scholarly journals OBSERVATION OF DUST LOADINGS FROM SPACE-BORNE MEASUREMENTS (2005–2016)

2018 ◽  
Vol XLII-5 ◽  
pp. 523-525
Author(s):  
M. Gumber ◽  
M. Mehta ◽  
M. Mittal
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Spatial Resolution ◽  
Spatial Information ◽  
Spatial Scales ◽  
Dust Particles ◽  
Orthogonal Polarization ◽  
Accurate Information ◽  
Ozone Monitoring Instrument ◽  
Level 3

<p><strong>Abstract.</strong> Dust particles of different size and origins, form major part of air pollution in the atmosphere. The qualitative and quantitative estimates of dust from ground-based measurements provide accurate information at regional scales. However, data from space-borne instruments provide continuous spatial information at a variety of different spatial scales. In this paper, we attempt to study signals of dust as observed from CALIOP (Cloud Aerosol Lidar with Orthogonal Polarization) sensor on-board CALIPSO satellite. Utilization of these freely available datasets can effectively contribute to the capacity building in the domain of aerosol science. This analysis is supplemented by absorbing aerosol levels as seen by OMI (Ozone Monitoring Instrument) sensor on-board AURA satellite. This study was conducted over the Middle-East and North Africa during JJA (June, July and August) season. For this study, we have used Level-3 AOD (Aerosol Optical Depth) due to dust from CALIOP at spatial resolution of 2&amp;deg;<span class="thinspace"></span>&amp;times;<span class="thinspace"></span>5&amp;deg; and Level-3 Absorbing Aerosol Optical Depth (AAOD) data from OMI at spatial resolution of 1&amp;deg;<span class="thinspace"></span>&amp;times;<span class="thinspace"></span>1&amp;deg;.The time frame for the study was 2005 to 2016.</p>

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

2020 ◽  
Vol 12 (17) ◽  
pp. 2847 ◽  
Author(s):  
Pawan Gupta ◽  
Lorraine A. Remer ◽  
Falguni Patadia ◽  
Robert C. Levy ◽  
Sundar A. Christopher
Keyword(s):  
High Resolution ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Atmospheric Aerosols ◽  
Spatial Scales ◽  
Data Sets ◽  
Spatial Coverage ◽  
Data Volume ◽  
Level 3 ◽  
Level 2

The state-of-art satellite observations of atmospheric aerosols over the last two decades from NASA’s Moderate Resolution Imaging Spectroradiometer (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 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 created a high spatial resolution (high-resolution gridded (HRG), 0.1 × 0.1 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 meet 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 an 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.

scholarly journals Assessment of the Level-3 MODIS daily aerosol optical depth in the context of surface solar radiation and numerical weather modeling

2012 ◽  
Vol 12 (9) ◽  
pp. 23219-23260 ◽  
Author(s):  
J. A. Ruiz-Arias ◽  
J. Dudhia ◽  
C. A. Gueymard ◽  
D. Pozo-Vázquez
Keyword(s):  
Solar Radiation ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Spatial Resolution ◽  
Surface Solar Radiation ◽  
Numerical Weather ◽  
Level 3 ◽  
Weather Modeling ◽  
The Mean ◽  
Level 2

Abstract. The Level-3 MODIS aerosol optical depth (AOD) product offers interesting features for surface solar radiation and numerical weather modeling applications. Remarkably, the Collection 5.1 dataset extends over more than a decade, and provides daily values of AOD over a global regular grid of 1°×1° spatial resolution. However, most of the validation efforts so far have focused on Level-2 products (10-km, at original resolution) and only rarely on Level-3 (at aggregated spatial resolution of 1°×1°). In this contribution, we compare the Level-3 Collection 5.1 MODIS AOD dataset available since 2000 against observed daily AOD values at 550 nm from more than 500 AERONET ground stations around the globe. One aim of this study is to check the advisability of this MODIS dataset for surface shortwave solar radiation calculations using numerical weather models. Overall, the mean error of the dataset is 0.03 (17%, relative to the mean ground-observed AOD), with a root mean square error of 0.14 (73%, relative to the same), albeit these values are found highly dependent on geographical region. For AOD values below about 0.3 the expected error is found very similar to that of the Level-2 product. However, for larger AOD values, higher errors are found. Consequently, we propose new functions for the expected error of the Level-3 AOD, as well as for both its mean error and its standard deviation. Additionally, we investigate the role of pixel count vis-à-vis the reliability of the AOD estimates. Our results show that a higher pixel count does not necessarily turn into a more reliable AOD estimate. Therefore, we recommend to verify this assumption in the dataset at hand if the pixel count is meant to be used. We also explore to what extent the spatial aggregation from Level-2 to Level-3 influences the total uncertainty in the Level-3 AOD. In particular, we found that, roughly, half of the error might be attributable to Level-3 AOD sub-pixel variability. Finally, we use a~radiative transfer model to investigate how the Level-3 AOD uncertainty propagates into the calculated direct normal (DNI) and global horizontal (GHI) irradiances. Overall, results indicate that, for Level-3 AODs smaller than 0.5, the induced uncertainty in DNI due to the AOD uncertainty alone is below 15% on average, and below 5% for GHI (for a solar zenith angle of 30°. However, the uncertainty in AOD is highly spatially variable, and so is that in irradiance.

scholarly journals Aerosol optical depth retrievals at the Izaña Atmospheric Observatory from 1941 to 2013 by using artificial neural networks

2016 ◽  
Vol 9 (1) ◽  
pp. 53-62 ◽  
Author(s):  
R. D. García ◽  
O. E. García ◽  
E. Cuevas ◽  
V. E. Cachorro ◽  
A. Barreto ◽  
...  
Keyword(s):  
Neural Networks ◽  
Time Series ◽  
Artificial Neural Networks ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Mineral Dust ◽  
Dust Particles ◽  
Filter Radiometer ◽  
Artificial Neural

Abstract. This paper presents the reconstruction of a 73-year time series of the aerosol optical depth (AOD) at 500 nm at the subtropical high-mountain Izaña Atmospheric Observatory (IZO) located in Tenerife (Canary Islands, Spain). For this purpose, we have combined AOD estimates from artificial neural networks (ANNs) from 1941 to 2001 and AOD measurements directly obtained with a Precision Filter Radiometer (PFR) between 2003 and 2013. The analysis is limited to summer months (July–August–September), when the largest aerosol load is observed at IZO (Saharan mineral dust particles). The ANN AOD time series has been comprehensively validated against coincident AOD measurements performed with a solar spectrometer Mark-I (1984–2009) and AERONET (AErosol RObotic NETwork) CIMEL photometers (2004–2009) at IZO, obtaining a rather good agreement on a daily basis: Pearson coefficient, R, of 0.97 between AERONET and ANN AOD, and 0.93 between Mark-I and ANN AOD estimates. In addition, we have analysed the long-term consistency between ANN AOD time series and long-term meteorological records identifying Saharan mineral dust events at IZO (synoptical observations and local wind records). Both analyses provide consistent results, with correlations  >  85 %. Therefore, we can conclude that the reconstructed AOD time series captures well the AOD variations and dust-laden Saharan air mass outbreaks on short-term and long-term timescales and, thus, it is suitable to be used in climate analysis.

scholarly journals Airborne observation during KORUS-AQ show aerosol optical depth are more spatially self-consistent than aerosol intensive properties

2022 ◽  
Author(s):  
Samuel E. LeBlanc ◽  
Michal Segal-Rozenhaimer ◽  
Jens Redemann ◽  
Connor J. Flynn ◽  
Roy R. Johnson ◽  
...  
Keyword(s):  
Air Quality ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Temporal Variability ◽  
Spatial Scales ◽  
Aerosol Emission ◽  
Fine Mode ◽  
Predominant Factor ◽  
Spatio Temporal ◽  
Microphysical Processes

Abstract. Aerosol particles can be emitted, transported, removed, or transformed, leading to aerosol variability at scales impacting the climate (days to years and over hundreds of kilometers) or the air quality (hours to days and from meters to hundreds of kilometers). We present the temporal and spatial scales of changes in AOD (Aerosol Optical Depth), and aerosol size (using Angstrom Exponent; AE, and Fine-Mode-Fraction; FMF) over Korea during the 2016 KORUS-AQ (KORea-US Air Quality) atmospheric experiment. We use measurements and retrievals of aerosol optical properties from airborne instruments for remote sensing (4STAR; Spectrometers for Sky-Scanning Sun Tracking Atmospheric Research) and in situ (LARGE; NASA Langley Aerosol Research Group Experiment) on board the NASA DC-8, geostationary satellite (GOCI; Geostationary Ocean Color Imager; Yonsei aerosol retrieval (YAER) version 2) and reanalysis (MERRA-2; Modern-Era Retrospective Analysis for Research and Applications, version 2). Measurements from 4STAR when flying below 500 m, show an average AOD at 501 nm of 0.43 and an average AE of 1.15 with large standard deviation (0.32 and 0.26 for AOD and AE respectively) likely due to mixing of different aerosol types (fine and coarse mode). The majority of AODs due to fine mode aerosol is observed at altitudes lower than 2 km. Even though there are large variations, for 18 out of the 20 flight days, the column AOD measurements by 4STAR along the NASA DC-8 flight trajectories matches the south-Korean regional average derived from GOCI. We also observed that, contrary to prevalent understanding, AE and FMF are more spatially variable than AOD during KORUS-AQ, even when accounting for potential sampling biases by using Monte Carlo resampling. Averaging between measurements and model for the entire KORUS-AQ period, a reduction in correlation by 15 % is 65.0 km for AOD and shorter at 22.7 km for AE. While there are observational and model differences, the predominant factor influencing spatial-temporal homogeneity is the meteorological period. High spatio-temporal variability occur during the dynamic period (25–31 May), and low spatio-temporal variability occur during blocking Rex pattern (01–07 June). The changes in spatial variability scales between AOD and FMF/AE, while inter-related, indicate that microphysical processes that impact mostly the dominant aerosol size, like aerosol particle formation, growth, and coagulation, vary at shorter scales than the aerosol concentration processes that mostly impact AOD, like aerosol emission, transport, and removal.

The NASA-TROPOMI Aerosol Algorithm: Evaluation of first results

2021 ◽  
Author(s):  
Omar Torres ◽  
Hiren Jethva ◽  
Changwoo Ahn ◽  
Glen Jaross ◽  
Diego Loyola
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Spatial Resolution ◽  
Single Scattering ◽  
Initial Evaluation ◽  
Continental Scale ◽  
Related Information ◽  
Fine Spatial Resolution ◽  
Direct Measurements ◽  
First Results

&lt;p&gt;The NASA-TROPOMI aerosol algorithm (TropOMAER), is an adaptation of the currently operational OMI near-UV (OMAERUV &amp; OMACA) inversion schemes, that take advantage of TROPOMI&amp;#8217;s unprecedented fine spatial resolution at UV wavelengths, and the availability of ancillary aerosol-related information to derive aerosol loading in cloud-free and above-cloud aerosols scenes. In this presentation we will introduce the NASA TROPOMI aerosol algorithm and discuss initial evaluation results of retrieved aerosol optical depth (AOD) and single scattering albedo (SSA) by direct comparison to AERONET AOD direct measurements and SSA inversions. We will also demonstrate TropOMAER retrieval capabilities in the context of recent continental scale aerosol events.&lt;/p&gt;

scholarly journals The regime of Aerosol Optical Depth and Ångström exponent over Central and South Asia

2019 ◽  
Vol 99 ◽  
pp. 01003
Author(s):  
Athina Avgousta Floutsi ◽  
Marios Bruno Korras Carraca ◽  
Christos Matsoukas ◽  
Nikos Hatzianastassiou ◽  
George Biskos
Keyword(s):  
South Asia ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Atmospheric Aerosols ◽  
Dust Particles ◽  
Desert Dust ◽  
Angstrom Exponent ◽  
Ångström Exponent ◽  
Dust Load ◽  
Ångstrom Exponent

Central and South Asia are regions of particular interest for studying atmospheric aerosols, being among the largest sources of desert dust aerosols globally. In this study we use the newest collection (C061) of MODIS - Aqua aerosol optical depth (AOD) at 550 nm and Ångström exponent (a) at 412/470 nm over the 15-year period between 2002 and 2017, providing the longest analyzed dataset for this region. According to our results, during spring and summer, high aerosol load (AOD up to 1.2) consisting of coarse desert dust particles, as indicated by a values as low as 0.15, is observed over the Taklamakan, Thar and Registan deserts and the region between the Aral and Caspian seas. The dust load is much lower during winter and autumn (lower AOD and higher a values compared to the other seasons). The interannual variation of AOD and a suggests that the dust load exhibits large decreasing trends (AOD slopes down to -0.22, a slopes up to 0.47 decade-1) over the Thar desert and large increasing trends between the Aral and Caspian seas (AOD and a slopes up to 0.23 decade-1 and down to -0.61 decade-1, respectively.) The AOD data are evaluated against AERONET surface-based measurements. Generally, MODIS and AERONET data are in good agreement with a correlation coefficient (R) equal to 0.835.

scholarly journals A low-cost monitor for measurement of fine particulate matter and aerosol optical depth – Part 2: Citizen-science pilot campaign in northern Colorado

2019 ◽  
Vol 12 (12) ◽  
pp. 6385-6399 ◽  
Author(s):  
Bonne Ford ◽  
Jeffrey R. Pierce ◽  
Eric Wendt ◽  
Marilee Long ◽  
Shantanu Jathar ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Aerosol Optical Depth ◽  
Citizen Science ◽  
Optical Depth ◽  
Spatial Scales ◽  
Fine Particulate Matter ◽  
Optical Measurements ◽  
Fine Particulate ◽  
Northern Colorado

Abstract. A pilot field campaign was conducted in the fall and winter of 2017 in northern Colorado to test the deployment of the Aerosol Mass and Optical Depth (AMOD) instrument as part of the Citizen-Enabled Aerosol Measurements for Satellites (CEAMS) network. Citizen scientists were recruited to set up the device to take filter and optical measurements of aerosols in their backyards. The goal of the network is to provide more surface particulate matter and aerosol optical depth (AOD) measurements to increase the spatial and temporal resolution of ratios of fine particulate matter (PM2.5) to AOD and to improve satellite-based estimates of air quality. Participants collected 65 filters and 160 multi-wavelength AOD measurements, from which 109 successful PM2.5 : AOD ratios were calculated. We show that PM2.5, AOD, and their ratio (PM2.5 : AOD) often vary substantially over relatively short spatial scales; this spatial variation is not typically resolved by satellite- and model-based PM2.5 exposure estimates. The success of the pilot campaign suggests that citizen-science networks are a viable means for providing new insight into surface air quality. We also discuss lessons learned and AMOD design modifications, which will be used in future wider deployments of the CEAMS network.

scholarly journals The potential of elastic and polarization lidars to retrieve extinction profiles

2020 ◽  
Vol 13 (2) ◽  
pp. 893-905 ◽  
Author(s):  
Elina Giannakaki ◽  
Panos Kokkalis ◽  
Eleni Marinou ◽  
Nikolaos S. Bartsotas ◽  
Vassilis Amiridis ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Dust Particles ◽  
Depolarization Ratio ◽  
Lidar System ◽  
Lidar Measurements ◽  
Lidar Ratio ◽  
Linear Depolarization Ratio ◽  
Aerosol Types ◽  
532 Nm

Abstract. A new method, called ElEx (elastic extinction), is proposed for the estimation of extinction coefficient lidar profiles using only the information provided by the elastic and polarization channels of a lidar system. The method is applicable to lidar measurements both during daytime and nighttime under well-defined aerosol mixtures. ElEx uses the particle backscatter profiles at 532 nm and the vertically resolved particle linear depolarization ratio measurements at the same wavelength. The particle linear depolarization ratio and the lidar ratio values of pure aerosol types are also taken from literature. The total extinction profile is then estimated and compared well with Raman retrievals. In this study, ElEx was applied in an aerosol mixture of marine and dust particles at Finokalia station during the CHARADMExp campaign. Any difference between ElEx and Raman extinction profiles indicates that the nondust component could be probably attributed to polluted marine or polluted continental aerosols. Comparison with sun photometer aerosol optical depth observations is performed as well during daytime. Differences in the total aerosol optical depth are varying between 1.2 % and 72 %, and these differences are attributed to the limited ability of the lidar to correctly represent the aerosol optical properties in the near range due to the overlap problem.

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