Fig 5 - uploaded by Andrew M. Sayer
Content may be subject to copyright.
Density plots of satellite product vs. satellite product AODs. (a) IASI/SEVIRI, (c) MISR/SEVIRI, (e) MODIS/SEVIRI, (g) IASI/MISR, (i) IASI/MODIS, (k) MODIS/MISR: 'dry' conditions. (b), (d), (f), (h), (j), (l): as for left-hand panels, but for 'moist' conditions. The boundary between moisture regimes is at 20 mm. The dashed lines indicate the lines of best fit for all points, while the diamonds represent the mean y-axis satellite AOD in each 0.1 x-axis AOD bin (for which there are ≥5 points). There are 7580 points in the left panels, 3871 points in the right panels. The biases are y-x.
Source publication
Four aerosol optical depth retrieval algorithms over the Sahara Desert during June 2011 from the IASI, MISR, MODIS, and SEVIRI satellite instruments are compared against each other in order to understand the strengths and weaknesses of each retrieval approach. Particular attention is paid to the effects of meteorological conditions, land surface pr...
Context in source publication
Context 1
... seen between meteorological conditions and AOD are a function of the sensitivity of the retrievals to these conditions? Or, more explicitly, to what extent is the dust activity itself related to these conditions? To address this question we recast the density plots of retrieval vs. retrieval AOD shown in Fig. 4 as a function of column moisture (Fig. 5), to which the majority of retrievals appear most Table of the percentages (out of all points where all four satellite instruments had co-located observations) of points where the two named satellite products agreed that the retrieval was either valid or invalid (due to, for example, cloud presence), or where the two satellite products ...
Similar publications
Dust storms (DS) are considered common environmental phenomenon in numerous countries of the world, especially in the arid and semi-arid regions. DS cause significant impact on human health, climate, the environment and many associated socioeconomic factors. The main goal of this study is to assess the sources of DS in the State of Kuwait. The pres...
Satellite retrievals of atmospheric desert dust have the ability to
capture the spatial and temporal distribution of dust on regional and
global scales, although it is known that retrievals may be sensitive to
variations in the atmospheric state and the background surface.
Observations of dust from satellite instruments played an important role
in...
The Ensemble Adjustment Kalman Filter (EAKF) is used to estimate the
erodibility fraction parameter field in a coupled meteorology and dust
aerosol model (Coupled Ocean Atmosphere Mesoscale Prediction
System-COAMPS) over the Sahara desert. Erodibility is often employed as
the key parameter to map dust source. It is used along with surface
winds (or...
Atmospheric aerosol is important element of atmospheric system and became a major uncertainty in global climate simulation. Therefore proper assessment of aerosol is crucial in current climate diagnostic. In this paper the characteristics of aerosol optical depth (AOD), angstrom exponent (AE) and fine mode fraction (FMF) are derived using MODerate...
The National Meteorological Satellite Center in Korea retrieves land surface temperature (LST) by applying the split-window LST algorithm (CSW_v1.0) to Communication, Ocean, and Meteorological Satellite (COMS) data. Considerable errors were detected under conditions of high water vapor content or temperature lapse rates during validation with Moder...
Citations
... A comparison of VNIR AOD retrievals from MISR and MODIS and TIR retrievals from IASI and SEVERI over North Africa shows that MODIS and IASI tend to perform best at lower AOD, whereas the SEVIRI TIR method performs best at higher AOD, and SEVIRI along with MISR perform best over bright surfaces, when compared to AER-ONET. In addition, sensitivity to surface emissivity, elevation, and moisture also affect the performance of different techniques (Banks et al., 2013). ...
Mineral dust particles suspended in the atmosphere span more than three orders of magnitude in diameter, from <0.1 µm to more than 100 µm. This wide size range makes dust a unique aerosol species with the ability to interact with many aspects of the Earth system, including radiation, clouds, hydrology, atmospheric chemistry, and biogeochemistry. This review focuses on coarse and super-coarse dust aerosols, which we respectively define as dust particles with a diameter of 2.5–10 µm and 10–62.5 µm. We review several lines of observational evidence indicating that coarse and super-coarse dust particles are transported farther than previously expected and that the abundance of these particles is substantially underestimated in current global models. We synthesize previous studies that used observations, theories, and model simulations to highlight the impacts of coarse and super-coarse dust aerosols on the Earth system, including their effects on dust-radiation interactions, dust-cloud interactions, atmospheric chemistry, and biogeochemistry. Specifically, coarse and super-coarse dust aerosols produce a net positive direct radiative effect (warming) at the top of the atmosphere and can modify temperature and water vapor profiles, influencing the distribution of clouds and precipitation. In addition, coarse and super-coarse dust aerosols contribute a substantial fraction of ice-nucleating particles, especially at temperatures above –23 °C. They also contribute a substantial fraction to the available reactive surfaces for atmospheric processing and the dust deposition flux that impacts land and ocean biogeochemistry by supplying important nutrients such as iron and phosphorus. Furthermore, we examine several limitations in the representation of coarse and super-coarse dust aerosols in current model simulations and remote-sensing retrievals. Because these limitations substantially contribute to the uncertainties in simulating the abundance and impacts of coarse and super-coarse dust aerosols, we offer some recommendations to facilitate future studies. Overall, we conclude that an accurate representation of coarse and super-coarse properties is critical in understanding the impacts of dust aerosols on the Earth system.
... Therefore, the main reason for the non-similar RMB in SD and ME is also expected to be the aerosol composition. Coarse-mode aerosols are dominant at sites located in the Arabian Peninsula while the magnitude of coarse-mode aerosols depends on the site location in Africa (Banks et al., 2013;Logothetis et al., 2020), to some extent which is demonstrated by the smaller RMSE (0.035 and 0.075) in ME for fineand coarse-mode AOD products. ...
The latest Multi-angle Imaging Spectro Radiometer (MISR) Version (V) 23 aerosol optical depth (AOD) products were released, with an improved spatial resolution of 4.4 km, providing an unprecedented opportunity for the refined regional application. To ensure the reliability of their applications and build a scientific reference for the further optimization, it is imperative to conduct a comprehensive evaluation, especially for the unique size-resolved AOD products: small-size AOD (AODS, representing the contribution of fine-mode aerosols), medium-size AOD (AODM), and large-size AOD (AODL), and AODM+L represents the AOD part of coarse-mode aerosols. AErosol RObotic NETwork (AERONET) and MODerate-resolution Imaging Spectroradiometer (MODIS) Collection (C) 6.1 aerosol products from 2001 to 2020 are utilized for the validation, analysis, and inter-comparison, considering three spatial scales and four key factors. In general, MISR V23 aerosol products show a good accuracy compared with AERONET. The best performance for all AOD products appears in forest units (the highest R ~ 0.93, data percentage within Expected Error bounds, %EE > 93), related to the inactive human activity and dark underlying surface. Dependences of retrieval deviations illustrate that the performance of MISR AOD deteriorates as aerosol loading increase. Namely, with the increase of aerosols, total AOD (AODT) and AODS show increasing negative deviations, while increasing positive deviations are observed for AODM+L. This suggests that the Empirical Orthogonal Functions do not perform well in this situation, since numerous aerosol particles can obstruct the underlying reflection and reduce the surface spectral contrast. In addition, AODT and AODS often exhibit anomalous positive deviations in areas with low vegetation cover, such as deserts, revealing that MISR will overestimate aerosol content over bright surfaces and in environments dominated by coarse-mode particles. The above findings not only deepen the understanding of MISR aerosols products from multiple perspectives, but also provide useful information for the product improvement.
... A comparison of VNIR AOD retrievals from MISR and MODIS and TIR retrievals from IASI and SEVERI over North Africa shows that MODIS and IASI tend to perform best at lower AOD, whereas the SEVIRI TIR method performs best at higher AOD, and SEVIRI along with MISR preform best over bright surfaces, when compared to AERONET. In addition, sensitivity to surface emissivity, elevation, and moisture also affect the performance of different techniques (Banks et al., 2013). ...
Mineral dust particles suspended in the atmosphere span more than three orders of magnitude in diameter, from less than 0.1 µm to more than 100 µm. This wide size range makes dust a unique aerosol species with the ability to interact with many aspects of the Earth system, including radiation, clouds, hydrology, atmospheric chemistry, and biogeochemistry. This review focuses on coarse and super-coarse dust aerosols, which we respectively define as dust particles with a diameter between 2.5 - 10 µm and 10 - 62.5 µm. We review several lines of observational evidence indicating that coarse and super-coarse dust particles are transported farther than previously expected and that the abundance of these particles is substantially underestimated in current global models. We synthesize previous studies that used observations, theories, and model simulations to highlight the impacts of coarse and super-coarse dust aerosols on the Earth system, including their effects on dust-radiation interactions, dust-cloud interactions, and atmospheric chemistry, and biogeochemistry. In addition, we examine several limitations in the representation of coarse and super-coarse dust aerosols in current model simulations and in remote-sensing retrievals. Because these limitations substantially contribute to the uncertainties in simulating the abundance and impacts of coarse and super-coarse dust aerosols, we offer some recommendations to facilitate future studies. Overall, we conclude that an accurate representation of coarse and super-coarse properties is critical in understanding the overall impacts of dust aerosols on the Earth system.
... Some focused on the Ganga Basin in India [3], others on Central China [4], on Latin America [5] or validated a specific satellite dataset over Turkey [6]. Among the several published papers that were dedicated to investigate aerosols in Africa (i.e., in West Africa [7], at Durban, South Africa [8], and covering a particular event in June 2011 over the west African Sahara [9,10]), some have directly concerned Morocco. ...
The present study investigates the optical properties of aerosols on daily and seasonal scales with the use of the aerosol optical depth (AOD) and Angström exponent (AE) data retrieved from AErosol RObotic NETwork (AERONET) and collected at four stations in Southern Morocco—Saada (31.63° N; 8.16° W), Ouarzazate (30.93° N; 6.91° W), Oukaïmeden (31.21° N; 7.86° W) and Ras-El-Aïn (31.67° N; 7.60° W). An evaluation of the aerosol volumetric size distribution (AVSD) is also obtained for Saada and Ouarzazate. An AOD inter-comparison is performed between AERONET data and satellite sensors (MODerate resolution Imaging Spectroradiometer—MODIS), as well as assimilation products (Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) and Copernicus Atmosphere Monitoring Service (CAMS)), by the means of a linear regression. Regardless of site location and elevation, the results show the prevalence of the annual cycle of AOD, with a maximum in summer and a minimum in winter. In association with this seasonal variation, the variations in AE and AVSD showed an increase in coarse mode over Ouarzazate and Saada during summer (July to August), underlining that Southern Morocco is prone to the regular transport of desert dust on a seasonal basis. The inter-comparison reveals that the MERRA-2 dataset is slightly more appropriate for the study region, since it shows correlation coefficients (r) ranging from 0.758 to 0.844 and intercepts ranging from 0.021 to 0.070, depending on the study site. The statistical analysis of the back-trajectories simulated by the HYbrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model were consistent with the observations and confirmed the dominance of desert dust aerosols during the summer over the study region. On the other hand, the winter season reveals a predominance of anthropogenic and oceanic aerosols originating from the north and the west of the study site.
... With the advancement of science and technology, a series of satellites has been successfully launched, and the pieces of remote sensing equipment carried by them have realized the vertical monitoring of aerosols. Therefore, most scholars studied dust events based on the aerosol optical depth (AOD) obtained from the secondary product of satellites (Banks et al., 2013;Feng et al., 2015;Long et al., 2015;Guo et al., 2017;Reiji, 2018). However, the relationship between the temporal and spatial variability of the AOD and the ground-monitoring particulate matter varies with places (Li et al., 2014a;Li et al., 2015;Xu et al., 2021) and seasons (Schafer et al., 2008;Li et al., 2014b;Hu et al., 2016;Ma et al., 2016). ...
In order to improve the accuracy of dust storm prediction and reduce the damage and losses by a dust storm event, it is necessary to conduct an in-depth study on the same. The data of the national air quality stations, backward trajectories generated by the Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT), and the lidar network data from Wuwei, Baiyin, and Dingxi were used to study a large-scale dust storm event that occurred from 12 to 14 May 2019. This study explores the cause of the dust storm and physical characteristics of dust aerosols in three-dimensional space, as well as its impact on air quality. Results show that the dust storm was caused by the eastward movement of the East Asian trough and affected most cities in northern China from northwest to southeast. Consequently, the air quality deteriorated seriously, especially over the Hexi Corridor. The hourly peak concentrations of PM10 in Wuwei and Baiyin were close to 3,000 μg·m⁻³. The observations from the lidar network show that the dust intensities were similar at different cities, and their extinction coefficients were close. However, the depolarization ratio varied with sources and the physical characteristics of dust particles. According to the simulation results of extinction coefficients and particle concentrations, due to the impact of dust transported at high altitudes, the concentration of particles in Dingxi did not decrease with the increase in altitude. The particle concentrations from ground-based monitoring were lower than those of Baiyin and Wuwei, while particle concentrations above 0.3 km were higher than those of Baiyin and Wuwei.
... North Africa/Middle East (NAME) is the world's largest mineral dust aerosol source (Banks et al., 2013;Hsu et al., 2006). Since DB was originally designed for bright surface like desert (Hsu et al., 2004), the total matchups of DB is significantly larger than that of DT, and correlation R and EE within ratio of DB are also higher than those of DT as expected. ...
... DTB generally has better statistics than DB and DT, including higher correlation R and EE within ratio, larger matchups, and lower median bias. South Africa (SAF) has various aerosol sources, like the transported dust from NAME in the northern part and locally biomass burning aerosols in the southern part (Banks et al., 2013;Hansell et al., 2007). Correlation R for all products over SAF is higher than the global average while EE within ratio is slightly lower. ...
... Better performance is observed over forest, savannas, cropland, and urban while relatively poorer statistics (lower R and EE within ratio) are observed over barren. A relatively large positive bias is also observed over barren for all products, indicating that further modification on surface radiance correction and aerosol model is necessary to fill the gap (Banks et al., 2013;Sayer et al., 2019;Wei et al., 2019). DT shows the poorest performance over barren with the lowest correlation R and EE within ratio (<0.4) as expected, but it is our expectation that DB shows better performance than DT over 'dark' surfaces like forest and savannas, which agrees well with the comparison work from Wei et al. (2019) that MODIS C6.1 DB retrievals show similar good or even better performance than the DT and DTB retrievals for densely vegetated areas. ...
This study presents a comprehensive evaluation of eight aerosol optical depth (AOD) products from the latest MODIS C6.1 DT, DB and DTB, MISR V23, and VIIRS V1 DB dataset against the Aerosol Robotic Network (AERONET) measurements on global scale during 2012 to 2019. The latest MODIS DB products are found to be superior over DT in most cases. MODIS DTB products generally have a better performance than either DT or DB. VIIRS shows the best overall performance on global and regional scale while MISR has a systematic underestimation in moderate and high AOD conditions. Median AOD bias shows distinct regional dependence with the biggest divergence between satellite AOD products appearing in Asia. All these AOD products tend to have better performance in high latitude region and poorer performance in the tropics likely due to the complex aerosol condition and common high cloud cover in the tropics. Time series stability evaluation shows a distinct temporal pattern of statistics, in which the observation number and median AOD bias tend to be high in summer while low in winter and correlation R has a reversing trend. Among these products, VIIRS V1 DB has the highest time series stability of bias. Influence of aerosol loading, particle size, land use, elevation, and precipitable water and temperature on AOD retrievals is broadly consistent between products. High aerosol loading, small particle size, bright surface, high altitude, and high precipitable water and temperature tend to decrease the retrieval accuracy, e.g. lower expected error (EE) within ratio and larger median bias. The latest AOD products need to be furthermore improved under extreme conditions like very fine aerosols, elevated terrain and high precipitable water and temperature.
... It is important to mention that MERRA-2 assimilated MISR data until June 2014 above regions characterized by high surface albedo [51]. However, MISR data are overestimated compared to both MODIS-Terra and Aqua in North Africa [121,122], which may produce discontinuity and affect the AOD there. To examine this, we compared the total AOD derived from MODIS-Terra, MODIS-Aqua and MISR and we found that after the cessation of the MISR assimilation, MERRA-2 AOD approached that of MODIS-Terra and Aqua (results not shown here). ...
We assess the 40-year climatological clear-sky global direct radiative effect (DRE) of five main aerosol types using the MERRA-2 reanalysis and a spectral radiative transfer model (FORTH). The study takes advantage of aerosol-speciated, spectrally and vertically resolved optical properties over the period 1980–2019, to accurately determine the aerosol DREs, emphasizing the attribution of the total DREs to each aerosol type. The results show that aerosols radiatively cool the Earth’s surface and heat its atmosphere by 7.56 and 2.35 Wm−2, respectively, overall cooling the planet by 5.21 Wm−2, partly counterbalancing the anthropogenic greenhouse global warming during 1980–2019. These DRE values differ significantly in terms of magnitude, and even sign, among the aerosol types (sulfate and black carbon aerosols cool and heat the planet by 1.88 and 0.19 Wm−2, respectively), the hemispheres (larger NH than SH values), the surface cover type (larger land than ocean values) or the seasons (larger values in local spring and summer), while considerable inter-decadal changes are evident. These DRE differences are even larger by up to an order of magnitude on a regional scale, highlighting the important role of the aerosol direct radiative effect for local and global climate.
... The dust RGB imagery was made by referring to the dust RGB recipe based on Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI) developed by EUMETSAT. The BTD between the 12.3 μm and 10.4 μm channels is applied for the red (R) component, while the BTD of 10.4 μm and 8.6 μm channels is applied for the green (G) component (Lensky and Rosenfeld 2008;Banks et al. 2013). The BTD of the 10.4μm and 13.3 μm channels is applied for the blue (B) component for the clear-sky and the high cloud tests, unlike the recipe from MSG SEVIRI (Ganci et al. 2011). ...
... The ability to continuously monitor the progression of a dust storm when using dust RGB imagery from GEO satellites can help overcome some of the color ambiguity in dust RGB imagery. Thus, it is common to use the dust RGB imagery for validation of the spatial distribution of a dust storm (Fuell et al. 2016;Ashpole and Washington 2012;Banks et al. 2013;Miller et al. 2017). ...
A combined algorithm comprising multiple dust detection methods was developed using infrared (IR) channels onboard the GEOstationary Korea Multi-Purpose SATellite 2A equipped with the Advanced Meteorological Imager (GK2A/AMI). Six cloud tests using brightness temperature difference (BTD) were utilized to reduce errors caused by clouds. For detecting dust storms, three standard BTD tests (i.e., $${BT}_{12.3}-{BT}_{10.5}$$ , $${BT}_{8.7}-{BT}_{10.5}$$ , and $${BT}_{11.2}-{BT}_{10.5}$$ ) were combined with the polarized optical depth index (PODI). The combined algorithm normalizes the indices for cloud and dust detection, and adopts weighted combinations of dust tests depending on the observation time (day/night) and surface type (land/sea). The dust detection results were produced as quantitative confidence factors and displayed as false color imagery, applying a dynamic enhancement background reduction algorithm (DEBRA). The combined dust detection algorithm was qualitatively assessed by comparing it with dust RGB imageries and ground-based lidar data. The combined algorithm especially improved the discontinuity in weak dust advection to the sea and considerably reduced false alarms as compared to previous dust monitoring methods. For quantitative validation, we used aerosol optical thickness (AOT) and fine mode fraction (FMF) derived from low Earth orbit (LEO) satellites in daytime. For both severe and weakened dust cases, the probability of detection (POD) ranged from 0.667 to 0.850 and it indicated that the combined algorithm detects more potential dust pixels than other satellites. In particular, the combined algorithm was advantageous in detecting weak dust storms passing over the warm and humid Yellow Sea with low dust height and small AOT.
... Satellite sensors have emerged as the most efficient and powerful tools to identify the sources of atmospheric dust (Banks et al., 2013;Ginoux et al., 2012;Schepanski et al., 2012). The Moderate Resolution Imaging Spectroradiometer (MODIS) sensor measures columnar aerosol properties with a cross-track resolution ∼2,330 km, onboard the National Atmospheric Space Agency (NASA) polar-orbiting Terra and Aqua satellites. ...
Mineral dust emitted from the arid regions of the Arabian Peninsula (AP), in particular Kingdom of Saudi Arabia (KSA), is an important contributor to the northern hemispheric aerosol loading. Dust events over AP are frequent and persistent throughout the year, with a peak in occurrence and intensity between March and August. This study examines the variability of dust events that occurred over AP during 2003–2017 using long‐term dust optical depth retrieved from MODIS satellite measurements. Dust profiles were derived from CALIOP satellite measurements to assess the vertical distributions of the dust events. Our analysis suggests that the formation of extreme dust events is primarily associated with strong high‐pressure systems that occur over AP. Northerly Shamal winds transport dust aerosols from surrounding arid regions to the AP, amplifying the dust aerosol loading across the country. CALIOP dust profiles show that the dust aerosols reach up to 4 km height above sea level, with peak concentrations at an altitude around 1.5 km. Dry deposition of dust is the dominant removal process over the Arabian Gulf, and wet deposition of dust is the dominant removal process over the Red Sea. A total of 49 extreme dust events occurred during the period between 2003 and 2017, over a combined total of 207 days. We observe a significant increase in the frequency of dust events between 2007 and 2012, peaking in 2012, followed by a marked decrease in the following years. We attribute this sudden decline in dust activity after 2012 to enhanced winter rainfall, after noticing increased soil moisture and vegetation coverage during the dust seasons that followed wetter winters. A strengthened Red Sea trough in the middle and the upper altitudes produced favorable conditions for strong moisture convergence and increased rainfall over AP, which may have dampened dust activity during 2013–2017.
... There is general agreement on large scales, but regionally, differences can still be significant (Li et al., 2009;Prasad & Singh, 2007;Boiyo et al., 2017;Kahn et al., 2010;Tao et al., 2015;Li et al., 2019;Wang et al., 2017;Wei et al., 2018;. Discrepancies are also observed among different satellite data sets (Banks et al., 2013;Bibi et al., 2015;de Leeuw et al., 2015;de Leeuw et al., 2018). Moreover, even for the monthly mean product in which random errors have been largely averaged out, there are still disagreements. ...
Satellite‐ and ground‐based remote sensing are two widely used techniques to measure aerosol properties. However, neither is perfect in that satellite retrievals suffer from various sources of uncertainties, and ground observations have limited spatial coverage. In this study, focusing on improving estimates of aerosol information on large scale, we develop a data synergy technique based on the ensemble Kalman filter (EnKF) to effectively combine these two types of measurements and yield a monthly mean aerosol optical depth (AOD) product with global coverage and improved accuracy. We first construct a 474‐member ensemble using 11 monthly mean AOD data sets to represent the variability of the AOD field. Then Moderate Resolution Imaging Spectroradiometer AOD retrievals are selected as the background field into which ground‐based measurements from 135 Aerosol Robotic Network sites are assimilated using the EnKF. Compared with satellite data, the bias and root‐mean‐square errors of the combined field are greatly reduced, and correlation coefficients are greatly improved. Moreover, cross validation shows that at locations where surface observations were not assimilated, the reduction in root‐mean‐square error and bias and the increase in correlation can still reach ~20%. Locations where the spatial representativeness of AOD is large or the site density is high are where the greatest changes are typically found. This study shows that the EnKF technique effectively extends the information obtained at surface sites to a larger area, paving the way for combining information from different types of measurements to yield better estimates of aerosol properties as well as their space‐time variability.
