scholarly journals Variations in optical properties of aerosols on monsoon seasonal change and estimation of aerosol optical depth using ground-based meteorological and air quality data

2014 ◽  
Vol 14 (13) ◽  
pp. 19747-19789
Author(s):  
F. Tan ◽  
H. S. Lim ◽  
K. Abdullah ◽  
T. L. Yoon ◽  
B. Holben
Keyword(s):  
Optical Properties ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Statistical Tests ◽  
Air Pollutant ◽  
Quality Data ◽  
Supplementary Information ◽  
Northeast Monsoon ◽  
Data Set ◽  
Proposed Model

Abstract. In this study, the optical properties of aerosols in Penang, Malaysia were analyzed for four monsoonal seasons (northeast monsoon, pre-monsoon, southwest monsoon, and post-monsoon) based on data from the AErosol RObotic NETwork (AERONET) from February 2012 to November 2013. The aerosol distribution patterns in Penang for each monsoonal period were quantitatively identified according to the scattering plots of the aerosol optical depth (AOD) against the Angstrom exponent. A modified algorithm based on the prototype model of Tan et al. (2014a) was proposed to predict the AOD data. Ground-based measurements (i.e., visibility and air pollutant index) were used in the model as predictor data to retrieve the missing AOD data from AERONET because of frequent cloud formation in the equatorial region. The model coefficients were determined through multiple regression analysis using selected data set from in situ data. The predicted AOD of the model was generated based on the coefficients and compared against the measured data through standard statistical tests. The predicted AOD in the proposed model yielded a coefficient of determination R2 of 0.68. The corresponding percent mean relative error was less than 0.33% compared with the real data. The results revealed that the proposed model efficiently predicted the AOD data. Validation tests were performed on the model against selected LIDAR data and yielded good correspondence. The predicted AOD can beneficially monitor short- and long-term AOD and provide supplementary information in atmospheric corrections.

scholarly journals Monsoonal variations in aerosol optical properties and estimation of aerosol optical depth using ground-based meteorological and air quality data in Peninsular Malaysia

2015 ◽  
Vol 15 (7) ◽  
pp. 3755-3771 ◽  
Author(s):  
F. Tan ◽  
H. S. Lim ◽  
K. Abdullah ◽  
T. L. Yoon ◽  
B. Holben
Keyword(s):  
Optical Properties ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Statistical Tests ◽  
Air Pollutant ◽  
Quality Data ◽  
Supplementary Information ◽  
Percentage Error ◽  
Northeast Monsoon ◽  
Data Set

Abstract. Obtaining continuous aerosol-optical-depth (AOD) measurements is a difficult task due to the cloud-cover problem. With the main motivation of overcoming this problem, an AOD-predicting model is proposed. In this study, the optical properties of aerosols in Penang, Malaysia were analyzed for four monsoonal seasons (northeast monsoon, pre-monsoon, southwest monsoon, and post-monsoon) based on data from the AErosol RObotic NETwork (AERONET) from February 2012 to November 2013. The aerosol distribution patterns in Penang for each monsoonal period were quantitatively identified according to the scattering plots of the Ångström exponent against the AOD. A new empirical algorithm was proposed to predict the AOD data. Ground-based measurements (i.e., visibility and air pollutant index) were used in the model as predictor data to retrieve the missing AOD data from AERONET due to frequent cloud formation in the equatorial region. The model coefficients were determined through multiple regression analysis using selected data set from in situ data. The calibrated model coefficients have a coefficient of determination, R2, of 0.72. The predicted AOD of the model was generated based on these calibrated coefficients and compared against the measured data through standard statistical tests, yielding a R2 of 0.68 as validation accuracy. The error in weighted mean absolute percentage error (wMAPE) was less than 0.40% compared with the real data. The results revealed that the proposed model efficiently predicted the AOD data. Performance of our model was compared against selected LIDAR data to yield good correspondence. The predicted AOD can enhance measured short- and long-term AOD and provide supplementary information for climatological studies and monitoring aerosol variation.

scholarly journals Recent trends in aerosol optical properties derived from AERONET measurements

2014 ◽  
Vol 14 (22) ◽  
pp. 12271-12289 ◽  
Author(s):  
J. Li ◽  
B. E. Carlson ◽  
O. Dubovik ◽  
A. A. Lacis
Keyword(s):  
Quality Control ◽  
Optical Properties ◽  
North America ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Statistical Tests ◽  
Aerosol Optical Properties ◽  
Angstrom Exponent ◽  
Ångström Exponent ◽  
Ångstrom Exponent

Abstract. The Aerosol Robotic Network (AERONET) has been providing high-quality retrievals of aerosol optical properties from the surface at worldwide locations for more than a decade. Many sites have continuous and consistent records for more than 10 years, which enables the investigation of long-term trends in aerosol properties at these locations. In this study, we present the results of a trend analysis at selected stations with long data records. In addition to commonly studied parameters such as aerosol optical depth (AOD) and Ångström exponent (AE), we also focus on inversion products including absorption aerosol optical depth (ABS), single-scattering albedo (SSA) and the absorption Ångström exponent (AAE). Level 2.0 quality assured data are the primary source. However, due to the scarcity of level 2.0 inversion products resulting from the strict AOD quality control threshold, we have also analyzed level 1.5 data, with some quality control screening to provide a reference for global results. Two statistical methods are used to detect and estimate the trend: the Mann–Kendall test associated with Sen's slope and linear least-squares fitting. The results of these statistical tests agree well in terms of the significance of the trend for the majority of the cases. The results indicate that Europe and North America experienced a uniform decrease in AOD, while significant (>90%) increases in these two parameters are found for North India and the Arabian Peninsula. The AE trends turn out to be different for North America and Europe, with increases for the former and decreases for the latter, suggesting opposite changes in fine/coarse-mode fraction. For level 2.0 inversion parameters, Beijing and Kanpur both experienced an increase in SSA. Beijing also shows a reduction in ABS, while the SSA increase for Kanpur is mainly due the increase in scattering aerosols. Increased absorption and reduced SSA are found at Solar_Village. At level 1.5, most European and North American sites also show positive SSA and negative ABS trends, although the data are more uncertain. The AAE trends are less spatially coherent due to large uncertainties, except for a robust increase at three sites in West Africa, which suggests a possible reduction in black carbon. Overall, the trends do not exhibit obvious seasonality for the majority of parameters and stations.

scholarly journals Using the OMI Aerosol Index and Absorption Aerosol Optical Depth to evaluate the NASA MERRA Aerosol Reanalysis

2014 ◽  
Vol 14 (23) ◽  
pp. 32177-32231 ◽  
Author(s):  
V. Buchard ◽  
A. M. da Silva ◽  
P. R. Colarco ◽  
A. Darmenov ◽  
C. A. Randles ◽  
...  
Keyword(s):  
Optical Properties ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Biomass Burning ◽  
Saharan Dust ◽  
Aerosol Layer ◽  
Anthropogenic Aerosols ◽  
Aerosol Absorption ◽  
Modis Aod ◽  
Aerosol Index

Abstract. A radiative transfer interface has been developed to simulate the UV Aerosol Index (AI) from the NASA Goddard Earth Observing System version 5 (GEOS-5) aerosol assimilated fields. The purpose of this work is to use the AI and Aerosol Absorption Optical Depth (AAOD) derived from the Ozone Monitoring Instrument (OMI) measurements as independent validation for the Modern Era Retrospective analysis for Research and Applications Aerosol Reanalysis (MERRAero). MERRAero is based on a version of the GEOS-5 model that is radiatively coupled to the Goddard Chemistry, Aerosol, Radiation, and Transport (GOCART) aerosol module and includes assimilation of Aerosol Optical Depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Since AI is dependent on aerosol concentration, optical properties and altitude of the aerosol layer, we make use of complementary observations to fully diagnose the model, including AOD from the Multi-angle Imaging SpectroRadiometer (MISR), aerosol retrievals from the Aerosol Robotic Network (AERONET) and attenuated backscatter coefficients from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) mission to ascertain potential misplacement of plume height by the model. By sampling dust, biomass burning and pollution events in 2007 we have compared model produced AI and AAOD with the corresponding OMI products, identifying regions where the model representation of absorbing aerosols was deficient. As a result of this study over the Saharan dust region, we have obtained a new set of dust aerosol optical properties that retains consistency with the MODIS AOD data that were assimilated, while resulting in better agreement with aerosol absorption measurements from OMI. The analysis conducted over the South African and South American biomass burning regions indicates that revising the spectrally-dependent aerosol absorption properties in the near-UV region improves the modeled-observed AI comparisons. Finally, during a period where the Asian region was mainly dominated by anthropogenic aerosols, we have performed a qualitative analysis in which the specification of anthropogenic emissions in GEOS-5 is adjusted to provide insight into discrepancies observed in AI comparisons.

Relationship between MODIS based Aerosol Optical Depth and PM10 over Croatia

2014 ◽  
Vol 6 (1) ◽  
Author(s):  
Sanja Grgurić ◽  
Josip Križan ◽  
Goran Gašparac ◽  
Oleg Antonić ◽  
Zdravko Špirić ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Mass Concentration ◽  
Meteorological Data ◽  
Neural Network Approach ◽  
Data Set ◽  
Independent Variables ◽  
Data Variability ◽  
Modis Aod ◽  
The Relationship

AbstractThis study analyzes the relationship between Aerosol Optical Depth (AOD) obtained from Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and ground-based PM10 mass concentration distribution over a period of 5 years (2008–2012), and investigates the applicability of satellite AOD data for ground PM10 mapping for the Croatian territory. Many studies have shown that satellite AOD data are correlated to ground-based PM mass concentration. However, the relationship between AOD and PM is not explicit and there are unknowns that cause uncertainties in this relationship.The relationship between MODIS AOD and ground-based PM10 has been studied on the basis of a large data set where daily averaged PM10 data from the 12 air quality stations across Croatia over the 5 year period are correlated with AODs retrieved from MODIS Terra and Aqua. A database was developed to associate coincident MODIS AOD (independent) and PM10 data (dependent variable). Additional tested independent variables (predictors, estimators) included season, cloud fraction, and meteorological parameters — including temperature, air pressure, relative humidity, wind speed, wind direction, as well as planetary boundary layer height — using meteorological data from WRF (Weather Research and Forecast) model.It has been found that 1) a univariate linear regression model fails at explaining the data variability well which suggests nonlinearity of the AOD-PM10 relationship, and 2) explanation of data variability can be improved with multivariate linear modeling and a neural network approach, using additional independent variables.

scholarly journals Measurement of aerosol optical depth and sub-visual cloud detection using the optical depth sensor (ODS)

2016 ◽  
Vol 9 (2) ◽  
pp. 455-467 ◽  
Author(s):  
D. Toledo ◽  
P. Rannou ◽  
J.-P. Pommereau ◽  
A. Sarkissian ◽  
T. Foujols
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Diffuse Radiation ◽  
Dust Storms ◽  
Saharan Dust ◽  
Cloud Detection ◽  
Depth Sensor ◽  
Data Set ◽  
Good Agreement

Abstract. A small and sophisticated optical depth sensor (ODS) has been designed to work in the atmosphere of Mars. The instrument measures alternatively the diffuse radiation from the sky and the attenuated direct radiation from the Sun on the surface. The principal goals of ODS are to retrieve the daily mean aerosol optical depth (AOD) and to detect very high and optically thin clouds, crucial parameters in understanding the Martian meteorology and climatology. The detection of clouds is undertaken at twilight, allowing the detection and characterization of clouds with opacities below 0.03 (sub-visual clouds). In addition, ODS is capable to retrieve the aerosol optical depth during nighttime from moonlight measurements. Recently, ODS has been selected at the METEO meteorological station on board the ExoMars 2018 Lander. In order to study the performance of ODS under Mars-like conditions as well as to evaluate the retrieval algorithms for terrestrial measurements, ODS was deployed in Ouagadougou (Africa) between November 2004 and October 2005, a Sahelian region characterized by its high dust aerosol load and the frequent occurrence of Saharan dust storms. The daily average AOD values retrieved by ODS were compared with those provided by a CIMEL sunphotometer of the AERONET (Aerosol Robotic NETwork) network localized at the same location. Results represent a good agreement between both ground-based instruments, with a correlation coefficient of 0.77 for the whole data set and 0.94 considering only the cloud-free days. From the whole data set, a total of 71 sub-visual cirrus (SVC) were detected at twilight with opacities as thin as 1.10−3 and with a maximum of occurrence at altitudes between 14 and 20 km. Although further optimizations and comparisons of ODS terrestrial measurements are required, results indicate the potential of these measurements to retrieve the AOD and detect sub-visual clouds.

scholarly journals Ground Reflectance Retrieval on Horizontal and Inclined Terrains Using the Software Package REFLECT

2018 ◽  
Vol 10 (10) ◽  
pp. 1638
Author(s):  
Yacine Bouroubi ◽  
Wided Batita ◽  
François Cavayas ◽  
Nicolas Tremblay
Keyword(s):  
Optical Properties ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Software Package ◽  
Near Infrared ◽  
Solar Spectrum ◽  
Sensor Calibration ◽  
Topographic Effects ◽  
Atmospheric Conditions ◽  
Spectral Bands

This paper presents the software package REFLECT for the retrieval of ground reflectance from high and very-high resolution multispectral satellite images. The computation of atmospheric parameters is based on the 6S (Second Simulation of the Satellite Signal in the Solar Spectrum) routines. Aerosol optical properties are calculated using the OPAC (Optical Properties of Aerosols and Clouds) model, while aerosol optical depth is estimated using the dark target method. A new approach is proposed for adjacency effect correction. Topographic effects were also taken into account, and a new model was developed for forest canopies. Validation has shown that ground reflectance estimation with REFLECT is performed with an accuracy of approximately ±0.01 in reflectance units (for the visible, near-infrared, and mid-infrared spectral bands), even for surfaces with varying topography. The validation of the software was performed through many tests. These tests involve the correction of the effects that are associated with sensor calibration, irradiance, and viewing conditions, atmospheric conditions (aerosol optical depth AOD and water vapour), adjacency, and topographic conditions.

scholarly journals Simultaneous retrieval of aerosol and cloud properties during the MILAGRO field campaign

2011 ◽  
Vol 11 (13) ◽  
pp. 6245-6263 ◽  
Author(s):  
K. Knobelspiesse ◽  
B. Cairns ◽  
J. Redemann ◽  
R. W. Bergstrom ◽  
A. Stohl
Keyword(s):  
Optical Properties ◽  
Size Distribution ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Droplet Size ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Cloud Droplet Size Distribution ◽  
Distribution Parameters ◽  
Aerosol Properties

Abstract. Estimation of Direct Climate Forcing (DCF) due to aerosols in cloudy areas has historically been a difficult task, mainly because of a lack of appropriate measurements. Recently, passive remote sensing instruments have been developed that have the potential to retrieve both cloud and aerosol properties using polarimetric, multiple view angle, and multi spectral observations, and therefore determine DCF from aerosols above clouds. One such instrument is the Research Scanning Polarimeter (RSP), an airborne prototype of a sensor on the NASA Glory satellite, which unfortunately failed to reach orbit during its launch in March of 2011. In the spring of 2006, the RSP was deployed on an aircraft based in Veracruz, Mexico, as part of the Megacity Initiative: Local and Global Research Observations (MILAGRO) field campaign. On 13 March, the RSP over flew an aerosol layer lofted above a low altitude marine stratocumulus cloud close to shore in the Gulf of Mexico. We investigate the feasibility of retrieving aerosol properties over clouds using these data. Our approach is to first determine cloud droplet size distribution using the angular location of the cloud bow and other features in the polarized reflectance. The selected cloud was then used in a multiple scattering radiative transfer model optimization to determine the aerosol optical properties and fine tune the cloud size distribution. In this scene, we were able to retrieve aerosol optical depth, the fine mode aerosol size distribution parameters and the cloud droplet size distribution parameters to a degree of accuracy required for climate modeling. This required assumptions about the aerosol vertical distribution and the optical properties of the coarse aerosol size mode. A sensitivity study was also performed to place this study in the context of future systematic scanning polarimeter observations, which found that the aerosol complex refractive index can also be observed accurately if the aerosol optical depth is larger than roughly 0.8 at a wavelength of (0.555 μm).

scholarly journals Comparison of MODIS 3 km and 10 km resolution aerosol optical depth retrievals over land with airborne sunphotometer measurements during ARCTAS summer 2008

2014 ◽  
Vol 14 (4) ◽  
pp. 2015-2038 ◽  
Author(s):  
J. M. Livingston ◽  
J. Redemann ◽  
Y. Shinozuka ◽  
R. Johnson ◽  
P. B. Russell ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Retrieval Algorithm ◽  
Grid Cells ◽  
Data Set ◽  
Clear Sky ◽  
Modis Aod ◽  
Research Aircraft ◽  
Bright Surface ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. Airborne sunphotometer measurements acquired by the NASA Ames Airborne Tracking Sunphotometer (AATS-14) aboard the NASA P-3 research aircraft are used to evaluate dark-target over-land retrievals of extinction aerosol optical depth (AOD) from spatially and temporally near-coincident measurements by the Moderate Resolution Imaging Spectroradiometer (MODIS) during the summer 2008 Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) field campaign. The new MODIS Collection 6 aerosol data set includes retrievals of AOD at both 10 km × 10 km and 3 km × 3 km (at nadir) resolution. In this paper we compare MODIS and AATS AOD at 553 nm in 58 10 km and 134 3 km retrieval grid cells. These AOD values were derived from data collected over Canada on four days during short time segments of five (four Aqua and one Terra) satellite overpasses of the P-3 during low-altitude P-3 flight tracks. Three of the five MODIS–AATS coincidence events were dominated by smoke: one included a P-3 transect of a well-defined smoke plume in clear sky, but two were confounded by the presence of scattered clouds above smoke. The clouds limited the number of MODIS retrievals available for comparison, and led to MODIS AOD retrievals that underestimated the corresponding AATS values. This happened because the MODIS aerosol cloud mask selectively removed 0.5 km pixels containing smoke and clouds before the aerosol retrieval. The other two coincidences (one Terra and one Aqua) occurred during one P-3 flight on the same day and in the same general area, in an atmosphere characterized by a relatively low AOD (< 0.3), spatially homogeneous regional haze from smoke outflow with no distinguishable plume. For the ensemble data set for MODIS AOD retrievals with the highest-quality flag, MODIS AOD agrees with AATS AOD within the expected MODIS over-land AOD uncertainty in 60% of the retrieval grid cells at 10 km resolution and 69% at 3 km resolution. These values improve to 65 % and 74%, respectively, when the cloud-affected case with the strongest plume is excluded. We find that the standard MODIS dark-target over-land retrieval algorithm fails to retrieve AOD for thick smoke, not only in cloud-contaminated regions but also in clear sky. We attribute this to deselection, by the cloud and/or bright surface masks, of 0.5 km resolution pixels that contain smoke.

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