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To improve our understanding of the complex role of aerosols in the climate system and on air quality, measurements are needed of optical and microphysical aerosol. From many studies, it has become evident that a satellite-based multiangle, multiwavelength polarimeter will be essential to provide such measurements. Here, high accuracy (∼0.003) on the degree of linear polarization (DoLP) measurements is important to retrieve aerosol properties with an accuracy needed to advance our understanding of the aerosol effect on climate. SPEX airborne, a multiangle hyperspectral polarimeter, has been developed for observing and characterizing aerosols from NASA's high-altitude research aircraft ER-2. It delivers measurements of radiance and DoLP at visual wavelengths with a spectral resolution of 3 and 7-30 nm, respectively, for radiance and polarization, at nine fixed equidistant viewing angles from -56° to +56° oriented along the ground track, and a swath of 7° oriented across-track. SPEX airborne uses spectral polarization modulation to determine the state of linear polarization of scattered sunlight. This technique has been developed in the Netherlands and has been demonstrated with ground-based instruments. SPEX airborne serves as a demonstrator for a family of space-based SPEX instruments that have the ability to measure and characterize atmospheric aerosol by multiangle hyperspectral polarimetric imaging remotely from a satellite platform. SPEX airborne was calibrated radiometrically and polarimetrically using Jet Propulsion Laboratory (JPL) facilities including the Polarization Stage Generator-2 (PSG-2), which is designed for polarimetric calibration and validation of the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI). Using the PSG-2, the accuracy of the SPEX airborne DoLP measurements in the laboratory setup is found to be 0.002-0.004. Radiometric calibration is realized with an estimated accuracy of 4%. In 2017, SPEX airborne took part in the "Aerosol Characterization from Polarimeters and Lidar" campaign on the ER-2 that included four polarimeters and two lidars. Polarization measurements of SPEX airborne and the coflying Research Scanning Polarimeter (RSP), recorded during the campaign, were compared and display root-mean-square (RMS) differences ranging from 0.004 (at 555 nm) up to 0.02 (at 410 nm). For radiance measurements, excellent agreement between SPEX airborne and RSP is obtained with an RMS difference of ∼4%. The lab- and flight-performance values for polarization are similar to those recently published for AirMSPI, where also an intercomparison with RSP was made using data from field campaigns in 2013. The intercomparison of radiometric and polarimetric data both display negligible bias. The in-flight comparison results provide verification of SPEX airborne's capability to deliver high-quality data.

In early 2013, three airborne polarimeters were flown on the high altitude NASA ER-2 aircraft in California for the Polarimeter Definition Experiment (PODEX). PODEX supported the pre-formulation NASA Aerosol-Cloud-Ecosystem (ACE) mission, which calls for an imaging polarimeter in polar orbit (among other instruments) for the remote sensing of aerosols, oceans, and clouds. Several polarimeter concepts exist as airborne prototypes, some of which were deployed during PODEX as a capabilities test. Two of those instruments to date have successfully produced Level 1 (georegistered, calibrated radiance and polarization) data from that campaign: the Airborne Multiangle Spectropolarimetric Imager (AirMSPI) and the Research Scanning Polarimeter (RSP). We compared georegistered observations of a variety of scene types by these instruments to test whether Level 1 products agreed within stated uncertainties. Initial comparisons found radiometric agreement, but polarimetric biases beyond measurement uncertainties. After subsequent updates to calibration, georegistration, and the measurement uncertainty models, observations from the instruments now largely agree within stated uncertainties. However, the 470 nm reflectance channels have a roughly +6% bias of AirMSPI relative to RSP, beyond expected measurement uncertainties. We also find that observations of dark (ocean) scenes, where polarimetric uncertainty is expected to be largest, do not agree within stated polarimetric uncertainties. Otherwise, AirMSPI and RSP observations are consistent within measurement uncertainty expectations, providing credibility for the subsequent creation of Level 2 (geophysical product) data from these instruments, and comparison thereof. The techniques used in this work can also form a methodological basis for other intercomparisons, for example, of the data gathered during the recent Aerosol Characterization from Polarimeter and Lidar (ACEPOL) field campaign, carried out in October and November of 2017 with four polarimeters (including AirMSPI and RSP).

We present a comprehensive model that can be employed to describe and correct for degradation of (scan) mirrors and diffusers in satellite instruments that suffer from changing optical UV-VIS properties during their operational lifetime. As trend studies become more important, so does the importance to understand and correct for this degradation. This is the case not only with respect to the transmission of the optical components, but also with respect to wavelength, polarisation or scan-angle-effects. Our hypothesis is that mirrors in-flight suffer from the deposition of a thin absorbing layer of contaminant, which slowly builds up over time. We describe this with the Mueller matrix formalism and Fresnel equations for thin multi-layer contamination films. Special care is taken to avoid the confusion often present in earlier publications concerning Mueller matrix calculus with out of plane reflections. The method can be applied to any UV-VIS satellite instrument, and in any orbit, both low and geostationary. We illustrate and verify our approach on the optical behaviour of the multiple scan mirrors of SCIAMACHY (on board of ENVISAT). [ABSTRACT FROM AUTHOR]

In this paper, the use of a neural network algorithm for the retrieval of the aerosol properties from ground-based spectropolarimetric measurements is discussed. The neural network is able to retrieve the aerosol properties with an accuracy that is almost comparable to that of an iterative retrieval. By using the outcome of the neural network as a first guess of the iterative retrieval scheme, the accuracy of the fine and coarse mode optical thickness are further improved while for the other parameters the improvement is small or absent. The resulting scheme (neural network + iterative retrieval) is compared to the original one (look-up table + iterative retrieval) on a set of simulated ground-based measurements, and on a small set of real observations carried out by an accurate ground-based spectropolarimeter. The results show that the use of a neural network based first guess leads to an increase in the number of converging retrievals, and possibly to more accurate estimates of the aerosol effective radius and complex refractive index. [ABSTRACT FROM AUTHOR]

This study thoroughly examines the impact of aerosols on atmospheric heating rates over the North Atlantic Ocean, with a specific focus on developing African easterly waves (AEWs). The analysis leverages data from the National Aeronautics and Space Administration (NASA) DC-8 aircraft, dropsonde profiles, lidar observations, and satellite-based precipitation data obtained during NASA's Convective Processes Experiment – Cabo Verde (CPEX-CV) field campaign, as well as the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) and Copernicus Atmosphere Monitoring Service (CAMS) reanalyses. Using a four-stream radiative transfer model, the research specifically focuses on days characterized by Saharan dust coinciding with a developing AEW and contrasts its findings with a notable dust-only event in June 2020. The findings reveal notable differences in shortwave (SW) heating rates of over 1.5 K d−1 between reanalysis and observations, underlining the persistent challenges in accurately representing aerosol effects in the atmosphere, even after assimilating observational data. These discrepancies were present on days with both background and high dust concentrations, emphasizing the challenges in accurately representing aerosol radiative effects in models and highlighting the urgent need for improved aerosol representation in reanalysis datasets. Differences in heating rates were analyzed in a case study of two developing AEWs, one leading to a Category 4 hurricane (Fiona) and another leading to a short-lived tropical storm (TS; Hermine). [ABSTRACT FROM AUTHOR]

Small satellites are efficient at performing Earth science from space due to their limited cost and size. Small satellites (cubesats) achieve much with limited power production/storage, heat dissipation, data storage, and ground contact points/bandwidth. As such it is beneficial to offload as much as possible to ground support systems. Consider the HyperAngular Rainbow Polarimeter (HARP) Cubesat. Its goals were to serve as a technical demonstration prior to the development of HARP2 aboard the NASA Plankton Aerosol Cloud and ocean Ecosystem (PACE) mission and to serve as an Earth viewing remote sensing platform which measured the characteristics of clouds and aerosols. HARP cubesat was limited to taking 5-minute capture sequences once every 24 h. It took approximately 10 such captures before it needed to perform data downlink and have its memory cleared for continued use. A ground station at NASA Wallops supported HARP with approximately three points of contact each day. To maximize the value of each capture, ground support software was developed leveraging public data to inform the schedule of each capture. In this paper, we review the algorithms and data sources that allowed us to: 1; predict the HARP orbital track a week in advance, 2; predict also the location of other remote sensing satellites and ground stations relative to HARP, 3; predict the ground view geometry of the instrument along its orbital track, 4; compare global climatological data products of clouds and aerosols along the predicted orbital tracks, and 5; identify and integrate important ground target locations based on remote sensing literature and ongoing natural phenomena. This HARP Orbital Prediction System (HOPS) made HARP into a successful technical demonstration which also offered significant science value. The HOPS system presents a valuable methodology for small satellites to operate efficiently despite their limited capabilities. HOPS is also a useful testbed for studying the sensitivity of scene geometry. Using HOPS, we show that for a wide field-of-view (FOV) instrument, like HARP, latitude/longitude geolocation varies by approximately 0.1+ at a height of 8-10 km. Scattering angles vary less than 0.01+ at similar heights, with the worst performance near direct backscatter (180+). [ABSTRACT FROM AUTHOR]

The Airborne Hyper-Angular Rainbow Polarimeter (AirHARP) is a new imaging polarimeter instrument capable of sampling a single Earth target from up to 120 viewing angles, in four spectral channels, and in three linear polarization states across a 114° field of view (FOV). AirHARP is telecentric in the image space and simultaneously images three linear polarization states with no moving parts. These two aspects of the design allow for a simple and efficient quantitative calibration. Using coefficients derived at the center of the lens and the detector flatfields, we can calibrate the entire AirHARP sensor in a variety of laboratory, field, and space environments. We show that this telecentric calibration technique yields a 1 σ absolute uncertainty of 0.25 % in degree of linear polarization (DOLP) in the laboratory for all channels and for pixels around the optical axis. To validate across the FOV, we compare our multi-angle reflectance and polarization data with the Research Scanning Polarimeter (RSP) over targets sampled during the NASA Aerosol Characterization from Polarimeter and Lidar (ACEPOL) campaign. We use the error-normalized difference technique to estimate how well the instruments compare relative to their error models. We find that AirHARP and the RSP reasonably agree for reflectance and DOLP within 2 standard deviations of their mutual uncertainty at 550, 670, and 870 nm and over a limited set of ocean and desert scenes. This calibration technique makes the Hyper-Angular Rainbow Polarimeter (HARP) design attractive for new spaceborne climate missions: HARP CubeSat (2020–2022), HARP2 (2024–) on the NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE), and beyond. [ABSTRACT FROM AUTHOR]

Channeled spectropolarimetry or spectral polarization modulation is an accurate technique for measuring the continuum polarization in one shot with no moving parts. We show how a dual-beam implementation also enables spectral line polarimetry at the intrinsic resolution, as in a classic beam-splitting polarimeter. Recording redundant polarization information in the two spectrally modulated beams of a polarizing beam-splitter even provides the possibility to perform a postfacto differential transmission correction that improves the accuracy of the spectral line polarimetry. We perform an error analysis to compare the accuracy of spectral line polarimetry to continuum polarimetry, degraded by a residual dark signal and differential transmission, as well as to quantify the impact of the transmission correction. We demonstrate the new techniques with a blue sky polarization measurement around the oxygen A absorption band using the groundSPEX instrument, yielding a polarization in the deepest part of the band of 0.160±0.010, significantly different from the polarization in the continuum of 0.2284±0.0004. The presented methods are applicable to any dual-beam channeled polarimeter, including implementations for snapshot imaging polarimetry.

The springtime atmosphere over the southeast Atlantic Ocean (SEA) is subjected to a consistent layer of biomass burning (BB) smoke from widespread fires on the African continent. An elevated humidity signal is coincident with this layer, consistently proportional to the amount of smoke present. The combined humidity and BB aerosol has potentially significant radiative and dynamic impacts. Here, we use aircraft-based observations from the NASA ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) deployments in conjunction with reanalyses to characterize covariations in humidity and BB smoke across the SEA. The observed plume–vapor relationship, and its agreement with the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis version 5 (ERA5) and Copernicus Atmosphere Monitoring Service (CAMS) reanalysis, persists across all observations, although the magnitude of the relationship varies as the season progresses. Water vapor is well represented by the reanalyses, while CAMS tends to underestimate carbon monoxide especially under high BB. While CAMS aerosol optical depth (AOD) is generally overestimated relative to ORACLES AOD, the observations show a consistent relationship between carbon monoxide (CO) and aerosol extinction, demonstrating the utility of the CO tracer to understanding vertical aerosol distribution. We next use k -means clustering of the reanalyses to examine multi-year seasonal patterns and distributions. We identify canonical profile types of humidity and of CO, allowing us to characterize changes in vapor and BB atmospheric structures, and their impacts as they covary. While the humidity profiles show a range in both total water vapor concentration and in vertical structure, the CO profiles primarily vary in terms of maximum concentration, with similar vertical structures in each. The distribution of profile types varies spatiotemporally across the SEA region and through the season, ranging from largely one type in the northeast and southwest to more evenly distributed between multiple types where air masses meet in the middle of the SEA. These distributions follow patterns of transport from the humid, smoky source region (greatest influence in the northeast of the SEA) and the seasonal changes in both humidity and smoke (increasing and decreasing through the season, respectively). With this work, we establish a framework for a more complete analysis of the broader radiative and dynamical effects of humid aerosols over the SEA. [ABSTRACT FROM AUTHOR]

This article analyzes the impact of Alternative Dispute Resolution (ADR) on improving the investment environment in Indonesia. Indonesia seeks to enhance legal certainty and create a favorable climate for investors, both local and foreign, by incorporating Alternative Dispute Resolution (ADR) into its legal system. This will provide an efficient and non-judicial method for settling investment issues. This approach is further solidified by the state's adoption of the ICSID Convention via Law No. 5 of 1968, which provides a dependable arbitration mechanism for the resolution of disputes involving foreign investors and the state. The convergence of ADR principles and ICSID regulations not only corresponds to global benchmarks but also reflects the cultural ethos of "musyawarah mufakat" in Indonesia, which advocates for peaceful resolutions. Attracting investment, sustaining economic growth, and participating in regional and global trade frameworks are all dependent on these legal mechanisms being successful. There are far-reaching consequences for Indonesia's long-term economic development, and this research emphasizes the critical significance of legal frameworks in preserving investor trust. [ABSTRACT FROM AUTHOR]

The strengths and weaknesses of arbitration compared to litigation, as a system for solving procurement disputes between governments and their private counterparts has been a subject of debate among scholars. A particularly sensitive topic relates to the impartiality standards of each system and the determinants of its outcomes. Using a unique database of national arbitration resolutions we analyze the determinants of awards in procurement disputes related to public works. Estimating a cross-section model, we find evidence in favor of party capability theory and the influence of institutional factors in arbitration outcomes, like amendments to procurement law or the characteristics of the organization in charge of administering these processes. As well, we find indirect evidence that suggests that adverse outcomes for government entities are related with the lack of individual incentives of officials to settle with private contractors, and the presence of presumably undue influence among private contractors and arbitrators. [ABSTRACT FROM AUTHOR]

This paper describes a neural network cloud masking scheme from PARASOL (Polarization and Anisotropy of Reflectances for Atmospheric Science coupled with Observations from a Lidar) multi-angle polarimetric measurements. The algorithm has been trained on synthetic measurements and has been applied to the processing of 1 year of PARASOL data. Comparisons of the retrieved cloud fraction with MODIS (Moderate Resolution Imaging Spectroradiometer) products show overall agreement in spatial and temporal patterns, but the PARASOL neural network (PARASOL-NN) retrieves lower cloud fractions. Comparisons with a goodness-of-fit mask from aerosol retrievals suggest that the NN cloud mask flags fewer clear pixels as cloudy than MODIS (∼ 3 % of the clear pixels versus ∼ 15 % by MODIS). On the other hand the NN classifies more pixels incorrectly as clear than MODIS (∼ 20 % by NN, versus ∼ 15 % by MODIS). Additionally, the NN and MODIS cloud mask have been applied to the aerosol retrievals from PARASOL using the Remote Sensing of Trace Gas and Aerosol Products (RemoTAP) algorithm. Validation with AERONET shows that the NN cloud mask performs comparably with MODIS in screening residual cloud contamination in retrieved aerosol properties. Our study demonstrates that cloud masking from multi-angle polarimeter (MAP) aerosol retrievals can be performed based on the MAP measurements themselves, making the retrievals independent of the availability of a cloud imager. [ABSTRACT FROM AUTHOR]

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

In order to improve aerosol representation in the NASA Goddard Earth Observing System (GEOS) model, we evaluated simulations of the transport and properties of aerosols from southern African biomass burning sources that were observed during the first deployment of the NASA ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) field campaign in September 2016. An example case study of 24 September was analyzed in detail, during which aircraft-based in situ and remote sensing observations showed the presence of a multi-layered smoke plume structure with significant vertical variation in single scattering albedo (SSA). Our baseline GEOS simulations were not able to represent the observed SSA variation or the observed organic aerosol-to-black-carbon ratio (OA : BC). Analyzing the simulated smoke age suggests that the higher-altitude, less absorbing smoke plume was younger (∼4 d), while the lower-altitude and more absorbing smoke plume was older (∼7 d). We hypothesize a chemical or microphysical loss process exists to explain the change in aerosol absorption as the smoke plume ages, and we apply a simple loss rate to the model hydrophilic biomass burning OA to simulate this process. We also utilized the ORACLES airborne observations to better constrain the simulation of aerosol optical properties, adjusting the assumed particle size, hygroscopic growth, and absorption. Our final GEOS model simulation with additional OA loss and updated optics showed better performance in simulating aerosol optical depth (AOD) and SSA compared to independent ground- and space-based retrievals for the entire month of September 2016, including the Ozone Monitoring Instrument (OMI) Aerosol Index. In terms of radiative implications of our model adjustments, the final GEOS simulation suggested a decreased atmospheric warming of about 10 % (∼2 W m -2) over the southeastern Atlantic region and above the stratocumulus cloud decks compared to the model baseline simulations. These results improve the representation of the smoke age, transport, and optical properties in Earth system models. [ABSTRACT FROM AUTHOR]

International investment agreements (IIAs) promote foreign investment. However, they can undermine crucial health programs, creating a dilemma for governments between corporate and public health interests. For this reason, including clauses that safeguard health has become an essential practice in IIAs. According to the current literature, some countries have played a pivotal role in leading this inclusion, while others follow the former ones. However, the existing literature needs a unique approach that can quantify the influence strength of a country in disseminating clauses that explicitly mention health provisions to others. Following an NLP (Natural Language Processing)-based text similarity analysis of Bilateral Investment Treaties (BITs), this study proposes a metric, 'Influence' (INF), which provides insights into the role of different countries or regions in the propagation of IIA texts among BITs. We demonstrate a comprehensive application of this metric using a large agreement dataset. Our findings from this application corroborate the evidence in the current literature, supporting the validity of the proposed metric. According to the INF, Germany, Canada, and Brazil emerged as the most influential players in defensive, neutral, and offensive health mentions, respectively. These countries wield substantial bargaining power in international investment law and policy, and their innovative approaches to BITs set a path for others to follow. These countries provide crucial insights into the direction and sources of influence of international investment regulations to safeguard health. The proposed metric holds substantial usage for policymakers and investors. This can help them identify vital global countries in IIA text dissemination and create new policy guidelines to safeguard health while balancing economic development and public health protection. A software tool based on the proposed INF measure can be found at https://inftool.com/. [ABSTRACT FROM AUTHOR]

From a passive satellite remote sensing point of view, the richest set of information on aerosol properties can be obtained from instruments that measure both intensity and polarization of backscattered sunlight at multiple wavelengths and multiple viewing angles for one ground pixel. However, it is challenging to exploit this information at a global scale because complex algorithms are needed with many fit parameters (aerosol and land/ocean reflection), based on online radiative transfer models. So far, two such algorithms have demonstrated this capability at a global scale: the Generalized Retrieval of Atmosphere and Surface Properties (GRASP) algorithm and the Remote sensing of Trace gas and Aerosol Products (RemoTAP) algorithm. In this paper, we present a detailed comparison of the most recent versions of RemoTAP and GRASP. We evaluate both algorithms for synthetic observations, for real PARASOL (Polarization and Anisotropy of Reflectances for Atmospheric Science coupled with Observations from a Lidar) observations against AERONET (Aerosol Robotic Network) for common pixels, and for global PARASOL retrievals for the year 2008. For the aerosol optical depth (AOD) over land, both algorithms show a root mean square error (RMSE) of 0.10 (at 550 nm). For single scattering albedo (SSA), both algorithms show a good performance in terms of RMSE (0.04), but RemoTAP has a smaller bias (0.002) compared to GRASP (0.021). For the Ångström exponent (AE), GRASP has a smaller RMSE (0.367) than RemoTAP (0.387), mainly caused by a small overestimate of AE at low values (large particles). Over ocean both algorithms perform very well. For AOD, RemoTAP has an RMSE of 0.057 and GRASP an even smaller RMSE of 0.047. For AE, the RMSEs of RemoTAP and GRASP are 0.285 and 0.224, respectively. Based on the AERONET comparison, we conclude that both algorithms show very similar overall performance, where both algorithms have stronger and weaker points. For the global data products, we find a root mean square difference (RMSD) between RemoTAP and GRASP AOD of 0.12 and 0.038 over land and ocean, respectively. The largest differences occur over the biomass burning region in equatorial Africa. The global mean values are virtually unbiased with respect to each other. For AE the RMSD between RemoTAP and GRASP is 0.33 over land and 0.23 over ocean. For SSA, we find much better agreement over land (bias = - 0.01, RMSD = 0.043 for retrievals with AOD > 0.2) than over ocean (bias = 0.053, RMSD = 0.074). As expected, the differences increase towards low AOD, over both land and ocean. We also compared the GRASP and RemoTAP AOD and AE products against MODIS. For AOD over land, the agreement of either GRASP or RemoTAP with MODIS is worse than the agreement between the two PARASOL algorithms themselves. Over ocean, the agreement is very similar among the three products for AOD. For AE, the agreement between GRASP and RemoTAP is much better than the agreement of both products with MODIS. The agreement of the latest product versions with each other and with AERONET improved significantly compared to the previous version of the global products of GRASP and RemoTAP. The results demonstrate that the dedicated effort in algorithm development for multi-angle polarimetric (MAP) aerosol retrievals still leads to substantial improvement of the resulting aerosol products, and this is still an ongoing process. [ABSTRACT FROM AUTHOR]

The spectrometer of the Munich Aerosol Cloud Scanner (specMACS) is a high-spatial-resolution hyperspectral and polarized imaging system. It is operated from a nadir-looking perspective aboard the German High Altitude and LOng range (HALO) research aircraft and is mainly used for the remote sensing of clouds. In 2019, its two hyperspectral line cameras, which are sensitive to the wavelength range between 400 and 2500 nm, were complemented by two 2D RGB polarization-resolving cameras. The polarization-resolving cameras have a large field of view and allow for multi-angle polarimetric imaging with high angular and spatial resolution. This paper introduces the polarization-resolving cameras and provides a full characterization and calibration of them. We performed a geometric calibration and georeferencing of the two cameras. In addition, a radiometric calibration using laboratory calibration measurements was carried out. The radiometric calibration includes the characterization of the dark signal, linearity, and noise as well as the measurement of the spectral response functions, a polarization calibration, vignetting correction, and absolute radiometric calibration. With the calibration, georeferenced, absolute calibrated Stokes vectors rotated into the scattering plane can be computed from raw data. We validated the calibration results by comparing observations of the sunglint, which is a known target, with radiative transfer simulations of the sunglint. [ABSTRACT FROM AUTHOR]

This study thoroughly examines the impact of aerosols on atmospheric heating rates over the North Atlantic Ocean, with a specific focus on developing African Easterly Waves (AEWs). It utilizes data from the NASA DC-8 aircraft, dropsonde profiles, lidar observations, and satellite-based precipitation data obtained during NASA's CPEX-CV field campaign, as well as MERRA-2 and CAMS reanalyses. Using a four-stream radiative transfer model, the research focuses specifically on days characterized by Saharan dust coinciding with AEWs and tropical storm development and also contrasts its findings with a notable dust-only event in June 2020. The findings reveal notable differences in shortwave (SW) and longwave/infrared (LW/IR) heating rates, underscoring the persistent challenges in accurately representing aerosol effects in the atmosphere, even after assimilating observational data. These discrepancies persisted on days with both background and high dust concentrations, emphasizing the challenges in accurately representing aerosol radiative effects in models and highlighting the urgent need for improved aerosol representation in reanalysis datasets. [ABSTRACT FROM AUTHOR]

The advantages of performing aerosol retrieval with multi-angle, multi-spectral photopolarimetric measurements over intensity-only measurements come from this technique's sensitivity to aerosols' microphysical properties, such as their particle size, shape, and complex refraction index. In this study, an extended LUT (Look Up Table) algorithm inherited from a previous work based on the assumption of surface reflectance spectral shape invariance is proposed and applied to PARASOL (Polarization and Anisotropy of Reflectances for Atmospheric Science coupled with Observations from a Lidar) measurements to retrieve aerosols' optical properties including aerosol optical depth (AOD) and aerosol fine-mode fraction (FMF). Case studies conducted over East China for different aerosol scenes are investigated. A comparison between the retrieved AOD regional distribution and the corresponding MODIS (Moderate-resolution Imaging Spectroradiometer) C6 AOD products shows similar spatial distributions in the Jing-Jin-Ji (Beijing–Tianjin–Hebei, China's mega city cluster) region. The PARASOL AOD retrievals were compared against the AOD measurements of seven AERONET (Aerosol Robotic Network) stations in China to evaluate the performance of the retrieval algorithm. In the fine-particle-dominated regions, lower RMSEs were found at Beijing and Hefei urban stations (0.16 and 0.18, respectively) compared to those at other fine-particle-dominated AERONET stations, which can be attributed to the assumption of surface reflectance spectral shape invariance that has significant advantages in separating the contribution of surface and aerosol scattering in urban areas. For the FMF validation, an RMSE of 0.23, a correlation of 0.57, and a bias of −0.01 were found. These results show that the algorithm performs reasonably in distinguishing the contribution of fine and coarse particles. [ABSTRACT FROM AUTHOR]

In order to conduct accurate aerosol retrieval over snow, the Remote Sensing of Trace Gases and Aerosol Products (RemoTAP) algorithm developed by SRON Netherlands Institute for Space Research is extended with a bi-directional reflection distribution function (BRDF) for snow surfaces. The capability of the extended algorithm is validated with both synthetic measurements and real satellite measurements from the Polarization & Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar (PARASOL), and a comparison has been made to retrievals with the baseline RemoTAP (without a snow kernel). For retrievals with real PARASOL observations, we use pixels over Aerosol Robotic Network (AERONET) stations for validation and we use the MODIS snow cover products to identify pixels over snow. We evaluate the retrieved aerosol optical thickness (AOT) at 550 nm (τ550) , single-scattering albedo (SSA) at 550 nm (ω550) and Ångström exponent (AE) for 440–870 nm (AE440-870). The experiments with both synthetic and real data show that the extended RemoTAP maintains capability for snow-free pixels and has obvious advantages in accuracy and the fraction of successful retrievals for retrieval over snow, especially over surfaces with snow cover >75 %. According to the real-data experiment, we find that the retrieval algorithm has difficulty in fitting the PARASOL 1020 nm band, where snow reflectance is significantly lower than that for the visible bands. When we perform a four-band retrieval (490, 565, 670, 865 nm) with the extended RemoTAP, we obtain a good retrieval result for τ550 , ω550 and AE440-870. Therefore, the four-band retrieval with the extended RemoTAP is recommended for aerosol retrieval over snow. [ABSTRACT FROM AUTHOR]