Comparison Of Aerosol Optical Depth Research Articles

Evaluation of the hyperspectral radiometer (HSR1) at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site

Abstract. The Peak Design Ltd hyperspectral radiometer (HSR1) was tested at the Atmospheric Radiation Measurement (ARM) user facility Southern Great Plains (SGP) site in Lamont, Oklahoma, for 2 months from May to July 2022. The HSR1 is a prototype instrument that measures total (Ftotal) and diffuse (Fdiffuse) spectral irradiance from 360 to 1100 nm with a spectral resolution of 3 nm. The HSR1 spectral irradiance measurements are compared to nearby collocated spectral radiometers, including two multifilter rotating shadowband radiometers (MFRSRs) and the Shortwave Array Spectroradiometer–Hemispheric (SASHe) radiometer. The Ftotal at 500 nm for the HSR1 compared to the MFRSRs has a mean (relative) difference of 0.01 W m−2 nm−1 (1 %–2 %). The HSR1 mean Fdiffuse at 500 nm is smaller than the MFRSRs' by 0.03–0.04 (10 %) W m−2 nm−1. The HSR1 clear-sky aerosol optical depth (AOD) is also retrieved by considering Langley regressions and compared to collocated instruments such as the Cimel sunphotometer (CSPHOT), MFRSRs, and SASHe. The mean HSR1 AOD at 500 nm is larger than the CSPHOT's by 0.010 (8 %) and larger than the MFRSRs' by 0.007–0.017 (6 %–18 %). In general, good agreement between the HSR1 and other instruments is found in terms of the Ftotal, Fdiffuse, and AODs at 500 nm. The HSR1 quantities are also compared at other wavelengths to the collocated instruments. The comparisons are within ∼ 10 % for the Ftotal and Fdiffuse, except for 940 nm, where there is relatively larger disagreement. The AOD comparisons are within ∼ 10 % at 415 and 440 nm; however, a relatively larger disagreement in the AOD comparison is found for higher wavelengths.

Dust Transport from North Africa to the Middle East: Synoptic Patterns and Numerical Forecast

Every year, large quantities of dust are transported from North Africa to the Americas, Europe, and West Asia. The purpose of this study is to analyze four intense and pervasive dust storms that entered the Middle East from Northern Africa. Satellite products, ground-based remote sensing measurements, reanalysis data, and the outputs of the Aire Limitée Adaptation dynamique Développement InterNational-Dust (ALADIN-Dust) and the ICOsahedral Nonhydrostatic weather and climate model with Aerosols and Reactive Trace gases (ICON-ART) forecasting models were synergized. The dust storms originated from different source regions located in the north, northeastern, and central parts of the Sahara Desert. The transport height of the main dust plumes was about 3–5 km, triggered by the westerly zonal winds. The presence of a closed low over the Eastern Mediterranean and the penetration of a deep trough into North Africa at 500 hPa were the main synoptic circulation patterns favoring long-range dust transport during the four dust events. A comparison of aerosol optical depth (AOD) outputs from the two models with satellite data revealed that although both models forecasted dust transport from Africa to the Middle East, they considerably underestimated the AOD values, especially near the dust sources. The ICON-ART model performed slightly better than ALADIN in forecasting these dust storms, and for longer forecasting leading time, although the performance of both models decreased, the superiority of the ICON-ART model became more apparent.

Investigating the long-term trends in aerosol optical depth and its association with meteorological parameters and enhanced vegetation index over Turkey.

Aerosol optical depth (AOD) provides useful information on particulate matter pollution at both regional and global levels. In this study, the long-term datasets of aerosols, meteorological parameters, and enhanced vegetation index (EVI) were used from September 2002 to December 2021 over Turkey. This study examined the spatiotemporal distribution of aerosols and their association with meteorological parameters (temperature (Temp), relative humidity (RH), wind speed (WS)), and EVI over Turkey from 2002 to 2021. Moreover, this study also performed a comparison of AOD retrieved from Aqua with other satellites (Terra, SeaWiFS, and MISR) and ground-based (AERONET) products. The higher mean seasonal AOD (> 0.3) was observed over Southeastern Anatolia Region due to the dust transport from the Saharan Desert and Arabian Peninsula. Moreover, AOD was positively correlated with Temp and WS in the east of Turkey, while negative correlations were observed in the coastal regions. The correlation between AOD and RH was also observed negative in most parts of Turkey. Furthermore, in the coastal region, the correlation between AOD and EVI was found to be positive, whereas a negative correlation was seen over less vegetative areas. The multi-seasonal AOD averages were calculated as 0.187, 0.183, 0.138, and 0.104 for the spring, summer, autumn, and winter seasons, respectively. The most important result of this study is the regional differences in AOD over Turkey. For new studies, AOD should be observed separately for coastal areas and the eastern part of Turkey.

Regime shift in aerosol optical depth and long-term aerosol radiative forcing implications over the Arabian Peninsula Region

The Aerosol Optical Depth (AOD) and aerosol-induced radiative forcing trends inferred for the period 1995–2019 over the Arabian Peninsula region (APR) are extensively studied using the state-of-the-art Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) reanalysis data. We examine the long-term AOD change for five major aerosol species: Dust (DU), Sea Salt (SS), Sulfate (SU), Black Carbon (BC), and Organic Carbon (OC) over the APR. The MERRA-2 AOD comparisons with surface measurements show that it is capable to reproduce the AOD features over APR. The total AOD over the region shows a high value in JJA with the combined effect of DU and SU being major contributors. The total AOD over APR shows an increasing trend at a rate of ∼0.05/decade. Along with an incline in DUAOD, the anthropogenic signature on total AOD also hikes contributed mainly by the SU and OC. The increase in AOD also results in a surge in aerosol-induced atmospheric forcing (ATM) with a trend of 0.13 Wm-2 year−1 and 0.15 Wm-2 year−1 during MAM and JJA respectively. Overall, the study gives a comprehensive picture of the capability of the MERRA-2 in long-term aerosol monitoring over APR, primarily situated in the “dust-belt” region.

Comparison of Aerosol Optical Depth from MODIS Product Collection 6.1 and AERONET in the Western United States

Recent observations reveal that dust storms are increasing in the western USA, posing imminent risks to public health, safety, and the economy. Much of the observational evidence has been obtained from ground-based platforms and the visual interpretation of satellite imagery from limited regions. Comprehensive satellite-based observations of long-term aerosol records are still lacking. In an effort to develop such a satellite aerosol dataset, we compared and evaluated the Aerosol Optical Depth (AOD) from Deep Blue (DB) and Dark Target (DT) product collection 6.1 with the Aerosol Robotic Network (AERONET) program in the western USA. We examined the seasonal and monthly average number of Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua DB AOD retrievals per 0.1∘ × 0.1∘ from January 2003 to December 2017 across the region’s different topographic, climatic, and land cover conditions. The number of retrievals in the southwest United States was on average greater than 37 days per 90 days for all seasons except summer. Springtime saw the highest number of AOD retrievals across the southwest, consistent with the peak season for synoptic-scale dust events. The majority of Arizona, New Mexico, and western Texas showed the lowest number of retrievals during the monsoon season. The majority of collocating domains of AOD from the Aqua sensor showed a better correlation with AERONET AOD than AOD from Terra, and the correlation coefficients exhibited large regional variability across the study area. The correlation coefficient between the couplings Aqua DB AOD-AERONET AOD and Terra DB AOD-AERONET AOD ranges from 0.1 to 0.94 and 0.001 to 0.94, respectively. In the majority of the sites that exhibited less than a 0.6 correlation coefficient and few matched data points at the nearest single pixel, the correlations gradually improved when the spatial domain increased to a 50 km × 50 km box averaging domain. In general, the majority of the stations revealed significant correlation between MODIS and AERONET AOD at all spatiotemporal aggregating domains, although MODIS generally overestimated AOD compared to AERONET. However, the correlation coefficient in the southwest United States was the lowest and in stations from a higher latitude was the highest. The difference in the brightness of the land surface and the latitudinal differences in the aerosol inputs from the forest fires and solar zenith angles are some of the factors that manifested the latitudinal correlation differences.

Country-scale trends in air pollution and fossil fuel CO2 emissions during 2001–2018: confronting the roles of national policies and economic growth

Fossil fuel (FF) burning, the main energy source of the modern world’s economy, remains the major source of anthropogenic carbon dioxide (CO2) and pollutants in the atmosphere. Based on 18 years (2001–2018) of aerosol optical depth (AOD) data from Moderate Resolution Imaging Spectroradiometer satellite, FFCO2 emissions from the Open-Data Inventory for Anthropogenic Carbon dioxide, and gross domestic product (GDP) data from the World Bank, we found that air quality, FF consumption, and economy are strongly bonded at the continental scale but decoupled at the national level under favorable policies. The comparison of AOD vs PM2.5 and NO2 over urbanized areas shows that the pollutants leading to the AOD load can vary significantly by country. A strong connection between GDP and FFCO2 emissions indicates that economic growth deeply replies on FF consumption in most countries. Meanwhile, air pollution is more associated with the growing trend than the level of development of a country. With more mature technologies and renewable energy, economies can keep growing without compromising their environment and population health.

Retrieval of aerosol properties from Airborne Hyper-Angular Rainbow Polarimeter (AirHARP) observations during ACEPOL 2017

Abstract. Multi-angle polarimetric (MAP) imaging of Earth scenes can be used for the retrieval of microphysical and optical parameters of aerosols and clouds. The Airborne Hyper-Angular Rainbow Polarimeter (AirHARP) is an aircraft MAP instrument with a hyper-angular imaging capability of 60 along-track viewing angles at 670 nm and 20 along-track viewing angles at other wavelengths – 440, 550, and 870 nm – across the full 114∘ (94∘) along-track (cross-track) field of view. Here we report the retrieval of aerosol properties using the Generalized Retrieval of Aerosols and Surface Properties (GRASP) algorithm applied to AirHARP observations collected during the NASA Aerosol Characterization from Polarimeter and Lidar (ACEPOL) campaign in October–November 2017. The retrieved aerosol properties include spherical fraction (SF), aerosol column concentration in multiple size distribution modes, and, with sufficient aerosol loading, complex aerosol refractive index. From these primary retrievals, we derive aerosol optical depth (AOD), Angstrom exponent (AE), and single scattering albedo (SSA). AODs retrieved from AirHARP measurements are compared with the High Spectral Resolution LiDAR-2 (HSRL2) AOD measurements at 532 nm and validated with measurements from collocated Aerosol Robotic NETwork (AERONET) stations. A good agreement with HSRL2 (ρ=0.940, |BIAS|=0.062, mean absolute error (MAE) = 0.122) and AERONET AOD (0.010≤MAE≤0.015, 0.002≤|BIAS|≤0.009) measurements is observed for the collocated points. There was a mismatch between the HSRL2- and AirHARP-retrieved AOD for the pixels close to the forest fire smoke source and to the edges of the plume due to spatial mismatch in the sampling. This resulted in a higher BIAS and MAE for the HSRL2 AOD comparison. For the case of AERONET AOD comparison, two different approaches are used in the GRASP retrievals, and the simplified aerosol component-based GRASP/Models kernel which retrieves fewer number of aerosol parameter performed well compared to a more generous GRASP/Five mode approach in the low aerosol loading cases. Forest fire smoke intercepted during ACEPOL provided a situation with homogenous plume and sufficient aerosol loading to retrieve the real part of the refractive index (RRI) of 1.55 and the imaginary part of the refractive index (IRI) of 0.024. The derived SSAs for this case are 0.87, 0.86, 0.84, and 0.81 at wavelengths of 440, 550, 670, and 870 nm, respectively. Finer particles with an average AE of 1.53, a volume median radius of 0.157 µm, and a standard deviation (SD) of 0.55 for fine mode is observed for the same smoke plume. These results serve as a proxy for the scale and detail of aerosol retrievals that are anticipated from future space mission data, as HARP CubeSat (mission begins 2020) and HARP2 (aboard the NASA PACE mission with launch in 2023) are near duplicates of AirHARP and are expected to provide the same level of aerosol characterization.

An algorithm for hyperspectral remote sensing of aerosols: 3. Application to the GEO-TASO data in KORUS-AQ field campaign

This paper describes the third part of a series of investigations to develop algorithms for simultaneous retrieval of aerosol parameters and surface spectral reflectance from GEOstationary Trace gas and Aerosol Sensor Optimization (GEO-TASO) instrument. Since the algorithm is designed for future hyperspectral and geostationary satellite sensors, such as Tropospheric Emissions: Monitoring of Pollution (TEMPO), it is applied to GEO-TASO data measured over the same area by different flights as part of the Korea-United Stated Air Quality Study (KORUS-AQ) field campaign in 2016. While GEO-TASO has a spectral sampling interval of ~0.28 nm in the visible, its data is thinned through a band selection approach with consideration of atmospheric transmittance and different surface types, which yields 20 common spectral bands to be used by the algorithm. The algorithm starts with 4 common principal components (PCs) for surface spectral reflectance extracted from various spectral libraries; constraints of surface reflectance and aerosol model parameters are obtained respectively from k-means clustering analysis of the Rayleigh-corrected GEO-TASO spectra and AERONET data. The algorithm then proceeds iteratively with an optimal estimation approach to update PCs and retrieve aerosol optical depth (AOD) from GEO-TASO measured spectra until state vector converges. The comparison of AODs between GEO-TASO retrievals (y) and 7 AERONET (x) sites reveals that the iterative updates of surface PCs (and so surface reflectance) improve the inversions of fine-mode AOD, fine-mode fraction of AOD, Ångström exponent, and AOD at all (440, 550, 550, 675 nm) wavelengths. At 440 nm, the linear fitting equation, the Pearson correlation coefficient (R2), and mean absolute error are improved respectively from y = 0.72x + 0.11, 0.53, and 0.05 (without update of PCs) to y = 1.055x + 0.01, 0.76, and 0.033. Future work is to prepare the algorithm for TEMPO that carries an enhanced version of GEO-TASO instrument.

Observationally constrained analysis of sea salt aerosol in the marine atmosphere

Abstract. Atmospheric sea salt plays important roles in marine cloud formation and atmospheric chemistry. We performed an integrated analysis of NASA GEOS model simulations run with the GOCART aerosol module, in situ measurements from the PALMS and SAGA instruments obtained during the NASA ATom campaign, and aerosol optical depth (AOD) measurements from the AERONET Marine Aerosol Network (MAN) and from MODIS satellite observations to better constrain sea salt in the marine atmosphere. ATom measurements and GEOS model simulations both show that sea salt concentrations over the Pacific and Atlantic oceans have a strong vertical gradient, varying up to 4 orders of magnitude from the marine boundary layer to free troposphere. The modeled residence times suggest that the lifetime of sea salt particles with a dry diameter of less than 3 µm is largely controlled by wet removal, followed by turbulent process. During both boreal summer and winter, the GEOS-simulated sea salt mass mixing ratios agree with SAGA measurements in the marine boundary layer (MBL) and with PALMS measurements above the MBL. However, comparison of AOD from GEOS with AERONET/MAN and MODIS aerosol retrievals indicated that the model underestimated AOD over the oceans where sea salt dominates. The apparent discrepancy of slightly overpredicted concentration and large underpredicted AOD could not be explained by biases in the model RH affecting the particle hygroscopic growth, as modeled RH was found to be comparable to or larger than the in situ measurements. This conundrum could at least partially be explained by the difference in sea salt size distribution; the GEOS simulation has much less sea salt percentage-wise in the smaller particle size range and thus less efficient light extinction than what was observed by PALMS.

Aerosol optical depth comparison between GAW-PFR and AERONET-Cimel radiometers from long-term (2005–2015) 1 min synchronous measurements

Abstract. A comprehensive comparison of more than 70 000 synchronous 1 min aerosol optical depth (AOD) data from three Global Atmosphere Watch precision-filter radiometers (GAW-PFR), traceable to the World AOD reference, and 15 Aerosol Robotic Network Cimel radiometers (AERONET-Cimel), calibrated individually with the Langley plot technique, was performed for four common or “near” wavelengths, 380, 440, 500 and 870 nm, in the period 2005–2015. The goal of this study is to assess whether, despite the marked technical differences between both networks (AERONET, GAW-PFR) and the number of instruments used, their long-term AOD data are comparable and consistent. The percentage of data meeting the World Meteorological Organization (WMO) traceability requirements (95 % of the AOD differences of an instrument compared to the WMO standards lie within specific limits) is >92 % at 380 nm, >95 % at 440 nm and 500 nm, and 98 % at 870 nm, with the results being quite similar for both AERONET version 2 (V2) and version 3 (V3). For the data outside these limits, the contribution of calibration and differences in the calculation of the optical depth contribution due to Rayleigh scattering and O3 and NO2 absorption have a negligible impact. For AOD >0.1, a small but non-negligible percentage (∼1.9 %) of the AOD data outside the WMO limits at 380 nm can be partly assigned to the impact of dust aerosol forward scattering on the AOD calculation due to the different field of view of the instruments. Due to this effect the GAW-PFR provides AOD values, which are ∼3 % lower at 380 nm and ∼2 % lower at 500 nm compared with AERONET-Cimel. The comparison of the Ångström exponent (AE) shows that under non-pristine conditions (AOD >0.03 and AE <1) the AE differences remain <0.1. This long-term comparison shows an excellent traceability of AERONET-Cimel AOD with the World AOD reference at 440, 500 and 870 nm channels and a fairly good agreement at 380 nm, although AOD should be improved in the UV range.

Evaluation and comparison of multiangle implementation of the atmospheric correction algorithm, Dark Target, and Deep Blue aerosol products over China

Abstract. A new multiangle implementation of the atmospheric correction (MAIAC) algorithm has been applied in the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor and has recently provided globally high-spatial-resolution aerosol optical depth (AOD) products at 1 km. Moreover, several improvements have been modified in the classical Dark Target (DT) and Deep Blue (DB) aerosol retrieval algorithms in MODIS Collection 6.1 products. Thus, validation and comparison of the MAIAC, DT, and DB algorithms are urgent in China. In this paper, we present a comprehensive assessment and comparison of AOD products at a 550 nm wavelength based on three aerosol retrieval algorithms in the MODIS sensor using ground-truth measurements from AErosol RObotic NETwork (AERONET) sites over China from 2000 to 2017. In general, MAIAC products achieved better accuracy than DT and DB products in the overall validation and accuracy improvement of DB products after the QA filter, demonstrating the highest values among the three products. In addition, the DT algorithms had higher aerosol retrievals in cropland, forest, and ocean land types than the other two products, and the MAIAC algorithms were more accurate in grassland, built-up, unoccupied, and mixed land types among the three products. In the geometry dependency analysis, the solar zenith angle, scattering angle, and relative azimuth angle, excluding the view zenith angle, significantly affected the performance of the three aerosol retrieval algorithms. The three products showed different accuracies with varying regions and seasons. Similar spatial patterns were found for the three products, but the MAIAC retrievals were smaller in the North China Plain and higher in Yunnan Province compared with the DT and DB retrievals before the QA filter. After the QA filter, the DB retrievals were significantly lower than the MAIAC retrievals in south China. Moreover, the spatiotemporal completeness of the MAIAC product was also better than the DT and DB products.

Comparison of AOD from CALIPSO, MODIS, and Sun Photometer under Different Conditions over Central China

Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) provides three-dimensional information on aerosol optical properties across the globe. However, the performance of CALIPSO aerosol optical depth (AOD) products under different air quality conditions remains unclear. In this research, three years of CALIPSO level 2 AOD data (November 2013 to December 2017) were employed to compare with the Moderate Resolution Imaging Spectroradiometer (MODIS) level 2 columnar AOD products and ground-based sun photometer measurements for the same time period. To investigate the effect of air quality on AODs retrieved from CALIPSO, the AODs obtained from CALIPSO, MODIS, and sun photometer were inter-compared under different air quality conditions over Wuhan and Dengfeng. The average absolute bias of AOD between CALIPSO and sun photometer was 0.22 ± 0.21, 0.11 ± 0.07, and 0.14 ± 0.13 under clean, moderate, and polluted weather, respectively. The result indicates that the CALIPSO AOD were more reliable under moderate and polluted days. Moreover, the deviation of AOD between CALIPSO and sun photometer was largest (0.23 ± 0.21) in the autumn season, and lowest (0.13 ± 0.12) in the winter season. The results show that CALIPSO AOD products were more applicable to regions and seasons with high aerosol concentrations.

Comparison of aerosol optical depth between observation and simulation from MIROC-SPRINTARS: Effects of temporal inhomogeneous sampling

The global distribution of aerosol optical depth (AOD) is simulated using an aerosol transport model coupled to an atmospheric general circulation model with high spatial and temporal resolution. Daily representative AOD from model simulation is estimated after consideration of observation sampling in daytime (ground-based) and overpass time (satellite) after cloud masking. Large deviations in AOD are found after considering temporally inhomogeneous sampling, with positive differences over desert regions and negative differences over anthropogenic pollution and biomass burning regions. Mean difference in daily AOD of 5.33% (standard deviation of 8.02%), because of temporal inhomogeneous sampling, is identified based on observation time information from the Moderate-Resolution Imaging Spectroradiometer (MODIS). Relative differences in AOD of >50% and >30% were found in 7.9% and 22.8% of the data, respectively. Based on the observation time information from the AERONET, relative root mean square error (rRMSE) of AOD due to temporal inhomogeneous sampling is estimated to be 4.30–18.66%. After correcting for temporal sampling inhomogeneity, the simulated global AOD was compared with AODs from MODIS and AERONET. The simulated AOD becomes lower than MODIS AOD because of emission and transport discrepancies related to dust, a limited accounting of nitrate processes, and limitation errors from MODIS AOD retrieval. A regional positive bias in SPRINTARS AOD was found in biomass burning regions, which is due to transport pattern errors related to the initial injection height of emissions. A weak correlation is found over the regions with multiple aerosol sources because of complex interactions of individual aerosol types.

Comparison of aerosol optical depth from satellite (MODIS), sun photometer and broadband pyrheliometer ground-based observations in Cuba

Abstract. In the present study, we report the first comparison between the aerosol optical depth (AOD) and Ångström exponent (AE) of the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on the Terra (AODt) and Aqua (AODa) satellites and those measured using a sun photometer (AODSP) at Camagüey, Cuba, for the period 2008 to 2014. The comparison of Terra and Aqua data includes AOD derived with both deep blue (DB) and dark target (DT) algorithms from MODIS Collection 6. Combined Terra and Aqua (AODta) data were also considered. Assuming an interval of ±30 min around the overpass time and an area of 25 km around the sun photometer site, two coincidence criteria were considered: individual pairs of observations and both spatial and temporal mean values, which we call collocated daily means. The usual statistics (root mean square error, RMSE; mean absolute error, MAE; median bias, BIAS), together with linear regression analysis, are used for this comparison. Results show very similar values for both coincidence criteria: the DT algorithm generally displays better statistics and higher homogeneity than the DB algorithm in the behaviour of AODt, AODa, AODta compared to AODSP. For collocated daily means, (a) RMSEs of 0.060 and 0.062 were obtained for Terra and Aqua with the DT algorithm and 0.084 and 0.065 for the DB algorithm, (b) MAE follows the same patterns, (c) BIAS for both Terra and Aqua presents positive and negative values but its absolute values are lower for the DT algorithm; (d) combined AODta data also give lower values of these three statistical indicators for the DT algorithm; (e) both algorithms present good correlations for comparing AODt, AODa, AODta vs. AODSP, with a slight overestimation of satellite data compared to AODSP, (f). The DT algorithm yields better figures with slopes of 0.96 (Terra), 0.96 (Aqua) and 0.96 (Terra + Aqua) compared to the DB algorithm (1.07, 0.90, 0.99), which displays greater variability. Multi-annual monthly means of AODta establish a first climatology that is more comparable to that given by the sun photometer and their statistical evaluation reveals better agreement with AODSP for the DT algorithm. Results of the AE comparison showed similar results to those reported in the literature concerning the two algorithms' capacity for retrieval. A comparison between broadband aerosol optical depth (BAOD), derived from broadband pyrheliometer observations at the Camagüey site and three other meteorological stations in Cuba, and AOD observations from MODIS on board Terra and Aqua show a poor correlation with slopes below 0.4 for both algorithms. Aqua (Terra) showed RMSE values of 0.073 (0.080) and 0.088 (0.087) for the DB and DT algorithms. As expected, RMSE values are higher than those from the MODIS–sun photometer comparison, but within the same order of magnitude. Results from the BAOD derived from solar radiation measurements demonstrate its reliability in describing climatological AOD series estimates.

Evaluation and utilization of MODIS and CALIPSO aerosol retrievals over a complex terrain in Himalaya

The study elucidate upon the evaluation of satellite retrievals with ground based aerosol optical depth (AOD) measurements, their utilization in LiDAR ratio (LR) estimation, boundary layer (BL) height determination and the case studies on aerosol transport over Himalayan region. The AOD retrievals from the latest level-2 data collections (C5.1 and C6.0) of MODerate resolution Imaging Spectroradiometer (MODIS) onboard Aqua and Terra satellites and Cloud-Aerosol LiDAR and Infrared Pathfinder Satellite Observations (CALIPSO) versions (4.10 and 3) are subjected for quantitative analysis to assess the level of agreement with the quality assured level-2 ground based AErosol RObotic NETwork (AERONET) measurements over Manora peak (29.36° N, 79.46°E), a high altitude site in the Himalayas. Analysis revealed that the AOD from the latest MODIS Terra C6.0 deep blue (DB) 30km×30km and CALIPSO ver. 4.10 (overpass within ~100km distance) are in a very good agreement (R≥0.9) with that from coincident AERONET measurements averaged over the span of ±30min. About 77% of the AOD retrieved using MODIS and ~87% from CALIPSO were found to be within the expected error (EE) limits. The AOD comparison between MODIS Terra C6.0DB and CALIPSO ver. 4.10, suggested their synergic use for aerosol characterization over Himalayas. In comparison to the ver. 3, CALIPSO ver. 4.10 is found to have undergone substantial changes, and their long term inter-comparison in the grid 28.86°-29.86° N and 78.96°–79.96° E revealed that their vertical feature and aerosol sub-types are in agreement of ~94.6% and ~68.6%, respectively. Utilizing the AOD retrievals from AERONET and MODIS collections, the iteratively computed LR for three LiDAR systems was found to be lower (<16) during winter and higher (>43) during summer. Study on the BL height estimations suggested that the wavelet covariance transform (WCT) method for CALIPSO could be the best choice as compared to the threshold method, and complements well with the specific humidity gradient method used with the radiosonde observation. Case studies on the continental transport of smoke plumes emanating from crop-residue burning in post-monsoon, and long range transport of aerosols and dust over the region in summer are also discussed using the collocated measurements from ground-based AERONET and LiDAR, in conjunction with MODIS, CALIPSO, reanalysis data and trajectory modeling.

Aerosol Property Retrieval Algorithm over Northeast Asia from TANSO-CAI Measurements Onboard GOSAT

The presence of aerosol has resulted in serious limitations in the data coverage and large uncertainties in retrieving carbon dioxide (CO2) amounts from satellite measurements. For this reason, an aerosol retrieval algorithm was developed for the Thermal and Near-infrared Sensor for carbon Observation-Cloud and Aerosol Imager (TANSO-CAI) launched in January 2009 on board the Greenhouse Gases Observing Satellite (GOSAT). The algorithm retrieves aerosol optical depth (AOD), aerosol size information, and aerosol type in 0.1° grid resolution by look-up tables constructed using inversion products from Aerosol Robotic NETwork (AERONET) sun-photometer observation over Northeast Asia as a priori information. To improve the accuracy of the TANSO-CAI aerosol algorithm, we consider both seasonal and annual estimated radiometric degradation factors of TANSO-CAI in this study. Surface reflectance is determined by the same 23-path composite method of Rayleigh and gas corrected reflectance to avoid the stripes of each band. To distinguish aerosol absorptivity, reflectance difference test between ultraviolet (band 1) and visible (band 2) wavelengths depending on AODs was used. To remove clouds in aerosol retrieval, the normalized difference vegetation index and ratio of reflectance between band 2 (0.674 μm) and band 3 (0.870 μm) threshold tests have been applied. To mask turbid water over ocean, a threshold test for the estimated surface reflectance at band 2 was also introduced. The TANSO-CAI aerosol algorithm provides aerosol properties such as AOD, size information and aerosol types from June 2009 to December 2013 in this study. Here, we focused on the algorithm improvement for AOD retrievals and their validation in this study. The retrieved AODs were compared with those from AERONET and the Aqua/MODerate resolution Imaging Sensor (MODIS) Collection 6 Level 2 dataset over land and ocean. Comparisons of AODs between AERONET and TANSO-CAI over Northeast Asia showed good agreement with correlation coefficient (R) 0.739 ± 0.046, root mean square error (RMSE) 0.232 ± 0.047, and linear regression line slope 0.960 ± 0.083 for the entire period. Over ocean, the comparisons between Aqua/MODIS and TANSO-CAI for the same period over Northeast Asia showed improved consistency, with correlation coefficient 0.830 ± 0.047, RMSE 0.140 ± 0.019, and linear regression line slope 1.226 ± 0.063 for the entire period. Over land, however, the comparisons between Aqua/MODIS and TANSO-CAI show relatively lower correlation (approximate R = 0.67, RMSE = 0.40, slope = 0.77) than those over ocean. In order to improve accuracy in retrieving CO2 amounts, the retrieved aerosol properties in this study have been provided as input for CO2 retrieval with GOSAT TANSO-Fourier Transform Spectrometer measurements.

Comparison of AOD, AAOD and column single scattering albedo from AERONET retrievals and in situ profiling measurements

Abstract. Here we present new results comparing aerosol optical depth (AOD), aerosol absorption optical depth (AAOD) and column single scattering albedo (SSA) obtained from in situ vertical profile measurements with AERONET ground-based remote sensing from two rural, continental sites in the US. The profiles are closely matched in time (within ±3 h) and space (within 15 km) with the AERONET retrievals. We have used Level 1.5 inversion retrievals when there was a valid Level 2 almucantar retrieval in order to be able to compare AAOD and column SSA below AERONET's recommended loading constraint (AOD &gt; 0.4 at 440 nm). While there is reasonable agreement for the AOD comparisons, the direct comparisons of in situ-derived to AERONET-retrieved AAOD (or SSA) reveal that AERONET retrievals yield higher aerosol absorption than obtained from the in situ profiles for the low aerosol optical depth conditions prevalent at the two study sites. However, it should be noted that the majority of SSA comparisons for AOD440 &gt; 0.2 are, nonetheless, within the reported SSA uncertainty bounds. The observation that, relative to in situ measurements, AERONET inversions exhibit increased absorption potential at low AOD values is generally consistent with other published AERONET–in situ comparisons across a range of locations, atmospheric conditions and AOD values. This systematic difference in the comparisons suggests a bias in one or both of the methods, but we cannot assess whether the AERONET retrievals are biased towards high absorption or the in situ measurements are biased low. Based on the discrepancy between the AERONET and in situ values, we conclude that scaling modeled black carbon concentrations upwards to match AERONET retrievals of AAOD should be approached with caution as it may lead to aerosol absorption overestimates in regions of low AOD. Both AERONET retrievals and in situ measurements suggest there is a systematic relationship between SSA and aerosol amount (AOD or aerosol light scattering) – specifically that SSA decreases at lower aerosol loading. This implies that the fairly common assumption that AERONET SSA values retrieved at high-AOD conditions can be used to obtain AAOD at low-AOD conditions may not be valid.

The role of cloud contamination, aerosol layer height and aerosol model in the assessment of the OMI near-UV retrievals over the ocean

Abstract. Retrievals of aerosol optical depth (AOD) at 388 nm over the ocean from the Ozone Monitoring Instrument (OMI) two-channel near-UV algorithm (OMAERUV) have been compared with independent AOD measurements. The analysis was carried out over the open ocean (OMI and MODerate-resolution Imaging Spectrometer (MODIS) AOD comparisons) and over coastal and island sites (OMI and AERONET, the AErosol RObotic NETwork). Additionally, a research version of the retrieval algorithm (using MODIS and CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) information as constraints) was utilized to evaluate the sensitivity of the retrieval to different assumed aerosol properties. Overall, the comparison resulted in differences (OMI minus independent measurements) within the expected levels of uncertainty for the OMI AOD retrievals (0.1 for AOD &lt; 0.3, 30 % for AOD &gt; 0.3). Using examples from case studies with outliers, the reasons that led to the observed differences were examined with specific purpose to determine whether they are related to instrument limitations (i.e., pixel size, calibration) or algorithm assumptions (such as aerosol shape, aerosol height). The analysis confirms that OMAERUV does an adequate job at rejecting cloudy scenes within the instrument's capabilities. There is a residual cloud contamination in OMI pixels with quality flag 0 (the best conditions for aerosol retrieval according to the algorithm), resulting in a bias towards high AODs in OMAERUV. This bias is more pronounced at low concentrations of absorbing aerosols (AOD 388 nm ∼ &lt; 0.5). For higher aerosol loadings, the bias remains within OMI's AOD uncertainties. In pixels where OMAERUV assigned a dust aerosol model, a fraction of them (&lt; 20 %) had retrieved AODs significantly lower than AERONET and MODIS AODs. In a case study, a detailed examination of the aerosol height from CALIOP and the AODs from MODIS, along with sensitivity tests, was carried out by varying the different assumed parameters in the retrieval (imaginary index of refraction, size distribution, aerosol height, particle shape). It was found that the spherical shape assumption for dust in the current retrieval is the main cause of the underestimate. In addition, it is demonstrated in an example how an incorrect assumption of the aerosol height can lead to an underestimate. Nevertheless, this is not as significant as the effect of particle shape. These findings will be incorporated in a future version of the retrieval algorithm.

GOCI Yonsei Aerosol Retrieval (YAER) algorithm and validation during the DRAGON-NE Asia 2012 campaign

Abstract. The Geostationary Ocean Color Imager (GOCI) onboard the Communication, Ocean, and Meteorological Satellite (COMS) is the first multi-channel ocean color imager in geostationary orbit. Hourly GOCI top-of-atmosphere radiance has been available for the retrieval of aerosol optical properties over East Asia since March 2011. This study presents improvements made to the GOCI Yonsei Aerosol Retrieval (YAER) algorithm together with validation results during the Distributed Regional Aerosol Gridded Observation Networks – Northeast Asia 2012 campaign (DRAGON-NE Asia 2012 campaign). The evaluation during the spring season over East Asia is important because of high aerosol concentrations and diverse types of Asian dust and haze. Optical properties of aerosol are retrieved from the GOCI YAER algorithm including aerosol optical depth (AOD) at 550 nm, fine-mode fraction (FMF) at 550 nm, single-scattering albedo (SSA) at 440 nm, Ångström exponent (AE) between 440 and 860 nm, and aerosol type. The aerosol models are created based on a global analysis of the Aerosol Robotic Networks (AERONET) inversion data, and covers a broad range of size distribution and absorptivity, including nonspherical dust properties. The Cox–Munk ocean bidirectional reflectance distribution function (BRDF) model is used over ocean, and an improved minimum reflectance technique is used over land. Because turbid water is persistent over the Yellow Sea, the land algorithm is used for such cases. The aerosol products are evaluated against AERONET observations and MODIS Collection 6 aerosol products retrieved from Dark Target (DT) and Deep Blue (DB) algorithms during the DRAGON-NE Asia 2012 campaign conducted from March to May 2012. Comparison of AOD from GOCI and AERONET resulted in a Pearson correlation coefficient of 0.881 and a linear regression equation with GOCI AOD = 1.083 × AERONET AOD − 0.042. The correlation between GOCI and MODIS AODs is higher over ocean than land. GOCI AOD shows better agreement with MODIS DB than MODIS DT. The other GOCI YAER products (AE, FMF, and SSA) show lower correlation with AERONET than AOD, but still show some skills for qualitative use.

Comparisons of aerosol optical depth provided by seviri satellite observations and CAMx air quality modelling

Abstract. Satellite data provide high spatial coverage and characterization of atmospheric components for vertical column. Additionally, the use of air pollution modelling in combination with satellite data opens the challenging perspective to analyse the contribution of different pollution sources and transport processes. The main objective of this work is to study the AOD over Portugal using satellite observations in combination with air pollution modelling. For this purpose, satellite data provided by Spinning Enhanced Visible and Infra-Red Imager (SEVIRI) on-board the geostationary Meteosat-9 satellite on AOD at 550 nm and modelling results from the Chemical Transport Model (CAMx - Comprehensive Air quality Model) were analysed. The study period was May 2011 and the aim was to analyse the spatial variations of AOD over Portugal. In this study, a multi-temporal technique to retrieve AOD over land from SEVIRI was used. The proposed method takes advantage of SEVIRI's high temporal resolution of 15 minutes and high spatial resolution. CAMx provides the size distribution of each aerosol constituent among a number of fixed size sections. For post processing, CAMx output species per size bin have been grouped into total particulate sulphate (PSO4), total primary and secondary organic aerosols (POA + SOA), total primary elemental carbon (PEC) and primary inert material per size bin (CRST_1 to CRST_4) to be used in AOD quantification. The AOD was calculated by integration of aerosol extinction coefficient (Qext) on the vertical column. The results were analysed in terms of temporal and spatial variations. The analysis points out that the implemented methodology provides a good spatial agreement between modelling results and satellite observation for dust outbreak studied (10th -17th of May 2011). A correlation coefficient of r=0.79 was found between the two datasets. This work provides relevant background to start the integration of these two different types of the data in order to improve air pollution assessment.