A new satellite-based global climatology of dust aerosol optical depth

By mass, dust is the largest contributor to global aerosol burden, yet long-term observational records of dust, particularly over the ocean, are limited. Here, two nearly global observational datasets of dust aerosol optical depth τd are created primarily on the basis of optical measurements of the aerosol column from 1) the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Terra satellite spanning from 2001 to 2018 and 2) the Advanced Very High Resolution Radiometer (AVHRR) from 1981 to 2018. The quality of the new data is assessed by comparison with existing dust datasets that are spatially more limited. Between 2001 and 2018, τd decreased over Asia and increased significantly over the Sahara, Middle East, and parts of eastern Europe, with the largest increase found over the Aral Sea where emissive playa surfaces have been exposed. These daily, observational, and nearly global records of dust will allow for improvement in understanding the role of dust in climate variability

Accuracy Assessment of Aqua-MODIS Aerosol Optical Depth Over Coastal Regions: Importance of Quality Flag and Sea Surface Wind Speed

Coastal regions around the globe are a major source for anthropogenic aerosols in the atmosphere, but the underlying surface characteristics are not favorable for the Moderate Resolution Imaging Spectroradiometer (MODIS) algorithms designed for retrieval of aerosols over dark land or open-ocean surfaces. Using data collected from 62 coastal stations worldwide from the Aerosol Robotic Network (AERONET) from approximately 2002-2010, accuracy assessments are made for coastal aerosol optical depth (AOD) retrieved from MODIS aboard Aqua satellite. It is found that coastal AODs (at 550 nm) characterized respectively by the MODIS Dark Land (hereafter Land) surface algorithm, the Open-Ocean (hereafter Ocean) algorithm, and AERONET all exhibit a log-normal distribution. After filtering by quality flags, the MODIS AODs respectively retrieved from the Land and Ocean algorithms are highly correlated with AERONET (with R(sup 2) is approximately equal to 0.8), but only the Land algorithm AODs fall within the expected error envelope greater than 66% of the time. Furthermore, the MODIS AODs from the Land algorithm, Ocean algorithm, and combined Land and Ocean product show statistically significant discrepancies from their respective counterparts from AERONET in terms of mean, probability density function, and cumulative density function, which suggest a need for future improvement in retrieval algorithms. Without filtering with quality flag, the MODIS Land and Ocean AOD dataset can be degraded by 30-50% in terms of mean bias. Overall, the MODIS Ocean algorithm overestimates the AERONET coastal AOD by 0.021 for AOD less than 0.25 and underestimates it by 0.029 for AOD greater than 0.25. This dichotomy is shown to be related to the ocean surface wind speed and cloud contamination effects on the satellite aerosol retrieval. The Modern Era Retrospective-Analysis for Research and Applications (MERRA) reveals that wind speeds over the global coastal region 25 (with a mean and median value of 2.94 meters per second and 2.66 meters per second, respectively) are often slower than 6 meters per second assumed in the MODIS Ocean algorithm. As a result of high correlation (R(sup 2) greater than 0.98) between the bias in binned MODIS AOD and the corresponding binned wind speed over the coastal sea surface, an empirical scheme for correcting the bias of AOD retrieved from the MODIS Ocean algorithm is formulated and is shown to be effective over the majority of the coastal AERONET stations, and hence can be used in future analysis of AOD trend and MODIS AOD data assimilation

Evaluation and Windspeed Dependence of MODIS Aerosol Retrievals Over Open Ocean

The Maritime Aerosol Network (MAN) data set provides high quality ground-truth to validate the MODIS aerosol product over open ocean. Prior validation of the ocean aerosol product has been limited to coastal and island sites. Comparing MODIS Collection 5 ocean aerosol retrieval products with collocated MAN measurements from ships shows that MODIS is meeting the pre-launch uncertainty estimates for aerosol optical depth (AOD) with 64% and 67% of retrievals at 550 nm, and 74% and 78% of retrievals at 870 nm, falling within expected uncertainty for Terra and Aqua, respectively. Angstrom Exponent comparisons show a high correlation between MODIS retrievals and shipboard measurements (R= 0.85 Terra, 0.83 Aqua), although the MODIS aerosol algorithm tends to underestimate particle size for large particles and overestimate size for small particles, as seen in earlier Collections. Prior analysis noted an offset between Terra and Aqua ocean AOD, without concluding which sensor was more accurate. The simple linear regression reported here, is consistent with other anecdotal evidence that Aqua agreement with AERONET is marginally better. However we cannot claim based on the current study that the better Aqua comparison is statistically significant. Systematic increase of error as a function of wind speed is noted in both Terra and Aqua retrievals. This wind speed dependency enters the retrieval when winds deviate from the 6 m/s value assumed in the rough ocean surface and white cap parameterizations. Wind speed dependency in the results can be mitigated by using auxiliary NCEP wind speed information in the retrieval process

Remote sensing of aerosols in the Arctic for an evaluation of global climate model simulations

This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are madeIn this study Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua retrievals of aerosol optical thickness (AOT) at 555 nm are compared to Sun photometer measurements from Svalbard for a period of 9 years. For the 642 daily coincident measurements that were obtained, MODIS AOT generally varies within the predicted uncertainty of the retrieval over ocean (ΔAOT=±0.03±0.05·AOT). The results from the remote sensing have been used to examine the accuracy in estimates of aerosol optical properties in the Arctic, generated by global climate models and from in situ measurements at the Zeppelin station, Svalbard. AOT simulated with the Norwegian Earth System Model/Community Atmosphere Model version 4 Oslo global climate model does not reproduce the observed seasonal variability of the Arctic aerosol. The model overestimates clear-sky AOT by nearly a factor of 2 for the background summer season, while tending to underestimate the values in the spring season. Furthermore, large differences in all-sky AOT of up to 1 order of magnitude are found for the Coupled Model Intercomparison Project phase 5 model ensemble for the spring and summer seasons. Large differences between satellite/ground-based remote sensing of AOT and AOT estimated from dry and humidified scattering coefficients are found for the subarctic marine boundary layer in summer.Peer reviewe

Properties of aerosol and surface derived from OLCI/Sentinel-3A using GRASP approach: Retrieval development and preliminary validation

The Ocean and Land Color Instrument (OLCI) onboard the Copernicus Sentinel-3A satellite is a medium-resolution and multi-spectral push-broom imager acquiring radiance in 21 spectral bands covering from the visible to the far near-infrared. These measurements are primary dedicated to land & ocean color applications, but actually include also reliable information for atmospheric aerosol and surface brightness characterization. In the framework of the EUMETSAT funded study to support the Copernicus Program, we describe the retrieval of aerosol and surface properties from OLCI single-viewing multi-spectral Top-Of-Atmosphere (TOA) radiances based on the Generalized Retrieval of Atmosphere and Surface Properties (GRASP) algorithm. The high potential of the OLCI/GRASP configuration stems from the attempt to retrieve both aerosol load and surface reflectance simultaneously using a globally consistent high-level approach. For example, both over land and ocean surfaces OLCI/GRASP uses 9 spectral channels (albeit with different weights), strictly the same prescribed aerosol models and globally the same a priori constraints (though with some differences for observations over land and ocean). Due to the lack of angular multi-viewing information, the directional properties of underlying surface are strongly constrained in the retrieval: over ocean the Fresnel reflection together with foam/whitecap albedo are exclusively computed using a priori wind speed; over land, the Bidirectional Reflectance Distribution Function (BRDF) is slightly adjusted from a priori values of climatological Ross-Li volumetric and geometric terms. Meanwhile, the isotropic reflectance is retrieved globally under mild spectral smoothness constraints. It should be noticed that OLCI/GRASP configuration employs innovative multi-pixel concept (Dubovik et al., 2011) that enhance retrieval by simultaneously inverting large group of pixels. The concept allows for benefiting from knowledge about natural variability of the retrieved parameters. The obtained OLCI/GRASP products were validated with the Aerosol Robotic Network (AERONET) and Maritime Aerosol Network (MAN) and intercompared with the Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol and surface products. The overall performance is quite comparable to the community-referenced MODIS. Over ocean the OLCI/GRASP results are encouraging with 67% of the AOD (550 nm) satisfying the Global Climate Observing System (GCOS) requirement using AERONET coastal sites and 74% using MAN deep ocean measurements, and an AOD (550 nm) bias 0.01 with AERONET and nearly zero bias with MAN. Over land, 48% of OLCI/GRASP AOD (550 nm) satisfy the GCOS requirement and a bias within ±0.01 for total and AOD < 0.2. Key challenges are identified and discussed: adequate screening of cloud contaminations, retrieval of aerosol over bright surfaces and in the regions containing complex mixtures of aerosol

Estimating the maritime component of aerosol optical depth and its dependency on surface wind speed using satellite data

Six years (2003-2008) of satellite measurements of aerosol parameters from the Moderate Resolution Imaging Spectroradiometer (MODIS) and surface wind speeds from Quick Scatterometer (QuikSCAT), the Advanced Microwave Scanning Radiometer (AMSR-E), and the Special Sensor Microwave Imager (SSM/I), are used to provide a comprehensive perspective on the link between surface wind speed and marine aerosol optical depth over tropical and subtropical oceanic regions. A systematic comparison between the satellite derived fields in these regions allows to: (i) separate the relative contribution of wind-induced marine aerosol to the aerosol optical depth; (ii) extract an empirical linear equation linking coarse marine aerosol optical depth and wind intensity; and (iii) identify a time scale for correlating marine aerosol optical depth and surface wind speed. The contribution of wind induced marine aerosol to aerosol optical depth is found to be dominated by the coarse mode elements. When wind intensity exceeds 4 m/s, coarse marine aerosol optical depth is linearly correlated with the surface wind speed, with a remarkably consistent slope of 0.009±0.002 s/m. A detailed time scale analysis shows that the linear correlation between the fields is well kept within a 12 h time frame, while sharply decreasing when the time lag between measurements is longer. The background aerosol optical depth, associated with aerosols that are not produced in-situ through wind driven processes, can be used for estimating the contributions of terrestrial and biogenic marine aerosol to over-ocean satellite retrievals of aerosol optical depth

APPLICATIONS OF MODERATE-RESOLUTION REMOTE SENSING TECHNOLOGIES FOR SURFACE AIR POLLUTION MONITORING IN SOUTHEAST ASIA

Retrievals from Earth observation satellites are widely used for many applications, including analyzing dynamic lands and measuring atmospheric components. This research aims to evaluate appropriateness of using satellite retrievals to facilitate understanding characteristics of Southeast Asian (SEA) surface air pollution, attributed to regional biomass burnings and urban activities. The studies in this dissertation focused on using satellite retrievals for 1) mapping potential SEA air pollution sources; which are forests, rice paddies, and urban areas, 2) understanding dynamic optical characteristics of SEA biomass-burning aerosols, and 3) inferring surface ozone level. Data used in this study were from three NASA\u27s Earth Observing System (EOS) satellites, which are Terra, Aqua, and Aura. These retrievals have spatial resolution ranging from hundred meters to ten kilometers. Algorithms used for the SEA land cover classification were developed using time-series analyses of surface reflectance in multiple wavelength bands from Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra satellite. Comparing the results to national statistical databases, good agreement was obtained for spatial estimation of forest areas after correction with plantation areas. For estimation of rice paddies areas, the agreement depended on the rice ecosystems. It was good for rainfed rice and poor for deepwater rice. Models for irrigated and upland rice areas showed overall high coefficients of determination, suggesting that they effectively simulated the spatial distribution of those rice paddies; but were prone to underestimate and overestimate, respectively. Estimated SEA regional rice area was 42×106 ha, which agrees with previous published values. Analysis of the satellite retrieval could identify large urban areas. However, the satellite-derived urban areas also incorrectly included large sandy beaches. Optical properties of SEA background aerosols were investigated through the multivariate analyses of long-term ground-based aerosol measurements acquired from Aerosol Robotic Network (AERONET). The results in this study showed that from mid-September to December, the aerosol had both fine size and high light scattering efficiency. It was assumed to be largely urban/industrial aerosols, possibly coming from eastern China. From January to April, the aerosol had fine size and had single scattering albedo (SSA at 440 nm) of approximately 0.9. It was assumed to be smoke from local biomass burning. From October to January, when seasonal winds are strongest, more SEA urban aerosol was observed. This aerosol had coarser size and had SSA of ~0.9 or less. The appropriateness of using Ozone Monitoring Instrument (OMI) aerosol retrieval to facilitate understanding SEA biomass-burning aerosol properties was evaluated through three lines of evidence. These are 1) comparisons between the results obtained from multivariate analyses of the OMI aerosol retrieval and those obtained from the ground-measured AERONET data, 2) from Atmospheric Infrared Sounder (AIRS) total column CO product, and 3) from MODIS active fire detections. The results showed that the OMI retrieval used for large-scale SEA biomass-burning aerosol characterization was consistent with these alternative measures only when 1 \u3c OMI aerosol optical depth (442 nm) \u3c 3. The OMI aerosol retrieval was then used for the study on dynamic characteristics of biomass burning aerosol. This study considered the aerosols from two forest-fire episodes, 2007 SEA continent and 2008 Indonesian fires. Dependence of the aerosol optical properties on four variables was investigated. These variables were 1) wind speed/direction, 2) relative humidity (RH), 3) land use/cover as a surrogate of fuel type estimated from time-series analysis of MODIS surface reflectance, and 4) age of aerosol estimated from spatial-temporal analysis of MODIS active fire and the wind characteristics. Results from Pearson Chi-square test for independence showed that the dependence between aerosol group memberships with different optical properties and the limiting variables was significant for most cases, except for Indonesian aerosol age factor. These results agree with prior knowledge on regional burning conditions (types of fuel and relative humidity) and aerosol chemical/physical properties (chemical composition related to aerosol optical properties and hygroscopicity). Using EOS-Aura tropospheric column ozone (TCO) to infer surface ozone level was evaluated through analyses of linear relationships between TCO estimated from OMI and Microwave Limb Sounder (MLS) retrievals and coincident TCO from balloon-based ozonesonde measurements. This evaluation was for different tropospheric ozone profile shapes and for different geographical regions (for low, mid, and high latitudes and for Pacific and Atlantic regions). Results indicate that inference on ozone level derived from the satellite-based TCO requires corresponding information about tropospheric ozone profile shape. The use of satellite-based TCO was more appropriate for polluted low-latitude locations where upper troposphere ozone is rare and surface enhanced ozone is high

Applying the Dark Target Aerosol Algorithm with Advanced Himawari Imager Observations During the KORUS-AQ Field Campaign

For nearly 2 decades we have been quantitatively observing the Earth's aerosol system from space at one or two times of the day by applying the Dark Target family of algorithms to polar-orbiting satellite sensors, particularly MODIS and VIIRS. With the launch of the Advanced Himawari Imager (AHI) and the Advanced Baseline Imagers (ABIs) into geosynchronous orbits, we have the new ability to expand temporal coverage of the traditional aerosol optical depth (AOD) to resolve the diurnal signature of aerosol loading during daylight hours. The KoreanUnited States Air Quality (KORUS-AQ) campaign taking place in and around the Korean peninsula during MayJune 2016 initiated a special processing of full-disk AHI observations that allowed us to make a preliminary adoption of Dark Target aerosol algorithms to the wavelengths and resolutions of AHI. Here,we describe the adaptation and show retrieval results from AHI for this 2-month period. The AHI-retrieved AOD is collocated in time and space with existing AErosol RObotic NETwork stations across Asia and with collocated Terra and Aqua MODIS retrievals. The new AHI AOD product matches AERONET, and the standard MODIS product does as well, and the agreement between AHI and MODIS retrieved AOD is excellent, as can be expected by maintaining consistency in algorithm architecture and most algorithm assumptions. Furthermore, we show that the new product approximates the AERONET-observed diurnal signature. Examining the diurnal patterns of the new AHI AOD product we find specific areas over land where the diurnal signal is spatially cohesive. For example, in Bangladesh the AOD in-creases by 0.50 from morning to evening, and in northeast China the AOD decreases by 0.25. However, over open ocean the observed diurnal cycle is driven by two artifacts, one associated with solar zenith angles greater than 70t hat may be caused by a radiative transfer model that does not properly represent the spherical Earth and the other artifact associated with the fringes of the 40 degree glint angle mask. This opportunity during KORUS-AQ provides encouragement to move towards an operational Dark Target algorithm for AHI. Future work will need to re-examine masking including snow mask, reevaluate assumed aerosol models for geosynchronous geometry, address the artifacts over the ocean, and investigate size parameter retrieval from the over-ocean algorithm

Investigating organic aerosol loading in the remote marine environment

Aerosol loading in the marine environment is investigated using aerosol composition measurements from several research ship campaigns (ICEALOT, MAP, RHaMBLe, VOCALS and OOMPH), observations of total AOD column from satellite (MODIS) and ship-based instruments (Maritime Aerosol Network, MAN), and a global chemical transport model (GEOS-Chem). This work represents the most comprehensive evaluation of oceanic OM emission inventories to date, by employing aerosol composition measurements obtained from campaigns with wide spatial and temporal coverage. The model underestimates AOD over the remote ocean on average by 0.02 (21 %), compared to satellite observations, but provides an unbiased simulation of ground-based Maritime Aerosol Network (MAN) observations. Comparison with cruise data demonstrates that the GEOS-Chem simulation of marine sulfate, with the mean observed values ranging between 0.22 μg m−3 and 1.34 μg m−3, is generally unbiased, however surface organic matter (OM) concentrations, with the mean observed concentrations between 0.07 μg m−3 and 0.77 μg m−3, are underestimated by a factor of 2–5 for the standard model run. Addition of a sub-micron marine OM source of approximately 9 TgC yr−1 brings the model into agreement with the ship-based measurements, however this additional OM source does not explain the model underestimate of marine AOD. The model underestimate of marine AOD is therefore likely the result of a combination of satellite retrieval bias and a missing marine aerosol source (which exhibits a different spatial pattern than existing aerosol in the model)

Evaluation of Landsat-8 and Sentinel-2A Aerosol Optical Depth Retrievals Across Chinese Cities and Implications for Medium Spatial Resolution Urban Aerosol Monitoring

In urban environments, aerosol distributions may change rapidly due to building and transport infrastructure and human population density variations. The recent availability of medium resolution Landsat-8 and Sentinel-2 satellite data provide the opportunity for aerosol optical depth (AOD) estimation at higher spatial resolution than provided by other satellites. AOD retrieved from 30 m Landsat-8 and 10 m Sentinel-2A data using the Land Surface Reflectance Code (LaSRC) were compared with coincident ground-based Aerosol Robotic Network (AERONET) Version 3 AOD data for 20 Chinese cities in 2016. Stringent selection criteria were used to select contemporaneous data; only satellite and AERONET data acquired within 10 min were considered. The average satellite retrieved AOD over a 1470 m1470 m window centered on each AERONET site was derived to capture fine scale urban AOD variations. AERONET Level 1.5 (cloud-screened) and Level 2.0 (cloud-screened and also quality assured) data were considered. For the 20 urban AERONET sites in 2016 there were 106 (Level 1.5) and 67 (Level 2.0) Landsat-8 AERONET AOD contemporaneous data pairs, and 118 (Level 1.5) and 89 (Level 2.0) Sentinel-2A AOD data pairs. The greatest AOD values (>1.5) occurred in Beijing, suggesting that the Chinese capital was one of the most polluted cities in China in 2016. The LaSRC Landsat-8 and Sentinel-2A AOD retrievals agreed well with the AERONET AOD data (linear regression slopes > 0.96; coefficient of determination r(exp 2) > 0.90; root mean square deviation < 0.175) and demonstrate that the LaSRC is an effective and applicable medium resolution AOD retrieval algorithm over urban environments. The Sentinel-2A AOD retrievals had better accuracy than the Landsat-8 AOD retrievals, which is consistent with previously published research.The implications of the research and the potential for urban aerosol monitoring by combining the freely available Landsat-8 and Sentinel-2 satellite data are discussed