SEARCH · Engineering Papers

Results for “AOD”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 217 records · Page 12

All sources NASA NTRS DOE OSTI

NASA NTRS2018

Net Radiative Effects of Dust in the Tropical North Atlantic Based on Integrated Satellite Observations and in Situ Measurements

In this study, we integrate recent in situ measurements with satellite retrievals of dust physical and radiative properties to quantify dust direct radiative effects on shortwave (SW) and longwave (LW) radiation (denoted as DRESW and DRELW, respectively) in the tropical North Atlantic during the summer months from 2007 to 2010. Through linear regression of the CERES-measured top-of atmosphere (TOA) flux versus satellite aerosol optical depth (AOD) retrievals, we estimate the instantaneous DRESW efficiency at the TOA to be -49+/-7.1 W/sq.m AOD(exp -1) and -36+/-4:8W/sq.m AOD(exp -1) based on AOD from MODIS and CALIOP, respectively. We then perform various sensitivity studies based on recent measurements of dust particle size distribution (PSD), refractive index, and particle shape distribution to determine how the dust microphysical and optical properties affect DRE estimates and its agreement with the above-mentioned satellite-derived DREs. Our analysis shows that a good agreement with the observation-based estimates of instantaneous DRESW and DRELW can be achieved through a combination of recently observed PSD with substantial presence of coarse particles, a less absorptive SW refractive index, and spheroid shapes. Based on this optimal combination of dust physical properties we further estimate the diurnal mean dust DRE(sub SW) in the region of -10W/sq.m at TOA and -26W/sq.m at the surface, respectively, of which ~30% is canceled out by the positive DRE(sub LW). This yields a net DRE of about -6:9 and -18.3 W/sq.m at TOA and the surface, respectively. Our study suggests that the LW flux contains useful information on dust particle size, which could be used together with SW observations to achieve a more holistic understanding of the dust radiative effect.

Song, Qianqian↗

NASA NTRS2018

A13H-2537: Above Cloud Aerosol Optical Properties in the South East Atlantic from airborne observations during ORACLES

Aerosol overlying marine stratocumulus clouds is a persistent feature in the southeast Atlantic during the biomass burning season, July through November. We sampled aerosol and cloud from an airborne research platform, the NASA P3, during the deployments of ObseRvations of CLouds above Aerosols and their intEractionS (ORACLES) encompassing the peak biomass burning season. We used the Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) to quantify the aerosol’s optical properties, notably the aerosol optical depth (AOD) by directly measuring the amount of light attenuation. We present an overview of very recent AOD measurements and contrast those to previous deployments. We observed an average AOD at 500 nm of 0.33 (0.30) in September 2016 (August 2017), with similar spatial dependence as observed by the MODIS instrument on board the TERRA and AQUA satellites. We also show full spectral vertical dependence of AOD from flight profiles, which compares favorably to the integrated aerosol extinction profile obtained by the active remote sensing High Spectral Resolution Lidar-2 (HSRL-2). We also present a quantification of the gap extent separating cloud top and aerosol layer bottom. Using hyperspectral transmitted light measurements from 4STAR, in conjunction with hyperspectral hemispheric irradiance measurements from the Solar Spectral Flux Radiometers (SSFR), we retrieved aerosol intensive properties (asymmetry parameter, single scattering albedo), aerosol size distributions, cloud optical depth (COD), cloud particle effective radius, and cloud thermodynamic phase. Cloud properties, also presented here, are obtained from 4STAR measurements of scattered light below clouds.

Samuel E LeBlanc↗

NASA NTRSDate not supplied

TPSAS-NF1676L-11598-DND

Satellite data show a strong summertime maximum in aerosol optical depth (AOD) over the Southeastern (SE) USA that can not be explained by anthropogenic sulfate or organic aerosols at the surface (Goldstein et al., 2009). The biogenic volatile organic compound (BVOC) emissions peak over the same region and models indicate a large source of secondary organic aerosols (SOA) here (van Donkelaar et al., 2007, Zhang et al., 2007, Liao et al., 2007). Aircraft measurements indicate dominance of organic aerosols over sulfates with altitude and models suggest most SOA production from isoprene oxidation takes place above the surface layers. Goldstein et al. (2009) hypothesized that these SOA drive the AOD maximum in summer with an altitude dependence. We examine the distributions of AOD and other optical properties over SE USA using height resolved aerosol data from CALIPSO. We also use AOD data from MODIS and OMI and UV aerosol index from OMI to characterize the aerosols over SE USA.

J Kar↗

NASA NTRS2020

The interactive global fire module pyrE (v1.0)

Fires affect the composition of the atmosphere and Earth’s radiation balance by emitting a suite of reactive gases and particles. An interactive fire module in an Earth system model (ESM) allows us to study the natural and anthropogenic drivers, feedbacks, and interactions of open fires. To do so, we have developed pyrE, the NASA GISS (Goddard Institute for Space Studies) interactive fire emissions *module. The pyrE module is driven by environmental variables like flammability and cloud-to-ground lightning, calculated by the GISS ModelE ESM, and parameterized by anthropogenic impacts based on population density data. Fire emissions are generated from the flaming phase in pyrE (active fires). Using pyrE, we examine fire occurrence, regional fire suppression, burned area, fire emissions, and how it all affects atmospheric composition. To do so, we evaluate pyrE by comparing it to satellite-based datasets of fire count, burned area, fire emissions, and aerosol optical depth (AOD). We demonstrate pyrE’s ability to simulate the daily and seasonal cycles of open fires and resulting emissions. Our results indicate that interactive fire emissions are biased low by 32 %–42 %, depending on emitted species, compared to the GFED4s (Global Fire Emissions Database) inventory. The bias in emissions drives underestimation in column densities, which is diluted by natural and anthropogenic emissions sources and production and loss mechanisms. Regionally, the resulting AOD of a simulation with interactive fire emissions is underestimated mostly over Indonesia compared to a simulation with GFED4s emissions and to MODIS AOD. In other parts of the world pyrE’s performance in terms of AOD is marginal to a simulation with prescribed fire emissions.

Fires↗

NASA NTRS2020

Dust Aerosol Retrieval Over the Oceans With the MODIS/VIIRS Dark Target Algorithm: 2. Nonspherical Dust Model

The Dark‐target (DT) aerosol algorithm retrieves spectral Aerosol Optical Depth (AOD) and other aerosol properties from Moderate‐resolution Imaging Spectrometer (MODIS) reflectance observations. Over the ocean, the DT algorithm is known to contain scattering‐angle‐dependent biases in its retrievals of AOD, Angstrom Exponent (AE), and Fine Mode Fraction (FMF) for dust aerosols. Following a two‐step strategy to improve the DT retrieval of dust over ocean, for which the first step is to identify dusty pixels (reported in “Part 1”), in this “Part 2,” we report on construction of a new dust model lookup table (LUT) and the strategy for applying it within the existing DT algorithm. In particular, we evaluate different characterizations of dust optical properties from a variety of frameworks and databases, and compare them with the current DT retrieval assumptions. Substituting the standard operational LUT with a spheroid dust model with identified dusty pixels shows significant improvement when compared with collocated AERONET‐identified dusty pixels. Specifically, the application of the new dust model to dusty pixels reduces their AOD bias from 0.06 to 0.02 while improving the fraction of retrievals within expected error from 64% to 82%. At the same time, the overall bias in AE is reduced from 0.13 to 0.06, and the scattering‐angle‐dependent AE bias is largely eliminated. In testing on two full months of data (April and July), the new retrieval will reduce the monthly mean AOD by up to 0.1 and 0.2 in the north Atlantic and Arabian seas, respectively. The average AE and FMF are also reduced in these dust heavy regions

dust aerosol retrieval↗

NASA NTRS2021

Sky-Scanning Sun-Tracking Airborne Radiometer (3STAR): Instrument Design, Flight Testing, and Tracking Performance

The Sky-Scanning, Sun-Tracking Airborne Radiometer (3STAR) adapts commercial radiometer technology developed for the ocean color research community to airborne measurement of spectrally resolved solar irradiance and sky radiance. These atmospheric observations are used to derive aerosol optical depth (AOD), supporting localized AOD inputs for atmospheric correction of satellite and airborne data over terrestrial and aquatic (including optically dark) targets. The ability to regionally “tune” atmospheric correction schemes with relevant spatial AOD supports constraining atmospheric correction of remote sensing reflectance. Very wide dynamic range has been achieved for multi-channel band-pass-filter-radiometers originally designed for deployment into the water column. By actively tracking and directly pointing to the Sun, the light attenuation by aerosol particles in the atmospheric column can be quantified. These measurements improve knowledge of atmospheric constituents and the atmospheric corrections required to improve remote sensing capabilities for interpreting reflectance measurements from the Earth surface. 3STAR incorporates a custom Sun-tracking/sky-scanning pointing head, a Sun-tracking camera, and a commercially available, cylindrical, 19-channel radiometer tube assembly. An accurate and responsive mount and tracking system has been developed and certified to NASA and Naval Air Systems Command (NAVAIR) airworthiness standards for deployment into the aircraft slipstream. Ground and flight testing indicate typical tracking errors of less than 0.1 degrees, well within the field of view of the radiometer as required to minimize measurement uncertainty from alignment error. Preliminary AOD measurements compare to within 0.013 with 15 measurements from an Aerosol Robotic Network (AERONET) Cimel instrument at 500 nm wavelength and low solar angle.

Atmosphere↗

NASA NTRS2021

Validation of the aerosol optical property products derived by the GRASP/Component approach from multi-angular polarimetric observations

The multi-angle polarimetric satellite observations are helpful for improving the retrievals of aerosol parameters. However, practical applications of polarization technology are still limited because of complexity of measurement and interpretation of polarimetric observations. In this study, we analyze the performance of a new component approach developed in the frame of the Generalized Retrieval of Atmosphere and Surface Properties (GRASP) algorithm. In addition to aerosol optical properties including particle size distribution, non-sphericity and index of refraction that are commonly derived from multi-angle radiance and polarization measurements, the GRASP/Component approach also provides some information about aerosol composition. Specifically, in this approach aerosol is modeled as an internal mixture of several components with distinctly different chemical compositions and known refractive indices. The approach is intended not only to provide additional insight on aerosol composition but also to improve retrieval of basic aerosol optical properties. This study presents comprehensive validation and evaluation of Aerosol Optical Depth (AOD), Ångstrom exponent (AE), fine mode AOD (AODF), coarse mode AOD (AODC), and single scattering albedo (SSA) as retrieved by the GRASP/Component approach. The GRASP/Component products include aerosol retrievals using two different aerosol component mixing rules, i.e., Maxwell-Garnett (MG) effective medium approximation and a simple Volume- Weighted averaging (VW). The differences between the results obtained using these two assumptions are also discussed. The obtained results show that the aerosol optical property products of GRASP/Component approach have good agreement with the ground-based AERONET measurements, which is comparable to other PARASOL/ GRASP approaches. Specifically, the AOD retrieved by GRASP/Component approach show high correlation and nearly no bias both over land and ocean, as compared with AERONET. The more detailed aerosol properties such as AE, AODF, AODC and SSA also show one of the best comparisons with AERONET. These improvements can probably be attributed to the use of the additional physical constraints on spectral dependence of the complex refractive index and the reduction of total number of aerosol parameters directly retrieved in the GRASP/Component approach. In addition, the choice of mixing rules had no significant effect on optical retrievals. With the exception of SSA, the results obtained based on the MG mixing rule were found to be slightly better over those obtained using VW mixing rule, especially for bias.

Brent N Holben↗

NASA NTRSDate not supplied

Development of a Global Reference Surface Reflectance and BRDF Datasets from Geostationary Satellite Observations and AERONET Measurements

Surface reflectances and their dependency on illumination-view geometries (i.e., BRDF) are the foundation of many high-level satellite products for land and water monitoring. Yet it is difficult to evaluate the quality of satellite-based surface reflectances with ground-based measurements due to the spatial scale differences. In order to fill the gap, here we develop a reference dataset of surface reflectance and BRDF at the global AERONET sites with data streams from operational geostationary sensors including Himawari 8/9 AHI, GK-2A AMI, and GOES 16/17 ABI. Taking the top-of-atmosphere (TOA) reflectance and the site measured atmospheric aerosol optical depth (AOD) as the main inputs, we apply the GeoNEX-AC algorithm to performance accurate atmospheric correction and derive 10-minute surface reflectance and daily Ross-Thick-Li-Sparse (RTLS) BRDF parameters at AERONET sites where coincident AOD measurements and TOA observations are available from 2016 (for Himawari) or 2018 (for GOES) onwards. The algorithm ensures that the retrieved surface BRDF parameters, along with the site-measured AOD, allow the atmospheric radiative transfer model, SHARM, accurately simulate the observed TOA reflectance at diurnal and longer time scales. They are our best estimates of the surface optical properties and thus can serve as the “reference” to evaluate the performance of operational atmospheric correction algorithms (where AOD is assumed unknown and needs to be retrieved). The reference BRDF also allow us to evaluate the spectral band ratios between the SWIR (e.g., 2200 nm) and the visible (e.g., 650 nm) regions, which are commonly used in operational atmospheric correction algorithms. Finally, we demonstrate that the reference dataset can be used to develop potential data synergies between different GEO satellites as well as GEO-LEO sensors.

Weile Wang↗

NASA NTRSDate not supplied

Constraints on Wildfire Smoke Source Strength, Injection Height, and Particle Evolution

Aerosol sources are represented in climate and air quality models with an injection height and a source strength. We have applied a combination of Multi-angle Imaging SpectroRadiometer (MISR) and MODerate resolution Imaging Spectroradiometer (MODIS) observations to help constrain these two key model variables for wildfire smoke plumes. Injection height is obtained from MISR stereo imagery, which makes it possible to map plume elevation and estimate the associated motion vectors at plume altitude near-source, where contrast features in the plume can be identified in the multi-angle views. A current limitation of injection-height mapping is the relatively narrow MISR swath width (~380 km) and 10:30 AM equator crossing time on the day side of Earth. However, upcoming missions, as well as advanced imagers on geostationary platforms, promise to greatly expand the spatial and temporal range over which this technique can be applied. We estimate source strength by matching forward-simulated plume aerosol optical depth (AOD) from models with AOD snapshots retrieved from MODIS observations. This technique works best for large, isolated plumes common in boreal forest, and tends to fail where plume AOD is low and/or background AOD, distinct from the specific source of interest, is high. These two approaches for constraining aerosol modeling with satellite observations have been the subject of ongoing AeroCom/AeroSat studies by our group. A third effort applies the combination of MISR plume heights, wind vectors, and particle microphysical property constraints to infer smoke-plume particle evolution processes and timescales, including the emission and subsequent evolution of black and brown smoke. In this presentation, we will provide an update on the status of these efforts.

wildfire↗

NASA NTRS2022

Aerosols Optical and Radiative Properties in Indonesia Based on AERONET Version 3

Heterogeneity in seasonal aerosol types due to different sources, local characteristics, and meteorology lead to different optical and radiative properties from one place to another. This study analyzes the long-term averages of aerosol optical and radiative properties obtained by the Aerosol Robotic Network (AERONET) version 3 at four sites in Indonesia representing fire prone areas (Palangka Raya, Pontianak, Jambi: 2012–2020), and urban-industrial (Bandung: 2009–2018). We examined the seasonal variation of aerosol optical depth (AOD), Angstrom Exponent (AE), Precipitable Water Vapor (PWV), and Single Scattering Albedo (SSA) combined with meteorological parameters at these Indonesian sites. Multiple clustering techniques from different relationships among various aerosol optical and radiative parameters was employed to further study the aerosol type in respect to different seasonality. The results exhibited a distinct seasonal pattern at all sites except Bandung, whereas AOD increased owing to forest and peat fire outbreaks during the dry season. The trend in AOD annual depicts an increase in Bandung as emission from urban/industrial increases episodically, while it depicts a decrease at the three biomass burning sites. As AOD increased, Palangka Raya, Pontianak, and Jambi exhibited wider ranges of observed AE (1.2–1.8) and high FMF (>0.8) in the dry burning period (June to October). On the other hand, Bandung has more aerosol distribution in the range of FMF values 0.6–1 and AE 1–1.6, compared with other sites, suggesting contribution of complex aerosol emission from different sources and likely due to the formation of secondary aerosol production from trace gases. Palangka Raya, Pontianak, and Jambi exhibited non-absorbing characteristics, as indicated by high SSA (>0.95), high FMF, and high EAE values (1.2–1.7) with no discrepancy in seasonal patterns, implying that biomass burning aerosols in Indonesia tend to cool the atmosphere with strong scattering rather than absorbing. At Bandung, aerosols mixed with slightly absorbing and non-absorbing aerosols owing to urban and industrial emissions. This study lays a foundation for further research on the contribution of aerosol radiative forcing to climate within the complex aerosol and cloud environments in Indonesia.

Aerosol optical depth↗

NASA NTRS2022

Simultaneous Characterization of Wildfire Smoke and Surface Properties With Imaging Spectroscopy During the FIREX-AQ Field Campaign

We introduce and evaluate an approach for the simultaneous retrieval of aerosol and surface properties from Airborne Visible/Infrared Imaging Spectrometer Classic (AVIRIS-C) data collected during wildfires. The joint National Aeronautics and Space Administration (NASA) National Oceanic and Atmospheric Administration Fire Influence on Regional to Global Environments and Air Quality field campaign took place in August 2019, and involved two aircraft and coordinated ground-based observations. The AVIRIS-C instrument acquired data from onboard NASA's high altitude ER-2 research aircraft, coincident in space and time with aerosol observations obtained from the Aerosol Robotic Network (AERONET) DRAGON mobile platform in the smoke plume downwind of the Williams Flats Fire in northern Washington in August 2019. Observations in this smoke plume were used to assess the capacity of optimal-estimation based retrievals to simultaneously estimate aerosol optical depth (AOD) and surface reflectance from Visible Shortwave Infrared (VSWIR) imaging spectroscopy. Radiative transfer modeling of the sensitivities in spectral information collected over smoke reveal the potential capacity of high spectral resolution retrievals to distinguish between sulfate and smoke aerosol models, as well as sensitivity to the aerosol size distribution. Comparison with ground-based AERONET observations demonstrates that AVIRIS-C retrievals of AOD compare favorably with direct sun AOD measurements. Our analyses suggest that spectral information collected from the full VSWIR spectral interval, not just the shortest wavelengths, enables accurate retrievals. We use this approach to continuously map both aerosols and surface reflectance at high spatial resolution across heterogeneous terrain, even under relatively high AOD conditions associated with wildfire smoke.

FIREX-AQ↗

NASA NTRS2022

A Coupled Evaluation of Operational MODIS and Model Aerosol Products for Maritime Environments Using Sun Photometry: Evaluation of the Fine and Coarse Mode

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

Aerosols↗

NASA NTRS2023

Impacts of Estimated Plume Rise on PM 2.5 Exceedance Prediction During Extreme Wildfire Events: A Comparison of Three Schemes (Briggs, Freitas, and Sofiev)

Plume height plays a vital role in wildfire smoke dispersion and the subsequent effects on air quality and human health. In this study, we assess the impact of different plume rise schemes on predicting the dispersion of wildfire air pollution and the exceedances of the National Ambient Air Quality Standards (NAAQS) for fine particulate matter (PM 2.5 ) during the 2020 western United States wildfire season. Three widely used plume rise schemes (Briggs, 1969; Freitas et al., 2007; Sofiev et al., 2012) are compared within the Community Multiscale Air Quality (CMAQ) modeling framework. The plume heights simulated by these schemes are comparable to the aerosol height observed by the Multi-angle Imaging SpectroRadiometer (MISR) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). The performance of the simulations with these schemes varies by fire case and weather conditions. On average, simulations with higher plume injection heights predict lower aerosol optical depth (AOD) and surface PM 2.5 concentrations near the source region but higher AOD and PM 2.5 in downwind regions due to the faster spread of the smoke plume once ejected. The 2-month mean AOD difference caused by different plume rise schemes is approximately 20 %–30 % near the source regions and 5 %–10 % in the downwind regions. Thick smoke blocks sunlight and suppresses photochemical reactions in areas with high AOD. The surface PM 2.5 difference reaches 70 % on the West Coast of the USA, and the difference is lower than 15 % in the downwind regions. Moreover, the plume injection height affects pollution exceedance (>35 µg m−3) predictions. Higher plume heights generally produce larger downwind PM 2.5 exceedance areas. The PM 2.5 exceedance areas predicted by the three schemes largely overlap, suggesting that all schemes perform similarly during large wildfire events when the predicted concentrations are well above the exceedance threshold. At the edges of the smoke plumes, however, there are noticeable differences in the PM 2.5 concentration and predicted PM 2.5 exceedance region. For the whole period of study, the difference in the total number of exceedance days could be as large as 20 d in northern California and 4 d in the downwind regions. This disagreement among the PM 2.5 exceedance forecasts may affect key decision-making regarding early warning of extreme air pollution episodes at local levels during large wildfire events.

Yunyao Li↗

NASA NTRSDate not supplied

Breaking Barriers: Integrating Geo-Leo Aerosol Data with an Open-Source Approach

The scientific community is still examining the novel data from geostationary satellite observations and evaluating methods for effectively fusing the polar observations with various spatial and temporal resolutions. However, the merged data will present a significant ""Big Data"" challenge, including processing, storage, data discoverability, accessibility, and migration within cloud computing environments. We have developed an open-source package to fuse aerosol optical depths (AOD) products from six satellite sensors in the past four years (2019~2023), and this presentation will update our recent progress. Using this Python-based package, we produced a level 3 global (AOD) product in a quarter-degree spatial resolution every half-hour, fusing the Level 2 AOD data with the Dark Target aerosol retrieval algorithm from six satellites: three geostationary (GOES-16/17 and Himawari-8) with high temporal resolution, and three polar orbiting (TERRA/MODIS, AQUA/MODIS, and SNPP-VIIRS) with global coverage. By integrating these observations, the diurnal cycle of global AOD in this fused product can be characterized at local, regional, and global scales. Furthermore, we are committed to openness and transparency by providing our package and its associated functionalities as open-source. Our dedication to adhering to the FAIR, CARE, and TRUST principles ensures that our users can rely on the integrity and ethical standards of our work. For instance of Interoperability, this package fuses remote sensing products on demand into desired temporal and spatial domains. It can be run in a central processing unit (CPU) or a Graphics processing unit (GPU) mode. This package will empower researchers and practitioners to use satellite and sensor data efficiently in various applications and research.

Xiaohua Pan↗

NASA NTRS2023

Atmospheric Correction Inter-comparison eXercise, ACIX-II Land: An Assessment of Amospheric Correction Processors for Landsat 8 and Sentinel-2 Over Land

The correction of the atmospheric effects on optical satellite images is essential for quantitative and multi-temporal remote sensing applications. In order to study the performance of the state-of-the-art methods in an integrated way, a voluntary and open-access benchmark Atmospheric Correction Inter-comparison eXercise (ACIX) was initiated in 2016 in the frame of Committee on Earth Observation Satellites (CEOS) Working Group on Calibration & Validation (WGCV). The first exercise was extended in a second edition wherein twelve atmospheric correction (AC) processors, a substantially larger testing dataset and additional validation metrics were involved. The sites for the inter-comparison analysis were defined by investigating the full catalogue of the Aerosol Robotic Network (AERONET) sites for coincident measurements with satellites' overpass. Although there were more than one hundred sites for Copernicus Sentinel-2 and Landsat 8 acquisitions, the analysis presented in this paper concerns only the common matchups amongst all processors, reducing the number to 79 and 62 sites respectively. Aerosol Optical Depth (AOD) and Water Vapour (WV) retrievals were consequently validated based on the available AERONET observations. The processors mostly succeeded in retrieving AOD for relatively light to medium aerosol loading (AOD < 0.2) with uncertainties <0.08, while the overall uncertainty values were typically 0.23 ± 0.15. Better performances were observed for WV retrievals with >90% of the results falling within the suggested empirical specifications and with the Root Mean Square Error (RMSE) being mostly <0.25 g/cm2. Regarding Surface Reflectance (SR) validation two main approaches were followed. For the first one, a simulated SR reference dataset was computed over all of the test sites by using the 6SV (Second Simulation of the Satellite Signal in the Solar Spectrum vector code) full radiative transfer modelling (RTM) and AERONET measurements for the required aerosol variables and water vapour content. The performance assessment demonstrated that the retrievals were not biased for most of the bands. The uncertainties ranged from approximately 0.003 to 0.01 (excluding B01) for the best performing processors in both sensors' analyses. For the second one, measurements from the radiometric calibration network RadCalNet over La Crau (France) and Gobabeb (Namibia) were involved in the validation. The performance of the processors was in general consistent across all bands for both sensors and with low standard deviations (<0.04) between on-site and estimated surface reflectance. Overall, our study provides a good insight of AC algorithms' performance to developers and users, pointing out similarities and differences for AOD, WV and SR retrievals. Such validation though still lacks of ground-based measurements of known uncertainty to better assess and characterize the uncertainties in SR retrievals.

Atmospheric correction↗

NASA NTRS2024

Sensitivity studies of nighttime top-of-atmosphere radiances from artificial light sources using a 3-D radiative transfer model for nighttime aerosol retrievals

By accounting for surface-based light source emissions and top-of-atmosphere (TOA) downward lunar fluxes, we adapted the spherical harmonics discrete ordinate method (SHDOM) 3-dimensional (3-D) radiative transfer model (RTM) to simulate nighttime 3-D TOA radiances as observed from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) on board the Suomi-NPP satellite platform. Used previously for daytime 3-D applications, these new SHDOM enhancements allow for the study of the impacts of various observing conditions and aerosol properties on simulated VIIRS-DNB TOA radiances. Observations over Dakar, Senegal, selected for its bright city lights and a large range of aerosol optical depth (AOD), were investigated for potential applications and opportunities for using observed radiances containing VIIRS-DNB “bright pixels” from artificial light sources to conduct aerosol retrievals. We found that using the standard deviation (SD) of such bright pixels provided a more stable quantity for nighttime AOD retrievals than direct retrievals from TOA radiances. Further, both the mean TOA radiance and SD of TOA radiances over artificial sources are significantly impacted by satellite viewing angles. Light domes, the enhanced radiances adjacent to artificial light sources, are strong functions of aerosol properties and especially aerosol vertical distribution, which may be further utilized for retrieving aerosol layer height in future studies. Through inter-comparison with both day- and nighttime Aerosol Robotic Network (AERONET) data, the feasibility of retrieving nighttime AODs using 3-D RTM SHDOM over artificial light sources was demonstrated. Our study shows strong potential for using artificial light sources for nighttime AOD retrievals, while also highlighting larger uncertainties in quantifying surface light source emissions. This study underscores the need for surface light emission source characterizations as a key boundary condition, which is a complex task that requires enhanced input data and further research. We demonstrate how quality-controlled nighttime light data from NASA’s Black Marble product suite could serve as a primary input into estimations of surface light source emissions for nighttime aerosol retrievals.

Jianglong Zhang↗

NASA NTRSDate not supplied

Sea Salt and Dust Optical Depths in the Caribbean and Equatorial Western Atlantic: A Multi-technique Analysis

Many instruments and algorithms can estimate aerosol optical depth (AOD) of the atmosphere. The Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua spacecraft provides estimates at several wavelengths. The Synergized Optical Depth of Aerosols (SODA) algorithm utilizes the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) spacecraft and the Cloud Profiling Radar (CPR) onboard the CloudSat spacecraft’s ocean returns to estimate AOD. CALIOP routinely estimates AOD for all individual layers detected within a column and these can be summed to generate a total column approximation. With the release of the Version 4.51 Lidar Level 2 data products in October 2023, direct estimates of total column optical depth are now derived using the Ocean Derived Column Optical Depths (ODCOD) algorithm. In this poster we investigate the multispectral AOD estimates, and derived Angstrom exponents of marine sea salt and dust provided by MODIS, SODA, CALIOP, and ODCOD in a major dust transport and deposition region of the equatorial Atlantic Ocean.

optical depth↗

NASA NTRS2020

Application of Low-Cost Fine Particulate Mass Monitors to Convert Satellite Aerosol Optical Depth Measurements to Surface Concentrations in North America and Africa

Low-cost particulate mass sensors provide opportunities to assess air quality at unprecedented spatial and temporal resolutions. Established traditional monitoring networks have limited spatial resolution and are simply absent in many major cities across sub-Saharan Africa (SSA). Satellites provide snapshots of regional air pollution but require ground-truthing. Low-cost monitors can supplement and extend data coverage from these sources worldwide, providing a better overall air quality picture. We investigate the utility of such a multi-source data integration approach using two case studies. First, in Pittsburgh, Pennsylvania, both traditional monitoring and dense low-cost sensor networks are compared with satellite aerosol optical depth (AOD) data from NASA's MODIS system, and a linear conversion factor is developed to convert AOD to surface fine particulate matter mass concentration (as PM2.5). With 10 or more ground monitors in Pittsburgh, there is a 2-fold reduction in surface PM2.5 estimation mean absolute error compared to using only a single ground monitor. Second, we assess the ability of combined regional-scale satellite retrievals and local-scale low-cost sensor measurements to improve surface PM2.5 estimation at several urban sites in SSA. In Rwanda, we find that combining local ground monitoring information with satellite data provides a 40 % improvement in surface PM2.5 estimation accuracy with respect to using low-cost ground monitoring data alone. A linear AOD-to-surface-PM2.5 conversion factor developed in Kigali, Rwanda, did not generalize well to other parts of SSA and varied seasonally for the same location, emphasizing the need for ongoing and localized ground-based monitoring, which can be facilitated by low-cost sensors. Overall, we find that combining ground-based low-cost sensor and satellite data, even without including additional meteorological or land use information, can improve and expand spatiotemporal air quality data coverage, especially in data-sparse regions.

AOD↗