Simultaneous Retrieval of Aerosol and Cloud Properties During the MILAGRO Field Campaign

Estimation of Direct Climate Forcing (DCF) due to aerosols in cloudy areas has historically been a difficult task, mainly because of a lack of appropriate measurements. Recently, passive remote sensing instruments have been developed that have the potential to retrieve both cloud and aerosol properties using polarimetric, multiple view angle, and multi spectral observations, and therefore determine DCF from aerosols above clouds. One such instrument is the Research Scanning Polarimeter (RSP), an airborne prototype of a sensor on the NASA Glory satellite, which unfortunately failed to reach orbit during its launch in March of 2011. In the spring of 2006, the RSP was deployed on an aircraft based in Veracruz, Mexico, as part of the Megacity Initiative: Local and Global Research Observations (MILAGRO) field campaign. On 13 March, the RSP over flew an aerosol layer lofted above a low altitude marine stratocumulus cloud close to shore in the Gulf of Mexico. We investigate the feasibility of retrieving aerosol properties over clouds using these data. Our approach is to first determine cloud droplet size distribution using the angular location of the cloud bow and other features in the polarized reflectance. The selected cloud was then used in a multiple scattering radiative transfer model optimization to determine the aerosol optical properties and fine tune the cloud size distribution. In this scene, we were able to retrieve aerosol optical depth, the fine mode aerosol size distribution parameters and the cloud droplet size distribution parameters to a degree of accuracy required for climate modeling. This required assumptions about the aerosol vertical distribution and the optical properties of the coarse aerosol size mode. A sensitivity study was also performed to place this study in the context of future systematic scanning polarimeter observations, which found that the aerosol complex refractive index can also be observed accurately if the aerosol optical depth is larger than roughly 0.8 at a wavelength of (0.555 m)

Comparisons of Bispectral and Polarimetric Retrievals of Marine Boundary Layer Cloud Microphysics: Case Studies Using a LES-Satellite Retrieval Simulator

Many passive remote-sensing techniques have been developed to retrieve cloud microphysical properties from satellite-based sensors, with the most common approaches being the bispectral and polarimetric techniques. These two vastly different retrieval techniques have been implemented for a variety of polar-orbiting and geostationary satellite platforms, providing global climatological data sets. Prior instrument comparison studies have shown that there are systematic differences between the droplet size retrieval products (effective radius) of bispectral (e.g., MODIS, Moderate Resolution Imaging Spectroradiometer) and polarimetric (e.g., POLDER, Polarization and Directionality of Earth's Reflectances) instruments. However, intercomparisons of airborne bispectral and polarimetric instruments have yielded results that do not appear to be systematically biased relative to one another. Diagnosing this discrepancy is complicated, because it is often difficult for instrument intercomparison studies to isolate differences between retrieval technique sensitivities and specific instrumental differences such as calibration and atmospheric correction. In addition to these technical differences the polarimetric retrieval is also sensitive to the dispersion of the droplet size distribution (effective variance), which could influence the interpretation of the droplet size retrieval. To avoid these instrument-dependent complications, this study makes use of a cloud remote-sensing retrieval simulator. Created by coupling a large-eddy simulation (LES) cloud model with a 1-D radiative transfer model, the simulator serves as a test bed for understanding differences between bispectral and polarimetric retrievals. With the help of this simulator we can not only compare the two techniques to one another (retrieval intercomparison) but also validate retrievals directly against the LES cloud properties. Using the satellite retrieval simulator, we are able to verify that at high spatial resolution (50 m) the bispectral and polarimetric retrievals are highly correlated with one another within expected observational uncertainties. The relatively small systematic biases at high spatial resolution can be attributed to different sensitivity limitations of the two retrievals. In contrast, a systematic difference between the two retrievals emerges at coarser resolution. This bias largely stems from differences related to sensitivity of the two retrievals to unresolved inhomogeneities in effective variance and optical thickness. The influence of coarse angular resolution is found to increase uncertainty in the polarimetric retrieval but generally maintains a constant mean value

Observations of Aerosol-Radiation-Cloud Interactions in the South-East Atlantic: First Results from the ORACLES Deployments in 2016 and 2017

Southern Africa produces almost a third of the Earths biomass burning (BB) aerosol particles. Particles lofted into the mid-troposphere are transported westward over the South-East (SE) Atlantic, home to one of the three permanent subtropical stratocumulus (Sc) cloud decks in the world. The SE Atlantic stratocumulus deck interacts with the dense layers of BB aerosols that initially overlay the cloud deck, but later subside and often mix into the clouds. These interactions include adjustments to aerosol-induced solar heating and microphysical effects, and their global representation in climate models remains one of the largest uncertainties in estimates of future climate. Hence, new observations over the SE Atlantic have significant implications for regional and global climate change predictions.The low-level clouds in the SE Atlantic have limited vertical extent and therefore present favorable conditions for their exploration with remote sensing. On the other hand, the normal coexistence of BB aerosols and Sc clouds in the same scene also presents significant challenges to conventional remote sensing techniques. We describe first results from NASAs airborne ORACLES (ObseRvations of Aerosols Above Clouds and Their IntEractionS) deployments in September 2016 and August 2017. We emphasize the unique role of polarimetric observations by two instruments, the Research Scanning Polarimeter (RSP) and the Airborne Multi-angle SpectroPolarimeter Imager (AirMSPI), and describe how these instruments help address specific ORACLES science objectives. Initial assessments of polarimetric observation accuracy for key cloud and aerosol properties will be presented, in as far as the preliminary nature of measurements permits

Combined Retrievals of Boreal Forest Fire Aerosol Properties with a Polarimeter and Lidar

Absorbing aerosols play an important, but uncertain, role in the global climate. Much of this uncertainty is due to a lack of adequate aerosol measurements. While great strides have been made in observational capability in the previous years and decades, it has become increasingly apparent that this development must continue. Scanning polarimeters have been designed to help resolve this issue by making accurate, multi-spectral, multi-angle polarized observations. This work involves the use of the Research Scanning Polarimeter (RSP). The RSP was designed as the airborne prototype for the Aerosol Polarimetery Sensor (APS), which was due to be launched as part of the (ultimately failed) NASA Glory mission. Field observations with the RSP, however, have established that simultaneous retrievals of aerosol absorption and vertical distribution over bright land surfaces are quite uncertain. We test a merger of RSP and High Spectral Resolution Lidar (HSRL) data with observations of boreal forest fire smoke, collected during the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS). During ARCTAS, the RSP and HSRL instruments were mounted on the same aircraft, and validation data were provided by instruments on an aircraft flying a coordinated flight pattern. We found that the lidar data did indeed improve aerosol retrievals using an optimal estimation method, although not primarily because of the constraints imposed on the aerosol vertical distribution. The more useful piece of information from the HSRL was the total column aerosol optical depth, which was used to select the initial value (optimization starting point) of the aerosol number concentration. When ground based sun photometer network climatologies of number concentration were used as an initial value, we found that roughly half of the retrievals had unrealistic sizes and imaginary indices, even though the retrieved spectral optical depths agreed within uncertainties to independent observations. The convergence to an unrealistic local minimum by the optimal estimator is related to the relatively low sensitivity to particles smaller than 0.1 ( m) at large optical thicknesses. Thus, optimization algorithms used for operational aerosol retrievals of the fine mode size distribution, when the total optical depth is large, will require initial values generated from table look-ups that exclude unrealistic size/complex index mixtures. External constraints from lidar on initial values used in the optimal estimation methods will also be valuable in reducing the likelihood of obtaining spurious retrievals

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

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.</p

Comparisons of bispectral and polarimetric retrievals of marine boundary layer cloud microphysics: case studies using a LES–satellite retrieval simulator

Many passive remote-sensing techniques have been developed to retrieve cloud microphysical properties from satellite-based sensors, with the most common approaches being the bispectral and polarimetric techniques. These two vastly different retrieval techniques have been implemented for a variety of polar-orbiting and geostationary satellite platforms, providing global climatological data sets. Prior instrument comparison studies have shown that there are systematic differences between the droplet size retrieval products (effective radius) of bispectral (e.g., MODIS, Moderate Resolution Imaging Spectroradiometer) and polarimetric (e.g., POLDER, Polarization and Directionality of Earth's Reflectances) instruments. However, intercomparisons of airborne bispectral and polarimetric instruments have yielded results that do not appear to be systematically biased relative to one another. Diagnosing this discrepancy is complicated, because it is often difficult for instrument intercomparison studies to isolate differences between retrieval technique sensitivities and specific instrumental differences such as calibration and atmospheric correction. In addition to these technical differences the polarimetric retrieval is also sensitive to the dispersion of the droplet size distribution (effective variance), which could influence the interpretation of the droplet size retrieval. To avoid these instrument-dependent complications, this study makes use of a cloud remote-sensing retrieval simulator. Created by coupling a large-eddy simulation (LES) cloud model with a 1-D radiative transfer model, the simulator serves as a test bed for understanding differences between bispectral and polarimetric retrievals. With the help of this simulator we can not only compare the two techniques to one another (retrieval intercomparison) but also validate retrievals directly against the LES cloud properties. Using the satellite retrieval simulator, we are able to verify that at high spatial resolution (50 m) the bispectral and polarimetric retrievals are highly correlated with one another within expected observational uncertainties. The relatively small systematic biases at high spatial resolution can be attributed to different sensitivity limitations of the two retrievals. In contrast, a systematic difference between the two retrievals emerges at coarser resolution. This bias largely stems from differences related to sensitivity of the two retrievals to unresolved inhomogeneities in effective variance and optical thickness. The influence of coarse angular resolution is found to increase uncertainty in the polarimetric retrieval but generally maintains a constant mean value

Maritime Aerosol Network as a component of Aerosol Robotic Network

Author Posting. © American Geophysical Union, 2009. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 114 (2009): D06204, doi:10.1029/2008JD011257.The paper presents the current status of the Maritime Aerosol Network (MAN), which has been developed as a component of the Aerosol Robotic Network (AERONET). MAN deploys Microtops handheld Sun photometers and utilizes the calibration procedure and data processing (Version 2) traceable to AERONET. A web site dedicated to the MAN activity is described. A brief historical perspective is given to aerosol optical depth (AOD) measurements over the oceans. A short summary of the existing data, collected on board ships of opportunity during the NASA Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) Project is presented. Globally averaged oceanic aerosol optical depth (derived from island-based AERONET measurements) at 500 nm is ∼0.11 and Angstrom parameter (computed within spectral range 440–870 nm) is calculated to be ∼0.6. First results from the cruises contributing to the Maritime Aerosol Network are shown. MAN ship-based aerosol optical depth compares well to simultaneous island and near-coastal AERONET site AOD.The work of Tymon Zielinski was supported by Polish national grant AERONET59

An overview of the ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) project: aerosol–cloud–radiation interactions in the southeast Atlantic basin

This is the final version. Available on open access from the European Geosciences Union via the DOI in this recordData availability: All ORACLES data are accessible via the digital object identifiers (DOIs) provided under ORACLES Science Team (2020a–d) references: https://doi.org/10.5067/Suborbital/ORACLES/P3/2018_V2 (ORACLES Science Team, 2020a), https://doi.org/10.5067/Suborbital/ORACLES/P3/2017_V2 (ORACLES Science Team, 2020b), https://doi.org/10.5067/Suborbital/ORACLES/P3/2016_V2 (ORACLES Science Team, 2020c), and https://doi.org/10.5067/Suborbital/ORACLES/ER2/2016_V2 (ORACLES Science Team, 2020d). The only exceptions are noted as footnotes to Table B2.Southern Africa produces almost a third of the Earth's biomass burning (BB) aerosol particles, yet the fate of these particles and their influence on regional and global climate is poorly understood. ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) is a 5-year NASA EVS-2 (Earth Venture Suborbital-2) investigation with three intensive observation periods designed to study key atmospheric processes that determine the climate impacts of these aerosols. During the Southern Hemisphere winter and spring (June–October), aerosol particles reaching 3–5 km in altitude are transported westward over the southeast Atlantic, where they interact with one of the largest subtropical stratocumulus (Sc) cloud decks in the world. The representation of these interactions in climate models remains highly uncertain in part due to a scarcity of observational constraints on aerosol and cloud properties, as well as due to the parameterized treatment of physical processes. Three ORACLES deployments by the NASA P-3 aircraft in September 2016, August 2017, and October 2018 (totaling ∼350 science flight hours), augmented by the deployment of the NASA ER-2 aircraft for remote sensing in September 2016 (totaling ∼100 science flight hours), were intended to help fill this observational gap. ORACLES focuses on three fundamental science themes centered on the climate effects of African BB aerosols: (a) direct aerosol radiative effects, (b) effects of aerosol absorption on atmospheric circulation and clouds, and (c) aerosol–cloud microphysical interactions. This paper summarizes the ORACLES science objectives, describes the project implementation, provides an overview of the flights and measurements in each deployment, and highlights the integrative modeling efforts from cloud to global scales to address science objectives. Significant new findings on the vertical structure of BB aerosol physical and chemical properties, chemical aging, cloud condensation nuclei, rain and precipitation statistics, and aerosol indirect effects are emphasized, but their detailed descriptions are the subject of separate publications. The main purpose of this paper is to familiarize the broader scientific community with the ORACLES project and the dataset it produced.NAS

Cloud thermodynamic phase detection with polarimetrically sensitive passive sky radiometers

The primary goal of this project has been to investigate if ground-based visible and near-infrared passive radiometers that have polarization sensitivity can determine the thermodynamic phase of overlying clouds, i.e., if they are comprised of liquid droplets or ice particles. While this knowledge is important by itself for our understanding of the global climate, it can also help improve cloud property retrieval algorithms that use total (unpolarized) radiance to determine cloud optical depth (COD). This is a potentially unexploited capability of some instruments in the NASA Aerosol Robotic Network (AERONET), which, if practical, could expand the products of that global instrument network at minimal additional cost. <br><br> We performed simulations that found, for zenith observations, that cloud thermodynamic phase is often expressed in the sign of the <i>Q</i> component of the Stokes polarization vector. We chose our reference frame as the plane containing solar and observation vectors, so the sign of <i>Q</i> indicates the polarization direction, parallel (positive) or perpendicular (parallel) to that plane. Since the fraction of linearly polarized to total light is inversely proportional to COD, optically thin clouds are most likely to create a signal greater than instrument noise. Besides COD and instrument accuracy, other important factors for the determination of cloud thermodynamic phase are the solar and observation geometry (scattering angles between 40 and 60° are best), and the properties of ice particles (pristine particles may have halos or other features that make them difficult to distinguish from water droplets at specific scattering angles, while extreme ice crystal aspect ratios polarize more than compact particles). <br><br> We tested the conclusions of our simulations using data from polarimetrically sensitive versions of the Cimel 318 sun photometer/radiometer that compose a portion of AERONET. Most algorithms that exploit Cimel polarized observations use the degree of linear polarization (DoLP), not the individual Stokes vector elements (such as <i>Q</i>). Ability to determine cloud thermodynamic phase depends on <i>Q</i> measurement accuracy, which has not been rigorously assessed for Cimel instruments. For this reason, we did not know if cloud phase could be determined from Cimel observations successfully. Indeed, comparisons to ceilometer observations with a single polarized spectral channel version of the Cimel at a site in the Netherlands showed little correlation. Comparisons to lidar observations with a more recently developed, multi-wavelength polarized Cimel in Maryland, USA, show more promise. The lack of well-characterized observations has prompted us to begin the development of a small test instrument called the Sky Polarization Radiometric Instrument for Test and Evaluation (SPRITE). This instrument is specifically devoted to the accurate observation of <i>Q</i>, and the testing of calibration and uncertainty assessment techniques, with the ultimate goal of understanding the practical feasibility of these measurements

In Situ Mg/Ca Measurements on Foraminifera: Comparison Between Laser Ablation Inductively Coupled Plasma Mass Spectrometry and Wavelength‐Dispersive X‐Ray Spectroscopy by Electron Probe Microanalyzer

Abstract We present a comparison of two different techniques: Laser Ablation Inductively Coupled Plasma Mass Spectrometry (LA‐ICP‐MS) and wavelength‐dispersive X‐Ray Spectroscopy by electron probe microanalyzer (EPMA) for obtaining Mg/Ca ratios in individual foraminifera shells. The goal is to assess the use of EPMA as an alternative technique for Mg/Ca analyses of single foraminiferal calcite shells. Foraminifera obtained from sediments (benthic, Uvigerina spp.) and from plankton tows (planktonic, Orbulina universa) were analyzed. All specimens were prepared in epoxy mounts and exposed in cross‐section such that multiple high‐resolution analyses could be completed on the shells using both techniques. We examined our data using statistical methods designed for the assessment and comparison of measurement techniques. In the case of Uvigerina, the mean difference for ratios obtained using EPMA and LA‐ICP‐MS is very small (−0.046 mmol mol−1) and scale independent. The Limits of Agreement (LoA, the standard deviation of the bias plus the mean bias) is [−0.315, 0.223] mmol mol−1. For samples with ratios lower than 13 mmol mol−1, we found a mean EPMA–LA‐ICP‐MS bias of −2.44 mmol mol−1 and a corresponding LoA of [−3.85, −1.04] mmol mol−1. For ratios higher than 13 mmol mol−1, there appears to be a scale dependent bias, meaning that the EPMA measured ratios become progressively larger than those of LA‐ICP‐MS as the Mg/Ca ratio increases, so the mean bias and LoA metrics are not meaningful. Results indicate that it is possible to use EPMA to collect Mg/Ca data, if the ratios are lower than ∼13 mmol mol−1