Distribution Of Aerosol Optical Thickness Research Articles

Retrieval of Aerosol Optical Thickness with Custom Aerosol Model Using SKYNET Data over the Chiba Area

The retrieval of the aerosol optical thickness (AOT) from remotely-sensed data relies on the adopted aerosol model. However, the method of this technique has been rather limited because of the high variability of the surface albedo, in addition to the spatial variability in the aerosol properties over the land surfaces. To overcome unsolved problems, we proposed a method for the visibility-derived AOT estimation from SKYNET-based measurement and daytime satellite images with a custom aerosol model over the Chiba area (35.62° N, 140.10° E), which is located in the greater Tokyo metropolitan area in Japan. Different from conventionally-used aerosol models for the boundary layer, we created a custom aerosol model by using sky-radiometer observation data of aerosol volume size distribution and refractive indices, coupled with spectral response functions (SPFs) of satellite visible bands to alleviate the wide range of path-scattered radiance. We utilized the radiative transfer code 6S to implement the radiative transfer calculation based on the created custom aerosol model. The concurrent data from ground-based measurement are used in the radiative analysis, namely the temporal variation of AOT from SKYNET. The radiative estimation conducted under clear-sky conditions with minimum aerosol loading is used for the determination of the surface albedo, so that the 6S simulation yields a well-defined relation between total radiance and surface albedo. We made look-up tables (LUTs) pixel-by-pixel over the Chiba area for the custom aerosol model to retrieve the satellite AOT distribution based on the surface albedo. Therefore, such a reference of surface albedo generated from clear-sky conditions, in turn, can be employed to retrieve the spatial distribution of AOT on both clear and relatively turbid days. The value for the AOTs retrieved using the custom aerosol model is found to be stable than conventionally-used typical aerosol models, indicating that our method yields substantially better performance.

Retrieval of aerosol optical thickness and surface parameters based on multi-spectral and multi-viewing space-borne measurements

We present a novel approach to derive Aerosol Optical Thickness (AOT) at 0.5 µm and the surface reflectance for five spectral channels at native spatial resolution from the measurements of the Polarization and Directionality of Earth’s Reflectances-3 (POLDER) instrument aboard the Polarization & Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar (PARASOL) satellite. POLDER had multi-spectral and multi-viewing capabilities. This publication describes the first step in the design of a high-quality AOT and surface property retrieval algorithm, enabling the global evaluation of future missions providing multi-spectral and multi-viewing space-borne measurements. The developed retrieval approach is based on the radiative transfer and retrieval model SCIATRAN using an analytical linearized retrieval mode. The surface is parametrized according to the Ross-Li model and the aerosol typing was using prescribed types based on the approach by Levy et al. [26]. The minimization using SCIATRAN has been done by solving the quadratic programming problem which minimizes the considered system of equations (typically) based on linear constraints. In this study we constrained the retrieval so far only by assuming that the retrieved AOT at 0.5 µm is larger than 0.01 and smaller than 1.5. Until now, the retrieval is based only upon unpolarized POLDER data and shows promisingly weak dependence on a priori information.As a first validation, the retrieved AOT values have been compared with ground based measurements over Atmospheric Radiation Measurement Climate Research Facilities (ARM) in the Southern Great Plains (SGP). The SCIATRAN retrievals are mostly homogeneous and consistent in the region around the US ARM/SGP measurement stations. The retrieval results agree well with the ARM ground based measurements of AOT. The correlation coefficient was R=0.84and part of the remaining differences between ARM measurements and SCIATRAN retrievals can be attributed to unmasked clouds. Histogram based analysis of the AOT values showed reasonable distributions using SCIATRAN. Most distributions based on SCIATRAN AOT retrievals within a radius of 25 km around the stations are significantly broader than those derived from ARM measurements during 30 minutes but are well centered around the ARM AOT distributions.

Spatial and Temporal Variation of Aerosol and Water Vapour Effects on Solar Radiation in the Mediterranean Basin during the Last Two Decades

This study aims to calculate and analyse the spatial and temporal variation of aerosol optical thickness (AOT) and precipitable water vapour (PWV) and their effects on solar radiation at the surface in the Mediterranean basin, one of the maritime areas with the largest aerosol loads in the world. For the achievement of this objective, a novel and validated methodology was applied. Satellite data, specifically CERES (Clouds and the Earth’s Radiant Energy System) SYN1deg products during the period 2000–2018, were used. Results show that the spatial distribution of AOT and PWV are closely linked to the spatial distributions of its effects on solar radiation. These effects are negative, indicating a reduction of solar radiation reaching the surface due to aerosol and water vapour effects. This reduction ranges between 2% and 8% for AOT, 11.5% and 15% for PWV and 14% and 20% for the combined effect. The analysis of the temporal distribution has focused on the detection of trends from their anomalies. This study has contributed to a better understanding of AOT and PWV effects on solar radiation over the Mediterranean basin, one of the most climatically sensitive regions of the planet, and highlighted the importance of water vapour.

Assessment of urban aerosol pollution over the Moscow megacity by the MAIAC aerosol product

Abstract. We estimated the distribution of aerosol optical thickness (AOT) with a spatial resolution of 1 km over the Moscow megacity using the MAIAC aerosol product based on MODIS satellite data (Lyapustin et al., 2018) for the warm period of the year (May–September, 2001–2017). AERONET (Aerosol Robotic Network)-based validation of satellite estimates near the city centre at Moscow_MSU_MO and over the Moscow suburbs at Zvenigorod revealed that MAIAC AOT at 0.47 µm is in agreement with AERONET AOT though underestimated by 0.05–0.1 for AOT<1 and overestimated for smoke conditions with AOT>1. The MAIAC AOT biases were almost the same for the Moscow_MSU_MO and Zvenigorod AERONET sites, which indicated that the MAIAC algorithm effectively removed the effect of the bright urban surface in the city centre. For the ground-based measurements, the difference between annual median AOT at Moscow_MO_MSU and Zvenigorod (ΔAOT) varied within −0.002 to +0.03, with statistically significant positive bias for most years, and an average ΔAOT was about 0.02. According to the MAIAC dataset, the ΔAOT varied within ±0.01 and was not statistically significant. The ΔAOT started decreasing recently due to intensive urban development of the territory around Zvenigorod and the decrease in pollutant emissions in Moscow, which is mainly caused by the environmental regulations. According to the MAIAC dataset, the most pronounced spatial AOT differences over the territory of Moscow were observed at the 5 % quantile level, where they reached 0.05–0.06 over several locations and could be attributed to the stationary sources of aerosol pollution, for example, large areas of construction sites, aerosol pollution from roads and highways, or agriculture activities. The differences between the maximum and the mean AOT for different quantiles, except the 95 % quantile, within the Moscow region, were about 0.02–0.04, which could be attributed to the local aerosol sources. The application of the MAIAC algorithm over the whole Moscow region has revealed a decreasing AOT trend over the centre of Moscow and an increasing trend over the “New” Moscow territory which experienced an intensive build-up and agricultural development.

乌鲁木齐市一次灰霾天气过程中的AOD时空动态分析

乌鲁木齐市一次灰霾天气过程中的AOD时空动态分析

Aerosol model evaluation using two geostationary satellites over East Asia in May 2016

This study newly applies measurements from two geostationary satellites, the Advanced Himawari Imager (AHI) onboard the geostationary satellite Himawari-8 and the Geostationary Ocean Color imager (GOCI) onboard the geostationary satellite COMS, to evaluate a unique regional aerosol-transport model coupled to a non-hydrostatic icosahedral atmospheric model (NICAM) at a high resolution without any nesting technique and boundary conditions of the aerosols. Taking advantage of the unique capability of these geostationary satellites to measure aerosols with unprecedentedly high temporal resolution, we focus on a target area (115°E-155°E, 20°N-50°N) in East Asia in May 2016, which featured the periodic transport of industrial aerosols and a very heavy aerosol plume from Siberian wildfires. The aerosol optical thickness (AOT) fields are compared among the AHI, GOCI, MODIS, AERONET and NICAM data. The results show that both AHI- and GOCI-retrieved AOTs were generally comparable to the AERONET-retrieved ones, with high correlation coefficients of approximately 0.7 in May 2016. They also show that NICAM successfully captured the detailed horizontal distribution of AOT transported from Siberia to Japan on the most polluted day (18 May 2016). The monthly statistical metrics, including correlation between the model and either AHI or GOCI, are estimated to be >0.4 in 42–49% of the target area. With the aid of sensitivity model experiments with and without Siberian wildfires, it was found that a long-range transport of aerosols from Siberian wildfires (from as far as 3000 km) to Japan influenced the monthly mean aerosol levels, accounting for 7–35% of the AOT, 26–49% of the surface PM2.5 concentrations, and 25–66% of the aerosol extinction above 3 km in height over Japan. Therefore, the air pollutants from Siberian wildfire cannot be ignored for the spring over Japan.

Cast Shadow Detection to Quantify the Aerosol Optical Thickness for Atmospheric Correction of High Spatial Resolution Optical Imagery

The atmospheric correction of optical remote sensing data requires the determination of aerosol and gas optical properties. A method is presented which allows the detection of the aerosol scattering effects from optical remote sensing data at spatial sampling intervals below 5 m in cloud-free situations from cast shadow pixels. The derived aerosol optical thickness distribution is used for improved atmospheric compensation. In a first step, a novel spectral cast shadow detection algorithm determines the shadow areas using spectral indices. Evaluation of the cast shadow masks shows an overall classification accuracy on an 80% level. Using the such derived shadow map, the ATCOR atmospheric compensation method is iteratively applied on the shadow areas in order to find the optimum aerosol amount. The aerosol optical thickness is found by analyzing the physical atmospheric correction of fully shaded pixels in comparison to directly illuminated areas. The shadow based aerosol optical thickness estimation method (SHAOT) is tested on airborne imaging spectroscopy data as well as on photogrammetric data. The accuracy of the reflectance values from atmospheric correction using the such derived aerosol optical thickness could be improved from 3–4% to a level of better than 2% in reflectance for the investigated test cases.

Winter seasons assessment of atmospheric aerosol over Coalfield region of India using geoinformatics

Aerosol optical thickness (AOT), temperature and precipitable water vapour (PWV) were measured using MICROTOPS II Sunphotometer during the month of January 2011 and January 2014 for their analysis in the winter season over South Karanpura Coalfield region, Jharkhand, India. Patterns of AOT concentration (at five different wavelengths 340, 500, 870, 936 and 1020nm) were measured along with water vapour and temperature, which were then spatially analyzed with reference to land use/land cover (LU/LC) of the region. Spatial distribution of AOT indicated higher concentration over industrial area (1.923–3.333 at 340nm) and construction sites (>2.955 at 340nm) and lower concentrations (<0.511 at 340nm) over planned residential areas. To determine the aerosol size distribution, Ǻngstrӧm parameters (α, β) were calculated at wavelengths 340–870nm (2011 and 2014) which ranged between 0.422 and 1.286 and 0.472 to 2.593 in January 2011 and 2014 respectively for ‘α’, whereas ‘β’ value lies between 0.127 and 1.379 in January 2011 and 0.031 to 1.923 in January 2014. The study indicates the presence of different particle sizes of aerosol associated with industries and coal mining activities which contribute significantly to increased aerosol concentration in the study area.

Simultaneous retrieval of aerosol optical thickness and chlorophyll concentration from multiwavelength measurement over East China Sea

AbstractA flexible inversion algorithm is proposed for simultaneously retrieving aerosol optical thickness (AOT) and surface chlorophyll a (Chl) concentration from multiwavelength observation over the ocean. In this algorithm, forward radiation calculation is performed by an accurate coupled atmosphere‐ocean model with a comprehensive bio‐optical ocean module. Then, a full‐physical nonlinear optimization approximation approach is used to retrieve AOT and Chl. For AOT retrieval, a global three‐dimensional spectral radiation‐transport aerosol model is used as the a priori constraint to increase the retrieval accuracy of aerosol. To investigate the algorithm's availability, the retrieval experiment is conducted using simulated radiance data to demonstrate that the relative errors in simultaneously determining AOT and Chl can be mostly controlled to within 10% using multiwavelength and angle covering in and out of sunglint. Furthermore, the inversion results are assessed using the actual satellite observation data obtained from Cloud and Aerosol Imager (CAI)/Greenhouse gas Observation SATellite GOSAT and MODerate resolution Imaging Spectroradiometer (MODIS)/Aqua instruments through comparison to Aerosol Robotic Network (AERONET) aerosol and ocean color (OC) products over East China Sea. Both the retrieved AOT and Chl compare favorably to the reported AERONET values, particularly when using the CASE 2 ocean module in turbid water, even when the retrieval is performed in the presence of high aerosol loading and sunglint. Finally, the CAI and MODIS images are used to jointly retrieve the spatial distribution of AOT and Chl in comparison to the MODIS AOT and OC products.

Reconciling satellite aerosol optical thickness and surface fine particle mass through aerosol liquid water

AbstractSummertime aerosol optical thickness (AOT) over the southeast U.S. is sharply enhanced over wintertime values. This seasonal pattern is unique and of particular interest because temperatures there have not warmed over the past 100 years. Patterns in surface fine particle mass are inconsistent with satellite reported AOT. In this work, we attempt to reconcile the spatial and temporal distribution of AOT over the U.S. with particle mass measurements at the surface by examining trends in aerosol liquid water (ALW), a particle constituent that scatters radiation and affects satellite AOT but is removed in mass measurements at routine surface monitoring sites. We employ the thermodynamic model ISORROPIAv2.1 to estimate ALW mass concentrations at Interagency Monitoring of PROtected Visual Environments sites using measured ion mass concentrations and North American Regional Reanalysis meteorological data. Excellent agreement between Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observations AOT and estimated ALW provides a plausible explanation for the discrepancies in the geographical patterns of AOT and aerosol mass measurements.

Temporal variability of aerosol optical thickness vertical distribution observed from CALIOP

AbstractTemporal variability in the vertical distribution of aerosol optical thickness (AOT) derived from the 0.532 µm aerosol extinction coefficient is described using Cloud‐Aerosol Lidar with Orthogonal Polarization (CALIOP) observations over 8.5 years (June 2006 to December 2014). Temporal variability of CALIOP column‐integrated AOT is largely consistent with total column AOT trends from several passive satellite sensors, such as the Moderate Resolution Imaging Spectroradiometer, Multiangle Imaging Spectroradiometer, and the Sea‐viewing Wide Field‐of‐view Sensor. Globally, a 0.0002 AOT per year positive trend in deseasonalized CALIOP total column AOT for daytime conditions is attributed to corresponding changes in near‐surface (i.e., 0.0–0.5 km or 0.5–1.0 km above ground level (agl)) aerosol particle loading, while a −0.0006 AOT per year trend during nighttime is attributed to elevated (i.e., 1.0–2.0 km or &gt;2.0 km agl) aerosols. Regionally, increasing daytime CALIOP AOTs are found over Southern Africa and India, mostly due to changes in aerosol loading at the 1.0–2.0 km and 0.0–0.5 km agl layers, respectively. Decreasing daytime CALIOP AOTs are observed over Northern Africa, Eastern U.S., and South America (due mostly to elevated aerosol loading), while the negative CALIOP AOT trends found over Eastern China, Europe, and Western U.S. are due mostly to aerosol layers nearer the surface. To our knowledge, this study is the first to provide both a globally comprehensive estimation of the temporal variation in aerosol vertical distribution and an insight into passive sensor column AOT trends in the vertical domain.

Seasonal variations in aerosol optical thickness over eastern China determined from VIIRS data and ground measurements

ABSTRACTTwo-year records of Visible Infrared Imaging Radiometer Suite (VIIRS) Intermediate Product (IP) data on aerosol optical thickness (AOT) at 550 nm were evaluated by comparing them to sun-sky radiometer measurements from the Chinese Sun Hazemeter Network (CSHNET) and the Aerosol Robotic Network (AERONET). The monthly and seasonal variations in the aerosol optical properties over eastern China were then investigated using collocated VIIRS IP data and CSHNET and AERONET measurements. Between 59.2 and 62.1% of the retrieved VIIR IP values fell within the range defined for MODIS (Moderate Resolution Imaging Spectroradiometer) and had similar values for the correlation coefficient (0.880–0.909). The performances of the current VIIRS IP AOT retrievals at the provisional stage were consistent with ground measurements. However, over urban areas, the VIIRS exhibits more scatter and therefore less precision than observed over marine and rural areas. Similar characteristics of seasonal and monthly variations were found among the measurements, though the observational methodologies were different, showing maxima in the summer and spring and minima in the winter and autumn. Although the intensities vary from season to season, the spatial AOT distribution patterns did not change. High-AOT centres were situated in the industrialized coastal regions of China and were related to the distribution of urban areas.

Trend estimates of AERONET-observed and model-simulated AOTs between 1993 and 2013

Abstract Recently, temporal changes in Aerosol Optical Thickness (AOT) have been investigated based on model simulations, satellite and ground-based observations. Most AOT trend studies used monthly or annual arithmetic means that discard details of the generally right-skewed AOT distributions. Potentially, such results can be biased by extreme values (including outliers). This study additionally uses percentiles (i.e., the lowest 5%, 25%, 50%, 75% and 95% of the monthly cumulative distributions fitted to Aerosol Robotic Network (AERONET)-observed and ECHAM/MESSy Atmospheric Chemistry (EMAC)-model simulated AOTs) that are less affected by outliers caused by measurement error, cloud contamination and occasional extreme aerosol events. Since the limited statistical representativeness of monthly percentiles and means can lead to bias, this study adopts the number of observations as a weighting factor, which improves the statistical robustness of trend estimates. By analyzing the aerosol composition of AERONET-observed and EMAC-simulated AOTs in selected regions of interest, we distinguish the dominant aerosol types and investigate the causes of regional AOT trends. The simulated and observed trends are generally consistent with a high correlation coefficient (R = 0.89) and small bias (slope±2σ = 0.75 ± 0.19). A significant decrease in EMAC-decomposed AOTs by water-soluble compounds and black carbon is found over the USA and the EU due to environmental regulation. In particular, a clear reversal in the AERONET AOT trend percentiles is found over the USA, probably related to the AOT diurnal cycle and the frequency of wildfires. In most of the selected regions of interest, EMAC-simulated trends are mainly attributed to the significant changes of the dominant aerosols; e.g., significant decrease in sea salt and water soluble compounds over Central America, increase in dust over Northern Africa and Middle East, and decrease in black carbon and organic carbon over Australia.

Spatio-temporal variability of Suomi-NPP VIIRS-derived aerosol optical thickness over China in 2013

The Visible Infrared Imaging Radiometer Suite (VIIRS) aerosol optical thickness (AOT) at 550 nm Intermediate Product (IP) data was evaluated by comparing it with measurements from Aerosol Robotic Network (AERONET) and Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals. The spatial and temporal variations in the regional AOT over China during 2013 (from 24 January to 31 December) were then firstly investigated using VIIRS aerosol IP data. Evaluation of VIIRS IP AOT with MODIS retrievals and AERONET measurements indicated that the performance of the VIIRS aerosol IP product is comparable to that of their counterparts from the heritage MODIS sensor. However, the VIIRS IP can produce more retrievals than MODIS due to its higher spatial resolution, therefore more suitable for regional AOT study. It was found that the VIIRS IP mean AOT over China differs from that of MODIS by −0.032 for the collocated retrievals, with a correlation of 0.928. Compared with AERONET measurements, VIIRS IP AOT shows a negative bias of −0.058 with the standard deviation of the difference of 0.192 over China. Among the 10 typical sites under study, the maximum annual average AOT550 values (with±standard deviation) were found in Chengdu (1.07±0.32), whereas the lowest annual mean AOT550 values were found in FB1 (0.242±0.25). The economically developed regions had high AOT values during all seasons. Based on the distribution of AOT, China can be divided into an economically developed eastern region with high AOT values and less-developed western regions, consistent with the boundary between China’s second and third terrain regions.

Impact of satellite viewing-swath width on global and regional aerosol optical thickness statistics and trends

Abstract. We use the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite aerosol optical thickness (AOT) product to assess the impact of reduced swath width on global and regional AOT statistics and trends. Along-track and across-track sampling strategies are employed, in which the full MODIS data set is sub-sampled with various narrow-swath (~ 400–800 km) and single pixel width (~ 10 km) configurations. Although view-angle artifacts in the MODIS AOT retrieval confound direct comparisons between averages derived from different sub-samples, careful analysis shows that with many portions of the Earth essentially unobserved, spatial sampling introduces uncertainty in the derived seasonal–regional mean AOT. These AOT spatial sampling artifacts comprise up to 60% of the full-swath AOT value under moderate aerosol loading, and can be as large as 0.1 in some regions under high aerosol loading. Compared to full-swath observations, narrower swath and single pixel width sampling exhibits a reduced ability to detect AOT trends with statistical significance. On the other hand, estimates of the global, annual mean AOT do not vary significantly from the full-swath values as spatial sampling is reduced. Aggregation of the MODIS data at coarse grid scales (10°) shows consistency in the aerosol trends across sampling strategies, with increased statistical confidence, but quantitative errors in the derived trends are found even for the full-swath data when compared to high spatial resolution (0.5°) aggregations. Using results of a model-derived aerosol reanalysis, we find consistency in our conclusions about a seasonal–regional spatial sampling artifact in AOT. Furthermore, the model shows that reduced spatial sampling can amount to uncertainty in computed shortwave top-of-atmosphere aerosol radiative forcing of 2–3 W m−2. These artifacts are lower bounds, as possibly other unconsidered sampling strategies would perform less well. These results suggest that future aerosol satellite missions having significantly less than full-swath viewing are unlikely to sample the true AOT distribution well enough to obtain the statistics needed to reduce uncertainty in aerosol direct forcing of climate.

Development of an image based integrated method for determining and mapping aerosol optical thickness (AOT) over urban areas using the darkest pixel atmospheric correction method, RT equation and GIS: A case study of the Limassol area in Cyprus

This paper presents the development of an image-based integrated method for determining and mapping aerosol optical thickness (AOT). Using the radiative transfer (RT) equation, a methodology was developed to create a Geographical Information System (GIS) model that can visually display the AOT distribution over urban areas. In this paper, the model was applied to eleven Landsat Thematic Mapper/Enhanced Thematic Mapper Plus (TM/ETM+) satellite images of Limassol, Cyprus during 2010 and 2011 to determine the AOT levels in Limassol Cyprus during satellite overpass. The study is innovative and unique in that the RT equation, satellite images, the darkest pixel (DP) method of atmospheric correction and GIS were integrated to derive AOT from satellite images and display the AOT distribution over an urban area without the input of any meteorological or atmospheric parameters. The accuracy of the algorithm was verified through statistical analysis by the strong agreement between the AOT values derived using the algorithm and the in situ AOT values from the ground-based sensors.

Simulation and validation of the aerosol optical thickness over China in 2006

The Model of Atmospheric Transport and Chemistry (MATCH) developed by the US National Center for Atmospheric Research (NCAR) was used to calculate the aerosol optical thickness (AOT) over China in 2006, with emission source data of the Intercontinental Chemical Transport Experiment Phase B (INTEX-B) and NCEP/NCAR reanalysis data as inputs. The simulation results of AOT were then validated with observational data from the Moderate Resolution Imaging Spectroradiometer (MODIS), Chinese Sun Hazemeter Network (CSHNET), Aerosol Robotics Network (AERONET), and China Aerosol Remote Sensing Network (CARSNET) at more than 30 stations over China. The comparison results indicated that the high values of AOT in the areas such as the Sichuan basin and East and South China and the low values of AOT over the Tibetan Plateau and Northwest and Northeast China were reasonably simulated by the MATCH. This model tended to underestimate the AOT values in high-aerosol-loading areas but overestimate the AOT values in less polluted areas because there are still large uncertainties in the expression of emission sources, the description of the optical properties of aerosols, the treatment of cloud and precipitation, and the selection of grid resolution. The modeling results were consistent with the CSHNET, CARSNET, AERONET, and MODIS data in most parts of China, and the correlation coefficient of the monthly mean AOT between the model and the observation was 0.79 with CSHNET data at 23 stations, 0.51 with MODIS data, and 0.88 with data at 3 CARSNET stations and 2 other stations. All of them passed the significance test with α < 0.0001. The results demonstrated that the MATCH has the ability to simulate the characteristics of the AOT distribution and its seasonal variation over China.

An Atmospheric Correction Algorithm for Landsat/TM Imagery Basing on Inverse Distance Spatial Interpolation Algorithm: A Case Study in Taihu Lake

In this study, an atmospheric correction algorithm is designed for Landsat/TM imagery. The lookup tables with multiple scattering and polarization correction are used to remove the reflectance resulting from Rayleigh scattering. The Landsat/TM imageries collected on October 28, 2003, in Taihu Lake, water-leaving reflectance measured by synchronized experiments and the aerosol lookup table are used to estimate the aerosol optical thickness (AOT) and atmospheric diffuse transmittance from Landsat/TM imagery at 15 experimental stations. The inverse distance spatial interpolation algorithm (IDSIA) is used to improve the uncertainty produced by the non-homogeneous distribution of AOT. According to the study results carried out by this paper, it is found that using IDSIA to improve the spatial changes of AOT at least decreases 4.5% uncertainty at TM3 and 16.4% uncertainty at TM4 from non-homogeneous distribution of AOT. The improved performance of IDSIA is fairly obviously. Additionally, water-leaving reflectance of Landsat imageries is estimated by this atmospheric correction algorithm. The stability and accuracy validation results show that the estimation accuracy of water-leaving reflectance is 8.31% at TM1 and 9.56% at TM2, respectively.

Aerosol optical thickness and spatial variability along coastal and offshore waters of the eastern Arabian Sea

AbstractMenon, H. B., Sangekar, N., Lotliker, A., Krishna Moorthy, K., and Vethamony, P. 2011. Aerosol optical thickness and spatial variability along coastal and offshore waters of the eastern Arabian Sea. – ICES Journal of Marine Science, 68: 745–750. Data from the ocean-colour monitor (OCM) on board the Indian Remote Sensing Satellite P4 were used to analyse the spatial and temporal distribution of aerosol optical thickness (AOT) over the coastal and offshore waters of the eastern Arabian Sea. Zero water-leaving radiance from the near infrared (NIR) region was assumed for oceanic (open ocean) waters, because of the absorption of long-wave radiation by water molecules. As this assumption fails in coastal waters, it was necessary to correct for water-leaving radiance and sun glint to the NIR bands. The aerosol size-distribution parameter (α) was derived from a relationship between two NIR bands. The Ångström turbidity parameter (β) was obtained using an algorithm relating in situ hand-held, sun-photometer measurements and aerosol radiance (La) at 490 nm. The relationship between β and La (490) was derived with a sensitivity analysis, using a calibrated radiative transfer model. AOTs were retrieved for each pixel of 500 nm. The algorithm's performance was tested by comparing OCM-derived AOT values with in situ AOT and MODIS-derived values. Aerosol maps thus generated from January to December 2005 demonstrate the potential of this new retrieval method for producing AOT climatology from OCM data over coastal waters.

A geostatistical data fusion technique for merging remote sensing and ground‐based observations of aerosol optical thickness

The Multiangle Imaging Spectroradiometer (MISR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the NASA Earth Observation System's Terra satellite have been measuring aerosol optical thickness (AOT) since early 2000. These remote‐sensing platforms complement the ground‐based Aerosol Robotic Network (AERONET) in better understanding the role of aerosols in climate and atmospheric chemistry. To date, however, there have been only limited attempts to exploit the complementary multiangle (MISR) and multispectral (MODIS) capabilities of these sensors along with the ground‐based observations in an integrated analysis. This paper describes a geostatistical data fusion technique that can take advantage of the spatial autocorrelation of the AOT distribution, while making optimal use of all available data sets. Using Level 2.0 AERONET, MISR, and MODIS AOT data for the contiguous United States, we demonstrate that this approach can successfully incorporate information from multiple sensors and provide accurate estimates of AOT with rigorous uncertainty bounds. Cross‐validation results show that the resulting AOT product is closer to the ground‐based AOT observations than either of the individual satellite measurements.