Validation Of Aerosol Optical Depth Research Articles

Monitoring aerosol optical depth during the Arctic night: Instrument development and first results

Moon-photometric measurements were made at two locations in the Arctic during winter nights using two different modified Sun photometers; a Carter Scott SP02 and a Precision Filter Radiometer (PFR) developed at PMOD/WRC. Values of aerosol optical depth (AOD) were derived from spectral irradiance measurements made at four wavelengths for each of the devices. The SP02 was located near Barrow, Alaska and recorded data from November 2012 to March 2013, spanning five lunar cycles, while the PFR was deployed to Ny-Ålesund, Svalbard each winter from February 2014 to February 2019 for a total of 56 measurement periods. A methodology was developed to process the raw data, involving calibration of the instruments and normalizing measured spectral irradiance values in accordance with site-specific determinations of the extraterrestrial atmospheric irradiance (ETI) as Moon phase cycled. Uncertainties of the derived AOD values were also evaluated and found to be in the range, 0.006–0.030, depending on wavelength and which device was evaluated.The magnitudes of AOD determined for the two sites were in general agreement with those reported in the literature for sunlit periods just before and after the dark periods of Arctic night. Those for the PFR were also compared with data obtained using star photometers and a Cimel CE318-T, recently deployed to Ny-Ålesund, showing that Moon photometry is viable as a means to monitor AOD during the Arctic night. Such data are valuable for more complete assessments of the role aerosols play in modulating climate, the validation of AOD derived using various remote sensing techniques, and applications related to climate modeling.

Retrieval of Aerosol Optical Properties over Land Using an Optimized Retrieval Algorithm Based on the Directional Polarimetric Camera

The Directional Polarization Camera (DPC) onboard the Chinese Gaofen-5 satellite, launched in May 2018, has similar specifications as the POLDER-3 instrument. The SRON Remote Sensing of Trace gas and Aerosol Products (RemoTAP) full retrieval algorithm is applied to DPC measurements to retrieve aerosol properties including the total Aerosol Optical Depth (AOD), the fine/coarse mode AOD and the SSA (Single Scattering Albedo). Measurements of the global ground-based AERONET network between December 2019 and April 2020 have been used for the validation of the DPC retrievals. According to the average Fine Mode Fraction (FMF) of the selected AERONET stations, the stations are divided into urban stations (FMF ≥ 0.5) and dust stations (FMF < 0.5). For the total AOD validation, DPC retrievals show better performance over urban stations than over dust stations, with average biases of 0.055 and 0.106, and RMSEs of 0.151 and 0.228, respectively. Regarding the fine mode AOD, the retrieval also performs better over urban stations. Compared with the total AOD validation, both the relatively lower bias (0.021 and 0.065) and the higher Gfrac (Fraction of Good retrieval, 63.8% and 47.3%, respectively) further indicate that DPC performs better when fine mode aerosols dominate. For the land SSA validation, most of our SSA retrievals (~71%) show differences with AERONET SSA retrievals lower than 0.05. Case studies over fire spots and dust over northern China demonstrate the encouraging application potential of DPC aerosol products. The difference between fine and coarse AOD can provide more aerosol source information compared with the total AOD alone. Since the SSA retrievals are particularly sensitive to absorbing fine particles, they can be easily used in the tracking of biomass burning aerosol.

Preliminary Assessment and Verification of the Langley Plots Calibration of the Sun Photometer at Mt Foyeding Observatory, Beijing

An assessment and verification of the Langley calibration method of the Sun photometer at Mt Foyeding (MFYD) Observatory in Beijing was performed. We explored whether the Langley plot calibration is practicable for this mountainous site by analyzing the aerosol climatology and carrying out a case study. Then, the aerosol optical depth (AOD) results were verified under the reference of AERONET AOD. The results showed that satisfactory atmospheric conditions are present on winter mornings, characterized by a smaller average AOD (~0.09–0.14) and a lower range ratio (~36.97–63.38%) than in the afternoons and over a whole day. The six days selected as the case study all showed stable atmospheric conditions characterized by daily average triplets of <2% for all wavelengths. The residual sum of squares for V0λ at all wavelengths was <0.0002 and the residual standard deviation was <0.2%. A large improvement was found in the linear regression at morning relative to the statistics obtained over the whole day, when the coefficient of determination and residual standard deviation were promoted by 0.22–2.90% and ~2.76–23.32, respectively. The final V0λ value was derived from 31 days of observation and the deviations from the reference V0λ were about −1.69, −1.29, −0.81, −0.42, −0.34, −0.22, −0.63 and −0.36% at 340, 380, 440, 500, 675, 870, 1020 and 1640 nm, respectively. The regression analysis of the AOD validation showed a perfect AOD performance, with 100% of the retrievals lying within the expected error (0.05 ± 10%) from 380 to 1640 nm and 99.99% for the 340 nm band. Good AOD agreement (correlation coefficients > 0.998) and residual standard deviation values ranging from ~0.006 to 0.011 were observed, with the relative mean bias varying from 0.999 to 1.066. The mean biases were concentrated within ±0.02 for the ultraviolet bands and within ±0.01 for the other bands; therefore, the results of this preliminary assessment and verification indicated that the Langley plots method is suitable for photometer calibration at the MFYD Observatory.

Validation and Analysis of MISR and POLDER Aerosol Products over China

Multi-angle polarization measurement is an important technical means of satellite remote sensing applied to aerosol monitoring. By adding angle information and polarization measurements, aerosol optical and microphysical properties can be more comprehensively and accurately retrieved. The accuracy of aerosol retrieval can reflect the advantages and specific accuracy improvement of multi-angle polarization. In this study, the Multi-angle Imaging SpectroRadiometer (MISR) V23 aerosol products and the Polarization and Directionality of the Earth’s Reflectance (POLDER) GRASP “high-precision” archive were evaluated with the Aerosol Robotic Network (AERONET) observations over China. Validation of aerosol optical depth (AOD), absorbing aerosol optical depth (AAOD), and the Ångström exponent (AE) properties was conducted. Our results show that the AOD inversion accuracy of POLDER-3/GRASP is higher with the correlation coefficient (R) of 0.902, slope of 0.896, root mean square error (RMSE) of 0.264, mean absolute error (MAE) of 0.190, and about 40.71% of retrievals within the expected error (EE, ± 0.05+0.2×AODAERONET) lines. For AAOD, the performance of two products is poor, with better results for POLDER-3/GRASP data. POLDER-3/GRASP AE also has higher R of 0.661 compared with that of MISR AE (0.334). According to the validation results, spatiotemporal distribution, and comparison with other traditional scalar satellite data, the performance of multi-angle polarization observations is better and is suitable for the retrieval of aerosol properties.

Ground-based validation of aerosol optical depth from CAMS reanalysis project: An uncertainty input on direct normal irradiance under cloud-free conditions

Under cloud-free skies, aerosols are mainly responsible for controlling the observed Direct Normal Irradiance (DNI) variability for studying and designing Solar Concentrating Technologies. In this study, the induced uncertainties on cloud-free DNI due to the use of aerosol optical properties from the CAMS reanalysis project (AODCAMS) are investigated. DNI is calculated using a radiative transfer model while a pre-comparison and calibration of aerosol reanalysis products are performed using as skill reference the observations from AERONET. The site-specific validation showed an overestimation of the AOD in locations affected by volcanic eruptions while underestimation and higher dispersion metrics are revealed in regions dominated by coarse aerosols from mineral dust and biomass burning. A pre-calibration process of AODCAMS significantly improved the error metrics in all AERONET locations providing significant reductions in all ‘hot-spot error’ regions. In terms of DNI, using the initial AODCAMS, rMBE extends between −28% and 30%, exhibiting higher magnitudes in South and South-Eastern Asia. Using the calibrated AODCAMS, the pre-described error metrics are significantly improved in site-specific and regional scales.

A Dual-Channel Aerosol Optical Depth Retrieval Algorithm Incorporating the BRDF Effect from AVHRR over Eastern Asia

A NOAA/AVHRR dual-channel method over land is proposed to simultaneously retrieve aerosol optical depth (AOD) at 0.55 μm, and surface reflectance at 0.63 and 0.85 μm. Compared with previous well-established one-channel retrieval algorithms, this algorithm takes advantage of the surface reflectance ratio between 0.63 and 0.85 μm in an attempt to account for the effect induced by the surface bidirectional reflectance distribution function (BRDF). This effect cannot be negligible due to the orbit drift and phasing running of NOAA satellites, both of which potentially cause large solar angular variation. Meanwhile, the observation posture change of AVHRR would cause large sensor angular variation in time series measurements. The used surface reflectance ratio based on dual channels at 0.63 and 0.85 μm is found more reasonable to be assumed as unchanged during a certain period of time, compared to the traditional ratio when addressing the BRDF issue. AOD retrievals have been carried out over Eastern Asia. Validation against aerosol robotic network (AERONET) measurements shows that up to 83% of AOD validation collocations are within error lines (±0.15 ± 0.15τ, τ is AOD) with an R of 0.88 and an root mean square error (RMSE) of 0.15. The dual-channel algorithm taking into account the surface BRDF effect is proved outperforming the conventional 0.63 μm-channel method. It indicates that our algorithm has the potential to be applied to the retrieval of long series of AOD, especially to the AOD retrieval of the sensors which lack a shortwave infrared channel required in the MODerate resolution Imaging Spectroradiometer (MODIS) dark target AOD algorithm.

Retrieval and Validation of AOD from Himawari-8 Data over Bohai Rim Region, China

The geostationary satellite Himawari-8, possessing the Advanced Himawari Imager (AHI), which features 16 spectral bands from the visible to infrared range, is suitable for aerosol observations. In this study, a new algorithm is introduced to retrieve aerosol optical depth (AOD) over land at a resolution of 2 km from the AHI level 1 data. Considering the anisotropic effects of complex surface structures over land, Moderate Resolution Imaging Spectroradiometer (MODIS) bidirectional reflectance distribution function (BRDF) model parameters product (MCD19A3) is used to calculate the surface reflectance for Himawari-8’s view angle and band. In addition, daily BRDF model parameters are calculated in areas with dense vegetation, considering the rapid variation of surface reflectance caused by vegetation growth. Moreover, aerosol models are constructed based on long duration Aerosol Robotic Network (AERONET) single scattering albedo (SSA) values to stand for aerosol types in the retrieval algorithm. The new algorithm is applied to AHI images over Bohai Rim region from 2018 and is evaluated using the newest AERONET version 3 AOD measurements and the latest MODIS collection 6.1 AOD products. The AOD retrievals from the new algorithm show good agreement with the AERONET AOD measurements, with a correlation coefficient of 0.93 and root mean square error (RMSE) of 0.12. In addition, the new algorithm increases AOD retrievals and retrieval accuracy compared to the Japan Aerospace Exploration Agency (JAXA) aerosol products. The algorithm shows stable performance during different seasons and times, which makes it possible for use in climate or diurnal aerosol variation studies.

Spatio-Temporal Variability of Aerosol Optical Depth, Total Ozone and NO2 Over East Asia: Strategy for the Validation to the GEMS Scientific Products

In this study, the spatio-temporal variability of aerosol optical depth (AOD), total column ozone (TCO), and total column NO2 (TCN) was identified over East Asia using long-term datasets from ground-based and satellite observations. Based on the statistical results, optimized spatio-temporal ranges for the validation study were determined with respect to the target materials. To determine both spatial and temporal ranges for the validation study, we confirmed that the observed datasets can be statistically considered as the same quantity within the ranges. Based on the thresholds of R2>0.95 (temporal) and R>0.95 (spatial), the basic ranges for spatial and temporal scales for AOD validation was within 30 km and 30 min, respectively. Furthermore, the spatial scales for AOD validation showed seasonal variation, which expanded the range to 40 km in summer and autumn. Because of the seasonal change of latitudinal gradient of the TCO, the seasonal variation of the north-south range is a considerable point. For the TCO validation, the north-south range is varied from 0.87° in spring to 1.05° in summer. The spatio-temporal range for TCN validation was 20 min (temporal) and 20–50 km (spatial). However, the nearest value of satellite data was used in the validation because the spatio-temporal variation of TCN is large in summer and autumn. Estimation of the spatio-temporal variability for respective pollutants may contribute to improving the validation of satellite products.

A review and framework for the evaluation of pixel-level uncertainty estimates in satellite aerosol remote sensing

Abstract. Recent years have seen the increasing inclusion of per-retrieval prognostic (predictive) uncertainty estimates within satellite aerosol optical depth (AOD) data sets, providing users with quantitative tools to assist in the optimal use of these data. Prognostic estimates contrast with diagnostic (i.e. relative to some external truth) ones, which are typically obtained using sensitivity and/or validation analyses. Up to now, however, the quality of these uncertainty estimates has not been routinely assessed. This study presents a review of existing prognostic and diagnostic approaches for quantifying uncertainty in satellite AOD retrievals, and it presents a general framework to evaluate them based on the expected statistical properties of ensembles of estimated uncertainties and actual retrieval errors. It is hoped that this framework will be adopted as a complement to existing AOD validation exercises; it is not restricted to AOD and can in principle be applied to other quantities for which a reference validation data set is available. This framework is then applied to assess the uncertainties provided by several satellite data sets (seven over land, five over water), which draw on methods from the empirical to sensitivity analyses to formal error propagation, at 12 Aerosol Robotic Network (AERONET) sites. The AERONET sites are divided into those for which it is expected that the techniques will perform well and those for which some complexity about the site may provide a more severe test. Overall, all techniques show some skill in that larger estimated uncertainties are generally associated with larger observed errors, although they are sometimes poorly calibrated (i.e. too small or too large in magnitude). No technique uniformly performs best. For powerful formal uncertainty propagation approaches such as optimal estimation, the results illustrate some of the difficulties in appropriate population of the covariance matrices required by the technique. When the data sets are confronted by a situation strongly counter to the retrieval forward model (e.g. potentially mixed land–water surfaces or aerosol optical properties outside the family of assumptions), some algorithms fail to provide a retrieval, while others do but with a quantitatively unreliable uncertainty estimate. The discussion suggests paths forward for the refinement of these techniques.

Extracting Taklimakan Dust Parameters from AIRS with Artificial Neural Network Method

Two back-propagation artificial neural network retrieval models have been developed for obtaining the dust aerosol optical depth (AOD) and dust-top height (DTH), respectively, from Atmospheric InfraRed Sounder (AIRS) brightness temperature (BT) measurements over Taklimakan Desert area. China Aerosol Remote Sensing Network (CARSNET) measurements at Tazhong station were used for dust AOD validation. Results show that the correlation coefficient of dust AODs between AIRS and CARSNET reaches 0.88 with a deviation of −0.21, which is the same correlation coefficient as the AIRS dust AOD and the Moderate-Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) product. In the AIRS DTH retrieval model, there is an option to include the collocated MODIS deep blue (DB) AOD as additional input for daytime retrieval; the independent dust heights from Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) are used for AIRS DTH validation, and results show that the DTHs derived from the combined AIRS BT measurements and MODIS DB AOD product have better accuracy than those from AIRS BT measurements alone. The correlation coefficient of DTHs between AIRS and independent CALIOP dust heights is 0.79 with a standard deviation of 0.41 km when MODIS DB AOD product is included in the retrieval model. A series of case studies from different seasons were examined to demonstrate the feasibility of retrieving dust parameters from AIRS and potential applications. The method and approaches can be applied to process measurements from advanced infrared (IR) sounder and high-resolution imager onboard the same platform.

Evaluation and modification of SARA high-resolution AOD retrieval algorithm during high dust loading conditions over bright desert surfaces

Many studies have been carried out for the validation of Aerosol Optical Depth (AOD) retrieved using MODerate resolution Imaging Spectroradiometer (MODIS) satellite data at the spatial resolution of several to several tens of km. Most of the validation efforts have focused on urban areas with fewer studies focused on deserts with high amounts of dust. On the other hand, calculating AOD at a high spatial resolution over desert surfaces is of high interest to identify local and accurate dust source regions. In this study, two different high-resolution MODIS AOD retrieval algorithms were evaluated to investigate the nature of high dust loading events over the Middle East region. These algorithms include the Simplified Aerosol Retrieval Algorithm (SARA) at 500 m resolution based on the MOD09 Level 2 daily (original SARAMOD09) and MCD43A4 16 day (modified SARAMCD43) surface reflectance products. These algorithms were validated using AERONET AOD observations at Kuwait University, and accuracy was evaluated using descriptive statistics and Expected Error (EE) over land. Also, the results of these algorithms were evaluated with the Collection 6 (C6) Deep Blue algorithm at 10 km spatial resolution (DB10km). Results show that the SARAMCD43 and SARAMOD09 AOD retrievals are well correlated (r) with AERONET data (SARAMCD43 = 0.89 and SARAMOD09 = 0.84), with a larger number of retrievals falling within the Expected Error (SARAMCD43 = 86% and SARAMOD09 = 77%) than the DB (DB10km = 60%) AOD product. The SARAMCD43 AOD exhibited good agreement with DB10km AOD over desert surfaces areas during high aerosol loading events, with an average correlation coefficient of 0.92, RMSE of 0.09, and mean absolute error (MAE) of 0.08. While SARAMOD09 AOD over background desert areas is similar to SARAMCD43, significant differences were observed over high aerosol loading areas and SARAMOD09 dramatically underestimates AOD. The results demonstrate that: (i) the SARA algorithm (regardless of surface reflectance data used) is more robust than the MODIS AOD products (both DT and DB), and is better able to represent spatial dust aerosol conditions with an accurate AOD over desert areas over a range of low to high dust pollutant levels; (ii) SARAMCD43 is well correlated with the DB AOD observations and provides AOD with much greater accuracy and reliability than SARAMOD09 over desert areas during severe dust loading events.

Spatial and seasonal variations of aerosols over China from two decades of multi-satellite observations – Part 1: ATSR (1995–2011) and MODIS C6.1 (2000–2017)

Abstract. Aerosol optical depth (AOD) patterns and interannual and seasonal variations over China are discussed based on the AOD retrieved from the Along-Track Scanning Radiometer (ATSR-2, 1995–2002), the Advanced ATSR (AATSR, 2002–2012) (together ATSR) and the MODerate resolution Imaging Spectroradiometer (MODIS) aboard the Terra satellite (2000–2017). The AOD products used were the ATSR Dual View (ADV) v2.31 AOD and the MODIS/Terra Collection 6.1 (C6.1) merged dark target (DT) and deep blue (DB) AOD product. Together these datasets provide an AOD time series for 23 years, from 1995 to 2017. The difference between the AOD values retrieved from ATSR-2 and AATSR is small, as shown by pixel-by-pixel and monthly aggregate comparisons as well as validation results. This allows for the combination of the ATSR-2 and AATSR AOD time series into one dataset without offset correction. ADV and MODIS AOD validation results show similar high correlations with the Aerosol Robotic Network (AERONET) AOD (0.88 and 0.92, respectively), while the corresponding bias is positive for MODIS (0.06) and negative for ADV (−0.07). Validation of the AOD products in similar conditions, when ATSR and MODIS/Terra overpasses are within 90 min of each other and when both ADV and MODIS retrieve AOD around AERONET locations, show that ADV performs better than MODIS in autumn, while MODIS performs slightly better in spring and summer. In winter, both ADV and MODIS underestimate the AERONET AOD. Similar AOD patterns are observed by ADV and MODIS in annual and seasonal aggregates as well as in time series. ADV–MODIS difference maps show that MODIS AOD is generally higher than that from ADV. Both ADV and MODIS show similar seasonal AOD behavior. The AOD maxima shift from spring in the south to summer along the eastern coast further north. The agreement between sensors regarding year-to-year AOD changes is quite good. During the period from 1995 to 2006 AOD increased in the southeast (SE) of China. Between 2006 and 2011 AOD did not change much, showing minor minima in 2008–2009. From 2011 onward AOD decreased in the SE of China. Similar patterns exist in year-to-year ADV and MODIS annual AOD tendencies in the overlapping period. However, regional differences between the ATSR and MODIS AODs are quite large. The consistency between ATSR and MODIS with regards to the AOD tendencies in the overlapping period is rather strong in summer, autumn and overall for the yearly average; however, in winter and spring, when there is a difference in coverage between the two instruments, the agreement between ATSR and MODIS is lower. AOD tendencies in China during the 1995–2017 period will be discussed in more detail in Part 2 (a following paper: Sogacheva et al., 2018), where a method to combine AOD time series from ADV and MODIS is introduced, and combined AOD time series are analyzed.

Retrieval and Validation of Aerosol Optical Depth by using the GF-1 Remote Sensing Data

Based on the characteristics of GF-1 remote sensing data, the method and data processing procedure to retrieve the Aerosol Optical Depth (AOD) are developed in this study. The surface contribution over dense vegetation and urban bright target areas are respectively removed by using the dark target and deep blue algorithms. Our method is applied for the three serious polluted Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD) and Pearl River Delta (PRD) regions. The retrieved AOD are validated by ground-based AERONET data from Beijing, Hangzhou, Hong Kong sites. Our results show that, 1) the heavy aerosol loadings are usually distributed in high industrial emission and dense populated cities, with the AOD value near 1. 2) There is a good agreement between satellite-retrievals and in-site observations, with the coefficient factors of 0.71 (BTH), 0.55 (YRD) and 0.54(PRD). 3) The GF-1 retrieval uncertainties are mainly from the impact of cloud contamination, high surface reflectance and assumed aerosol model.

Characterizing the Aerosol and Surface Reflectance Over Australia Using AATSR

We present a new algorithm that simultaneously retrieves aerosol properties and land surface bidirectional reflectance distribution function (BRDF) over Australian from Advanced Along-Track Scanning Radiometer images. Three key components are addressed: 1) an analytical radiative transfer formulation, based on Green's function, linking top-of-atmosphere (TOA) reflectance to the surface BRDF; 2) a novel approach to modeling BRDF using an extended compositing period; and 3) a set of representative aerosol models based on a published typology of Australian aerosols. Due to the generally low aerosol loadings and widespread bright surfaces over Australia, BRDF modeling is crucial. By using a 9-month compositing period, 90% of the Australian continent can be modeled with an error in the forward-to-nadir reflectance ratio of 2.5% or less. Comparison with suitably processed Moderate Resolution Imaging Spectroradiometer BRDF/albedo products demonstrates satisfactory agreement. For the studying period from 2002 to 2008, validation of aerosol optical depth (AOD) against eight sun photometers across Australia encompassing widely different atmospheric and surface regimes shows high accuracy, with a mean absolute error in AOD at 550 nm of 0.03 and a bias of 0.007. About 60% of the matchup points are within an absolute error of 0.03, 80% are within 0.05, and 96% are within 0.1. The algorithm selects for each cell an optimal aerosol type from a set of four predefined candidate models. Continental aerosol maps derived from the new method indicate broadscale agreement with known seasonal aerosol sources, while providing new insights into the spatial and temporal distributions of aerosol over the Australian continent.

Aerosol climatology and discrimination of aerosol types retrieved from MODIS, MISR and OMI over Durban (29.88°S, 31.02°E), South Africa

The present study represents the characteristics of aerosol optical depth (AOD) retrieved from multiple satellite sensors (MODerate resolution Imaging Spectroradiometer (MODIS), Multi-angle Imaging SpectroRadiometer (MISR), and Ozone Monitoring Instrument (OMI)) during 2003–2013 over an urban–coastal region, Durban (DBN; 29.88°S, 31.02°E, 46 m°asl), situated on the east coast of South Africa. An intercomparison and validation of AOD is performed against the AOD measurements from ground-based AErosol RObotic NETwork (AERONET) Sunphotometer. The results revealed that MISR-AERONET comparison indicated strong correlation compared to MODIS-AERONET comparison. Also, the comparison between MODIS and MISR AODs noticed significant positive correlation over DBN with the overestimation of latter by former. Highest AOD characterizes during the spring (September–November) followed by summer (December–February) and autumn (March–May) with the lowest AOD observed during the winter (June–August) season. The Angstrom exponent (AE470–600) indicates predominance of fine-mode aerosols during spring and summer and dominance of coarse-mode aerosols in winter. A HYbrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model is used to locate the origin of airmass transport and understand the variability of aerosol source regions. Finally, the relationship between AOD and AE has been examined to classify different aerosol types and showed seasonal heterogeneity in their contribution depending upon variability in sources. This is the first ever attempt to classify aerosols over this environment.

Validation of Aerosol Optical Depth from Terra and Aqua MODIS Retrievals over a Tropical Coastal Site in China

AbstractThis study compares the aerosol optical depth (AOD) Level 2 Collection 5 products from the Terra and Aqua Moderate Resolution Imaging Spectroradiometers (MODIS) with ground-based measurements from a Microtops II sun photometer over Sanya (18.23°N, 109.52°E), a tropical coastal site in China, from July 2005 to June 2006. The results indicate that the Terra and Aqua MODIS AOD retrievals at 550 nm have good correlations with the measurements from the Microtops II sun photometer. The correlation coefficients for the linear regression fits (R2) are 0.83 for Terra and 0.78 for Aqua, and the regressed intercepts are near zero (0.005 for Terra, 0.009 for Aqua). However, the Terra and Aqua MODIS are found to consistently underestimate AOD with respect to the Microtops II sun photometer, with slope values of 0.805 (Terra) and 0.767 (Aqua). The comparison of the monthly mean AOD indicates that for each month, the Terra and Aqua MODIS retrievals are matched with corresponding Microtops measurements but are sy...

Instrument calibration and aerosol optical depth validation of the China Aerosol Remote Sensing Network

This paper introduced the calibration of the CE‐318 sunphotometer of the China Aerosol Remote Sensing Network (CARSNET) and the validation of aerosol optical depth (AOD) by AOD module of ASTPWin software compared with the simultaneous measurements of the Aerosol Robotic Network (AERONET)/Photométrie pour le Traitement Opérationnel de Normalization Satellitaire (PHOTONS) and PREDE skyradiometer. The results show that the CARSNET AOD measurements have the same accuracy as the AERONET/PHOTONS. On the basis of a comparison between CARSNET and AERONET, the AODs from CARSNET at 1020, 870, 670, and 440 nm are about 0.03, 0.01, 0.01, and 0.01 larger than those from AERONET, respectively. The aerosol optical properties over Beijing acquired through the CE‐318 sunphotometers of one AERONET/PHOTONS site and two CARSNET sites were analyzed on the basis of 4‐year measurements. It was obvious that the AOD of the Shangdianzi site (rural site) was lower than that of the two urban sites (the Institute of Atmospheric Physics (IAP) site (north urban site) and the Beijing Meteorological Observatory (BJO) site (south urban site)). The AOD of BJO was about 0.05, 0.04, 0.05, and 0.06 larger than that of IAP at 1020, 870, 670, and 440 nm, respectively, indicating that there is more local pollution in the south part of Beijing. The highest AOD was found in summer because of the stagnation planetary boundary layer and transport of pollutants from large pollution centers south of Beijing. The high temperature and relative humidity in summer also favor the production of aerosol precursor and the hygroscopic growth of the existing particles locally, which results in high AOD. In contrast, the lowest AOD at the two urban sites and one rural site in Beijing occurred in winter as the frequent cold air masses help pollutants diffuse easily.