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At least 217 records · Page 12

Aerosol Optical Depth Changes in Version 4 CALIPSO Level 2 Product

The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) version 4.10 (V4) products were released in November 2016 with substantial enhancements. There have been improvements in the V4 CALIOP level 2 aerosol optical depth (AOD) compared to V3 (version 3) due to various factors. AOD change from V3 to V4 is investigated by separating factors. CALIOP AOD was compared with the Moderate Resolution Imaging Spectroradiometer (MODIS) and Aerosol Robotic Network (AERONET) for both V3 and V4.

Kim, Man-Hae↗

Optimal Estimation-Based Algorithm to Retrieve Aerosol Optical Properties for GEMS Measurements Over Asia

The Geostationary Environment Monitoring Spectrometer (GEMS) is scheduled to be in orbit in 2019 onboard the GEO-KOMPSAT 2B satellite and will continuously monitor air quality over Asia. The GEMS will make measurements in the UV spectrum (300-500 nm) with 0.6 nm resolution. In this study, an algorithm is developed to retrieve aerosol optical properties from UV-visible measurements for the future satellite instrument and is tested using 3 years of existing OMI L1B data. This algorithm provides aerosol optical depth (AOD), single scattering albedo (SSA) and aerosol layer height (ALH) using an optimized estimation method. The retrieved AOD shows good correlation with Aerosol Robotic Network (AERONET) AOD with correlation coefficients of 0.83, 0.73 and 0.80 for heavy-absorbing fine (HAF) particles, dust and non-absorbing (NA) particles, respectively. However, regression tests indicate underestimation and overestimation of HAF and NA AOD, respectively. In comparison with AOD from the OMI/Aura Near-UV Aerosol Optical Depth and Single Scattering Albedo 1-orbit L2 Swath 13 km x 24 km V003 (OMAERUV) algorithm, the retrieved AOD has a correlation coefficient of 0.86 and linear regression equation, AOD(sub GEMS) = 1.18AOD(sub OMAERUV) + 0.09. An uncertainty test based on a reference method, which estimates retrieval error by applying the algorithm to simulated radiance data, revealed that assumptions in the spectral dependency of aerosol absorptivity in the UV cause significant errors in aerosol property retrieval, particularly the SSA retrieval. Consequently, retrieved SSAs did not show good correlation with AERONET values. The ALH results were qualitatively compared with the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) products and were found to be well correlated for highly absorbing aerosols. The difference between the attenuated-backscatter-weighted height from CALIOP and retrieved ALH were mostly closed to zero when the retrieved AOD is higher than 0.8 and SSA is lower than 0.93. Although retrieval accuracy was not significantly improved, the simultaneous consistent retrieval of AOD, SSA and ALH alone demonstrates the value of this stand-alone algorithm, given their nature for error using other methods. The use of these properties as input parameters for the air mass factor calculation is expected to improve the retrieval of other trace gases over Asia.

Geostationary Environment Monitoring Spectrometer ↗

Satellite Observations of Cloud-Related Variations in Aerosol Properties

This paper presents an overview of our efforts to characterize and better understandcloud-related changes in aerosol properties. These efforts primarily involved the statistical analysisof global or regional datasets of Moderate Resolution Imaging Spectroradiometer (MODIS) andCloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aerosol and cloud observations. Theresults show that in oceanic regions, more than half of all aerosol measurements by passive satelliteinstruments come from near-cloud areas, where clouds and cloud-related processes may significantlymodify aerosol optical depth and particle size. Aerosol optical depth is also shown to increasesystematically with regional cloud amount throughout the Earth. In contrast, it is shown thateffective particle size can either increase or decrease with increasing cloud cover. In bimodal aerosolpopulations, the sign of changes depends on whether coarse mode or small mode aerosols are mostaffected by clouds. The results also indicate that over large parts of Earth, undetected cloud particlesare not the dominant reason for the satellite-observed changes with cloud amount, and that 3Dradiative processes contribute about 30% of the observed near-cloud changes. The findings underlinethe need for improving our ability to accurately measure aerosols near clouds.

aerosol; cloud; satellite↗

Seasonal and Diurnal Opportunities for XCH4, XCO2, and XCO for the Amazonian Rainforest Region Allowing Sampling and Validation

There is considerable interest in the aggregate methane emissions from the Amazon and similar moist tropical regions, and XCH4 measurements are well suited to constrain sources to the global atmosphere. Similarly, XCO2 measurements constrain CO2 in the region. XCO helps to partition CO2 patterns among burning and respiration processes. GeoCarb may allow these column measurements over the Western Hemisphere, but satellite retrieval require exacting calibration and validation by sun-focused Fourier transform spectrometers (FTS). The rarity of sufficiently large gaps in the cloud cover over the Amazon and similar rainforests restricts the validation opportunities for useful FTS observations and even more the opportunities for accurate retrievals. TropOMI observational statistics are extremely poor for the region. We have used two data sources to evaluate FTS opportunities at Manaus, Brazil, an FTS operated for 8 months near Manaus by Mavendra Dubey, and also sun-photometer measurements at several stations. The promise of using data from other satellites, e.g. GOES-16 ( (Geostationary Operational Environmental Satellite) and CALIOP (Cloud-Aerosol LIdar with Orthogonal Polarization gaps and aerosol layering will be described. We report initial results on five questions: (1) how frequent are observing opportunities of FTS?, (2) What evidence is there that gaps in clouds are wide enough for satellite retrievals at an appropriate accuracy, (3) What is the diurnal and seasonal variability of cloud gaps?, and (4) What limitations are currently suggested for unbiased FTS measurement of XCH4 due to diurnal effects, and (5) What evidence is there for incidence of problematic high aerosol extinction at higher layers of the troposphere (800 hPa to 120 hPa) which alter the XCH4 light-paths?

Chatfield, Robert↗

CALIPSO Lidar Level 3 Aerosol Profile Product: Version 3 Algorithm Design

The CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) level 3 aerosol profile product reports globally gridded, quality-screened, monthly mean aerosol extinction profiles retrieved by CALIOP (the Cloud-Aerosol Lidar with Orthogonal Polarization). This paper describes the quality screening and averaging methods used to generate the version 3 product. The fundamental input data are CALIOP level 2 aerosol extinction profiles and layer classification information (aerosol, cloud, and clear-air). Prior to aggregation, the extinction profiles are quality-screened by a series of filters to reduce the impact of layer detection errors, layer classification errors, extinction retrieval errors, and biases due to an intermittent signal anomaly at the surface. The relative influence of these filters are compared in terms of sample rejection frequency, mean extinction, and mean aerosol optical depth (AOD). The “extinction QC flag” filter is the most influential in preventing high-biases in level 3 mean extinction, while the “misclassified cirrus fringe” filter is most aggressive at rejecting cirrus misclassified as aerosol. The impact of quality screening on monthly mean aerosol extinction is investigated globally and regionally. After applying quality filters, the level 3 algorithm calculates monthly mean AOD by vertically integrating the monthly mean quality-screened aerosol extinction profile. Calculating monthly mean AOD by integrating the monthly mean extinction profile prevents a low bias that would result from alternately integrating the set of extinction profiles first and then averaging the resultant AOD values together. Ultimately, the quality filters reduce level 3 mean AOD by −24 and −31 % for global ocean and global land, respectively, indicating the importance of quality screening.

Tackett, Jason L.↗

Characterization and Application of Artificial Light Sources for Nighttime Aerosol Optical Depth Retrievals using the Visible Infrared Imager Radiometer Suite Day/Night Band

Using nighttime observations from Visible Infrared Imager Radiometer Suite (VIIRS) Day/Night band (DNB), the characteristics of artificial light sources are evaluated as functions of observation conditions, and incremental improvements are documented on nighttime aerosol retrievals using VIIRS DNB data on a regional scale. We find that the standard deviation of instantaneous radiance for a given artificial light source is strongly dependent upon the satellite viewing angle but is weakly dependent on lunar fraction and lunar angle. Retrieval of nighttime aerosol optical thickness (AOT) based on the novel use of these artificial light sources is demonstrated for three selected regions (United States, Middle East and India) during 2015. Reason-able agreement is found between nighttime AOTs from the VIIRS DNB and temporally adjacent daytime AOTs from the AErosol RObotic NETwork (AERONET) as well as from coincident nighttime AOT retrievals from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), indicating the potential of this method to begin filling critical gaps in diurnal AOT information at both regional and global scales. Issues related to cloud, snow and ice contamination during the winter season, as well as data loss due to the misclassification of thick aerosol plumes as clouds, must be addressed to make the algorithm operationally robust.

Jianglong Zhang↗

CALIPSO Level 3 Stratospheric Aerosol Product: Version 1.00 Algorithm Description and Initial Assessment

In August 2018,the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) project released a new level 3 stratospheric aerosol profile data product derived from nearly 12 years of measurements acquired by the space-borne Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP).This monthly averaged, gridded level 3 product is based on version 4.2 of the CALIOP level 1 and level 2 data products, which feature significantly improved calibration that now makes it possible to reliably retrieve profiles of stratospheric aerosol extinction and backscatter coefficients. This paper describes the science algorithm and data handling techniques that were developed to generate the CALIPSO version 1.00 level 3 stratospheric aerosol profile product. Further, we show that the retrieved extinction profiles capture the major stratospheric perturbations over the last decade resulting from volcanic eruptions, extreme smoke events, and signatures of stratospheric dynamics. Initial assessment of the product by inter-comparison with the stratospheric aerosol retrievals from the Stratospheric Aerosol and Gas Experiment III (SAGE III) on the International Space Station (ISS) indicates good agreement in the tropical stratospheric aerosol layer (30oN-30oS),where the average difference between zonal mean extinction profiles is typically less than 25% between 20km and 30km. However, differences can exceed 100% in the very low aerosol loading regimes found above 25 km at higher latitudes.

Jayanta Kar↗

TPSAS-NF1676L-35847-DND

Aerosols, especially particulate matter with aerodynamic diameters smaller than 2.5 ?m (PM2.5), contribute to air pollution and negatively impact human health. Past studies have estimated PM2.5 concentrations through the use of aerosol optical thickness (AOT) datasets from passive satellite sensors like MODIS and MISR. However, a major limitation of using passive AOTs for PM2.5 applications is that they are column-integrated, while PM2.5 is a surface measurement. In this study, we employ a bulk-mass-modeling-based method to directly derive PM2.5 concentrations over the contiguous United States (CONUS) using two years (2008-2009) of daytime and nighttime near-surface aerosol extinction retrievals from the NASA Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument, bulk mass extinction efficiencies, and model-based hygroscopicity. Results reveal that CALIOP-derived PM2.5 agrees reasonably well with ground-based PM2.5 observations from the U.S. Environmental Protection Agency (EPA), implying this method exhibits some merit in monitoring PM2.5 concentrations from CALIOP data. The newly developed method is then applied to CALIOP aerosol extinction retrievals using nearly the entire CALIOP data record (2007-2018), and an initial trend analysis is conducted. Results from various sensitivity studies are also shown, including those of surface layer height and assumed aerosol type.

Travis D Toth↗

TPSAS-NF1676L-23557-DND

The Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) measures both parallel and perpendicular backscatter of linearly polarized 532 nm light from cloud particles in the atmosphere. The perpendicular component of the return signal allows differentiation between cloud layers consisting of spherical water droplets from those with non-spherical ice particles. A two-way distribution of layer-integrated 532 nm total backscatter and the layer-integrated 532 nm depolarization ratio further differentiates between water cloud layers with significant multiple scattering, horizontally-oriented ice particles that cause specular reflections, and randomly-oriented ice particles, as described in Hu et al., 2009. The cloud phase algorithm functions well for the majority of clouds, but there have been some recent changes and improvements that are described in this poster. The impact of the CALIOP viewing angle change from near-nadir (0.3 degrees) to slightly tilted (3.0 degrees) on the optical properties of the various CALIOP cloud particle phases is also shown. A major improvement to the phase algorithm is the limitation of a spatial coherence test for horizontally-oriented ice to cloud layers that have sufficient integrated attenuated backscatter to likely contain HOI. This change reduces a "striping" effect caused by noisiness in the spatial coherence test for thin cloud layers. Additional temperature tests are considered, and the regional and vertical distribution of cloud layers with the various CALIOP cloud phases is shown. Only one cloud particle phase is allowed for each 5 km portion of a cloud layer that is considered by the cloud phase algorithm, so we use in situ aircraft and CloudSat observations to determine how the CALIOP cloud phase algorithm is treating optically and thermally thick clouds, which may be mixed-phase.

Melody Avery↗

Synergistic Use of Hyperspectral UV-Visible OMI and Broadband Meteorological Imager MODIS Data for a Merged Aerosol Product

The retrieval of optimal aerosol datasets by the synergistic use of hyperspectral ultraviolet(UV)–visible and broadband meteorological imager (MI) techniques was investigated. The Aura Ozone Monitoring Instrument (OMI) Level 1B (L1B) was used as a proxy for hyperspectral UV–visible instrument data to which the Geostationary Environment Monitoring Spectrometer (GEMS) aerosol algorithm was applied. Moderate-Resolution Imaging Spectroradiometer (MODIS) L1B and dark target aerosol Level 2 (L2) data were used with a broadband MI to take advantage of the consistent time gap between the MODIS and the OMI. First, the use of cloud mask information from the MI infrared (IR) channel was tested for synergy. High-spatial-resolution and IR channels of the MI helped mask cirrus and sub-pixel cloud contamination of GEMS aerosol, as clearly seen in aerosol optical depth (AOD) validation with Aerosol Robotic Network (AERONET) data. Second, dust aerosols were distinguished in the GEMS aerosol-type classification algorithm by calculating the total dust confidence index (TDCI) from MODIS L1B IR channels. Statistical analysis indicates that the Probability of Correct Detection (POCD) between the forward and inversion aerosol dust models (DS) was increased from 72% to 94% by use of the TDCI for GEMS aerosol-type classification, and updated aerosol types were then applied to the GEMS algorithm. Use of the TDCI for DS type classification in the GEMS retrieval procedure gave improved single-scattering albedo (SSA) values for absorbing fine pollution particles (BC) and DS aerosols. Aerosol layer height (ALH) retrieved from GEMS was compared with Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data, which provides high-resolution vertical aerosol profile information. The CALIOP ALH was calculated from total attenuated backscatter data at 1064 nm, which is identical to the definition of GEMS ALH. Application of the TDCI value reduced the median bias of GEMS ALH data slightly. The GEMS ALH bias approximates zero, especially for GEMS AOD values of>~0.4 and GEMS SSA values of<~0.95.Finally, the AOD products from the GEMS algorithm and MI were used in aerosol merging with the maximum-likelihood estimation method, based on a weighting factor derived from the standard deviation of the original AOD products. With the advantage of the UV–visible channel in retrieving aerosol properties over bright surfaces, the combined AOD products demonstrated better spatial data availability than the original AOD products, with comparable accuracy. Furthermore, pixel-level error analysis of GEMS AOD data indicates improvement through MI synergy.

aerosol↗

Investigation of CATS Aerosol Products and Application Toward Global Diurnal Variation of Aerosols

We present a comparison of 1064 nm aerosol optical depth (AOD) and aerosol extinction profiles from the Cloud-Aerosol Transport System (CATS) level 2 aerosol product with collocated Aerosol Robotic Network (AERONET) AOD, Moderate Imaging Spectroradiometer (MODIS) Aqua and Terra Dark Target AOD and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) AOD and extinction data for the period of March 2015–October 2017. Upon quality-assurance checks of CATS data, reasonable agreement is found between aerosol data from CATS and other sensors. Using quality-assured CATS aerosol data, for the first time, variations in AODs and aerosol extinction profiles are evaluated at 00:00, 06:00, 12:00 and 18:00 UTC (and/or 00:00, 06:00, 12:00 and 18:00 local time or LT) on both regional and global scales. This study suggests that marginal variations are found in AOD from a global mean perspective, with the minimum aerosol extinction values found at 18:00 LT near the surface layer for global oceans, for both the June–November and December–May seasons. Over land, below 500 m, the daily minimum and maximum aerosol extinction values are found at 12:00 and 00:00/06:00 LT, respectively. Strong diurnal variations are also found over north Africa, the Middle East and India for the December–May season, and over north Africa, south Africa, the Middle East and India for the June–November season.

Logan Lee↗

Cloud Aerosol LIDAR Infrared Pathfinder Satellite Observations (CALIPSO) - Data Management - Data Products Catalog V4.94

The CALIPSO V2.00 Lidar Level 2 Polar Stratospheric Cloud data product is an updated version of an already order-able dat set. The changes were signed off by the CALIPSO Configuration Control Board, versioned, and the code uploaded to a code repository. There is no ITAR/SBU data or code associated with this product. Data will be publicly order-able at the NASA LaRC Atmospheric Sciences Data Center (ASDC). All documentation and web sites will be made public once the data product is released. The data is in HDF4 format and will be generated for majority of the mission (June 2006 - March 2021). The attached Data Products Catalog (v4.94) describes this new product in section 2.14, pp 115- 119.

Mark Vaughan↗

Assessment of the Accuracy and Consistency of Cloud Property Retrievals from Passive Radiometers with Varying Spectral Information

Over the past few decades, space-based passive radiometers have been used to study the spatial distribution of clouds and some of their basic properties. Modern radiometers have significantly higher spatial resolution and collect more spectral information (i.e., have more spectral bands) than early instruments, and these advances have allowed researchers to characterize cloud physical and microphysical properties with greater detail. There is significant interest in utilizing as much of the existing satellite record as possible to study global and regional changes in cloud occurrence and distribution as well as the associated changes in reflected shortwave and outgoing longwave fluxes. Cloud property retrieval algorithms such as the NASA Satellite Cloud Optical and Radiative Property System (SatCORPS) have traditionally utilized as much spectral information as possible in order to maximize the accuracy of the retrievals. However, changes to the retrieval algorithm over time in order to take advantage of progressively more spectral information results in inconsistencies in cloud properties which in turn results in inconsistencies with products derived from these properties. It is not possible to implement modern state-of-the-art algorithms to earlier instruments which lack diverse spectral information, but many instruments since the early 2000s generally have approximately similar spectral bands in the visible (~0.65 microns), longwave infrared (~11 microns), and in many cases, the midwave infrared (~3.8 microns) and water vapor absorption (~6.7 microns), portions of the electromagnetic spectrum. Different versions of SatCORPS have been implemented with either the full set of spectral information collected by imagers such as GOES-16 and MODIS or with a reduced set of spectral bands in order to be more consistent with past imagers that lack such diverse spectral information. This study uses independent cloud property retrievals from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) to assess the accuracy of the retrievals (e.g., cloud fraction, thermodynamic phase, altitude) from the different retrieval methods and to demonstrate the advantages and disadvantages of using a reduced set of common spectral bands in order to achieve temporal and spatial consistency across different instruments.

Christopher R. Yost↗

Three-Wavelength Approach for Aerosol-Cloud Discrimination in the Sage III/ISS Aerosol Extinction Dataset

The tropical upper troposphere and lower stratosphere (UTLS) region is dominated by aerosols and clouds affecting Earth’s radiation budget and climate. Thus, satellites’ continuous monitoring and identification of these layers is crucial for quantifying their radiative impact. However, distinguishing between aerosols and clouds is challenging, especially under the perturbed UTLS conditions during post-volcanic eruptions and wildfire events. Aerosol-cloud discrimination is primarily based on their disparate wavelength-dependent scattering and absorption properties. In this study, we use aerosol extinction observations in the tropical (15°N-15°S) UTLS from June 2017 to February 2021, available from the latest generation of the Stratospheric Aerosol and Gas Experiment (SAGE) instrument-SAGE III onboard the International Space Station (ISS) to study aerosols and clouds. During this period, the SAGE III/ISS provided better coverage over the tropics at additional wavelength channels (relative to previous SAGE missions) and witnessed several volcanic and wildfire events that perturbed the tropical UTLS. We explore the advantage of having an extinction coefficient at an additional wavelength channel (1550 nm) from the SAGE III/ISS in aerosol-cloud discrimination using a method based on thresholds of two extinction coefficient ratios, R1R1 (520 nm/1020 nm) and R2R2 (1020 nm/1550 nm). This method was proposed earlier by Kent et al. [Appl. Opt. 36, 8639 (1997) [CrossRef] ] for the SAGE III-Meteor-3M but was never tested for the tropical region under volcanically perturbed conditions. We call this method the Extinction Color Ratio (ECR) method. The ECR method is applied to the SAGE III/ISS aerosol extinction data to obtain cloud-filtered aerosol extinction coefficients, cloud-top altitude, and seasonal cloud occurrence frequency during the entire study period. Cloud-filtered aerosol extinction coefficient obtained using the ECR method revealed the presence of enhanced aerosols in the UTLS following volcanic eruptions and wildfire events consistent with the Ozone Mapping and Profiler Suite (OMPS) and space-borne lidar-Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). The cloud-top altitude obtained from the SAGE III/ISS is within 1 km of the nearly co-located observations from OMPS and CALIOP. In general, the seasonal mean cloud-top altitude from the SAGE III/ISS events peaks during the December, January, and February months, with sunset events showing higher cloud tops than the sunrise events, indicating the seasonal and diurnal variation of the tropical convection. The seasonal altitude distribution of cloud occurrence frequency obtained from the SAGE III/ISS also agrees well with CALIOP observations within 10%. We show that the ECR method is a simple approach that relies on thresholds independent of the sampling period, providing cloud-filtered aerosol extinction coefficients uniformly for climate studies irrespective of the UTLS conditions. However, since the predecessor of SAGE III did not include a 1550 nm channel, the usefulness of this approach is limited to short-term climate studies after 2017.

Clouds Aerosols↗

Dispersion and Aging of Volcanic Aerosols after the La Soufriere Eruption in April 2021

Volcanic aerosols change the atmospheric composition and thereby affect weather and climate. Aerosol dynamic processes such as nucleation, condensation, and coagulation modify the shape, size, and mass of aerosol particles, which influence their atmospheric lifetime and radiative properties. Nevertheless, most models omit these processes for ash particles. In this work, we explore the ash aerosol aging and sulfate production during the first 4 days following the 2021 La Soufrière (St. Vincent) eruption with the ICON-ART model (ICOsahedral Nonhydrostatic model with Aerosol and Reactive Trace gases). Online coupling of ICON-ART with a one-dimensional volcanic plume model calculates volcanic emission, which makes it possible to resolve the different eruption phases of the noncontinuous La Soufrière eruption. We compared our simulated aerosol distribution and composition with observations from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument, the Multiangle Imaging SpectroRadiometer (MISR) Research Aerosol (RA) Algorithm, and the Barbados Cloud Observatory (BCO). We show that online coupling is essential to adequately model the emissions and plume development close to the volcano. The modeled aerosol aging is in very good agreement with observations from MISR near the emission source and with CALIOP at larger distances. Furthermore, particle aging occurs faster in the troposphere than in the stratosphere due to the availability of water vapor and OH, but a layer of coated ash appears at the plume top due to faster oxidation of SO2 and lofting by aerosol-radiation interaction. This paper gives the first direct comparison of aerosol aging in volcanic eruption plumes between simulations and observations

volcanic aerosols↗

Satellite-Assisted Particulate Matter (SAPM) for the Models, In situ, and Remote sensing of Aerosols (MIRA) Working Group

Models, In situ, and Remote sensing of Aerosols (MIRA) is an international working group that aims to foster collaborations amongst these three major aerosol specialties. It consists of a collection of interdisciplinary and independently funded projects/topics with clearly-defined goals. Currently there are four MIRA topic areas, including Satellite-Assisted Particulate Matter (SAPM), which is focused specifically on fine particulate matter (PM2.5). The study of PM2.5 is important due to its significant contribution to air pollution and resultant, adverse human health effects. The goal of the SAPM topic group is to conduct and provide intercomparisons of various methods and techniques to obtain surface PM2.5 estimates assisted by satellite remote sensors, global aerosol models, and in situ aerosol measurements. Some benefits of space-based/model-assisted PM2.5 retrievals include providing PM2.5 approximations in regions with poor in situ ground station coverage and a means for assessing spatial/temporal PM2.5 variations on regional and/or global scales. Furthermore, benefits of spaceborne lidar/model-assisted PM2.5 retrievals include providing nighttime PM2.5 estimates and characterization of near-surface aerosol vertical structure. SAPM is seeking international datasets of mass scattering/absorption coefficient and aerosol hygroscopic properties for different aerosol species, as well as ground-based in situ PM2.5 measurements. In this poster presentation, we give an overview of SAPM, and show results from three recent/ongoing PM2.5 studies. These efforts involve deriving surface PM2.5 concentrations from two spaceborne lidars, the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and Cloud-Aerosol Transport System (CATS), and investigating key variables that impact the estimation of PM2.5 from model simulated aerosol optical depth (AOD) using the Goddard Earth Observing System (GEOS) model.

Travis D. Toth↗

Progress Towards a Common CERES Cloud Mask Algorithm for MODIS and VIIRS: Evaluation using CALIOP Data

For over two decades The Clouds and the Earth’s Radiant Energy System (CERES) project has endeavored to produce a long-term global climate data record for detecting changes in the Earth’s radiation budget and to improve understanding of how clouds contribute to those changes. CERES incorporates cloud information derived from passive narrowband satellite imaging radiometers, and over the course of the project different instruments have contributed to this effort, namely the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Visible Infrared Imaging Radiometer Suite (VIIRS).Cloud properties have been derived from MODIS on the Aqua satellite for CERES since 2002,and VIIRS on the NOAA-20 satellite launched in 2017 will continue the cloud record once Aqua-MODIS reaches the end of its operational lifetime. However, MODIS and VIIRS have different spectral capabilities and characteristics which complicates our ability to seamlessly transition the record from MODIS to VIIRS. This study evaluates some of the recent algorithm modifications incorporated by the CERES Cloud Working Group towards developing a unified cloud mask algorithm for MODIS and VIIRS that utilizes a set of spectral bands common to both instruments. Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data products are used to evaluate MODIS and VIIRS regional cloud fraction estimates and identify areas where improvements can be made. The cloud mask algorithm relies on computed estimates of cloud-free top-of-atmosphere radiances to differentiate cloudy and cloud-free imager pixels. The unified cloud mask algorithm currently under development uses a reduced number of spectral bands common to both MODIS and VIIRS and so relies on the accuracy of these simulated cloud-free radiances more heavily than predecessor algorithms, i.e., the CERES Edition 4 cloud mask, which use as much spectral information as available on each imager with less consideration for cross-platform consistency. Our validation strategy using CALIOP data is also described. The CALIOP observations are critical for assessing cloud detection accuracies and for independently confirming cloud-free conditions which enables a more robust evaluation of the simulated cloud-free radiances for biases due to factors such as view angle and the spectral dependence of water vapor absorption. These effects are known to differ for the two satellite instruments. Comparisons of MODIS and VIIRS cloud fractions are presented in context with estimates from CALIOP and from the CERES Edition 4 cloud mask algorithm to gauge current progress in developing accurate and consistent MODIS and VIIRS cloud properties for CERES.

CERES↗

Thermal Infrared Dust Optical Depth and Coarse-Mode Effective Diameter Over Oceans Retrieved From Collocated MODIS and CALIOP Observations

In this study, we developed a novel algorithm based on the collocated Moderate Resolution Imaging Spectroradiometer (MODIS) thermal infrared (TIR) observations and dust vertical profiles from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) to simultaneously retrieve dust aerosol optical depth at 10 µm (DAOD10μm) and the coarse-mode dust effective diameter (Deff) over global oceans. The accuracy of the Deff retrieval is assessed by comparing the dust lognormal volume particle size distribution (PSD) corresponding to retrieved Deff with the in-situ measured dust PSDs from the AER-D, SAMUM-2 and SALTRACE field campaigns through case studies. The new DAOD10μm retrievals were evaluated first through comparisons with the collocated DAOD10.6μm retrieved from the combined Imaging Infrared Radiometer (IIR) and CALIOP observations from our previous study (Zheng et al. 2022). The pixel-to-pixel comparison of the two DAOD retrievals indicates a good agreement (R~0.7) and a significant reduction of (~50%) retrieval uncertainties largely thanks to the better constraint on dust size. In a climatological comparison, the seasonal and regional (5°×2°) mean DAOD10um retrievals based on our combined MODIS and CALIOP method are in good agreement with the two independent Infrared Atmospheric Sounding Interferometer (IASI) products over three dust transport regions (i.e., North Atlantic (NA; R = 0.9), Indian Ocean (IO; R = 0.8) and North Pacific (NP; R = 0.7)). Using the new retrievals from 2013 to 2017, we performed a climatological analysis of coarse mode dust Deff over global oceans. We found that dust Deff over IO and NP are up to 20% smaller than that over NA. Over NA in summer, we found a ~50% reduction of the number of retrievals with Deff > 5 μm from 15°W to 35°W and a stable trend of Deff average at 4.4 μm from 35°W throughout the Caribbean Sea (90°W). Over NP in spring, only ~5% of retrieved pixels with Deff > 5 μm are found from 150°E to 180°, while the mean Deff remains stable at 4.0 μm throughout eastern NP. To our best knowledge, this study is the first to retrieve both DAOD and coarse-mode dust particle size over global oceans for multiple years. This retrieval dataset provides insightful information for evaluating dust long-wave radiative effects and coarse mode dust particle size in models.

dust optical depth↗