Total Aerosol Optical Depth Research Articles

Direct and semi-direct radiative forcing of biomass-burning aerosols over the southeast Atlantic (SEA) and its sensitivity to absorbing properties: a regional climate modeling study

Abstract. Simulations are performed for the period 2000–2015 by two different regional climate models, ALADIN and RegCM, to quantify the direct and semi-direct radiative effects of biomass-burning aerosols (BBAs) in the southeast Atlantic (SEA) region. Different simulations have been performed using strongly absorbing BBAs in accordance with recent in situ observations over the SEA. For the July–August–September (JAS) season, the single scattering albedo (SSA) and total aerosol optical depth (AOD) simulated by the ALADIN and RegCM models are consistent with the MACv2 climatology and MERRA-2 and CAMS-RA reanalyses near the biomass-burning emission sources. However, the above-cloud AOD is slightly underestimated compared to satellite (MODIS and POLDER) data during the transport over the SEA. The direct radiative effect exerted at the continental and oceanic surfaces by BBAs is significant in both models and the radiative effects at the top of the atmosphere indicate a remarkable regional contrast over SEA (in all-sky conditions), with a cooling (warming) north (south) of 10 ∘S, which is in agreement with the recent MACv2 climatology. In addition, the two models indicate that BBAs are responsible for an important shortwave radiative heating of ∼0.5–1 K per day over SEA during JAS with maxima between 2 and 4 km a.m.s.l. (above mean sea level). At these altitudes, BBAs increase air temperature by ∼0.2–0.5 K, with the highest values being co-located with low stratocumulus clouds. Vertical changes in air temperature limit the subsidence of air mass over SEA, creating a cyclonic anomaly. The opposite effect is simulated over the continent due to the increase in lower troposphere stability. The BBA semi-direct effect on the lower troposphere circulation is found to be consistent between the two models. Changes in the cloud fraction are moderate in response to the presence of smoke, and the models differ over the Gulf of Guinea. Finally, the results indicate an important sensitivity of the direct and semi-direct effects to the absorbing properties of BBAs. Over the stratocumulus (Sc) region, DRE varies from +0.94 W m−2 (scattering BBAs) to +3.93 W m−2 (most absorbing BBAs).

The Relationship between Ultraviolet Radiation and Meteorological Factors and Atmospheric Turbidity: Part I. Role of Total Ozone Content, Clouds, and Aerosol Optical Depth

We analyze the interrelation between the daily UV–B radiation and a number of factors determining the absorption of UV radiation in the atmosphere (total ozone content (TOC), cloud amount, and aerosol optical depth (AOD)). This is done using a homogeneous time series of measurements of UV–B radiation at the Tropospheric Ozone Research (TOR) station of the Institute of Atmospheric Optics, Siberian Branch, Russian Academy of Sciences, from 2003 to 2016, satellite data on TOC, AOD data from the AERONET network, and data on cloud cover from the meteorological site of the Institute of Monitoring of Climatic and Ecological Systems, Siberian Branch, Russian Academy of Sciences. The regression equations are obtained, relating the increment of the diurnal intake of UV-B radiation as a function of the increment of TOC under different cloud conditions and atmospheric transparency.

Long-Term Variation of Black Carbon Absorption Aerosol Optical Depth from AERONET Data over East Asia

Absorption aerosol optical depth induced by black carbon (AAODBC) was retrieved using the depolarization ratio and single scattering albedo provided by the Aerosol Robotic Network (AERONET) inversion products over East Asia. Our analysis considered AERONET data from six sites in East Asia that are mostly affected by anthropogenic pollution, black carbon (BC) emissions, and natural mineral dust, during the period 2001–2018. We identified a rapid reduction in total aerosol optical depth (AODT) of −0.0106 yr−1 over Beijing, whereas no considerable trend was observed at the Korean and Japanese sites. The long-term data for AAODBC showed decreasing trends at all sites. We conclude that successful emission control policies were the major underlying driver of AODT and AAODBC reductions over East Asia, particularly in China, during the study period. Values of the AAODBC/AODT ratio revealed that, although these policies were successful, the Chinese government needs to undertake stricter measures toward reducing BC emissions. We found that AAODBC follows seasonal trends, peaking in the colder months. This suggests that in East Asia, particularly in China, domestic coal burning is still of concern.

Analysis of aerosol optical depth over Bahrain and Eastern Province of Saudi Arabia based on MERRA-2 model

Spatial and temporal variability of aerosol optical depth (AOD) together with aerosol-type specification were analyzed over Eastern Province of Kingdom of Saudi Arabia (KSA) and Bahrain from 2008 to 2019. To investigate study region with more details, the Eastern Province of Saudi Arabia and Bahrain was divided into three and four zones, respectively. This work utilized comprehensive satellite-based air quality data using NASA’s Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) model. The retrieved total AOD data exhibited relatively lower average values in the Bahraini zones in comparison with the Eastern KSA during the study period. The monthly total AOD values in Bahraini zones were in the range of 0.20 and 0.87, while they were in the range of 0.23 and 0.91 in KSA zones. The AOD values were positively correlated with ambient air temperature (r = 0.43), while they were negatively correlated with relative humidity (r = 0.59) in Bahrain. Seasonal wind rose diagrams for Bahrain and monthly synoptic maps of (20–40°N, 40–60°E) West Asia region demonstrates that dominant wind direction is from NNW to Bahrain. The data assimilation algorithms in MERRA-2 showed that the major aerosol species that contributed to total AOD were as follows: mineral dust (68–74%), sulfate (17–20%), organic carbon (4–5%), sea salt (3–5%) and black carbon (2%). Monthly, seasonal and annual variations of speciated AOD values assisted in understanding aerosols loading over study area.

Spatiotemporal regionalization of atmospheric dust based on multivariate analysis of MACC model over Iran

Extraordinary dry conditions on the desert and arid areas in Iran, along with strong influences from surrounding dust sources in the Middle East and Arabia, have exposed the country to substantial amounts of dust aerosols with serious impacts on environment, health and socio-economic aspects. Considering this threat, daily aerosol optical depth (AOD) data over Iran obtained from the Monitoring Atmospheric Composition and Climate (MACC) reanalysis during 2003–2012 were used to analyze the spatial and temporal patterns of total AOD (TAOD) and dust AOD (DAOD). This study identifies the areas mostly affected by TAOD and DAOD in terms of daily average values and the areas associated with distinct temporal patterns, utilizing S-mode and T-mode principal component analysis (PCA). The analysis reveals six distinct sub-regions in southeast, west-northwest, northeast, east, central and southwest of Iran, which are among the major centers influenced by TAOD and DAOD extremes. The main findings of the T-mode results, consistent with TAOD and DAOD S-mode patterns, are (i) the maximum dust loading over the eastern, southeastern and southwestern subregions in March and May, (ii) dust loading with peaks in November over the eastern and northeastern sub-regions; (iii) maximum number of dusty days in July and August over southwest, (iv) maximum dust in July over southeastern and Central Iran, (v) a dust pattern with identical extent over the west and northwest sub-region in March and October and, (vi) a prevailing dust loading over the dry areas (Lut desert, Sistan plain and southwest edge of the territory) in October. The spatiotemporal evolution of dust is a function of the growth and expansion of dust extremes originated from various sources in Iran and the Middle East. The PCA methodology, through simplification of aerosol distribution to simpler structures, was also incorporated to provide a geographical interpretation of the highly sensitive territory of Iran.

A feasibility study to use machine learning as an inversion algorithm for aerosol profile and property retrieval from multi-axis differential absorption spectroscopy measurements

Abstract. In this study, we explore a new approach based on machine learning (ML) for deriving aerosol extinction coefficient profiles, single-scattering albedo and asymmetry parameter at 360 nm from a single multi-axis differential optical absorption spectroscopy (MAX-DOAS) sky scan. Our method relies on a multi-output sequence-to-sequence model combining convolutional neural networks (CNNs) for feature extraction and long short-term memory networks (LSTMs) for profile prediction. The model was trained and evaluated using data simulated by Vector Linearized Discrete Ordinate Radiative Transfer (VLIDORT) v2.7, which contains 1 459 200 unique mappings. From the simulations, 75 % were randomly selected for training and the remaining 25 % for validation. The overall error of estimated aerosol properties (1) for total aerosol optical depth (AOD) is -1.4±10.1 %, (2) for the single-scattering albedo is 0.1±3.6 %, and (3) for the asymmetry factor is -0.1±2.1 %. The resulting model is capable of retrieving aerosol extinction coefficient profiles with degrading accuracy as a function of height. The uncertainty due to the randomness in ML training is also discussed.

High spatial resolution WRF-Chem model over Asia: Physics and chemistry evaluation

The representation of air quality and meteorology over Asia remains challenging for chemical transport models as a result of the complex interactions between the East Asian monsoons and the large uncertainty (in space and time) of the high anthropogenic emissions levels over the region. High spatial resolution models allow resolving small-scale features induced by the complex topography of this region. In this study, the Weather Research and Forecasting model with Chemistry (WRF-Chem) was used to simulate the spatial and seasonal variability of main physical and chemical variables over Asia for the year 2015 at 8-km horizontal resolution to enable resolving small-scale features induced by the region complex topography. The simulated atmospheric composition was evaluated against satellite retrievals (MOPITT, IASI + GOME2, MODIS and OMI) in addition to ground-based observations in China for the year 2015, while the meteorological variables were evaluated by several observational-based datasets (ERA5, CRU, MODIS, MTE). Results showed low to moderate seasonal biases for major meteorological variables, i.e. air temperature, relative humidity, precipitation, latent heat, sensible heat and snow cover fraction. Overall, WRF-Chem reproduced well the spatial and seasonal variability of lowermost tropospheric ozone content, total column carbon monoxide and aerosol optical depth, while large discrepancies were found for tropospheric nitrogen dioxide content, mainly during the warm season. In consistency with previous studies, the different biases between model-simulated and satellite-retrieved values can be mainly attributed to i) the large uncertainties in anthropogenic and natural nitrogen oxides emission estimates, as well as dust and sea salt emissions in the case of aerosol optical depth, and ii) some coarse parameterizations used to reproduce main small-scale features (e.g. meteorology, chemical processes, dry deposition to vegetation). Compared to ground-based observations, the WRF-Chem model reproduced well the mean annual cycle of surface nitrogen dioxide, ozone and fine particles concentrations in all seasons across China. Our results suggest that WRF-Chem provides reliable spatio-temporal patterns for most of the meteorological and chemical variables, adding thus confidence to its applicability in the context of air pollution risk assessment to human and ecosystems health.

A Multi Linear Regression Model to Derive Dust PM10 in the Sahel Using AERONET Aerosol Optical Depth and CALIOP Aerosol Layer Products

Due to a limited number of monitoring stations in Western Africa, the impact of mineral dust on PM10 surface concentrations is still poorly known. We propose a new method to retrieve PM10 dust surface concentrations from sun photometer aerosol optical depth (AOD) and CALIPSO/CALIOP Level 2 aerosol layer products. The method is based on a multi linear regression model that is trained using co-located PM10, AERONET and CALIOP observations at 3 different locations in the Sahel. In addition to the sun photometer AOD, the regression model uses the CALIOP-derived base and top altitude of the lowermost dust layer, its AOD, the columnar total and columnar dust AOD. Due to the low revisit period of the CALIPSO satellite, the monthly mean annual cycles of the parameters are used as predictor variables rather than instantaneous observations. The regression model improves the correlation coefficient between monthly mean PM10 and AOD from 0.15 (AERONET AOD only) to 0.75 (AERONET AOD and CALIOP parameters). The respective high and low PM10 concentration during the winter dry season and summer season are well produced. Days with surface PM10 above 100 μg/m3 are better identified when using the CALIOP parameters in the multi linear regression model. The number of true positives (actual and predicted concentrations above the threshold) is increased and leads to an improvement in the classification sensitivity (recall) by a factor 1.8. Our methodology can be extrapolated to the whole Sahel area provided that satellite derived AOD maps are used in order to create a new dataset on population exposure to dust events in this area.

How Long Is Too Long? Variogram Analysis of AERONET Data to Aid Aerosol Validation and Intercomparison Studies

AbstractGeophysical data sets derived from satellite sensors, ground/airborne instrumentation, and computational models are often compared against each other. A common example is the validation of satellite aerosol optical depth (AOD) retrievals against measurements from Aerosol Robotic Network (AERONET) Sun photometers. Spatiotemporal mismatch between data set sampling means that uncaptured variation in the underlying geophysical field introduces apparent disagreement into such comparisons, known as representation or collocation matchup uncertainty. This study uses variogram analysis of AERONET data to estimate temporal mismatch uncertainties and decorrelation time scales for the global AERONET record. As well as total AOD, the fine‐ and coarse‐mode AODs, Ångström Exponent (AE), and fine‐mode fraction (FMF) of AOD are analyzed. Globally, a time difference of 30 min typically induces from 0.011–0.035 variation in AOD. For total, fine, and coarse AODs the typical time to decorrelation is around 2–10 days. For AE and FMF it is 3–33 days; that is, aerosol systems often persist significantly longer than individual events in them. Biomass burning regions tend to show the largest and fastest subdaily AOD variability and also longest times to decorrelation. Some sites show significant season‐to‐season variations in behavior. These results can be used to inform site‐specific time collocation thresholds for aerosol validation analyses and account for temporal variation when estimating data set uncertainty. They also have implications for comparisons between different satellite products or models, data aggregation, and time series analyses. Results are provided on a site‐by‐site basis to facilitate use by other researchers.

Apparent dust size discrepancy in aerosol reanalysis in north African dust after long-range transport

Abstract. North African dust reaches the southeastern United States every summer. Size-resolved dust mass measurements taken in Miami, Florida, indicate that more than one-half of the surface dust mass concentrations reside in particles with geometric diameters less than 2.1 µm, while vertical profiles of micropulse lidar depolarization ratios show dust reaching above 4 km during pronounced events. These observations are compared to the representation of dust in the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) aerosol reanalysis and closely related Goddard Earth Observing System model version 5 (GEOS-5) Forward Processing (FP) aerosol product, both of which assimilate satellite-derived aerosol optical depths using a similar protocol and inputs. These capture the day-to-day variability in aerosol optical depth well, in a comparison to an independent sun-photometer-derived aerosol optical depth dataset. Most of the modeled dust mass resides in diameters between 2 and 6 µm, in contrast to the measurements. Model-specified mass extinction efficiencies equate light extinction with approximately 3 times as much aerosol mass, in this size range, compared to the measured dust sizes. GEOS-5 FP surface-layer sea salt mass concentrations greatly exceed observed values, despite realistic winds and relative humidities. In combination, these observations help explain why, despite realistic total aerosol optical depths, (1) free-tropospheric model volume extinction coefficients are lower than those retrieved from the micro-pulse lidar, suggesting too-low model dust loadings in the free troposphere, and (2) model dust mass concentrations near the surface can be higher than those measured. The modeled vertical distribution of dust, when captured, is reasonable. Large, aspherical particles exceeding the modeled dust sizes are also occasionally present, but dust particles with diameters exceeding 10 µm contribute little to the measured total dust mass concentrations after such long-range transport. Remaining uncertainties warrant a further integrated assessment to confirm this study's interpretations.

Simulation of long-term direct aerosol radiative forcing over the arctic within the framework of the iAREA project

This paper presents the climatology of aerosol optical properties and radiative forcing over the Arctic obtained within the framework of the iAREA (impact of absorbing aerosols on radiative forcing in the European Arctic) project. The presented data were obtained from the Navy Aerosol Analysis and Prediction System (NAAPS) and the Fu-Liou radiative transfer model. NAAPS was used to simulate particle concentration and aerosol optical depth (AOD) at 1 ° × 1 ° spatial resolution. Direct aerosol radiative forcing (ARF) was calculated for clear-sky and all-sky conditions based on NAAPS reanalysis (with AOD assimilation) and satellite observations of surface and cloud properties. Long-term data (2003–2015) from NAAPS show that anthropogenic and biogenic aerosol, as well as sea salt, make the most important contribution to total AOD (35 and 30%, respectively). However, smoke (15%) and mineral dust (20%) cannot be neglected, especially during spring and summer. Results of numerical simulations indicate mean shortwave (SW) ARF for the whole Arctic (>70.5oN) at the Earth's surface to be −4 W/m2 for clear-sky and −1.3 W/m2 for all-sky conditions, and at top of the atmosphere (TOA) −1.3 W/m2 and -0.4 W/m2, respectively. TOA ARF for anthropogenic and biogenic particles is only −0.1 W/m2 for clear-sky and almost zero for all-sky conditions. For smoke and dust particles, SW ARF is very similar for both Earth's surface and TOA, as well as for clear-sky and all-sky conditions. For sea salt, SW ARF is the same at the surface and at TOA: 0.6 W/m2 for clear-sky and −0.3 W/m2 for all-sky conditions, because of negligible solar absorption. Cloud cover reduces surface cooling (direct clear-sky SW ARF) by a factor of 40% and shifts TOA SW ARF towards positive values.

Implications of different aerosol species to direct radiative forcing and atmospheric heating rate

The optical and radiative characteristics of water-soluble and carbonaceous aerosol species in the PM2.5 samples were examined for a representative megacity over the Indo-Gangetic Basin (IGB). Aerosol optical and radiative transfer models were used to extract sulphate (SO4), nitrate (NO3), organic carbon (OC) and elemental carbon (EC) from the observations done in 2012. Initial results suggest that the mass concentration of OC dominated over other species, but impacts on optical characteristics were mostly due to the SO4 aerosols. Further, EC shows relatively large impact on radiative forcing. The aerosol optical depth (AOD) at 500 nm for SO4, NO3, EC and OC was found to be contributing ~36%, 20%, 27% and 9%, respectively in the total AOD value (0.61 ± 0.18) during the entire study period. The single scattering albedo (SSA) for SO4 and NO3 was high and suggested their scattering nature; however, being the highly absorbing species, EC was found to show the lowest values of SSA during the study period. SSA for OC was, however, ~0.70, which was found to show the second highest warming species in the atmosphere with contribution of ~10%, after EC, which caused the highest warming (~70%), to the total atmospheric forcing.

Chemical speciation of PM2.5 in Tehran: Quantification of dust contribution and model validation

Each year, considerable levels of dust particles coming from arid regions of the earth contribute to the atmosphere. Because dust has serious environmental and human health effects, predictions of dust concentrations and their contribution to PM surface concentrations are essential for atmospheric research and the implementation of air quality programs and rules. This study aims to assess dust contributions to PM2.5 in Tehran in order to provide guidance for air quality management systems as well as validate the updated Dust Regional Atmospheric Model version 2 (BSC-DREAM8b) and the NMMB/BSC-Dust model using chemical speciation of ground-based measurements of PM2.5. Accurate and reliable measurements are necessary to determine the sources of pollutants as well as to confirm, validate, and improve models. For this purpose, dust concentration and contribution were calculated from chemical speciation of PM2.5 samples that were obtained on a 6 day basis for a whole year from February 2014 to February 2015. The comparison of the dust observations to the model products revealed that model outputs were in good agreement for the monthly averaged values. However, for the daily averaged values, models and ground observation showed a considerable difference. In order to understand possible reasons for the discrepancy, differences between neighboring grid cells were investigated, as well as the effect of sampling frequency. It is found that agreement between models and observations was sensitive to sampling duration and frequency but not to spatial variability between grid cells. This study is the first validation of model outputs with the calculated dust concentration from ground-based chemical speciation of PM2.5 rather than using total PM or aerosol optical depth measurements as a proxy for dust concentrations.

Potential Approach for Single-Peak Extinction Fitting of Aerosol Profiles Based on In Situ Measurements for the Improvement of Surface PM2.5 Retrieval from Satellite AOD Product

The vertical distribution of aerosols is important for accurate surface PM2.5 retrieval and initial modeling forecasts of air pollution, but the observation of aerosol profiles on the regional scale is usually limited. Therefore, in this study, an approach to aerosol extinction profile fitting is proposed to improve surface PM2.5 retrieval from satellite observations. Owing to the high similarity of the single-peak extinction profile in the distribution pattern, the log-normal distribution is explored for the fitting model based on a decadal dataset (3248 in total) from Micro Pulse LiDAR (MPL) measurements. The logarithmic mean, standard deviation, and the height of peak extinction near-surface (Mode) are manually derived as the references for model construction. Considering the seasonal impacts on the planetary boundary layer height (PBLH), Mode, and the height of the surface layer, the extinction profile is then constructed in terms of the planetary boundary layer height (PBLH) and the total column aerosol optical depth (AOD). A comparison between fitted profiles and in situ measurements showed a high level of consistency in terms of the correlation coefficient (0.8973) and root-mean-square error (0.0415). The satellite AOD is subsequently applied for three-dimensional aerosol extinction, and the good agreement of the extinction coefficient with the PM2.5 within the surface layer indicates the good performance of the proposed fitting approach and the potential of satellite observations for providing accurate PM2.5 data on a regional scale.

Random forest models for PM2.5 speciation concentrations using MISR fractional AODs

It is increasingly recognized that various chemical components of PM2.5 might have differential toxicities to human health, although such studies are hindered by the sparse or non-existent coverage of ground PM2.5 speciation monitors. The Multi-angle Imaging SpectroRadiometer (MISR) onboard the Terra satellite has an innovative design to provide information about aerosol shape, size and extinction that are more related to PM2.5 speciation concentrations. In this study, we developed random forest models that incorporated ground measurements of PM2.5 species, MISR fractional AODs, simulated PM2.5 speciation concentrations from a chemical transport model (CTM), land use variables and meteorological fields, to predict ground-level daily PM2.5 sulfate, nitrate, organic carbon (OC) and elemental carbon (EC) concentrations in California between 2005 and 2014. Our models had out-of-bag R2 of 0.72, 0.70, 0.68 and 0.70 for sulfate, nitrate, OC and EC, respectively. We also conducted sensitivity tests to explore the influence of variable selection on model performance. Results show that if there are sufficient ground measurements and predictor data to support the most sophisticated model structure, fractional AODs and total AOD have similar predicting power in estimating PM2.5 species. Otherwise, models using fractional AODs outperform those with total AOD. PM2.5 speciation concentrations are more sensitive to land use variables than other supporting data (e.g., CTM simulations and meteorological information).

Validation of POLDER GRASP aerosol optical retrieval over China using SONET observations

Monitoring fine mode aerosol pollutants is one of priorities in national environmental programs. Aerosol Optical Depth (AOD) and fine mode AOD are key parameters for estimation of particulate matter. POLDER/GRASP retrieval provides probably the most detailed aerosol products globally for 2005 – 2013. Current studies are focused on understanding the value of new satellite products for potential monitoring of air quality over China. As part of this objective, the quantitative evaluation of the products over China, a statistical comparison of total AOD, fine mode AOD and Fine Mode Fraction (FMF) with Sun–Sky Radiometer Observation Network (SONET) products is conducted. Two of available POLDER aerosol products: GRASP «models» and «high-precision» were evaluated at 8 SONET sites over China in this study. The results show the best agreement of the total AOD at 490 nm from «models» approach with AOD (500 nm) from SONET with correlation coefficient of ~0.96, slope of ~0.9, RMSE of 0.14 and bias (intercept) of 0.04, with about 76% of retrievals inside of Gfrac ranges. The validation results of the fine mode AOD at 490 nm with AOD the fine mode SONET-SDA product (500 nm) are quite comparable for both «high-precision» and «models» approaches, with slightly better results for «high-precision» data showing correlation coefficient of ~0.95, slope of ~0.78, RMSE of 0.14 and bias (intercept) of 0.07, with about 68% of retrievals inside of Gfrac ranges. The analysis is demonstrated that POLDER/GRASP results are one of most suitable aerosol products for characterization of FMF (Fine Mode Fraction) of aerosol. For example, compared with MODIS, the FMF from POLDER/GRASP is significantly closer to SONET-SDA FMF, with Gfrac increasing from 16.75% (MODIS) to 62.35% (POLDER/GRASP). Moreover, there is a clear similarity of spatial distribution of the fine mode AOD from GRASP with ground-level PM2.5 observations.

Analysis of the Transport of Aerosols over the North Tropical Atlantic Ocean Using Time Series of POLDER/PARASOL Satellite Data

The time series of total, fine and coarse POLAC/PARASOL aerosol optical depth (AOD) satellite products (2005–2013) processed by the POLAC algorithm are examined to investigate the transport of aerosols over the North Tropical Atlantic Ocean, a region that is characterized by significant dust aerosols events. First, the comparison of satellite observations with ground-based measurements acquired by AERONET ground-based measurements shows a satisfactory consistency for both total AOD and coarse mode AOD (i.e., correlation coefficients of 0.75 and bias ranging from −0.03 to 0.03), thus confirming the robustness and performance of POLAC/PARASOL data to investigate the spatio-temporal variability of the aerosols over the study area. Regarding fine mode aerosol, POLAC/PARASOL data present a lower performance with correlation coefficient ranging from 0.37 to 0.73. Second, the analysis of POLAC/PARASOL aerosol climatology reveals a high contribution of the coarse mode of aerosols ( AOD c between 0.1 and 0.4) at long distance from the African sources, confirming previous studies related to dust transport. The POLAC/PARASOL data were also compared with aerosol data obtained over the North Tropical Atlantic Ocean from MACC and MERRA-2 reanalyses. It is observed that the total AOD is underestimated in both reanalysis with a negative bias reaching −0.2. In summary, our results thus suggest that satellite POLAC/PARASOL observations of fine and coarse modes of aerosols could provide additional constraints useful to improve the quantification of the dust direct radiative forcing on a regional scale but also the biogeochemical processes such as nutrient supply to the surface waters.

Aerosol retrieval study from multiangle polarimetric satellite data based on optimal estimation method

Based on the optimal estimation (OE) theory, an inversion framework for aerosol retrieval from multiviewing polarimetric satellite measurements, is presented. The retrieved parameters include the wavelength-independent volume concentration and spectral aerosol optical depth (AOD). An OE-iteration approach is proposed to implement the framework. Polarization data from the polarization and directionality of the Earth’s reflectance sensor over the Chinese Beijing–Tianjin–Hebei region are selected to test the proposed algorithm. The validation against aerosol robotic network products produces high correlation coefficients (R) of 0.85, 0.9, and 0.86 for the fine-mode volume concentration, fine-mode AOD, and total AOD at 500 nm, respectively. These results indicate that the OE retrieval framework is practical and useful in the quantitative retrieval of AOD and fine-mode volume concentration from the multiangle polarization data.

The potential of elastic and polarization lidars to retrieve extinction profiles

Abstract. A new method, called ElEx (elastic extinction), is proposed for the estimation of extinction coefficient lidar profiles using only the information provided by the elastic and polarization channels of a lidar system. The method is applicable to lidar measurements both during daytime and nighttime under well-defined aerosol mixtures. ElEx uses the particle backscatter profiles at 532 nm and the vertically resolved particle linear depolarization ratio measurements at the same wavelength. The particle linear depolarization ratio and the lidar ratio values of pure aerosol types are also taken from literature. The total extinction profile is then estimated and compared well with Raman retrievals. In this study, ElEx was applied in an aerosol mixture of marine and dust particles at Finokalia station during the CHARADMExp campaign. Any difference between ElEx and Raman extinction profiles indicates that the nondust component could be probably attributed to polluted marine or polluted continental aerosols. Comparison with sun photometer aerosol optical depth observations is performed as well during daytime. Differences in the total aerosol optical depth are varying between 1.2 % and 72 %, and these differences are attributed to the limited ability of the lidar to correctly represent the aerosol optical properties in the near range due to the overlap problem.

Modeling dust sources, transport, and radiative effects at different altitudes over the Tibetan Plateau

Abstract. Mineral dust plays an important role in the climate of the Tibetan Plateau (TP) by modifying the radiation budget, cloud macro- and microphysics, precipitation, and snow albedo. Meanwhile, the TP, with the highest topography in the world, can affect intercontinental transport of dust plumes and induce typical distribution characteristics of dust at different altitudes. In this study, we conduct a quasi-global simulation to investigate the characteristics of dust source contribution and transport over the TP at different altitudes by using a fully coupled meteorology–chemistry model, the Weather Research and Forecasting model with chemistry (WRF-Chem), with a tracer-tagging technique. Generally, the simulation reasonably captures the spatial distribution of satellite-retrieved dust aerosol optical depth (AOD) at different altitudes. Model results show that dust particles are emitted into atmosphere through updrafts over major desert regions and then transported to the TP. The East Asian dust (mainly from the Gobi and Taklamakan deserts) is transported southward and is lifted up to the TP, contributing a mass loading of 50 mg m−2 at a height of 3 km and 5 mg m−2 at a height of 12 km over the northern slope of the TP. Dust from North Africa and the Middle East are concentrated over both of the northern and southern slopes below 6 km, where mass loadings range from 10 to 100 and 1 to 10 mg m−2 below 3 km and above 9 km, respectively. As the dust is transported to the north and over the TP, mass loadings are 5–10 mg m−2 above a height of 6 km. The dust mass flux carried from East Asia to the TP is 7.9 Tg yr−1, mostly occurring at heights of 3–6 km. The dust particles from North Africa and the Middle East are transported eastward following the westerly jet and then are carried into the TP at the west side with dust mass fluxes of 7.8 and 26.6 Tg yr−1, respectively. The maximum mass flux of the North African dust mainly occurs at 0–3 km (3.9 Tg yr−1), while the Middle Eastern dust occurs at 6–9 km (12.3 Tg yr−1). The dust outflow occurs on the east side (−17.89 Tg yr−1) and south side (−11.22 Tg yr−1) of the TP, with a peak value (8.7 Tg yr−1) at 6–9 km. Moreover, the dust (by mass) is concentrated within the size range of 1.25–5.0 µm and the dust (by particle number) is concentrated in the size range of 0.156–1.25 µm. Compared with other aerosols, the dust contributes to more than 50 % of the total AOD over the TP. The direct radiative forcing induced by the dust is −1.28 W m−2 at the top of the atmosphere (cooling), 0.41 W m−2 in the atmosphere (warming), and −1.68 W m−2 at the surface (cooling). Our quantitative analyses of the dust contributions from different source regions and the associated radiative forcing can help us to better understand the role of dust on the climate over the TP and surrounding regions.