AERONET Stations Research Articles

Global evaluation of sentinel 2 level 2A Sen2Cor aerosol optical thickness retrievals

ABSTRACT The present study aims to conduct the first known comprehensive global evaluation of Aerosol Optical Thickness (AOT) retrievals derived from the Sentinel 2 Sen2Cor algorithm between 2018 and 2022, using data from over 400 AERONET stations. The results indicate that Sentinel 2 tends to underestimate AOT, especially at higher aerosol loadings. Although there appears to be a good overall correlation (r = 0.57) with low RMSE (0.16) and relative mean bias (RMB = -2.46%) between AERONET and Sentinel 2 AOT datasets, regional analysis reveals significant variation in performance across regions, with areas like Europe and Americas exhibiting stronger correlations and lower RMSE than others like Indian subcontinent and Southern Africa. Temporal analysis also suggests an improvement in Sentinel 2 performance, particularly in capturing extreme AOT values in 2022. While elevation does not appear to have any noticeable impact on AOT estimation, slight variations could be observed over certain land cover types like sparse vegetation and permanent water bodies. Though improvements are certainly required over certain geographical regions like Indian subcontinent, Sentinel 2 AOT can, nevertheless, be reliably used for aerosol studies in urban areas or at a finer spatial resolution, especially in Europe, Mainland U.S.A. and East Asia.

Two decades of high-resolution aerosol product over the Sierra Nevada Mountain region (SE Spain): Spatio-temporal distribution and impact on ecosystems

Atmospheric aerosols play a pivotal role in shaping our environment, impacting climate, human health, and ecosystems. Characterizing the influence of aerosols on ecosystems, especially in mountain environments, is a challenging task due to their complex-orography and scarcity of aerosol ground stations. Satellite-based aerosol data can improve our knowledge over such complex-orography areas. Thus, we have analyzed the Aerosol Optical Depth (AOD) product from the MODerate resolution Imaging Spectrometer (MODIS) sensor produced by the inversion algorithm MultiAngle Implementation of Atmospheric Correction (MAIAC) over the last two decades for the period 2001–2022 with a spatial resolution of 1 × 1 km. Our study focuses on the Sierra Nevada Mountain region and National Park in Southeastern Spain. As a first step, we have validated the AOD from MODIS+MAIAC against three AERONET stations at different altitudes (680 m, 1800 m, and 2500 m above sea level (a.s.l.)). MODIS+MAIAC AOD showed good agreement with the ground-based AOD observations, with R values ranging from 0.75 to 0.82, RMSE values ranging from 0.047 to 0.066 and having 80% of the samples within the expected error (EE) of the product. The MODIS+MAIAC AOD product is able to characterize the fine-scale features of such complex-orography area and hence evaluate the spatio-temporal distribution of the AOD over the mountainous region. We have generated the most extended AOD dataset for a mountainous region, spanning the past two decades. We have deepened into the spatial and seasonal AOD patterns from 2001 to 2022, unveiling elevated AOD values near valleys and urban areas. In general, the AOD values decrease with increasing altitude with the exception of snow-covered areas at high altitudes (>2800 m a.s.l.), which might affect aerosol retrieval and provide bias due to higher-reflecting surfaces and pixel removal. For the first time, the relationship of aerosol loading with ecosystem type has been assessed in the protected environment of Sierra Nevada Natural Park. Monthly AOD trends across different ecosystem types and altitudinal ranges are analyzed in detail over the last two decades. In addition, Generalized Linear Models (GLM) are applied to reveal significant correlations between ecosystems and AOD, irrespective of altitude, latitude or longitude. Based on the interannual variation of AOD over the last two decades, we have analyzed the relationship of AOD with the different ecosystems of Sierra Nevada at 500 m elevation ranges. The patterns of the ecosystem's types are maintained over the elevation ranges 1200–1700 m and 1700–2200 m a.s.l., which demonstrates that land-type has an impact on the AOD product. Furthermore, it is observed that forest-like ecosystems tend to present lower AOD compared with bare-soil or low-growth vegetation ecosystems. In addition, the areas of the mountain closer to Granada city present generalized higher AOD values on the western part of the mountain, regardless of the ecosystem, showing the significant influence of the proximity of urban sites over the ecosystems and the potential impact on the environment.

The Recovery and Re-Calibration of a 13-Month Aerosol Extinction Profiles Dataset from Searchlight Observations from New Mexico, after the 1963 Agung Eruption

The recovery and re-calibration of a dataset of vertical aerosol extinction profiles of the 1963/64 stratospheric aerosol layer measured by a searchlight at 32° N in New Mexico, US, is reported. The recovered dataset consists of 105 aerosol extinction profiles at 550 nm that cover the period from December 1963 to December 1964. It is a unique record of the portion of the aerosol cloud from the March 1963 Agung volcanic eruption that was transported into the Northern Hemisphere subtropics. The data-recovery methodology involved re-digitizing the 105 original aerosol extinction profiles from individual Figures within a research report, followed by the re-calibration. It involves inverting the original equation used to compute the aerosol extinction profile to retrieve the corresponding normalized detector response profile. The re-calibration of the original aerosol extinction profiles used Rayleigh extinction profiles calculated from local soundings. Rayleigh and aerosol slant transmission corrections are applied using the MODTRAN code in transmission mode. Also, a best-estimate aerosol phase function was calculated from observations and applied to the entire column. The tropospheric aerosol phase function from an AERONET station in the vicinity of the searchlight location was applied between 2.76 to 11.7 km. The stratospheric phase function, applied for a 12.2 to 35.2 km altitude range, is calculated from particle-size distributions measured by a high-altitude aircraft in the vicinity of the searchlight in early 1964. The original error estimate was updated considering unaccounted errors. Both the re-calibrated aerosol extinction profiles and the re-calibrated stratospheric aerosol optical depth magnitudes showed higher magnitudes than the original aerosol extinction profiles and the original stratospheric aerosol optical depth, respectively. However, the magnitudes of the re-calibrated variables show a reasonable agreement with other contemporary observations. The re-calibrated stratospheric aerosol optical depth demonstrated its consistency with the tropics-to-pole decreasing trend, associated with the major volcanic eruption stratospheric aerosol pattern when compared to the time-coincident stratospheric aerosol optical depth lidar observations at Lexington at 42° N.

Consistency of Aerosol Optical Properties between MODIS Satellite Retrievals and AERONET over a 14-Year Period in Central–East Europe

Aerosols influence Earth’s climate by interacting with radiation and clouds. Remote sensing techniques aim to enhance our understanding of aerosol forcing using ground-based and satellite retrievals. Despite technological advancements, challenges persist in reducing uncertainties in satellite remote sensing. Our study examines retrieval biases in MODIS sensors on Terra and Aqua satellites compared to AERONET ground-based measurements. We assess their performance and the correlation with the AERONET aerosol optical depth (AOD) using 14 years of data (2010–2023) from 29 AERONET stations across 10 Central–East European countries. The results indicate discrepancies between MODIS Terra and Aqua retrievals: Terra overestimates the AOD at 16 AERONET stations, while Aqua underestimates the AOD at 21 stations. The examination of temporal biases in the AOD using the calculated estimated error (ER) between AERONET and MODIS retrievals reveals a notable seasonality in coincident retrievals. Both sensors show higher positive AOD biases against AERONET in spring and summer compared to fall and winter, with few ER values for Aqua indicating poor agreement with AERONET. Seasonal variations in correlation strength were noted, with significant improvements from winter to summer (from R2 of 0.58 in winter to R2 of 0.76 in summer for MODIS Terra and from R2 of 0.53 in winter to R2 of 0.74 in summer for MODIS Aqua). Over the fourteen-year period, monthly mean aerosol AOD trends indicate a decrease of −0.00027 from AERONET retrievals and negative monthly mean trends of the AOD from collocated MODIS Terra and Aqua retrievals of −0.00023 and −0.00025, respectively. An aerosol classification analysis showed that mixed aerosols comprised over 30% of the total aerosol composition, while polluted aerosols accounted for more than 22%, and continental aerosols contributed between 22% and 24%. The remaining 20% consists of biomass-burning, dust, and marine aerosols. Based on the aerosol classification method, we computed the bias between the AERONET AE and MODIS AE, which showed higher AE values for AERONET retrievals for a mixture of aerosols and biomass burning, while for marine aerosols, the MODIS AE was larger and for dust the results were inconclusive.

Variability of Aerosol Optical Depth and Altitude for Key Aerosol Types over Southern West Africa via CALIPSO/CALIOP Observations

The atmosphere of southern West Africa (SWA) is one of the world’s most aerosol-laden regions. This study investigated the seasonal variability of aerosol optical thickness using photometric and CALIPSO/CALIOP observations. The mean daily aerosol optical thickness (AOD) at 550 nm over the 11 AERONET stations in SWA ranged from 0.35 in the Sahel area to 0.49 in the Guinea coast area and a maximum of 0.53 observed in the Savanna area. The AERONET and CALIOP observations reveal a seasonal variability of AOD that is comparable across all sub-regions studied. The seasonal variation of the AOD spectral dependency was related to the change in the occurrence of the CALIOP-derived aerosol types, and in particular to the contribution of dust to the AOD. We also observed a north–south gradient of 2 km in the mean extinction height of the dust layer, being at 4 km and 6 km high in the Sahel and Guinea areas, respectively. This gradient is attributed to the northward migration of the monsoon flow.

Benchmarking GOCART-2G in the Goddard Earth Observing System (GEOS)

Abstract. The Goddard Chemistry Aerosol Radiation and Transport (GOCART) model, which controls the sources, sinks, and chemistry of aerosols within the Goddard Earth Observing System (GEOS), recently underwent a major refactoring and update, including a revision of the emissions datasets and the addition of brown carbon. A 4-year benchmark simulation utilizing the new version of the model code, termed GOCART Second Generation (GOCART-2G) and coupled to the Goddard Earth Observing System (GEOS) model, was evaluated using in situ and spaceborne measurements to develop a baseline and prioritize future development. A comparison of simulated aerosol optical depth between GOCART-2G and MODIS retrievals indicates the model captures the overall spatial pattern and seasonal cycle of aerosol optical depth but overestimates aerosol extinction over dusty regions and underestimates aerosol extinction over Northern Hemisphere boreal forests, requiring further investigation and tuning of emissions. This MODIS-based analysis is corroborated by comparisons to MISR and selected AERONET stations; however, discrepancies between the Aqua and Terra satellites indicate there is a diurnal component to biases in aerosol optical depth over southern Asia and northern Africa. Despite the underestimate of aerosol optical depth in biomass burning regions in GEOS, there is an overestimate in the surface mass of organic carbon in the United States, especially during the summer months. Over Europe, GOCART-2G is unable to match the summertime peak in aerosol optical depth, opposing the observed late fall and early spring peaks in surface mass concentration. A comparison of the vertical profile of attenuated backscatter to observations from CALIPSO indicates the GEOS model is capable of capturing the vertical profile of aerosol; however, the mid-troposphere plumes of dust in the North Atlantic and smoke in the southeastern Atlantic are perhaps too low in altitude. The results presented highlight priorities for future development with GOCART-2G, including improvements for dust, biomass burning aerosols, and anthropogenic aerosols.

The Aerosol Pollution Of The Atmosphere On The Example Of Lidar Sensing Data In St. Petersburg (Russia), Kuopio (Finland), Minsk (Belarus)

The results of lidar sensing of aerosol pollution in St. Petersburg (Russia) were compared with ones located in Minsk (Belarus) and Kuopio (Finland) to assess the impact of large cities on atmospheric pollution by aerosol particles. For comparison, aerosol optical depth (AOD) data obtained at the three stations from 2014 to 2021 were used. Lidar sounding of atmospheric aerosols was carried out using aerosol Nd:YAG lasers operating at three wavelengths: 355, 532 and 1064 nm. Due to differences in the lidar station equipment characteristics and, consequently, in the lower limit for determining aerosols, the aerosol optical depth was compared in the range of heights from 800 to 1600 m at 355 and 532 nm. Since the compared stations do not have data for all years, the period from 2014 to 2016 was analyzed separately. The average annual AOD 355 in Minsk in the period 2014-2016 is almost the same as the average annual AOD in St. Petersburg. When comparing data in St. Petersburg and Minsk for the period 2014-2020, AOD 355 in St. Petersburg exceeds AOD 355 in Minsk by 1.46 times. AOD 532 nm in Minsk is larger than in St. Petersburg, regardless of the chosen comparison period. The average annual AOT 355 in Kuopio is lower than in Minsk and St. Petersburg by 2.1 times, while at a wavelength of 532 nm they are 3.6 times lower than in Minsk and 2.6 times in St. Petersburg. The calculated Angstrom exponent coefficient shows that the coarse mode in Minsk is higher than in St. Petersburg. The atmosphere over Kuopio has a lower content of aerosol particles. Since 2017, there was a steady excess of aerosol content over St. Petersburg compared to Minsk. Additionally, a comparison of the lidar data with the total AOD of AERONET stations located in Kuopio, Minsk and Peterhof (25 km from the lidar station in St. Petersburg) was carried out. The AOD obtained by lidar and AERONET method is in good agreement.

Spatio-Temporal Variability of the Aerosol Optical Depth over the Gorky and Cheboksary Reservoirs in 2022–2023

The present study aimed to investigate atmospheric optical characteristics over the Gorky and Cheboksary Reservoirs and their multi-scale temporal variations to obtain the background characteristics and to identify events involving the transfer of absorbing aerosol to the studied region in 2022–2023. The region is located at a considerable distance (500 km) from the nearest AERONET station; therefore, previous atmospheric data were not available. As a solution, the in situ self-measured aerosol optical depth (AOD) and Angström exponent, as well as satellite products (MAIAC and CALIPSO) for MODIS data, were used. This allowed us to set background values of an AOD of 0.11 at a wavelength of 500 nm and an Angström exponent of 1.2, against their maximum values of 0.38 and 2.5, respectively. To explain these variations, the registered conditions and the microstructure of the dust aerosol over the studied region are presented. For days with background values, the analysis of the particle size distribution data did not show a predominance of any particle size. The optical properties of a smoke aerosol in an atmospheric column are described, and an analysis of the dynamics of particle size variability is presented. A comparative analysis of the optical characteristics of atmospheric aerosol over the Gorky and Cheboksary Reservoirs using in situ and MODIS products was carried out.

Anomalous Selective Absorption of Smoke Aerosol during Forest Fires in Alaska in July–August 2019

According to the monitoring data of the optical and microphysical characteristics of smoke aerosol at AERONET stations during forest fires in the summer of 2019 in Alaska, anomalous selective absorption of smoke aerosol was detected in the visible and near infrared spectral range from 440 to 1020 nm. With anomalous selective absorption, the imaginary part of the refractive index of smoke aerosol reached 0.315 at a wavelength of 1020 nm. A power-law approximation of the spectral dependence of the imaginary part of the refractive index with an exponent from 0.26 to 2.35 is proposed. It is shown that for anomalous selective absorption, power-law approximations of the spectral dependences of the aerosol optical extinction and absorption depths are applicable with an Angstrom exponent from 0.96 to 1.65 for the aerosol optical extinction depth and from 0.97 to –0.89 for the aerosol optical absorption depth, which reached 0.72. Single scattering albedo varied from 0.62 to 0.96. In the size distribution of smoke aerosol particles with anomalous selective absorption, the fine fraction of particles of condensation origin dominated. The similarity of the fraction of particles distinguished by anomalous selective absorption with the fraction of tar balls detected by electron microscopy in smoke aerosol, which, apparently, arise during the condensation of terpenes and their oxygen-containing derivatives, is noted.

Aerosol Optical Properties and Type Retrieval via Machine Learning and an All-Sky Imager

This study investigates the applicability of using the sky information from an all-sky imager (ASI) to retrieve aerosol optical properties and type. Sky information from the ASI, in terms of Red-Green-Blue (RGB) channels and sun saturation area, are imported into a supervised machine learning algorithm for estimating five different aerosol optical properties related to aerosol burden (aerosol optical depth, AOD at 440, 500 and 675 nm) and size (Ångström Exponent at 440–675 nm, and Fine Mode Fraction at 500 nm). The retrieved aerosol optical properties are compared against reference measurements from the AERONET station, showing adequate agreement (R: 0.89–0.95). The AOD errors increased for higher AOD values, whereas for AE and FMF, the biases increased for coarse particles. Regarding aerosol type classification, the retrieved properties can capture 77.5% of the total aerosol type cases, with excellent results for dust identification (>95% of the cases). The results of this work promote ASI as a valuable tool for aerosol optical properties and type retrieval.

An algorithm for retrieving aerosol optical depth from Landsat 8 Operational Land Imager in Vietnam

High-resolution aerosol products offer advantages over lower spatial-resolution products for monitoring pollution in urban areas and industrial zones. Therefore, in this study we develop a Landsat 8 algorithm to retrieve aerosol optical depth (AOD) based on the MODIS Dark Target (DT) algorithm. This algorithm uses the direct surface reflectance of Landsat 8 to build a surface reflectance relationship between the visible (BLUE, RED) and short-wave infrared bands (SWIR2). AOD data from AERONET stations in the study area and AOD data from MODIS 3 km were used for validation of the estimated Landsat 8 AOD. The estimated AOD was highly correlated at most AERONET AOD, with =0.98, (RMSE = 0.3), except Bac Lieu, but only had a moderate correlation with MODIS AOD which was attributed to the difference in data retrieval time and associated changes in climate conditions. This is the first high-resolution AOD retrieval in Vietnam, leading to more practical applications for air quality monitoring.

Performance evaluation of MODIS and VIIRS satellite AOD products over the Indian subcontinent

In the present study, the first systematic performance evaluation of aerosol optical depth (AOD) products retrieved using two satellite sensors i.e., Visible Infrared Imaging Radiometer Suite (VIIRS) and Aqua-Moderate-Resolution Imaging Spectroradiometer (MODIS) is carried out over India. We have used ground-based AOD from AERONET at 550 nm wavelength for inter-comparison with MODIS Aqua version C6.1 (C061) Deep Blue (DB) aerosol product and VIIRS/SNPP collection version 1.1 (V1.1) DB aerosol product over the time span of 7-year (2014–2020) observation periods. For validation, the average value of satellite pixels falling within the box of 50 Km x 50 Km keeping the AERONET station at the center is retrieved. The average daily data from the AERONET sun photometer (2014–2019) were obtained within ±15 min of satellite overpass time. Statistical parameters like correlation coefficient (R), RMSE, MAE, and RMB were calculated. The uncertainty of satellite AOD is evaluated using an envelope of Expected Error (EE = ±0.05 + 0.15 AOD for land). Statistical analysis shows that the MODIS AOD product outperforms VIIRS-retrieved AOD. The AOD retrieved from both sensors yields a high correlation (0.86—Jaipur, 0.79—Kanpur, 0.84—Gandhi College, and 0.74—Pune for MODIS and 0.75—Jaipur, 0.77—Kanpur, 0.49—Gandhi College, and 0.86—Pune for VIIRS) and low MAE (0.12—Jaipur, 0.20—Kanpur, 0.15—Gandhi College, and 0.09—Pune for MODIS and 0.13—Jaipur, 0.13—Kanpur, 0.26—Gandhi College, and 0.10—Pune for VIIRS). Other statistical measures such as RMSE, RMB, and P also suggest similar performance. More than 66% of the total data fall within the range of EE for both the satellite products at each station. Spatial comparison exhibits the same AOD pattern seasonally as well as annually having a minimum bias from −0.3 to +0.3 between MODIS and VIIRS. Slight underestimation and overestimation are observed in all the stations by MODIS, whereas VIIRS continuously underestimates AOD with increase in optical depth, suggesting improvements in the aerosol model and surface reflection in retrieval. Overall, the comparison of ground AERONET AOD reveals better accuracy of MODIS AOD with that of VIIRS satellite datasets over India.

Anomalous Absorption of Smoke Aerosol in the Visible and Near-Infrared Regions of the Spectrum

Anomalous absorption of finely dispersed smoke aerosol was recorded in large-scale smoke haze during mass fires in the boreal forests of Alaska in July 2019 in the visible and near-infrared regions of the spectrum (440‒1020 nm) according to the data of monitoring of the spectral dependences in the refractive index imaginary part on the network of AERONET stations. The variations in the spectral dependences of the aerosol optical depths (extinction and absorption), as well as the size distribution function of aerosol particles, are analyzed. During the anomalous absorption, the imaginary part of the refractive index increased by a factor of 1.8‒7.2 with an increasing optical wavelength from 440 to 1020 nm, reaching a value of 0.315 for the wavelength of 1020 nm. A power approximation is proposed for the spectral dependence of the imaginary part of the refractive index with indices of power approximately from 0.7 to 2.3.

Estimation of Respiratory Disease Burden Attributed to Particulate Matter from Biomass Burning in Northern Thailand Using 1-km Resolution MAIAC-AOD

The upper northern Thailand suffers from air pollution due to open burning, which has been known for a long time. It was also found that different respiratory diseases were attributed to air pollution, especially particulate matter. This study estimated the health impacts attributed to PM10 between 2014 and 2016 using the burden of disease in terms of the disability adjusted life year (DALYs). The spatial correlation was evaluated based on applicable remote sensing data using the geographically weighted regression (GWR) model. The average measured PM10 concentrations for the summer and annual periods between 2014 and 2016 were 73 and 89 µg m-3, respectively, exceeded the national standard (50 µg m-3). In the months of March and April, when PM10 concentrations were at their highest, the maximum values of the Multi-Angle Implementation of Atmospheric Correction (MAIAC-AOD), 2.70 and 3.48, were recorded. There was a strong correlation between the MAIAC-AOD and the ground-based AOD measurements (AERONET stations), with R of 0.8468, 0.8396, and 0.8334 between 2014–2016. The correlation coefficients for the 3,208 co-located gridded of PM10 emissions vs. measured PM10, measured PM10 vs. MAIAC-AOD, and MAIAC-AOD vs. PM10 emissions were 0.6656, 0.6446, and 0.5580, respectively. The spatial correlation between the interpolated measured PM10 and 1-km MAIAC-AOD was 0.5979, 0.3741, and 0.7584 as an outcome of GWR. The total DALYs of chronic obstructive pulmonary disease (COPD) attributable to PM10 in 2014–2016 were 115,930 years per 100,000 population, with the relative risk of COPD related to PM10 at a 95% confidence interval of 1.2045–1.2107.

ANOMALOUS ABSORPTION OF SMOKE AEROSOL IN THE VISIBLE AND NEAR-INFRARED OF SPECTRUM INTERVALS

In large-scale smoke haze during mass fires in the boreal forests of Alaska in July 2019 in the visible and near infrared of spectrum intervals 440–1020 nm, according to monitoring data on the network of AERONET stations of the spectral dependences of the refractive index imaginary part, anomalous absorption of the fine smoke aerosol was found. Variations in the spectral dependences of the aerosol optical extinction and absorption depths, as well as the size distribution function of aerosol particles, are analyzed. With anomalous absorption, the imaginary part of the refractive index increased by a factor of 1.8–7.2 with increasing wavelength from 440 to 1020 nm, reaching a value of 0.315 for the wavelength of 1020 nm. A power-law approximation of the spectral dependence of the refractive index imaginary part with exponents approximately from 0.7 to 2.3 is proposed.

Dry air intrusions link Rossby wave breaking to large-scale dust storms in Northwest Africa: Four extreme cases

Large dust storms in the Saharan desert and the subsequent transport of airborne dust over large distances are a major meteorological hazard. Several mechanisms associated to dust emission, occurring on a range of scales, have been previously documented, notably involving Rossby wave breaking and a low-level jet. However, the mechanistic link between the different features and actual dust concentrations has not been coherently established. Here, using a Lagrangian approach, and the conceptual view of extratropical cyclone airstreams, the role of the dry intrusion airstream for translating the influence of the upper-tropospheric Rossby wave perturbation to near-surface flow conductive for the highest dust concentrations is examined. To this end, four large-scale dust storms that were accompanied by dry intrusions in west Africa are studied. Data from the Copernicus Atmospheric Monitoring Service (validated against AERONET station data) are combined with atmospheric data from reanalysis and objectively-identified Lagrangian trajectories of dry intrusions. Common, coherent structures highlighting the role of dry intrusions link the upper-tropospheric Rossby wave breaks with the lower-tropospheric dry and cold jets. These conditions favor dust uplift and transport along an arc-shaped cold front trailing from a Mediterranean cyclone. Consequently, the southwest side of the front is characterized by the highest near-surface dust concentrations ahead of the dry intrusion outflow, where the Intertropical Discontinuity shifts equatorward by 3 to 7°. The northeast part of the front is, however, accompanied by southerly, warm conveyor belt-like flow transporting the dust northward to the Mediterranean, Middle East and/or Europe at mid and upper-tropospheric levels. While case-to-case variations exists, the central role of dry intrusions in all cases calls for systematic investigation of its occurrence as a predictive tool for large dust transport events.

Modeling and spatial characterization of aerosols at Middle East AERONET stations

Modeling and spatial characterization of aerosols at Middle East AERONET stations

Impacts of the Aerosol Representation in WRF-Solar Clear-Sky Irradiance Forecasts over CONUS

Abstract Aerosol optical depth (AOD) is a primary source of solar irradiance forecast error in clear-sky conditions. Improving the accuracy of AOD in NWP models like WRF will thus reduce error in both direct normal irradiance (DNI) and global horizontal irradiance (GHI), which should improve solar power forecast errors, at least in cloud-free conditions. In this study clear-sky GHI and DNI was analyzed from four configurations of the WRF-Solar model with different aerosol representations: 1) the default Tegen climatology, 2) imposing AOD forecasts from the GEOS-5 model, 3) imposing AOD forecasts from the Copernicus Atmosphere Monitoring Service (CAMS) model, and 4) the Thompson–Eidhammer aerosol-aware water/ice-friendly aerosol climatology. More than 8 months of these 15-min output forecasts are compared with high-quality irradiance observations at NOAA SURFRAD and Solar Radiation (SOLRAD) stations located across CONUS. In general, WRF-Solar with GEOS-5 AOD had the lowest errors in clear-sky DNI, while WRF-Solar with CAMS AOD had the highest errors, higher even than the two aerosol climatologies, which is consistent with validation of the four AOD550 datasets against AERONET stations. For clear-sky GHI, the statistics differed little between the four models, as expected because of the lesser sensitivity of GHI to aerosol loading. Hourly average clear-sky DNI and GHI were also analyzed, and they were additionally compared with CAMS model output directly. CAMS irradiance performed competitively with the best WRF-Solar configuration (with GEOS-5 AOD). The markedly different performance of CAMS versus WRF-Solar with CAMS AOD indicates that CAMS is apparently less sensitive to AOD550 than WRF-Solar is. Significance Statement Particles in the atmosphere called aerosols, which can include dust, smoke, sea salt, sulfates, black carbon, and organic carbon, absorb and scatter incoming sunlight. Improving the representation of aerosols in numerical weather prediction models reduces forecast errors in solar irradiance at ground level, particularly direct normal irradiance, during cloud-free conditions. This in turn should result in improved accuracy of solar power forecasts, especially for concentrated solar power (CSP) plants. CSP plants tend to be built in more arid, less cloudy regions that are also prone to dust loading, so accurate aerosol forecasts are particularly relevant. Comparing four representations of aerosols in the WRF-Solar model over eight months of forecasts across the United States reveals substantial differences in clear-sky irradiance forecast skill.

Aerosol Information Retrieval from GF-5B DPC Data over North China Using the Dark Dense Vegetation Algorithm

A directional polarimetric camera (DPC) is a key payload on board China’s Gaofen 5B (hereafter denoted as GF-5B) satellite, a hyperspectral observation instrument for monitoring aerosols. On the basis of the dark dense vegetation (DDV) algorithm, this study applied DDV algorithm to DPC measurements. First, the reflectance of vegetation in three channels (0.443, 0.49, and 0.675 μm) was analyzed, and inversion channels were identified. Subsequently, the decrease in normalized difference vegetation index associated with various view angles was simulated, and the optimal view angle for extracting dark pixels was determined. Finally, the top-of-atmosphere reflectance at different view angles was simulated to determine the optimal view angle for aerosol inversion. The inversion experiments were conducted by using DPC data collected over North China from November 2021 to January 2022. The results revealed that DDV algorithm could monitor pollution from 30 December 2021 to 4 January 2022, and the inversion results were strongly correlated with Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol product and AERONET station data (R > 0.85).

Dynamic Characteristics of Aerosol Optical Properties over Dibrugarh City in the North-Eastern Indian Region during 2018–2021

Aerosols play an important role in the earth's environment across the globe through their involvement in various earth system cycles. The change in the aerosol properties may cause short and long-term impacts, the knowledge of such changes is useful in the estimation of the pollution sources of any region. We have carried out the analysis of the aerosols' optical and radiative properties using AERONET station data from 2018 to 2021 in Dibrugarh City. The higher Aerosol Optical Depth (AOD) values during winter and pre-monsoon months indicate high anthropogenic activities, and biomass burning in Dibrugarh. The impact of various sources and daily meteorological parameters help in understanding the diurnal variations of the AOD, Ångström Exponent (AE), and column water (CW). Fine aerosol fractions dominate the aerosol volume, but sometimes the long-range transport of dust affects aerosol properties during pre-monsoon months (MAM). MODIS-derived AOD and AERONET AOD values show a good correlation, with R2 = 0.68. The highest volume of the aerosols reaches up to 0.11 µm3 µm-2 during pre-monsoon months, whereas it lies below 0.05 µm3 µm-2 in other seasons. SSA values indicate the presence of scattering aerosols but in 2020, a sudden decline in the SSA values shows a strong rise in the absorbing aerosols. Throughout the study period (2018–2021), the positive radiative forcing indicates a rise in atmospheric heating.