scholarly journals The Climatology of Australian Aerosol

2017 ◽  
Author(s):  
Ross M. Mitchell ◽  
Bruce W. Forgan ◽  
Susan K. Campbell
Keyword(s):  
Time Series ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Biomass Burning ◽  
Atmospheric Correction ◽  
Periodic Component ◽  
Spectral Variation ◽  
Anthropogenic Aerosols ◽  
Continental Scale ◽  
Periodic Components

Abstract. Airborne particles or aerosols have long been recognized for their major contribution to uncertainty in climate change. In addition, aerosol amounts must be known for accurate atmospheric correction of remotely sensed images, and are required to accurately gauge the available solar resource. However, despite great advances in surface networks and satellite retrievals over recent years, long-term continental-scale aerosol data sets are lacking. Here we present an aerosol assessment over Australia based on combined sun photometer measurements from the Bureau of Meteorology Radiation Network and CSIRO/AeroSpan. The measurements are continental in coverage, comprising 22 stations, and generally decadal in time-scale, totalling 207 station-years. Spectral decomposition shows that the time series can be represented as a weighted sum of sinusoids with periods of 12, 6 and 4 months, corresponding to the annual cycle and its second and third harmonics. Their relative amplitudes and phase relationships leads to sawtooth-like waveforms sharply rising to an austral spring peak, with a slower decline often including a secondary peak during the summer. The amplitude and phase of these periodic components show significant regional change across the continent. Fits based on this harmonic analysis are used to separate the periodic and episodic components of the aerosol time series. Classification of the aerosol types is undertaken based on (a) the spectral variation of the optical depth expressed in the Ångström exponent, (b) the Fourier decomposition, and (c) the ratio of episodic to periodic variation in aerosol optical depth. It is shown that Australian aerosol can be broadly grouped into three classes: Temperate, Arid, and Tropical. The Temperate class is characterised by a small amplitude periodic component, with an increasing episodic component toward the fire-prone Eucalypt forests of the south-east. Arid zone aerosol has a larger periodic component, with pronounced twin spring-summer peaks, and an increasing episodic component towards active dust source regions. Tropical aerosol is characterised by a very large periodic component due to seasonal biomass burning in the savanna belt, with significant interannual variability due to variation in the strength of the monsoon and its effect on the fuel source. Statistically significant decadal trends are found at 4 of the 22 stations. Despite the apparently small associated declining trends in mid-visible aerosol optical depth of between 0.001 to 0.002 per year, these trends are much larger than those projected to occur due to declining emissions of anthropogenic aerosols from the northern hemisphere. There is remarkable long-range coherence in the aerosol cycle across the continent, suggesting broadly similar source characteristics, including a possible role for inter-continental transport of biomass burning aerosol.

scholarly journals The Climatology of Australian Aerosol

2017 ◽  
Vol 17 (8) ◽  
pp. 5131-5154 ◽  
Author(s):  
Ross M. Mitchell ◽  
Bruce W. Forgan ◽  
Susan K. Campbell
Keyword(s):  
Time Series ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Atmospheric Correction ◽  
Periodic Variation ◽  
Anthropogenic Aerosols ◽  
Austral Spring ◽  
Continental Scale ◽  
Intercontinental Transport ◽  
Periodic Components

Abstract. Airborne particles or aerosols have long been recognised for their major contribution to uncertainty in climate change. In addition, aerosol amounts must be known for accurate atmospheric correction of remotely sensed images, and are required to accurately gauge the available solar resource. However, despite great advances in surface networks and satellite retrievals over recent years, long-term continental-scale aerosol data sets are lacking. Here we present an aerosol assessment over Australia based on combined sun photometer measurements from the Bureau of Meteorology Radiation Network and CSIRO/AeroSpan. The measurements are continental in coverage, comprising 22 stations, and generally decadal in timescale, totalling 207 station-years. Monthly climatologies are given at all stations. Spectral decomposition shows that the time series can be represented as a weighted sum of sinusoids with periods of 12, 6 and 4 months, corresponding to the annual cycle and its second and third harmonics. Their relative amplitudes and phase relationships lead to sawtooth-like waveforms sharply rising to an austral spring peak, with a slower decline often including a secondary peak during the summer. The amplitude and phase of these periodic components show significant regional change across the continent. Fits based on this harmonic analysis are used to separate the periodic and episodic components of the aerosol time series. An exploratory classification of the aerosol types is undertaken based on (a) the relative periodic amplitudes of the Ångström exponent and aerosol optical depth, (b) the relative amplitudes of the 6- and 4-month harmonic components of the aerosol optical depth, and (c) the ratio of episodic to periodic variation in aerosol optical depth. It is shown that Australian aerosol can be broadly grouped into three classes: tropical, arid and temperate. Statistically significant decadal trends are found at 4 of the 22 stations. Despite the apparently small associated declining trends in mid-visible aerosol optical depth of between 0.001 and 0.002 per year, these trends are much larger than those projected to occur due to declining emissions of anthropogenic aerosols from the Northern Hemisphere. There is remarkable long-range coherence in the aerosol cycle across the continent, suggesting broadly similar source characteristics, including a possible role for intercontinental transport of biomass burning aerosol.

scholarly journals The Aerosol Index and Land Cover Class Based Atmospheric Correction Aerosol Optical Depth Time Series 1982–2014 for the SMAC Algorithm

2017 ◽  
Vol 9 (11) ◽  
pp. 1095 ◽  
Author(s):  
Emmihenna Jääskeläinen ◽  
Terhikki Manninen ◽  
Johanna Tamminen ◽  
Marko Laine
Keyword(s):  
Time Series ◽  
Land Cover ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Atmospheric Correction ◽  
Land Cover Class ◽  
Cover Class ◽  
Aerosol Index

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.

scholarly journals Using the OMI aerosol index and absorption aerosol optical depth to evaluate the NASA MERRA Aerosol Reanalysis

2015 ◽  
Vol 15 (10) ◽  
pp. 5743-5760 ◽  
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 southern 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.

scholarly journals An Aerosol Optical Depth time series 1982–2014 for atmospheric correction based on OMI and TOMS Aerosol Index

2016 ◽  
Author(s):  
Emmihenna Jääskeläinen ◽  
Terhikki Manninen ◽  
Johanna Tamminen ◽  
Marko Laine
Keyword(s):  
Time Series ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Surface Albedo ◽  
Atmospheric Correction ◽  
In Situ Measurements ◽  
Ozone Monitoring Instrument ◽  
Data Set ◽  
Aerosol Index

Abstract. The atmospheric correction of old optical satellite data is problematic, because corresponding Aerosol Optical Depth (AOD) measurements in the visible wavelength range do not exist. The construction of an AOD time series for atmospheric correction purposes to cover the period 1982–2014 is described in this paper. The AOD estimates are calculated from the Aerosol Index (AI) data from the Total Ozone Mapping Spectrometer (TOMS) and the Ozone Monitoring Instrument (OMI). We apply this time series to the generation of the surface albedo data set CLARA-A2-SAL (the Surface ALbedo from the CM SAF cLoud, Albedo and RAdiation data set, the second version). The constructed AOD time series is temporally homogeneous, and it has sufficient quality compared to the AOD from OMI observations and from in situ measurements. The simulated atmospheric correction calculations, where the constructed AOD data are used as an aerosol input, are similar to the simulations where the aerosol information from OMI and in situ measurements is used. Also, the simulations show that the use of the constructed AOD time series decreases the surface reflectance values (the output of the atmospheric correction) globally compared to the use of the constant AOD value 0.1.

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.

Aerosol Optical Depth for Atmospheric Correction of AVHRR Composite Data

2000 ◽  
Vol 26 (4) ◽  
pp. 273-284 ◽  
Author(s):  
G. Fedosejevs ◽  
N.T. O'Neill ◽  
A. Royer ◽  
P.M. Teillet ◽  
A.I. Bokoye ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Atmospheric Correction ◽  
Composite Data

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 Retrieval of the Fine-Mode Aerosol Optical Depth over East China Using a Grouped Residual Error Sorting (GRES) Method from Multi-Angle and Polarized Satellite Data

2018 ◽  
Vol 10 (11) ◽  
pp. 1838 ◽  
Author(s):  
Yang Zhang ◽  
Zhengqiang Li ◽  
Zhihong Liu ◽  
Juan Zhang ◽  
Lili Qie ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Residual Error ◽  
East China ◽  
Anthropogenic Aerosols ◽  
Aerosol Model ◽  
Retrieval Accuracy ◽  
Aerosol Loading ◽  
Fine Mode ◽  
Fine Mode Aerosol

The fine-mode aerosol optical depth (AODf) is an important parameter for the environment and climate change study, which mainly represents the anthropogenic aerosols component. The Polarization and Anisotropy of Reflectances for Atmospheric Science coupled with Observations from a Lidar (PARASOL) instrument can detect polarized signal from multi-angle observation and the polarized signal mainly comes from the radiation contribution of the fine-mode aerosols, which provides an opportunity to obtain AODf directly. However, the currently operational algorithm of Laboratoire d’Optique Atmosphérique (LOA) has a poor AODf retrieval accuracy over East China on high aerosol loading days. This study focused on solving this issue and proposed a grouped residual error sorting (GRES) method to determine the optimal aerosol model in AODf retrieval using the traditional look-up table (LUT) approach and then the AODf retrieval accuracy over East China was improved. The comparisons between the GRES retrieved and the Aerosol Robotic Network (AERONET) ground-based AODf at Beijing, Xianghe, Taihu and Hong_Kong_PolyU sites produced high correlation coefficients (r) of 0.900, 0.933, 0.957 and 0.968, respectively. The comparisons of the GRES retrieved AODf and PARASOL AODf product with those of the AERONET observations produced a mean absolute error (MAE) of 0.054 versus 0.104 on high aerosol loading days (AERONET mean AODf at 865 nm = 0.283). An application using the GRES method for total AOD (AODt) retrieval also showed a good expandability for multi-angle aerosol retrieval of this method.

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