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 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 Different strategies to retrieve aerosol properties at night-time with the GRASP algorithm

2019 ◽  
Vol 19 (22) ◽  
pp. 14149-14171 ◽  
Author(s):  
Jose Antonio Benavent-Oltra ◽  
Roberto Román ◽  
Juan Andrés Casquero-Vera ◽  
Daniel Pérez-Ramírez ◽  
Hassan Lyamani ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Sierra Nevada ◽  
Volume Concentration ◽  
In Situ Measurements ◽  
Saharan Dust ◽  
Scattering Coefficient ◽  
Night Time ◽  
Aerosol Properties

Abstract. This study evaluates the potential of the GRASP algorithm (Generalized Retrieval of Aerosol and Surface Properties) to retrieve continuous day-to-night aerosol properties, both column-integrated and vertically resolved. The study is focused on the evaluation of GRASP retrievals during an intense Saharan dust event that occurred during the Sierra Nevada Lidar aerOsol Profiling Experiment I (SLOPE I) field campaign. For daytime aerosol retrievals, we combined the measurements of the ground-based lidar from EARLINET (European Aerosol Research Lidar Network) station and sun–sky photometer from AERONET (Aerosol Robotic Network), both instruments co-located in Granada (Spain). However, for night-time retrievals three different combinations of active and passive remote-sensing measurements are proposed. The first scheme (N0) uses lidar night-time measurements in combination with the interpolation of sun–sky daytime measurements. The other two schemes combine lidar night-time measurements with night-time aerosol optical depth obtained by lunar photometry either using intensive properties of the aerosol retrieved during sun–sky daytime measurements (N1) or using the Moon aureole radiance obtained by sky camera images (N2). Evaluations of the columnar aerosol properties retrieved by GRASP are done versus standard AERONET retrievals. The coherence of day-to-night evolutions of the different aerosol properties retrieved by GRASP is also studied. The extinction coefficient vertical profiles retrieved by GRASP are compared with the profiles calculated by the Raman technique at night-time with differences below 30 % for all schemes at 355, 532 and 1064 nm. Finally, the volume concentration and scattering coefficient retrieved by GRASP at 2500 m a.s.l. are evaluated by in situ measurements at this height at Sierra Nevada Station. The differences between GRASP and in situ measurements are similar for the different schemes, with differences below 30 % for both volume concentration and scattering coefficient. In general, for the scattering coefficient, the GRASP N0 and N1 show better results than the GRASP N2 schemes, while for volume concentration, GRASP N2 shows the lowest differences against in situ measurements (around 10 %) for high aerosol optical depth values.

Towards the removal of model bias from ESA CCI SM by using an L-band scaling reference

2021 ◽  
Author(s):  
Rémi Madelon ◽  
Nemesio Rodriguez-Fernandez ◽  
Robin Van Der Shalie ◽  
Yann Kerr ◽  
Tracy Scalon ◽  
...  
Keyword(s):  
Time Series ◽  
Soil Moisture ◽  
Climate Models ◽  
In Situ Measurements ◽  
Time Data ◽  
Data Set ◽  
Spatial Coverage ◽  
L Band ◽  
Better Than

<p>Merging data from different instruments is required to construct long time data records of soil moisture (SM). This is the goal of projects such as the ESA Climate Change Initiative (CCI) for SM (Gruber et al., 2019), which uses both active and passive microwave sensors. Currently, the GLDAS v2.1 model is used as reference to re-scale active and passive time series by matching their Cumulative Density Function (CDF) to that of the model. Removing the dependency on models is important, in particular for data assimilation applications into hydrological or climate models, and it has been proposed (Van der Schalie et al., 2018) to use L-band data from one of the two instruments specifically designed to measure SM, ESA Soil Moisture and Ocean Salinity (SMOS) and NASA Soil Moisture Active Passive (SMAP) satellites, as reference to re-scale other time series.<br>To investigate this approach, AMSR-2 SM time series obtained from C1-, C2- and X-band observations using LPRM (Land Parameter Retrieval Model) were re-scaled by CDF-matching (Brocca et al., 2011) using different SMAP and SMOS official (SMAP L2 V005, SMOS L3 V300, SMOS NRT V100&V200) and research (SMOS IC V103) SM products as well as the SMAP and SMOS LPRM v6 SM data used by the ESA CCI. The time series re-scaled using L-band remote sensing data were compared to those re-scaled using GLDAS and were evaluated against in situ measurements at several hundred sites retrieved from the International Soil Moisture Network (Dorigo et al., 2011). The results were analyzed as a function of the land cover class and the Koppen-Geiger climate classification.<br>Overall, AMSR-2 time series re-scaled using SMAP L2, SMAP LPRM and SMOS IC data sets as reference gave the best correlations with respect to in situ measurements, similar to those obtained by the time series re-scaled using GLDAS and slightly better than those of the original AMSR-2 time series. These results imply that different SMAP and SMOS products could actually be used to replace GLDAS as reference for the re-scaling of other sensors time series within the ESA CCI. However, one must bear in mind that this study is limited to the re-scaling of AMSR-2 data at a few hundred sites.<br>For a more detailed assessment of the L-band data set to be used for a global re-scaling, it is necessary to investigate other effects such as the spatial coverage or the time series length. SMAP spatial coverage is better than that of SMOS in regions affected by radio frequency interference. In contrast, the length of SMAP time series can be too short to capture the long term SM variability for climate applications in some regions. The CDF of SMOS time series computed from the date of SMAP launch is significantly different to those of the full length SMOS time series in some regions of the Globe. Possible ways of using a coherent SMAP/SMOS L-band data set will be discussed.</p>

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 Aerosol data assimilation in the chemical-transport model MOCAGE during the TRAQA/ChArMEx campaign: Aerosol optical depth

2016 ◽  
Author(s):  
Bojan Sič ◽  
Laaziz El Amraoui ◽  
Andrea Piacentini ◽  
Virginie Marécal ◽  
Emanuele Emili ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Vertical Profile ◽  
Transport Model ◽  
Control Variable ◽  
Concentration Data ◽  
Validation Data ◽  
Data Set ◽  
Direct Model

Abstract. In this study, we describe the development of the aerosol optical depth (AOD) assimilation module in the chemistry-transport model (CTM) MOCAGE (Modèle de Chimie Atmosphérique à Grande Echelle). Our goal is to assimilate the 2D column AOD data from the National Aeronautics and Space Administration (NASA) Moderate-resolution Imaging Spectroradiometer (MODIS) instrument and to estimate improvements in a 3D CTM assimilation run compared to a direct model run. Our assimilation system uses 3D-FGAT (First Guess at Appropriate Time) as an assimilation method and the total 3D aerosol concentration as a control variable. In order to have an extensive validation data set, we set our experiment in the northern summer of 2012 when the pre-ChArMEx (CHemistry and AeRosol MEditerranean EXperiment) field campaign TRAQA (TRAnsport à longue distance et Qualité de l’Air dans le bassin méditerranéen) took place in the western Mediterranean basin. The assimilated model run is evaluated independently against a range of aerosol properties (2D and 3D) measured by in-situ instruments (the TRAQA size-resolved balloon and aircraft measurements), the satellite Spinning Enhanced Visible and InfraRed Imager (SEVIRI) instrument and ground-based instruments from the Aerosol Robotic Network (AERONET) network. The evaluation demonstrates that the AOD assimilation greatly improves aerosol representation in the model. For example, the comparison of the direct and the assimilated model run with AERONET data shows that the assimilation reduced the bias in the AOD (from 0.050 to 0.006) and increased the correlation (from 0.74 to 0.88). When compared to the 3D concentration data obtained by the in-situ aircraft and balloon measurements, the assimilation consistently improves the model output. The best results as expected occur when the shape of the vertical profile is correctly simulated by the direct model. We also examine how the assimilation can influence the modelled aerosol vertical distribution. The results show that a 2D continuous AOD assimilation can improve the 3D vertical profile, as a result of differential horizontal transport of aerosols in the model.

scholarly journals HIGH RESOLUTION AEROSOL OPTICAL DEPTH MAPPING OF BEIJING USING LANSAT8 IMAGERY

2016 ◽  
Vol XLI-B8 ◽  
pp. 1309-1312
Author(s):  
Yan Li ◽  
Yuanliang Liu ◽  
Jianliang Wu
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Urban Areas ◽  
Surface Albedo ◽  
Atmospheric Correction ◽  
Solar Spectrum ◽  
Temporal Data ◽  
A Value ◽  
Innovative Method ◽  
Satellite Signal

Aerosol Optical Depth (AOD) is one of the most important parameters in the atmospheric correction of remote sensing images. We present a new method of per pixel AOD retrieval using the imagery of Landsat8. It is based on Second Simulation of the Satellite Signal in the Solar Spectrum (6S). General dark target method takes dense vegetation pixels as dark targets and derives their 550nm AODs directly from the LUT, and interpolates the AODs of other pixels according to spatial neighbourhood using those of dark target pixels. This method will down estimate the AOD levels for urban areas. We propose an innovative method to retrieval the AODs using multiple temporal data. For a pixel which has nothing change between the associated time, there must exists an intersection of surface albedo. When there are enough data to find the intersection it ought to be a value that meet the error tolerance. In this paper, we present an example of using three temporal Landsat ETM+ image to retrieve AOD taking Beijing as the testing area. The result is compared to the commonly employed dark target algorithm to show the effectiveness of the methods.

scholarly journals Above-aircraft cirrus cloud and aerosol optical depth from hyperspectral irradiances measured by a total-diffuse radiometer

2021 ◽  
Author(s):  
Matthew S. Norgren ◽  
John Wood ◽  
K. Sebastian Schmidt ◽  
Bastiaan van Diedenhoven ◽  
Snorre A. Stamnes ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Low Cost ◽  
In Situ Measurements ◽  
Cirrus Cloud ◽  
Optical Extinction ◽  
Direct Beam ◽  
Diffuse Irradiance ◽  
Sun Photometer

Abstract. This study develops the use of spectral total and diffuse irradiance measurements, made from a prototype hyperspectral total-diffuse Sunshine Pyranometer (SPN-S), to retrieve layer fine-mode aerosol (τaer) and total optical depths from airborne platforms. Additionally, we use spectral analysis in an attempt to partition the total optical depth it into its τaer and cirrus cloud optical depth (τcld) components in the absence of coarse-mode aerosols. Two retrieval methods are developed: one leveraging information in the diffuse irradiance, and the other using spectral characteristics of the transmitted direct beam, with each approach best suited for specific cloud and aerosol conditions. SPN-S has advantages over traditional sun-photometer systems including no moving parts and a low cost. However, a significant drawback of the instrument is that it is unable to measure the direct beam irradiance as accurately as sun-photometers. To compensate for the greater measurement uncertainty of the radiometric irradiances these retrieval techniques employ ratioed inputs or spectral information to reduce output uncertainty. This analysis uses irradiance measurements from SPN-S and the Solar Spectral Flux Radiometer (SSFR) aboard the National Aeronautics and Space Administration’s (NASA) P-3 aircraft during the 2018 deployment of the ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) campaign and the 2019 Cloud, Aerosol and Monsoon Processes Philippines Experiment (CAMP2Ex) mission to quantify above-aircraft cirrus τcld and derive vertical profiles of layer τaer. Validation of the τaer retrieval is accomplished by comparison with collocated measurements of direct solar irradiance made by the Sky-Scanning Sun-Tracking Atmospheric Research (4STAR) and in situ measurements of aerosol optical depth. For the aggregated 2018 ORACLES results, regression between the SPN-S based method and sun-photometer τaer values yield a slope of 0.96 with an R2 of 0.96, while the root-mean-square error (RMSE) is 3.0 × 10−2. When comparing the retrieved τaer to profiles of integrated in situ measurements of optical extinction, the slope, R2, and RMSE values for ORACLES are 0.90, 0.96, 3.4 × 10−2, and for CAMP2Ex are 0.94, 0.97, 3.4 × 10−2 respectively. This paper is a demonstration of methods for deriving cloud and aerosol optical properties in environments where both atmospheric constituents may be present. With improvements to the low-cost SPN-S radiometer instrument, it may be possible to extend these methods to a broader set of sampling applications, such as ground-based settings.

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 HIGH RESOLUTION AEROSOL OPTICAL DEPTH MAPPING OF BEIJING USING LANSAT8 IMAGERY

2016 ◽  
Vol XLI-B8 ◽  
pp. 1309-1312
Author(s):  
Yan Li ◽  
Yuanliang Liu ◽  
Jianliang Wu
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Urban Areas ◽  
Surface Albedo ◽  
Atmospheric Correction ◽  
Solar Spectrum ◽  
Temporal Data ◽  
A Value ◽  
Innovative Method ◽  
Satellite Signal

Aerosol Optical Depth (AOD) is one of the most important parameters in the atmospheric correction of remote sensing images. We present a new method of per pixel AOD retrieval using the imagery of Landsat8. It is based on Second Simulation of the Satellite Signal in the Solar Spectrum (6S). General dark target method takes dense vegetation pixels as dark targets and derives their 550nm AODs directly from the LUT, and interpolates the AODs of other pixels according to spatial neighbourhood using those of dark target pixels. This method will down estimate the AOD levels for urban areas. We propose an innovative method to retrieval the AODs using multiple temporal data. For a pixel which has nothing change between the associated time, there must exists an intersection of surface albedo. When there are enough data to find the intersection it ought to be a value that meet the error tolerance. In this paper, we present an example of using three temporal Landsat ETM+ image to retrieve AOD taking Beijing as the testing area. The result is compared to the commonly employed dark target algorithm to show the effectiveness of the methods.

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