scholarly journals Automated Aerosol Classification from Spectral UV Measurements Using Machine Learning Clustering

2020 ◽  
Vol 12 (6) ◽  
pp. 965 ◽  
Author(s):  
Nikolaos Siomos ◽  
Ilias Fountoulakis ◽  
Athanasios Natsis ◽  
Theano Drosoglou ◽  
Alkiviadis Bais
Keyword(s):  
Machine Learning ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Mahalanobis Distance ◽  
Single Scattering ◽  
Training Dataset ◽  
Classification Technique ◽  
Brewer Spectrophotometer ◽  
Aerosol Classification ◽  
Double Monochromator

In this study, we present an aerosol classification technique based on measurements of a double monochromator Brewer spectrophotometer during the period 1998–2017 in Thessaloniki, Greece. A machine learning clustering procedure was applied based on the Mahalanobis distance metric. The classification process utilizes the UV Single Scattering Albedo (SSA) at 340 nm and the Extinction Angstrom Exponent (EAE) at 320–360 nm that are obtained from the spectrophotometer. The analysis is supported by measurements from a CIMEL sunphotometer that were deployed in order to establish the training dataset of Brewer measurements. By applying the Mahalanobis distance algorithm to the Brewer timeseries, we automatically assigned measurements in one of the following clusters: Fine Non Absorbing Mixtures (FNA): 64.7%, Black Carbon Mixtures (BC): 17.4%, Dust Mixtures (DUST): 8.1%, and Mixed: 9.8%. We examined the clustering potential of the algorithm by reclassifying the training dataset and comparing it with the original one and also by using manually classified cases. The typing score of the Mahalanobis algorithm is high for all predominant clusters FNA: 77.0%, BC: 63.9%, and DUST: 80.3% when compared with the training dataset. We obtained high scores as well FNA: 100.0%, BC: 66.7%, and DUST: 83.3% when comparing it with the manually classified dataset. The flags obtained here were applied in the timeseries of the Aerosol Optical Depth (AOD) at 340 nm of the Brewer and the CIMEL in order to compare between the two and also stress the future impact of the proposed clustering technique in climatological studies of the station.

scholarly journals A First Approach to Aerosol Classification Using Space-Borne Measurement Data: Machine Learning-Based Algorithm and Evaluation

2021 ◽  
Vol 13 (4) ◽  
pp. 609
Author(s):  
Wonei Choi ◽  
Hanlim Lee ◽  
Jeonghyeon Park
Keyword(s):  
Machine Learning ◽  
Measurement Data ◽  
Wavelength Dependence ◽  
Single Scattering ◽  
New Method ◽  
Spherical Particles ◽  
Training Dataset ◽  
Aerosol Classification ◽  
Input Variables ◽  
Aerosol Types

A new method was developed for classifying aerosol types involving a machine-learning approach to the use of satellite data. An Aerosol Robotic NETwork (AERONET)-based aerosol-type dataset was used as a target variable in a random forest (RF) model. The contributions of satellite input variables to the RF-based model were quantified to determine an optimal set of input variables. The new method, based on inputs of satellite variables, allows the classification of seven aerosol types: pure dust, dust-dominant mixed, pollution-dominant mixed aerosols, and pollution aerosols (strongly, moderately, weakly, and non-absorbing). The performance of the model was statistically evaluated using AERONET data excluded from the model training dataset. Model accuracy for classifying the seven aerosol types was 59%, improving to 72% for four types (pure dust, dust-dominant mixed, strongly absorbing, and non-absorbing). The performance of the model was evaluated against an earlier aerosol classification method based on the wavelength dependence of single-scattering albedo (SSA) and fine-mode-fraction values from AERONET. Typical wavelength dependences of SSA for individual aerosol types are consistent with those obtained for aerosol types by the new method. This study demonstrates that an RF-based model is capable of satellite aerosol classification with sensitivity to the contribution of non-spherical particles.

scholarly journals Retrieval of aerosol single-scattering albedo and polarized phase function from polarized sun-photometer measurements for Zanjan's atmosphere

2013 ◽  
Vol 6 (10) ◽  
pp. 2659-2669 ◽  
Author(s):  
A. Bayat ◽  
H. R. Khalesifard ◽  
A. Masoumi
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Atmospheric Aerosols ◽  
Phase Function ◽  
Single Scattering ◽  
Single Scattering Albedo ◽  
Angstrom Exponent ◽  
Ångström Exponent ◽  
Sun Photometer ◽  
Ångstrom Exponent

Abstract. The polarized phase function of atmospheric aerosols has been investigated for the atmosphere of Zanjan, a city in northwest Iran. To do this, aerosol optical depth, Ångström exponent, single-scattering albedo, and polarized phase function have been retrieved from the measurements of a Cimel CE 318-2 polarized sun-photometer from February 2010 to December 2012. The results show that the maximum value of aerosol polarized phase function as well as the polarized phase function retrieved for a specific scattering angle (i.e., 60°) are strongly correlated (R = 0.95 and 0.95, respectively) with the Ångström exponent. The latter has a meaningful variation with respect to the changes in the complex refractive index of the atmospheric aerosols. Furthermore the polarized phase function shows a moderate negative correlation with respect to the atmospheric aerosol optical depth and single-scattering albedo (R = −0.76 and −0.33, respectively). Therefore the polarized phase function can be regarded as a key parameter to characterize the atmospheric particles of the region – a populated city in the semi-arid area and surrounded by some dust sources of the Earth's dust belt.

scholarly journals Effective aerosol optical depth from pyranometer measurements of surface solar radiation (global radiation) at Thessaloniki, Greece

2012 ◽  
Vol 12 (12) ◽  
pp. 33265-33289
Author(s):  
A. V. Lindfors ◽  
N. Kouremeti ◽  
A. Arola ◽  
S. Kazadzis ◽  
A. F. Bais ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Atmospheric Aerosol ◽  
Global Radiation ◽  
Single Scattering ◽  
Surface Radiation ◽  
Surface Solar Radiation ◽  
Long Time ◽  
Source Of Information

Abstract. Pyranometer measurements of the solar surface radiation (SSR) are available at many locations worldwide, often as long time series covering several decades into the past. These data constitute a potential source of information on the atmospheric aerosol load. Here, we present a method for estimating the aerosol optical depth (AOD) using pyranometer measurements of the SSR together with total water vapor column information. The method, which is based on radiative transfer simulations, was developed and tested using recent data from Thessaloniki, Greece. The effective AOD calculated using this method was found to agree well with co-located AERONET measurements, exhibiting a correlation coefficient of 0.9 with 2/3 of the data found within ±20% or ±0.05 of the AERONET AOD. This is similar to the performance of current satellite aerosol methods. Differences in the AOD as compared to AERONET can be explained by variations in the aerosol properties of the atmosphere that are not accounted for in the idealized settings used in the radiative transfer simulations, such as variations in the single scattering albedo and Ångström exponent. Furthermore, the method is sensitive to calibration offsets between the radiative transfer simulations and the pyranometer SSR. The method provides an opportunity of extending our knowledge of the atmospheric aerosol load to locations and times not covered by dedicated aerosol measurements.

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

<p>The NASA-TROPOMI aerosol algorithm (TropOMAER), is an adaptation of the currently operational OMI near-UV (OMAERUV & OMACA) inversion schemes, that take advantage of TROPOMI’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.</p>

scholarly journals How much of the global aerosol optical depth is found in the boundary layer and free troposphere?

2017 ◽  
Author(s):  
Quentin Bourgeois ◽  
Annica M. L. Ekman ◽  
Jean-Baptiste Renard ◽  
Radovan Krejci ◽  
Abhay Devasthale ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Climate Models ◽  
Convective Transport ◽  
Free Troposphere ◽  
Range Transport ◽  
Aerosol Classification ◽  
The Tropics ◽  
The Vertical Distribution

Abstract. The global aerosol extinction from the CALIOP space lidar was used to compute aerosol optical depth (AOD) over a nine-year period (2007–2015) and partitioned between the boundary layer (BL) and the free troposphere (FT) using BL heights obtained from the ERA-Interim archive. The results show that the vertical distribution of AOD does not follow the diurnal cycle of the BL but remains similar between day and night highlighting the presence of a residual layer during night. The BL and FT contribute 69 % and 31 %, respectively, to the global tropospheric AOD during daytime in line with observations obtained using the Light Optical Aerosol Counter (LOAC) instrument. The FT AOD contribution is larger in the tropics than at mid-latitudes which indicates that convective transport largely controls the vertical profile of aerosols. Over oceans, the FT AOD contribution is mainly governed by long-range transport of aerosols from emission sources located within neighboring continents. According to the CALIOP aerosol classification, dust and smoke particles are the main aerosol types transported into the FT. Overall, the study shows that the fraction of AOD in the FT – and thus potentially located above low-level clouds – is substantial and deserves more attention when evaluating the radiative effect of aerosols in climate models. More generally, the results have implications for process determining the overall budgets, sources, sinks and transport of aerosol particles and their description in atmospheric models.

scholarly journals Deriving Aerosol Absorption Properties from Solar Ultraviolet Radiation Spectral Measurements at Thessaloniki, Greece

2019 ◽  
Author(s):  
Ilias Fountoulakis ◽  
Athanasios Natsis ◽  
Nikolaos Siomos ◽  
Theano Drosoglou ◽  
Alkiviadis F. Bais
Keyword(s):  
Solar Spectrum ◽  
Single Scattering ◽  
Spectral Measurements ◽  
City Center ◽  
Solar Ultraviolet Radiation ◽  
Aerosol Absorption ◽  
Brewer Spectrophotometer ◽  
Absorbing Aerosols ◽  
The City ◽  
Double Monochromator

The gap in knowledge regarding the radiative effects of aerosols in the UV region of the solar spectrum is large, mainly due to the lack of systematic measurements of the aerosol single scattering albedo (SSA) and absorption optical depth (AAOD). In the present study, spectral UV measurements performed in Thessaloniki, Greece by a double monochromator Brewer spectrophotometer in the period 1998 - 2017 are used for the calculation of the aforementioned optical properties. The main uncertainty factors have been described and there is an effort to quantify the overall uncertainties in SSA and AAOD. Analysis of the results suggests that the absorption by aerosols is much stronger in the UV relative to the visible. SSA follows a clear annual pattern ranging from ~0.7 in winter to ~0.85 in summer at wavelengths 320 – 360 nm, while AAOD peaks in summer and winter. The average AAOD for 2009 – 2011 is ~50% above the 2003 – 2006 average, possibly due to increased emissions of absorbing aerosols related to the economical crisis and the metro-railway construction works in the city center. A detailed analysis of the uncertainties in the retrieval of the SSA and the AAOD from the Brewer spectrophotometer has been also performed.

scholarly journals Retrieval of aerosol optical depth over land based on a time series technique using MSG/SERIVI data

2012 ◽  
Vol 12 (2) ◽  
pp. 4031-4071 ◽  
Author(s):  
L. Mei ◽  
Y. Xue ◽  
G. de Leeuw ◽  
T. Holzer-Popp ◽  
J. Guang ◽  
...  
Keyword(s):  
Time Series ◽  
Detailed Analysis ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Optimal Solution ◽  
Single Scattering ◽  
Asymmetry Factor ◽  
Surface Reflectance ◽  
Deep Blue ◽  
Aerosol Type

Abstract. A novel approach for the joint retrieval of aerosol optical depth (AOD) and surface reflectance, using Meteosat Second Generation – Spinning Enhanced Visible and Infrared Imagers (MSG/SEVIRI) observations in two solar channels, is presented. The retrieval is based on a time series (TS) technique, which makes use of the two visible bands at 0.6 μm and 0.8 μm in three orderly scan times (15 min interval between two scans) to retrieve the AOD over land. Using the radiative transfer equation for plane-parallel atmospheres two coupled differential equations for the upward and downward fluxes are derived. The boundary conditions for the upward and downward fluxes at the top and at the bottom of the atmosphere are used in these equations to provide an analytic solution for the surface reflectance. To derive these fluxes, the aerosol single scattering albedo (SSA) and asymmetry factor are required to provide a solution. These are provided from a set of six pre-defined aerosol types with the SSA and asymmetry factor (g). We assume one aerosol type for a grid of 1° × 1° and the surface reflectance changes little between two consequent scans. A k approximation was used in the inversion to find the best solution of atmospheric properties and surface reflectance. The algorithm makes use of numerical minimisation routines to obtain the optimal solution of atmospheric properties and surface reflectance by selection of the most suitable aerosol type from pre-defined sets. Also, it is assumed that the surface reflectance is little influenced by aerosol scattering at 1.6 μm and therefore the ratio of surface reflectances in the solar band for two consequent scans can be well-approximated by the ratio of the reflectances at 1.6 μm. A further assumption is that the surface reflectance varies only slightly over a period of 30 min. A detailed analysis of the retrieval results show that it is suitable for AOD retrieval over land. Six Aerosol Robotic Network (AERONET) sites with different surface types were used for detailed analysis and 42 other AERONET sites were used for validation. From 445 collocations representing stable and homogeneous aerosol type, we found that >75% of MSG-retrieved AOD values compared to AERONET observed values with an error envelope of ±0.05 ± 0.15τ and a high correlation (R > 0.86). The AOD datasets derived using the TS method with SEVIRI data was also compared with collocated AOD products derived from the NASA TERRA and AQUA MODIS data using the dark dense vegetation (DDV) method and the Deep Blue algorithms. Using the TS method, AOD could be retrieved for more pixels than with the NASA Deep Blue algorithm. The AOD values derived compare favourably.

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