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NASA NTRS2016

Comparison of Key Absorption and Optical Properties Between Pure and Transported Anthropogenic Dust over East and Central Asia

Asian dust particulate is one of the primary aerosol constituents in the Earth-atmosphere system that exerts profound influences on environmental quality, human health, the marine biogeochemical cycle, and Earth's climate. To date, the absorptive capacity of dust aerosol generated from the Asian desert region is still an open question. In this article, we compile columnar key absorption and optical properties of mineral dust over East and Central Asian areas by utilizing the multiyear quality-assured datasets observed at 13 sites of the Aerosol Robotic Network (AERONET). We identify two types of Asian dust according to threshold criteria from previously published literature. (1) The particles with high aerosol optical depth at 440 nm (AOD(440) > or = 0.4) and a low Angstrom wavelength exponent at 440-870 nm (alpha < 0.2) are defined as Pure Dust (PDU), which decreases disturbance of other non-dust aerosols and keeps high accuracy of pure Asian dust. (2) The particles with AOD(440) > or = 0.4 and 0.2 < alpha < 0.6 are designated as Transported Anthropogenic Dust (TDU), which is mainly dominated by dust aerosol and might mix with other anthropogenic aerosol types. Our results reveal that the primary components of high AOD days are predominantly dust over East and Central Asian regions, even if their variations rely on different sources, distance from the source, emission mechanisms, and meteorological characteristics. The overall mean and standard deviation of single-scattering albedo, asymmetry factor, real part and imaginary part of complex refractive index at 550 nm for Asian PDU are 0.935 +/- 0.014, 0.742 +/- 0.008, 1.526 +/- 0.029, and 0.00226 +/- 0.00056, respectively, while corresponding values are 0.921 +/- 0.021, 0.723 +/- 0.009, 1.521 +/- 0.025, and 0.00364 +/- 0.0014 for Asian TDU. Aerosol shortwave direct radiative effects at the top of the atmosphere (TOA), at the surface (SFC), and in the atmospheric layer (ATM) for Asian PDU (alpha < 0.2) and TDU (0.2 < alpha < 0.6) computed in this study, are a factor of 2 smaller than the results of Optical Properties of Aerosols and Clouds (OPAC) mineral-accumulated (mineral-acc.) and mineral-transported (mineral-tran.) modes. Therefore, we are convinced that our results hold promise for updating and improving accuracies of Asian dust characteristics in present-day remote sensing applications and regional or global climate models.

Bi, Jianrong↗

NASA NTRS2016

Radiative Effect of Springtime Biomass-Burning Aerosols over Northern Indochina During 7-SEAS Baseline 2013 Campaign

The direct aerosol radiative effects of biomass-burning (BB) aerosols over northern Indochina were estimated by using aerosol properties (physical, chemical, and optical) along with the vertical profile measurements from ground-based measurements with integration of an optical and a radiative transfer model during the Seven South East Asian Studies Biomass-Burning Aerosols Stratocumulus Environment: Lifecycles Interactions Experiment (7-SEASBASELInE) conducted in spring 2013. Cluster analysis of backward trajectories showed the air masses arriving at mountainous background site (Doi Ang Khang; 19.93degN, 99.05degE, 1536 m above mean sea level) in northern Indochina, mainly from near-source inland BB activities and being confined in the planetary boundary layer. The PM(sub10) and black carbon (BC)mass were 87 +/- 28 and 7 +/- 2 micrograms m(exp -3), respectively. The aerosol optical depth (AOD (sub 500) was found to be 0.26--1.13 (0.71 +/- 0.24). Finer (fine mode fraction is approximately or equal to 0.95, angstrom-exponent at 440-870 nm is approximately or equal to 1.77) and significantly absorbing aerosols(single scattering albedo is approximately or equal to 0.89, asymmetry-parameter is approximately or equal to 0.67, and absorption AOD 0.1 at 440 nm) dominated over this region. BB aerosols (water soluble and BC) were the main contributor to the aerosol radiative forcing (ARF), while others (water insoluble, sea salt and mineral dust) were negligible mainly due to their low extinction efficiency. BC contributed only 6 to the surface aerosol mass but its contribution to AOD was 12 (2 times higher). The overall mean ARF was 8.0 and -31.4 W m(exp -2) at top-of-atmosphere (TOA) and at the surface (SFC), respectively. Likely, ARF due to BC was +10.7 and -18.1 W m(exp -2) at TOA and SFC, respectively. BC imposed the heating rate of +1.4 K d(exp -1) within the atmosphere and highlighting its pivotal role in modifying the radiation budget. We propose that to upgrade our knowledge on BB aerosol radiative effects in BB source region, the long-term and extensive field measurements are needed.

aerosol optical properties↗

NASA NTRS2017

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↗

NASA NTRS2017

Seasonal Impact of Regional Outdoor Biomass Burning on Air Pollution in Three Indian Cities: Delhi, Bengaluru, and Pune

Air pollution in many of India's cities exceeds national and international standards, and effective pollution control strategies require knowledge of the sources that contribute to air pollution and their spatiotemporal variability. In this study, we examine the influence of a single pollution source, outdoor biomass burning, on particulate matter (PM) concentrations, surface visibility, and aerosol optical depth (AOD) from 2007 to 2013 in three of the most populous Indian cities. We define the upwind regions, or "airsheds," for the cities by using atmospheric back trajectories from the HYSPLIT model. Using satellite fire radiative power (FRP) observations as a measure of fire activity, we target pre-monsoon and post-monsoon fires upwind of the Delhi National Capital Region and pre-monsoon fires surrounding Bengaluru and Pune. We find varying contributions of outdoor fires to different air quality metrics. For the post-monsoon burning season, we find that a subset of local meteorological variables (air temperature, humidity, sea level pressure, wind speed and direction) and FRP as the only pollution source explained 39% of variance in Delhi station PM(sub 10) anomalies, 77% in visibility, and 30% in satellite AOD; additionally, per unit increase in FRP within the daily airshed (1000 MW), PM(sub 10) increases by 16.34 micrograms per cubic meter, visibility decreases by 0.097 km, and satellite AOD increases by 0.07. In contrast, for the pre-monsoon burning season, we find less significant contributions from FRP to air quality in all three cities. Further, we attribute 99% of FRP from post-monsoon outdoor fires within Delhi's average airshed to agricultural burning. Our work suggests that although outdoor fires are not the dominant air pollution source in India throughout the year, post-monsoon fires contribute substantially to regional air pollution and high levels of population exposure around Delhi. During 3-day blocks of extreme PM(sub 2.5) in the 2013 post-monsoon burning season, which coincided with statistically significant high fire activity, concentrations in Delhi averaged 304 micrograms per cubic meter, or more than 1000% above the 24-h PM(sub 2.5) guideline (25 micrograms per cubic meter) of the World Health Organization. These results suggest that providing viable alternatives to agricultural residue burning could help improve post-monsoon air quality for a growing population of 63 million (39% in urban areas) within Delhi's airshed.

Air quality; Outdoor fires; Crop residue burning; ↗

NASA NTRS2017

Mitigating Satellite-Based Fire Sampling Limitations in Deriving Biomass Burning Emission Rates: Application to WRF-Chem Model over the Northern sub-Saharan African Region

Largely used in several independent estimates of fire emissions, fire products based on MODIS sensors aboard the Terra and Aqua polar-orbiting satellites have a number of inherent limitations, including (a) inability to detect fires below clouds, (b) significant decrease of detection sensitivity at the edge of scan where pixel sizes are much larger than at nadir, and (c) gaps between adjacent swaths in tropical regions. To remedy these limitations, an empirical method is developed here and applied to correct fire emission estimates based on MODIS pixel level fire radiative power measurements and emission coefficients from the Fire Energetics and Emissions Research (FEER) biomass burning emission inventory. The analysis was performed for January 2010 over the northern sub-Saharan African region. Simulations from WRF-Chem model using original and adjusted emissions are compared with the aerosol optical depth (AOD) products from MODIS and AERONET as well as aerosol vertical profile from CALIOP data. The comparison confirmed an 30-50% improvement in the model simulation performance (in terms of correlation, bias, and spatial pattern of AOD with respect to observations) by the adjusted emissions that not only increases the original emission amount by a factor of two but also results in the spatially continuous estimates of instantaneous fire emissions at daily time scales. Such improvement cannot be achieved by simply scaling the original emission across the study domain. Even with this improvement, a factor of two underestimations still exists in the modeled AOD, which is within the current global fire emissions uncertainty envelope. Plain Language Summary Polar-orbiting satellites sensors, such as MODIS, have limitations in detecting fires under clouds or when viewing angles are large or in the gaps among satellites' different ground swaths. Here we developed an empirical method to mitigate the effect of these limitations in fire emission estimate. The method is applied to a fire emission inventory (FEER) based on MODIS. We show that, with our method, the adjusted emission inventory improves WRF-Chem simulation of smoke transport and distribution.

emissions properties↗

NASA NTRS2017

Developing and Diagnosing Climate Change Indicators of Regional Aerosol Optical Properties

Given the importance of aerosol particles to radiative transfer via aerosol-radiation interactions, a methodology for tracking and diagnosing causes of temporal changes in regional-scale aerosol populations is illustrated. The aerosol optical properties tracked include estimates of total columnar burden (aerosol optical depth, AOD), dominant size mode (Ångström exponent, AE), and relative magnitude of radiation scattering versus absorption (single scattering albedo, SSA), along with metrics of the structure of the spatial field of these properties. Over well-defined regions of North America, there are generally negative temporal trends in mean and extreme AOD, and SSA. These are consistent with lower aerosol burdens and transition towards a relatively absorbing aerosol, driven primarily by declining sulfur dioxide emissions. Conversely, more remote regions are characterized by increasing mean and extreme AOD that is attributed to increased local wildfire emissions and long-range (transcontinental) transport. Regional and national reductions in anthropogenic emissions of aerosol precursors are leading to declining spatial autocorrelation in the aerosol fields and increased importance of local anthropogenic emissions in dictating aerosol burdens. However, synoptic types associated with high aerosol burdens are intensifying (becoming more warm and humid), and thus changes in synoptic meteorology may be offsetting aerosol burden reductions associated with emissions legislation.

Ryan C Sullivan↗

NASA NTRS2018

Seasonal and Interannual Assessment of Cloud Cover and Atmospheric Constituents Across the Amazon (2000 - 2015): Insights for Remote Sensing and Climate Analysis

The quantitative assessment of cloud cover and atmospheric constituents improves our ability to exploit the climate feedback into the Amazon basin. In the 21st century, three droughts have already occurred in the Amazonia (e.g. 2005, 2010, 2015), inducing regional changes in the seasonal patterns of atmospheric constituents. In addition to climate, the atmospheric dynamic and attenuation properties are long-term challenges for satellite-based remote sensing of this ecosystem: high cloudiness, abundant water vapor content and biomass burning season. Therefore, while climatology analysis supports the understanding of atmospheric variability and trends, it also offers valuable insights for remote sensing applications. In this study, we evaluate the seasonal and interannual variability of cloud cover and atmospheric constituents (aerosol loading, water vapor and ozone content) over the Amazon basin, with focus on both climate analysis and remote sensing implications. We take the advantage of new atmosphere daily products at 1 km resolution derived from Multi-Angle Implementation for Atmospheric Correction (MAIAC) algorithm developed for Moderate Resolution Imaging Spectroradiometer (MODIS) data. An intercomparison of Aerosol Robotic Network (AERONET) and MAIAC aerosol optical depth (AOD) and columnar water vapor (CWV) showed quantitative information with a correlation coefficient higher than 0.81. Our results show distinct regional patterns of cloud cover across the Amazon basin: northwestern region presets a persistent cloud cover (> 80%) throughout the year, while low cloud cover (0-20%) occurs in the southern Amazon during the dry season. The cloud-free period in the southern Amazon is followed by an increase in the atmospheric burden due to fire emissions. Our results reveal that AOD records are changing in terms of area and intensity. During the 2005 and 2010 droughts, the positive AOD anomalies (δ > 0.1) occurred over 39.03% (240.3 million ha) and 27.14% (165.99 million ha) of total basin in the SON season, respectively. In contrast, the recent 2015 drought occurred towards the end of year (October through December) and these anomalies were observed over 23.72% (145 million ha) affecting areas in the central and eastern Amazon unlike previous droughts. The water vapor presents high concentration values (4.0-5.0 g/sq.cm) in the wet season (DJF), while we observed a strong spatial gradient from northwestern to southeastern of the basin during the dry season. In addition, we also found a positive trend of water vapor content ( ∼0.3 g/sq.cm) between 2000 and 2015. The total ozone typically varies between 220 and 270 DU, and it has a seasonal change of ∼25-35 DU from wet season to dry season caused by large emissions of ozone precursors and long-range transport. Finally, while this study contributes to climatological analysis of atmospheric constituents, the remote sensing users can also understand the regional constraints caused by atmospheric attenuation, such as high aerosol loading and cloud obstacles for surface observations.

ozone↗

NASA NTRS2018

Correcting for Trace Gas Absorption When Retrieving Aerosol Optical Depth from Satellite Observations of Reflected Shortwave Radiation

Retrieving aerosol optical depth (AOD) from top-of-atmosphere (TOA) satellite measured radiance requires separating the aerosol signal from the total observed signal. Total TOA radiance includes signal from underlying surface and from atmospheric constituents such as aerosols, clouds and gases. Multispectral retrieval algorithms, such as the dark-target (DT) algorithm that operates upon Moderate Resolution Imaging Spectroradiometer (MODIS, onboard Terra and Aqua satellites) and Visible Infrared Imaging Radiometer Suite (VIIRS, onboard Suomi-NPP) sensors, use wavelength bands in "window" regions. However, while small, the gas absorptions in these bands are non-negligible and require correction. In this paper we use High-resolution TRANsmission (HITRAN) database and Line-by-Line Radiative Transfer Model (LBLRTM) to derive consistent gas corrections for both MODIS and VIIRS wavelength bands. Absorptions from H2O, CO2 and O3 are considered, as well as other trace gases. Even though MODIS and VIIRS bands are "similar", they are different enough that applying MODIS specific gas corrections to VIIRS observations results in an underestimate of global mean AOD (by 0.01), but with much larger regional AOD biases up to 0.07. As recent studies are attempting to create a long-term data record by joining multiple satellite datasets, including MODIS and VIIRS, the consistency of gas correction becomes even more crucial.

Satellite Remote Sensing↗

NASA NTRS2019

Can OMPS and VIIRS Be Used as a Single Virtual Sensor for Aerosol Retrieval?

Satellite earth observation of aerosols using a single sensor have been done for more than three decades. The retrieved global distribution of column integrated aerosol optical depth (AOD) has been refined with higher accuracy and finer resolutions. However, the other aerosol properties, such as aerosol absorption and aerosol height, haven not been mapped as extensively using passive sensors. The detectors sensitive to these properties (UV-based sensors such as Aura-OMI) lack the adequate visible channels to tease out the absorption, height and loading contributions. In addition, their spatial resolution is prone to frequent cloud contamination impacting aerosol loading retrievals using only these spectral ranges. However, the deployment of the VIIRS and OMPS-NM sensors on the same Suomi NPP platform provides a first opportunity to carry out retrievals of aerosol single scattering albedo (SSA) and AOD with little cloud contamination using an expanded spectral range from the UV to the near-IR wavelengths. After collocated VIIRS pixel within the large OMPS footprint during the high resolution OMPS observing mode, we compared the radiance from OMPS and VIIRS to ensure the calibration from individual sensors are comparable. Then a look up table (LUT) was created for a smoke case over central Africa. The LUT is generated using 10 channels from 0.357 to 2.1 micron with 44 combinations of aerosol models and 4 different aerosol heights. With CALIOP and AERONET observation nearby, the possibility of using OMPS and VIIRS radiance as a single virtual sensor to simultaneously and consistently retrieve AOD, SSA, and aerosol height is explored.

Shi, Yingxi↗

NASA NTRS2019

TPSAS-NF1676L-34010-DND

We invert global black carbon (BC), organic carbon (OC) and desert dust (DD) aerosol emissions from POLDER/PARASOL spectral aerosol optical depth (AOD) and aerosol absorption optical depth (AAOD) using the GEOSChem inverse modelling framework. Our inverse modeling framework uses standard a priori emissions to provide a posteriori emissions that are constrained by POLDER/PARASOL AODs and AAODs. Our satellite-derived global aerosol emission database indicates an increase of BC and OC, while a decrease of DD with respect to the a priori emission inventories used in standard GEOS-Chem runs. The model simulations using a posteriori emissions (i.e. retrieved emissions) provide new estimate of global aerosol extinction and absorption constrained by observations. Additionally, the a posteriori model simulation of AOD, AAOD, single scattering albedo, Angstrom exponent, and absorption Angstrom exponent show better agreement with independent AERONET, MODIS, and OMI measurements than the a priori simulation. Thus, this study suggests that using satellite-constrained global aerosol emissions in aerosol transport models can improve the accuracy of simulated global aerosol properties and have potential to better understanding global aerosol effects on climate and human health.

Cheng Chen↗

NASA NTRS2020

Global Estimates and Long-Term Trends of Fine Particulate Matter Concentrations (1998-2018)

Exposure to outdoor fine particulate matter (PM2.5) is a leading risk factor for mortality. We develop global estimates of annual PM2.5 concentrations and trends for 1998–2018 using advances in satellite observations, chemical transport modeling, and ground-based monitoring. Aerosol optical depths (AODs) from advanced satellite products including finer resolution, increased global coverage, and improved long-term stability are combined and related to surface PM2.5 concentrations using geophysical relationships between surface PM2.5 and AOD simulated by the GEOS-Chem chemical transport model with updated algorithms. The resultant annual mean geophysical PM2.5 estimates are highly consistent with globally distributed ground monitors (R2 = 0.81; slope = 0.90). Geographically weighted regression is applied to the geophysical PM2.5 estimates to predict and account for the residual bias with PM2.5 monitors, yielding even higher cross validated agreement (R2 = 0.90–0.92; slope = 0.90–0.97) with ground monitors and improved agreement compared to all earlier global estimates. The consistent long-term satellite AOD and simulation enable trend assessment over a 21 year period, identifying significant trends for eastern North America (−0.28 ± 0.03 μg/m3/yr), Europe (−0.15 ± 0.03 μg/m3/yr), India (1.13 ± 0.15 μg/m3/yr), and globally (0.04 ± 0.02 μg/m3/yr). The positive trend (2.44 ± 0.44 μg/m3/yr) for India over 2005–2013 and the negative trend (−3.37 ± 0.38 μg/m3/yr) for China over 2011–2018 are remarkable, with implications for the health of billions of people.

Melanie S. Hammer↗

NASA NTRS2020

High-Resolution Gridded Level 3 Aerosol Optical Depth Data from MODIS

The state-of-art satellite observations of atmospheric aerosols over the last two decades from NASA's MODIS instruments have been extensively utilized in climate change and air quality research and applications. The operational algorithms now produce level 2 aerosol data at varying spatial resolutions (1, 3, and 10 km) and level 3 data at 1 degree. The local and global applications have been benefited from the coarse resolution gridded data sets (i.e., level 3, 1 degree), as it is easier to use since data volume is low and, several online and offline tools are readily available to access and analyze the data with minimal computing resources. At the same time, researchers who require data at much finer spatial scales have to go through a challenging process of obtaining, processing, and analyzing larger volumes of data sets that require high-end computing resources and coding skills. Therefore, we have created a high spatial resolution (HRG, 0.1x0.1 degree) daily and monthly aerosol optical depth (AOD) product by combining two MODIS operational algorithms, namely Deep Blue (DB) and Dark Target (DT). The new HRG AODs meets the accuracy requirements of level 2 AOD data and provide either the same or more spatial coverage on daily and monthly scales. The data sets are provided in daily and monthly files through open Ftp server with python scripts to read and map the data. The reduced data volume with an easy to use format and tools to access the data will encourage more users to utilize the data for research and applications.

aerosol↗

NASA NTRS2020

Revisiting the Relationship between Atlantic Dust and Tropical Cyclone Activity using Aerosol Optical Depth Reanalyses: 2003-2018

Previous studies have noted a relationship between African dust and Atlantic tropical cyclone (TC) activity. However, due to the limitations of past dust analyses, the strength of this relationship remains uncertain. The emergence of aerosol reanalyses, including the Navy Aerosol Analysis and Prediction System (NAAPS) aerosol optical depth (AOD) reanalysis, NASA Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), and ECMWF Copernicus Atmosphere Monitoring Service reanalysis (CAMSRA), enables an investigation of the relationship between African dust and TC activity over the tropical Atlantic and Caribbean in a consistent temporal and spatial manner for 2003–2018. Although June–July–August (JJA) 550 nm dust AOD (DAOD) from all three reanalysis products correlates significantly over the tropical Atlantic and Caribbean, the difference in DAOD magnitude between products can be as large as 60 % over the Caribbean and 20 % over the tropical North Atlantic. Based on the three individual reanalyses, we have created an aerosol multi-reanalysis consensus (MRC). The MRC presents overall better root mean square error over the tropical Atlantic and Caribbean compared to individual reanalyses when verified with ground-based AErosol RObotic NETwork (AERONET) AOD measurements. Each of the three individual reanalyses and the MRC have significant negative correlations between JJA Caribbean DAOD and seasonal Atlantic accumulated cyclone energy (ACE), while the correlation between JJA tropical North Atlantic DAOD and seasonal ACE is weaker. Possible reasons for this regional difference are provided. A composite analysis of 3 high-JJA-Caribbean-DAOD years versus 3 low-JJA-Caribbean-DAOD years reveals large differences in overall Atlantic TC activity. We also show that JJA Caribbean DAOD is significantly correlated with large-scale fields associated with variability in interannual Atlantic TC activity including zonal wind shear, mid-level moisture, and sea surface temperature (SST), as well as the El Niño–Southern Oscillation (ENSO) and the Atlantic Meridional Mode (AMM), implying confounding effects of these factors on the dust–TC relationship. We find that seasonal Atlantic DAOD and the AMM, the leading mode of coupled Atlantic variability, are inversely related and intertwined in the dust–TC relationship. Overall, DAOD in both the tropical Atlantic and Caribbean is negatively correlated with Atlantic hurricane frequency and intensity, with stronger correlations in the Caribbean than farther east in the tropical North Atlantic.

Dust particles↗

NASA NTRSDate not supplied

Airborne Remote Sensing Measurements of Particles in Different Parts of the World

Around the globe, atmospheric aerosols pose a significant yet uncertain impact on the Earth's climate, environmental air quality and human health. Suborbital sunphotometer measurements of Aerosol Optical Depth (AOD) (i.e., the amount of direct-beam solar light attenuated by aerosols within the atmospheric column) are used to validate satellite aerosol retrievals and are valuable when studying aerosol-solar radiation and/ or aerosol-cloud interactions. Since 1985, NASA Ames Research Center (ARC) has been using airborne sun-tracking sunphotometers to measure atmospheric constituents such as aerosols, clouds, and gases. The NASA Ames Airborne Tracking Sunphotometer (AATS-6) and then (AATS-14) operate by tracking the sun and measuring the transmission of solar radiation in 6 to 14 discrete spectral channels (Russell et al., 1986). The AATS systems were followed by the more advanced hyperspectral 4STAR instrument (Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research; Dunagan et al., 2013), which combines the airborne sun-tracking capability of the AATS-14 with a sky scanning feature similar to the ground-based Aerosol Robotic Network Sun/sky photometers (AERONET). We present a comprehensive analysis of ~30 airborne campaigns undertaken by NASA and DoE based on a new database of airborne sunphotometer measurements. Using this database, we present a clear picture of airborne AODs over the range of historical campaigns and the aerosol sizes per region, especially over the ocean where AERONET data is limited. With this database, we can investigate systematic differences in AOD such as those observed over different land and ocean surfaces in specific geographical regions. Finally, we will briefly show comparisons with satellite aerosol retrievals from MODIS and/or VIIRS. Russell, P. B., T. Matsumoto, V. J. Banta, J. M. Livingston, C. Mina, D. S. Colburn, and R. F. Pueschel (1986), Measurements with an airborne, autotracking, external-head sunphotometer, Preprint Volume, Sixth Conference on Atmospheric Radiation, May 13–16, 1986, Amer. Meteor.Soc., Boston, MA, 55–58. Dunagan, Stephen E., et al. "Spectrometer for sky-scanning sun-tracking atmospheric research (4STAR): Instrument technology." Remote Sensing 5.8 (2013): 3872-3895

Brendan Stover Cornelison↗

NASA NTRS2019

VIIRS Deep Blue Aerosol Products Over Land: Extending the EOS Long‐Term Aerosol Data Records

A primary goal of the Deep Blue (DB) project is to create consistent long‐term aerosol data records, suitable for climate studies, using multiple satellite instruments. In order to continue Earth Observing System (EOS)‐era aerosol products into the Joint Polar Satellite System era, we have successfully ported the DB algorithm to process data from the Visible Infrared Imaging Radiometer Suite (VIIRS). Although the basic structure of the VIIRS algorithm is similar to that for the Moderate Resolution Imaging Spectroradiometer (MODIS), many enhancements have been made compared to the MODIS collection 6 (C6) version. Most have also been implemented in the latest MODIS Collection 6.1 (C6.1). For example, a new smoke mask was developed based on the spectral curvature of measured reflectance to distinguish biomass burning smoke from weakly absorbing urban/industrial aerosols. Consequently, a new aerosol‐type flag was added into the VIIRS DB data set. In addition, new dust models have been developed to account for the nonsphericity of mineral dust. As a result, a discontinuity in the retrieved aerosol optical depth (AOD) of Saharan dust plumes seen in MODIS C6 products near the boundary between North Africa and the Atlantic has been much reduced. We have also evaluated the VIIRS and MODIS Terra/Aqua C6.1 AOD against Aerosol Robotic Network data. VIIRS and MODIS retrievals show similar performance; around 80% of matchups agree with Aerosol Robotic Network within the expected error of ±(0.05 + 20)%, indicating that DB can provide consistent AOD through the historical EOS and present Joint Polar Satellite System eras.

aerosols↗

NASA NTRS2019

Aerosol Properties Over Tibetan Plateau From a Decade of AERONET Measurements: Baseline, Types, and Influencing Factors

In this study, a decade long measurement of aerosol optical properties at two AERONET stations (Nam Co during 2006–2016 and QOMS during 2009–2017) in the Tibetan Plateau (TP), a region sensitive to climate change and human perturbation, is presented. The baseline value of aerosol optical depth (AOD) was 0.029 and 0.027 at Nam Co and QOMS, respectively, which are comparable to or even lower than those at some Arctic and remote ocean locations. The seasonality of AOD values were the order of spring > summer > winter > autumn. Based on AOD and Ångström exponent (α), major aerosol types over the TP were further identified as continental background, biomass burning, and dust. Although continental background aerosol was the main feature in remote areas of TP, biomass burning plumes frequently occurred, especially during spring (March–April). In one of such biomass burning event in April 2014, MODIS observations demonstrated that intensive open fires occurred in South Asia, covering the foothills of Himalayas and Indo‐Gangetic Plain. The air mass back trajectories and CALIOP observations further revealed that biomass burning plume could be uplifted to higher altitudes and reach the Himalayas. Moreover, an occasional dust event detected in April 2008 over the TP demonstrated that the dust from Taklamakan Desert may impact the main body of TP episodically, although the local dust from the inside of TP cannot be excluded and warrants further study.

Manisha Pokharel↗

NASA NTRS2020

The Relationship Between MAIAC Smoke Plume Heights and Surface PM

Biomass burning is a source of fine particulate matter (PM2.5) air pollution, which adversely impacts human health. However, quantifying the health effects from biomass burning PM2.5 is difficult. Monitoring networks generally lack the spatial density needed to capture the heterogeneity of biomass burning smoke. Satellite aerosol optical depth (AOD) can be used to fill spatial gaps but does not distinguish surface‐level aerosols. Plume height (PH) observations may provide constraints on the vertical distribution of smoke and its impact on surface concentrations. We assessed PH characteristics from Multi‐Angle Implementation of Atmospheric Correction (MAIAC) and evaluated its correlation with colocated PM2.5 and AOD measurements. PH is generally highest over the western United States. The ratio PM2.5:AOD generally decreases with increasing PH:PBLH (planetary boundary layer height), showing that PH has the potential to refine surface PM2.5 estimates for collections of smoke events.

satellite retrieved smoke plume heights↗

NASA NTRS2020

The AERONET Version 3 Aerosol Retrieval Algorithm, Associated Uncertainties and Comparisons to Version 2

The Aerosol Robotic Network (AERONET) Version 3 (V3) aerosol retrieval algorithm is described, which is based on the Version 2 (V2) algorithm with numerous updates. Comparisons of V3 aerosol retrievals to those of V2 are presented, along with a new approach to estimate uncertainties in many of the retrieved aerosol parameters. Changes in the V3 aerosol retrieval algorithm include (1) a new polarized radiative transfer code (RTC), which replaced the scalar RTC of V2, (2) detailed characterization of gas absorption by adding NO2 and H2O to specify total gas absorption in the atmospheric column, specification of vertical profiles of all the atmospheric species, (3) new bidirectional reflectance distribution function (BRDF) parameters for land sites adopted from the MODIS BRDF/Albedo product, (4) a new version of the extraterrestrial solar flux spectrum, and (5) a new temperature correction procedure of both direct Sun and sky radiance measurements. The potential effect of each change in V3 on single scattering albedo (SSA) retrievals was analyzed. The operational almucantar retrievals of V2 versus V3 were compared for four AERONET sites: GSFC, Mezaira, Mongu, and Kanpur. Analysis showed very good agreement in retrieved parameters of the size distributions. Comparisons of SSA retrievals for dust aerosols (Mezaira) showed a good agreement in 440 nm SSA, while for longer wavelengths V3 SSAs are systematically higher than those of V2, with the largest mean difference at 675 nm due to cumulative effects of both extraterrestrial solar flux and BRDF changes. For non-dust aerosols, the largest SSA deviation is at 675 nm due to differences in extraterrestrial solar flux spectrums used in each version. Further, the SSA 675 nm mean differences are very different for weakly (GSFC) and strongly (Mongu) absorbing aerosols, which is explained by the lower sensitivity to a bias in aerosol scattering optical depth by less absorbing aerosols. A new hybrid (HYB) sky radiance measurement scan is introduced and discussed. The HYB combines features of scans in two different planes to maximize the range of scattering angles and achieve scan symmetry, thereby allowing for cloud screening and spatial averaging, which is an advantage over the principal plane scan that lacks robust symmetry. We show that due to an extended range of scattering angles, HYB SSA retrievals for dust aerosols exhibit smaller variability with solar zenith angles (SZAs) than those of almucantar (ALM), which allows extension of HYB SSA retrievals to SZAs less than 50∘ to as small as 25∘. The comparison of SSA retrievals from closely time-matched HYB and ALM scans in the 50 to 75∘ SZA range showed good agreement with the differences below ∼0.005. We also present an approach to estimate retrieval uncertainties which utilizes the variability in retrieved parameters generated by perturbing both measurements and auxiliary input parameters as a proxy for retrieval uncertainty. The perturbations in measurements and auxiliary inputs are assumed as estimated biases in aerosol optical depth (AOD), radiometric calibration of sky radiances combined with solar spectral irradiance, and surface reflectance. For each set of Level 2 Sun/sky radiometer observations, 27 inputs corresponding to 27 combinations of biases were produced and separately inverted to generate the following statistics of the inversion results: average, standard deviation, minimum and maximum values. From these statistics, standard deviation (labeled U27) is used as a proxy for estimated uncertainty, and a lookup table (LUT) approach was implemented to reduce the computational time. The U27 climatological LUT was generated from the entire AERONET almucantar (1993–2018) and hybrid (2014–2018) scan databases by binning U27s in AOD (440 nm), Angström exponent (AE, 440–870 nm), and SSA (440, 675, 870, 1020 nm). Using this LUT approach, the uncertainty estimates U27 for each individual V3 Level 2 retrieval can be obtained by interpolation using the corresponding measured and inverted combination of AOD, AE, and SSA.

Aliaksandr Siniuk↗