories were ending in western Europe, mid-Atlantic and western Russia, respectively, The in-situ measured mass concentrations of BCtotal and BC apportioned to biomass burning as well as particulate matter (PM) concentrations in accumulation mode were twice higher during the first and last episodes compared to the second episode, representing long-range transport from different source regions. The obtained complementary surface, column-integrated, and layer-derived size distributions and other parameters demonstrate the added value of multisensor analyses.

Global Gridded Aerosol Models Established for Atmospheric Correction Over Inland and Nearshore Coastal Waters

AbstractThe use of standard aerosol models for atmospheric correction over inland and nearshore coastal waters generates large uncertainties due to their inability to appropriately characterize aerosols in those regions. To address this problem, we developed new aerosol models using data acquired from 1,475 Aerosol Robotic Network (AERONET) sites distributed in inland and coastal regions throughout the globe. We established spatially gridded (5° × 5°) aerosol models on a climatological monthly scale, with a total of 3,207 new aerosol models developed for 310 grid cells worldwide. The monthly aerosol model for each grid was derived using mean monthly values of microphysical aerosol properties from AERONET data. The optical properties (i.e., single scattering albedo and Ångström coefficient) of our global gridded aerosol models demonstrated considerable spatial and seasonal dynamics and deviated substantially from the aerosol models currently utilized by the National Aeronautics and Space Administration (NASA). We built associated lookup tables for all aerosol models and incorporated them into two atmospheric correction algorithms: the combined near‐infrared and shortwave infrared algorithm (NIR‐SWIR) and the Atmospheric Correction algorithm for inLand and Nearshore Coastal waters (ACLANC). For both algorithms, the accuracies of atmospherically corrected satellite remote sensing reflectance (Rrs) improved markedly when the new aerosol models were used, and improvements were noted across all spectral bands and across all six inland and nearshore water bodies used in this study. Our new aerosol models can be easily applied to all ocean color satellite missions to obtain accurate Rrs products for inland and coastal waters worldwide.

The PACE-MAPP algorithm: Simultaneous aerosol and ocean polarimeter products using coupled atmosphere-ocean vector radiative transfer

We describe the PACE-MAPP algorithm that simultaneously retrieves aerosol and ocean optical parameters using multiangle and multispectral polarimeter measurements from the SPEXone, Hyper-Angular Rainbow Polarimeter 2 (HARP2), and Ocean Color Instrument (OCI) instruments onboard the NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) observing system. PACE-MAPP is adapted from the Research Scanning Polarimeter (RSP) Microphysical Aerosol Properties from Polarimetry (RSP-MAPP) algorithm. The PACE-MAPP algorithm uses a coupled vector radiative transfer model such that the atmosphere and ocean are always considered together as one system. Consequently, this physically consistent treatment of the system across the ultraviolet, (UV: 300–400 nm), visible (VIS: 400–700 nm), near-infrared (NIR: 700–1100 nm), and shortwave infrared (SWIR: 1100–2400 nm) spectral bands ensures that negative water-leaving radiances do not occur. PACE-MAPP uses optimal estimation to simultaneously characterize the optical and microphysical properties of the atmosphere’s aerosol and ocean constituents, find the optimal solution, and evaluate the uncertainties of each parameter. This coupled approach, together with multiangle, multispectral polarimeter measurements, enables retrievals of aerosol and water properties across the Earth’s oceans. The PACE-MAPP algorithm provides aerosol and ocean products for both the open ocean and coastal areas and is designed to be accurate, modular, and efficient by using fast neural networks that replace the time-consuming vector radiative transfer calculations in the forward model. We provide an overview of the PACE-MAPP framework and quantify its expected retrieval performance on simulated PACE-like data using a bimodal aerosol model for observations of fine-mode absorbing aerosols and coarse-mode sea salt particles. We also quantify its performance for observations over the ocean of dust-laden scenes using a trimodal aerosol model that incorporates non-spherical coarse-mode dust particles. Lastly, PACE-MAPP’s modular capabilities are described, and we discuss plans to implement a new ocean bio-optical model that uses a mixture of coated and uncoated particles, as well as a thin cirrus model for detecting and correcting for sub-visual ice clouds.

Aerosol optical properties calculated from size distribution measurements: An uncertainty study

We use Monte Carlo uncertainty propagation to estimate the uncertainty of aerosol scattering coefficients, σs, that have been derived from measured particle size distributions. We consider the particular case where the size distributions are measured using a combination of a scanning mobility particle sizer (SMPS) and an aerodynamic particle sizer (APS). Uncertainties that are propagated include those intrinsic to the instruments and those that arise from variabilities in aerosol microphysical properties, including particle shape, density, and complex refractive index. Particular emphasis is put on the size dependent counting efficiency of both instruments which have weaknesses in a particle size range that dominates aerosol optical properties. The T-matrix method is utilized to simulate the effect of particle shapes on σs. To narrow the probability distribution of aerosol properties we discuss uncertainties for a single geographic location, which is the Southern Great Plains site (SGP) of the Department of Energy’s Atmospheric Radiation Measurement (ARM) User Facility. We estimate a 95% confidence interval for σs between −40% and +68%. A partial dependence analysis, for which we use generalized additive models, identifies uncertainties in counting efficiency and particle shapes as the dominant contributors to the size of the confidence interval.

The impact and estimation of uncertainty correlation for multi-angle polarimetric remote sensing of aerosols and ocean color

Abstract. Multi-angle polarimetric (MAP) measurements contain rich information for characterization of aerosol microphysical and optical properties that can be used to improve atmospheric correction in ocean color remote sensing. Advanced retrieval algorithms have been developed to obtain multiple geophysical parameters in the atmosphere–ocean system, although uncertainty correlation among measurements is generally ignored due to lack of knowledge on its strength and characterization. In this work, we provide a practical framework to evaluate the impact of the angular uncertainty correlation from retrieval results and a method to estimate correlation strength from retrieval fitting residuals. The Fast Multi-Angular Polarimetric Ocean coLor (FastMAPOL) retrieval algorithm, based on neural-network forward models, is used to conduct the retrievals and uncertainty quantification. In addition, we also discuss a flexible approach to include a correlated uncertainty model in the retrieval algorithm. The impact of angular correlation on retrieval uncertainties is discussed based on synthetic Airborne Hyper-Angular Rainbow Polarimeter (AirHARP) and Hyper-Angular Rainbow Polarimeter 2 (HARP2) measurements using a Monte Carlo uncertainty estimation method. Correlation properties are estimated using autocorrelation functions based on the fitting residuals from both synthetic AirHARP and HARP2 data and real AirHARP measurement, with the resulting angular correlation parameters found to be larger than 0.9 and 0.8 for reflectance and degree of linear polarization (DoLP), respectively, which correspond to correlation angles of 10 and 5∘. Although this study focuses on angular correlation from HARP instruments, the methodology to study and quantify uncertainty correlation is also applicable to other instruments with angular, spectral, or spatial correlations and can help inform laboratory calibration and characterization of the instrument uncertainty structure.