Range Of Aerosol Optical Depth Research Articles

Evaluation and Comparison of Multi-Satellite Aerosol Optical Depth Products over East Asia Ocean.

The atmosphere over the ocean is an important research field that involves multiple aspects such as climate change, atmospheric pollution, weather forecasting, and marine ecosystems. It is of great significance for global sustainable development. Satellites provide a wide range of measurements of marine aerosol optical properties and are very important to the study of aerosol characteristics over the ocean. In this study, aerosol optical depth (AOD) data from seventeen AERONET (Aerosol Robotic Network) stations were used as benchmark data to comprehensively evaluate the data accuracy of six aerosol optical thickness products from 2013 to 2020, including MODIS (Moderate-resolution Imaging Spectrometer), VIIRS (Visible Infrared Imaging Radiometer Suite), MISR (Multi-Angle Imaging Spectrometer), OMAERO (OMI/Aura Multi-wavelength algorithm), OMAERUV (OMI/Aura Near UV algorithm), and CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) in the East Asian Ocean. In the East Asia Sea, VIIRS AOD products generally have a higher correlation coefficient (R), expected error within ratio (EE within), lower root mean square error (RMSE), and median bias (MB) than MODIS AOD products. The retrieval accuracy of AOD data from VIIRS is the highest in spring. MISR showed a higher EE than other products in the East Asian Ocean but also exhibited systematic underestimation. In most cases, the OMAERUV AOD product data are of better quality than OMAERO, and OMAERO overestimates AOD throughout the year. The CALIPSO AOD product showed an apparent underestimation of the AOD in different seasons (EE Below = 58.98%), but when the AOD range is small (0 < AOD < 0.1), the CALIPSO data accuracy is higher compared with other satellite products under small AOD range. In the South China Sea, VIIRS has higher data accuracy than MISR, while in the Bohai-Yellow Sea, East China Sea, Sea of Japan, and the western Pacific Ocean, MISR has the best data accuracy. MODIS and VIIRS show similar trends in R, EE within, MB, and RMSE under the influence of AOD, Angstrom exponent (AE), and precipitable water. The study on the temporal and spatial distribution of AOD in the East Asian Ocean shows that the annual variation of AOD is different in different sea areas, and the ocean in the coastal area is greatly affected by land-based pollution. In contrast, the AOD values in the offshore areas are lower, and the aerosol type is mainly clean marine type aerosol. These findings can help researchers in the East Asian Ocean choose the most accurate and reliable satellite AOD data product to better study atmospheric aerosols' impact and trends.

Retrieval of nighttime aerosol optical depth by simultaneous consideration of artificial and natural light sources

Aerosol Optical Depth (AOD) is a critical optical parameter that quantifies the degree of light attenuation by aerosols and serves as a fundamental indicator of atmospheric quality. Therefore, accurate quantification and retrieval of AOD is crucial for relevant studies. However, current satellite-based AOD retrieval algorithms suffer from inapplicability under low-light conditions, limiting the development of nighttime AOD retrieval. Under this context, we proposed a novel algorithm, namely Simultaneous Consideration of Artificial and Natural light Sources (SCANS), to obtain nighttime AOD. The core of the SCANS algorithm is considering the synergy of both the natural and artificial light sources to obtain nighttime AOD by integrating atmospheric radiative transfer simulation into an extinction method and performing multiple iterations. SCANS was applied to the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) and the retrieved nighttime AOD was validated with in-situ measurements from five AERONET sites. Results indicate that the Mean Bias Errors (MBEs) of the retrieved nighttime AOD range from 0.0 to 0.08 and the corresponding Root Mean Square Errors (RMSEs) range from 0.11 to 0.17, which exhibit better accuracy than that of the nighttime MERRA-2 AOD. We further compared the retrieved nighttime AOD with the corresponding Air Quality Index (AQI) measurements at six environment monitoring stations and obtained high correlation coefficients (i.e., ranging from 0.733 to 0.940), indicating SCANS's reliability and high accuracy. The proposed SCANS algorithm can effectively obtain nighttime AOD with high quality, thereby advancing research on the diurnal variation of crucial Earth's key elements.

Assessment of severe aerosol events from NASA MODIS and VIIRS aerosol products for data assimilation and climate continuity

Abstract. While the use and data assimilation (DA) of operational Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol data is commonplace, MODIS is scheduled to sunset in the next year. For data continuity, focus has turned to the development of next-generation aerosol products and sensors such as those associated with the Visible Infrared Imaging Radiometer Suite (VIIRS) on Suomi NPOESS Preparation Project (S-NPP) and NOAA-20. Like MODIS algorithms, products from these sensors require their own set of extensive error characterization and correction exercises. This is particularly true in the context of monitoring significant aerosol events that tax an algorithm's ability to separate cloud from aerosol and account for multiple scattering related errors exacerbated by uncertainties in aerosol optical properties. To investigate the performance of polar-orbiting satellite algorithms to monitor and characterize significant events, a level 3 (L3) product has been developed using a consistent aggregation methodology for 4 years of observations (2016–2019) that is referred to as the SSEC/NRL L3 product. Included in this product are the AErosol RObotic NETwork (AERONET), MODIS Dark Target, Deep Blue, and Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithms. These MODIS “baseline algorithms” are compared to NASA's recently released NASA Deep Blue algorithm for use with VIIRS. Using this new dataset, the relative performance of the algorithms for both land and ocean were investigated with a focus on the relative skill of detecting severe events and accuracy of the retrievals using AERONET. Maps of higher-percentile aerosol optical depth (AOD) regions of the world by product identified those with the highest measured AODs and determined what is high by local standards. While patterns in AOD match across products and median to moderate AOD values match well, there are regionally correlated biases between products based on sampling, algorithm differences, and AOD range – in particular for higher AOD events. Most notable are differences in boreal biomass burning and Saharan dust. Significant percentile biases must be accounted for when data are used in trend studies, data assimilation, or inverse modeling. These biases vary by aerosol regime and are likely due to retrieval assumptions in lower boundary conditions and aerosol optical models.

Sensitivity studies of nighttime top-of-atmosphere radiances from artificial light sources using a 3-D radiative transfer model for nighttime aerosol retrievals

Abstract. By accounting for surface-based light source emissions and top-of-atmosphere (TOA) downward lunar fluxes, we adapted the spherical harmonics discrete ordinate method (SHDOM) 3-dimensional (3-D) radiative transfer model (RTM) to simulate nighttime 3-D TOA radiances as observed from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) on board the Suomi-NPP satellite platform. Used previously for daytime 3-D applications, these new SHDOM enhancements allow for the study of the impacts of various observing conditions and aerosol properties on simulated VIIRS-DNB TOA radiances. Observations over Dakar, Senegal, selected for its bright city lights and a large range of aerosol optical depth (AOD), were investigated for potential applications and opportunities for using observed radiances containing VIIRS-DNB “bright pixels” from artificial light sources to conduct aerosol retrievals. We found that using the standard deviation (SD) of such bright pixels provided a more stable quantity for nighttime AOD retrievals than direct retrievals from TOA radiances. Further, both the mean TOA radiance and SD of TOA radiances over artificial sources are significantly impacted by satellite viewing angles. Light domes, the enhanced radiances adjacent to artificial light sources, are strong functions of aerosol properties and especially aerosol vertical distribution, which may be further utilized for retrieving aerosol layer height in future studies. Through inter-comparison with both day- and nighttime Aerosol Robotic Network (AERONET) data, the feasibility of retrieving nighttime AODs using 3-D RTM SHDOM over artificial light sources was demonstrated. Our study shows strong potential for using artificial light sources for nighttime AOD retrievals, while also highlighting larger uncertainties in quantifying surface light source emissions. This study underscores the need for surface light emission source characterizations as a key boundary condition, which is a complex task that requires enhanced input data and further research. We demonstrate how quality-controlled nighttime light data from the NASA's Black Marble product suite could serve as a primary input into estimations of surface light source emissions for nighttime aerosol retrievals.

Assessment of Satellite AOD during the 2020 Wildfire Season in the Western U.S.

Satellite remote sensing of aerosol optical depth (AOD) is essential for detection, characterization, and forecasting of wildfire smoke. In this work, we evaluate the AOD (550 nm) retrievals during the extreme wildfire events over the western U.S. in September 2020. Three products are analyzed, including the Moderate-resolution Imaging Spectroradiometers (MODIS) Multi-Angle Implementation of Atmospheric Correction (MAIAC) product collections C6.0 and C6.1, and the NOAA-20 Visible Infrared Imaging Radiometer (VIIRS) AOD from the NOAA Enterprise Processing System (EPS) algorithm. Compared with the Aerosol Robotic Network (AERONET) data, all three products show strong linear correlations with MAIAC C6.1 and VIIRS presenting overall low bias (&lt;0.06). The accuracy of MAIAC C6.1 is found to be substantially improved with respect to MAIAC C6.0 that drastically underestimated AOD over thick smoke, which validates the effectiveness of updates made in MAIAC C6.1 in terms of an improved representation of smoke aerosol optical properties. VIIRS AOD exhibits comparable uncertainty with MAIAC C6.1 with a slight tendency of increased positive bias over the AERONET AOD range of 0.5–3.0. Averaging coincident retrievals from MAIAC C6.1 and VIIRS provides a lower root mean square error and higher correlation than for the individual products, motivating the benefit of blending these datasets. MAIAC C6.1 and VIIRS are further compared to provide insights on their retrieval strategy. When gridded at 0.1° resolution, MAIAC C6.1 and VIIRS provide similar monthly AOD distribution patterns and the latter exhibits a slightly higher domain average. On daily scale, over thick plumes near fire sources, MAIAC C6.1 reports more valid retrievals where VIIRS tends to have retrievals designated as low or medium quality, which tends to be due to internal quality checks. Over transported smoke near scattered clouds, VIIRS provides better retrieval coverage than MAIAC C6.1 owing to its higher spatial resolution, pixel-level processing, and less strict cloud masking. These results can be used as a guide for applications of satellite AOD retrievals during wildfire events and provide insights on future improvement of retrieval algorithms under heavy smoke conditions.

A Simple Band Ratio Library (BRL) Algorithm for Retrieval of Hourly Aerosol Optical Depth Using FY-4A AGRI Geostationary Satellite Data

The Advanced Geostationary Radiation Imager (AGRI) is one of the primary payloads aboard the FY-4A geostationary meteorological satellite, which can provide high-frequency, wide coverage, and multiple spectral channel observations for China and surrounding areas. There are currently few studies on aerosol optical depth (AOD) inversion from FY-4A AGRI data. Based on AGRI data, a new land AOD retrieval algorithm called the band ratio library (BRL) algorithm was proposed in this study. The monthly average surface reflectance band ratio library was established after obtaining the relationship of band surface reflectance ratio from the MODIS combined AOD dataset. In order to calculate the hourly AOD, look-up tables (LUT) for the various aerosol models were constructed using the 6SV model. We quantitatively compared AOD produced from AGRI data with AERONET ground observations to validate the BRL algorithm. AGRI-retrieved AOD is in good agreement with AOD measured by AERONET, which has a correlation coefficient of R is 0.84, the linear regression function is AODAGRI = 0.80 ∗ AODAERONET − 0.004, the root-mean-square error (RMSE) is 0.16, and approximately 60% of the AGRI AOD results fall within the uncertain range of AOD = ±(0.2 × AODAERONET + 0.05). A cross-comparison was made with the MODIS AOD product provided by NASA. The comparison and verification show the proposed algorithm has a good accuracy of land AOD estimation from AGRI data.

AEROsol generic classification using a novel Satellite remote sensing Approach (AEROSA)

Numerous studies (hereafter GA: general approach studies) have been made to classify aerosols into desert dust (DD), biomass-burning (BB), clean continental (CC), and clean maritime (CM) types using only aerosol optical depth (AOD) and Ångström exponent (AE). However, AOD represents the amount of aerosol suspended in the atmospheric column while the AE is a qualitative indicator of the size distribution of the aerosol estimated using AOD measurements at different wavelengths. Therefore, these two parameters do not provide sufficient information to unambiguously classify aerosols into these four types. Evaluation of the performance of GA classification applied to AErosol Robotic NETwork (AERONET) data, at sites for situations with known aerosol types, provides many examples where the GA method does not provide correct results. For example, a thin layer of haze was classified as BB and DD outside the crop burning and dusty seasons respectively, a thick layer of haze was classified as BB, and aerosols from known crop residue burning events were classified as DD, CC, and CM by the GA method. The results also show that the classification varies with the season, for example, the same range of AOD and AE were observed during a dust event in the spring (20th March 2012) and a smog event in the autumn (2nd November 2017). The results suggest that only AOD and AE cannot precisely classify the exact nature (i.e., DD, BB, CC, and CM) of aerosol types without incorporating more optical and physical properties. An alternative approach, AEROsol generic classification using a novel Satellite remote sensing Approach (AEROSA), is proposed to provide aerosol amount and size information using AOD and AE, respectively, from the Terra-MODIS (MODerate resolution Imaging Spectroradiometer) Collection 6.1 Level 2 combined Dark Target and Deep Blue (DTB) product and AERONET Version 3 Level 2.0 data. Although AEROSA is also based on AOD and AE, it does not claim the nature of aerosol types, instead providing information on aerosol amount and size. The purpose is to introduce AEROSA for those researchers who are interested in the generic classification of aerosols based on AOD and AE, without claiming the exact aerosol types such as DD, BB, CC, and CM. AEROSA not only provides 9 generic aerosol classes for all observations but can also accommodate variations in location and season, which GA aerosol types do not.

A Comparison of Multi-Angle Implementation of Atmospheric Correction and MOD09 Daily Surface Reflectance Products From MODIS

This study presents the first systematic comparison of MAIAC Collection 6 MCD19A1 daily surface reflectance (SR) product with standard MODIS SR (MOD/MYD09). The study was limited to four tiles located in mid-Atlantic United States (H11V05), Canada (H12V03), central Amazon (H11V09), and North-Eastern China (H27V05) and used over 5000 MODIS granules in 2018. Overall, there is a remarkable agreement between the best quality pixels of the two products, in particular in the Red and NIR bands. Over selected tiles, the evaluation found that MAIAC provides from 4 to 25% more high-quality retrievals than MOD09 annually, with the largest difference in tropical regions, confirming results of the previous studies. The comparison of spectral characteristics showed a systematic MAIAC-MOD09 difference increasing from NIR to Blue, typical of biases of a Lambertian assumption in MOD09 algorithm. Over the North-Eastern China, MCD19A1 SR is found more stable at wide range of aerosol optical depth (AOD) variations, whereas MOD09 SR shows a consistent positive bias increasing with AOD and at shorter wavelengths. The observed SR differences can be attributed to differences in cloud detection, aerosol retrieval and in atmospheric correction which is performed using an accurate BRDF-coupled radiative transfer model in MAIAC and a Lambertian surface model in MOD09. While this study is not representative of the global performance because of its limited geographical coverage, it should help the land community to better understand the differences between the two products.

The climate impact of aerosols on the lightning flash rate: is it detectable from long-term measurements?

Abstract. The effect of aerosols on lightning has been noted in many case studies, but much less is known about the long-term impact, relative importance of dynamics–thermodynamics versus aerosol, and any difference by different types of aerosols. Attempts are made to tackle all these factors, whose distinct roles are discovered by analyzing 11-year datasets of lightning, aerosol loading and composition, and dynamic–thermodynamic data from satellite and model reanalysis. Variations in the lightning rate are analyzed with respect to changes in dynamic–thermodynamic variables and indices such as the convective available potential energy (CAPE) and vertical wind shear. In general, lightning has strong diurnal and seasonal variations, peaking in the afternoon and during the summer. The lightning flash rate is much higher in moist central Africa than in dry northern Africa presumably because of the combined influences of surface heating, CAPE, relative humidity (RH), and aerosol type. In both regions, the lightning flash rate changes with aerosol optical depth (AOD) in a boomerang shape: first increasing with AOD, tailing off around AOD = 0.3, and then behaving differently, i.e., decreasing for dust and flattening for smoke aerosols. The deviation is arguably caused by the tangled influences of different thermodynamics (in particular humidity and CAPE) and aerosol type between the two regions. In northern Africa, the two branches of the opposite trends seem to echo the different dominant influences of the aerosol microphysical effect and the aerosol radiative effect that are more pronounced under low and high aerosol loading conditions, respectively. Under low-AOD conditions, the aerosol microphysical effect more likely invigorates deep convection. This may gradually yield to the suppression effect as AOD increases, leading to more and smaller cloud droplets that are highly susceptible to evaporation under the dry conditions of northern Africa. For smoke aerosols in moist central Africa, the aerosol invigoration effect can be sustained across the entire range of AOD by the high humidity and CAPE. This, plus a potential heating effect of the smoke layer, jointly offsets the suppression of convection due to the radiative cooling at the surface by smoke aerosols. Various analyses were done that tend to support this hypothesis.

Aerosol vertical distribution and optical properties of different pollution events in Beijing in autumn 2017

As one of the largest metropolitan areas in the world, Beijing has a high aerosol loading. Although the government has taken various measures to reduce emissions, the large-scale and intermittent occurrence of pollution is still a major issue. To understand the mechanisms and characteristics of pollution, Raman-Mie lidar and CE-318 sun photometer were used to study the aerosol vertical distribution and optical properties during dust, haze and clean periods in Beijing that occurred in September to October 2017. Combined with meteorological data, the sources and transmission paths of the pollution events were analyzed. The results are as follows. For the dust event, irregular particles with a large linear particle depolarization ratio played a leading role. The aerosol boundary layer height reached 3.5 km. The volume concentration of coarse particles was obviously larger in the volume size distribution. Strong northwest winds at high altitudes cause high-altitude long-distance transmission of pollutants. And this process can exacerbate air quality of Beijing. For the haze event, high-spherical water-soluble particles were dominant. The extinction coefficient exceeded 1 km−1 while the linear particle depolarization ratio was relatively small. The aerosol boundary layer height was <1 km. The range of aerosol optical depth at 440 nm varied between 0.8 and 2.4. Compared with the dust process, meteorological conditions contribute differently to the haze pollution. Aerosols from the south-west is one of the major resources of haze in Beijing. Combined with static weather such as low wind speed, the pollution level can be continuously increased. During the clean period, favorable weather conditions, such as high wind speed, provided good conditions for the diffusion of local particles. The extinction coefficient and the linear particle depolarization ratio were significantly lower. The single-scattering albedo fluctuated between 0.75 and 0.85, the scattering of light was weak and the visibility was generally high.

Monitoring temporal–spatial variations of AOD over the Yangtze River Delta, China

Aerosol can induce visibility reduction, affect radiation balance and modify cloud property on the environmental effect, and show the harmful effects on human health. Insight of aerosol becomes an integral task in the process of control measures for environmental pollution. The present study provided an analysis of temporal–spatial variations of aerosol optical depth (AOD) using the MOD04 level-2 in collection 6 (C6) with the deep blue retrieval algorithm from January 2005 to December 2015 over Yangtze River Delta (YRD) in China. The AOD validations between MODIS and Aerosol Robotic Network (AERONET) were estimated by the methods of regression, correlation. Then, the periodic features and trends of AOD and angstrom exponent (AE) were explored with the wavelet transformation (WT) procedure. Further, the variations of AOD and AE spatial distribution on multi-time scales (annual, monthly and season) were demonstrated. Meantime, the sources of AOD are discussed. It was found that the daily AOD from MODIS has a strong correlation relationship (slope = 0.9838, r = 0.84) with AERONET over YRD. The variations of both AOD and AE on time series have been distinct temporal periodic (12, 6 and 4 months) characteristics, and show the decreasing trends on annual and semi-annual periods. On annual, the AOD on spatial distribution is slowly declining from the northwest towards the southeast, and the AE on spatial distribution is gradually decreasing from the northwest to the southeast and from the land to the coast. The variations both inter-annual AOD and AE on spatial distribution show the inverse trends, respectively. On monthly, the means of AOD range from minimum 0.46 in January to maximum 0.90 in July, and the variations of spatial distribution mainly occur in the north parts of Yangtze River and some scattered areas with high terrain and south coast. The means of AE range from minimum 1.13 in October to maximum 1.58 in April, and the variations of spatial distribution are mainly found in the south of Henan, the north of Jiangsu, the coast belt and the riverside of Yangtze River and the high terrain regions. On seasonality, the means of AOD reaches its maximum 0.68 in summer and minimum 0.50 in winter, and the variations of spatial distribution mainly occur in the coast belt, the north parts of Hongze Lake and the south parts with high terrain. The means of AE reaches its maximum 1.48 in spring and minimum 1.25 in autumn, and the variations of spatial distribution were shown the similarity with that of monthly.

New approach to the retrieval of AOD and its uncertainty from MISR observations over dark water

Abstract. A new method for retrieving aerosol optical depth (AOD) and its uncertainty from Multi-angle Imaging SpectroRadiometer (MISR) observations over dark water is outlined. MISR's aerosol retrieval algorithm calculates cost functions between observed and pre-simulated radiances for a range of AODs (from 0.0 to 3.0) and a prescribed set of aerosol mixtures. The previous version 22 (V22) operational algorithm considered only the AOD that minimized the cost function for each aerosol mixture and then used a combination of these values to compute the final, “best estimate” AOD and associated uncertainty. The new approach considers the entire range of cost functions associated with each aerosol mixture. The uncertainty of the reported AOD depends on a combination of (a) the absolute values of the cost functions for each aerosol mixture, (b) the widths of the cost function distributions as a function of AOD, and (c) the spread of the cost function distributions among the ensemble of mixtures. A key benefit of the new approach is that, unlike the V22 algorithm, it does not rely on empirical thresholds imposed on the cost function to determine the success or failure of a particular mixture. Furthermore, a new aerosol retrieval confidence index (ARCI) is established that can be used to screen high-AOD retrieval blunders caused by cloud contamination or other factors. Requiring ARCI ≥0.15 as a condition for retrieval success is supported through statistical analysis and outperforms the thresholds used in the V22 algorithm. The described changes to the MISR dark water algorithm will become operational in the new MISR aerosol product (V23), planned for release in 2017.

Application of a PCA‐Based Fast Radiative Transfer Model to XCO2 Retrievals in the Shortwave Infrared

AbstractIn this work, we extend the principal component analysis (PCA)‐based approach to accelerate radiative transfer (RT) calculations by accounting for the spectral variation of aerosol properties. Using linear error analysis, the errors induced by this fast RT method are quantified for a large number of simulated Greenhouse Gases Observing Satellite (GOSAT) measurements (N≈ 30,000). The computational speedup of the approach is typically 2 orders of magnitude compared to a line‐by‐line discrete ordinates calculation with 16 streams, while the radiance residuals do not exceed 0.01% for the most part compared to the same baseline calculations. We find that the errors due to the PCA‐based approach tend to be less than ±0.06 ppm for both land and ocean scenes when two or more empirical orthogonal functions are used. One advantage of this method is that it maintains the high accuracy over a large range of aerosol optical depths. This technique shows great potential to be used in operational retrievals for GOSAT and other remote sensing missions.

Tropospheric haze and colors of the clear twilight sky.

At the earth's surface, clear-sky colors during civil twilights depend on the combined spectral effects of molecular scattering, extinction by tropospheric aerosols, and absorption by ozone. Molecular scattering alone cannot produce the most vivid twilight colors near the solar horizon, for which aerosol scattering and absorption are also required. However, less well known are haze aerosols' effects on twilight sky colors at larger scattering angles, including near the antisolar horizon. To analyze this range of colors, we compare 3D Monte Carlo simulations of skylight spectra with hyperspectral measurements of clear twilight skies over a wide range of aerosol optical depths. Our combined measurements and simulations indicate that (a) the purest antisolar twilight colors would occur in a purely molecular, multiple-scattering atmosphere, whereas (b) the most vivid solar-sky colors require at least some turbidity. Taken together, these results suggest that multiple scattering plays an important role in determining the redness of the antitwilight arch.

Retrieval of aerosol optical depth from surface solar radiation measurements using machine learning algorithms, non-linear regression and a radiative transfer-based look-up table

Abstract. In order to have a good estimate of the current forcing by anthropogenic aerosols, knowledge on past aerosol levels is needed. Aerosol optical depth (AOD) is a good measure for aerosol loading. However, dedicated measurements of AOD are only available from the 1990s onward. One option to lengthen the AOD time series beyond the 1990s is to retrieve AOD from surface solar radiation (SSR) measurements taken with pyranometers. In this work, we have evaluated several inversion methods designed for this task. We compared a look-up table method based on radiative transfer modelling, a non-linear regression method and four machine learning methods (Gaussian process, neural network, random forest and support vector machine) with AOD observations carried out with a sun photometer at an Aerosol Robotic Network (AERONET) site in Thessaloniki, Greece. Our results show that most of the machine learning methods produce AOD estimates comparable to the look-up table and non-linear regression methods. All of the applied methods produced AOD values that corresponded well to the AERONET observations with the lowest correlation coefficient value being 0.87 for the random forest method. While many of the methods tended to slightly overestimate low AODs and underestimate high AODs, neural network and support vector machine showed overall better correspondence for the whole AOD range. The differences in producing both ends of the AOD range seem to be caused by differences in the aerosol composition. High AODs were in most cases those with high water vapour content which might affect the aerosol single scattering albedo (SSA) through uptake of water into aerosols. Our study indicates that machine learning methods benefit from the fact that they do not constrain the aerosol SSA in the retrieval, whereas the LUT method assumes a constant value for it. This would also mean that machine learning methods could have potential in reproducing AOD from SSR even though SSA would have changed during the observation period.

Diurnal cycle of the dust instantaneous direct radiative forcing over the Arabian Peninsula

Abstract. In this study we attempted to better quantify radiative effects of dust over the Arabian Peninsula and their dependence on input parameters. For this purpose we have developed a stand-alone column radiation transport model coupled with the Mie, T-matrix and geometric optics calculations and driven by reanalysis meteorological fields and atmospheric composition. Numerical experiments were carried out for a wide range of aerosol optical depths, including extreme values developed during the dust storm on 18–20 March 2012. Comprehensive ground-based observations and satellite retrievals were used to estimate aerosol optical properties, validate calculations and carry out radiation closure. The broadband surface albedo, fluxes at the bottom and top of the atmosphere as well as instantaneous dust radiative forcing were estimated both from the model and observations. Diurnal cycle of the shortwave instantaneous dust direct radiative forcing was studied for a range of aerosol and surface characteristics representative of the Arabian Peninsula. Mechanisms and parameters responsible for diurnal variability of the radiative forcing were evaluated. We found that intrinsic variability of the surface albedo and its dependence on atmospheric conditions, along with anisotropic aerosol scattering, are mostly responsible for diurnal effects.

Diurnal Characteristics of Angstrom Turbidity Parameters Over Manila, Philippines

The diurnal variation of the aerosol optical depth (AOD) at 500nm wavelength and the Angstrom turbidity coefficients (α and β) were derived from direct beam measurements. Results of the measurements showed that the AOD, α, and β variations at different time intervals were mainly influenced by human activities and industrial operations as the day progressed. Hourly variability of AOD (in terms of percent departure from the daily mean) showed that it increases from morning and then reaches its maximum diversion from the mean (25%) at noontime (around 11 AM local time) and then slowly decreases in the afternoon. The wavelength exponent showed an almost similar pattern of diurnal variability as AOD. Its variation ranges at about 6 % above and below the average value of α. However β has a different pattern as compared to AOD and α. It consistently departs above the mean at around 20% in the morning and close to 30% below the mean in the afternoon. Daily values of AOD range from 0.545 to 2.174 with values frequently in the range of 0.5 to 1.5. Daily α was frequently around 1.75 but its values ranged from 0.502 to 3.236. This denoted that fine particles were dominating over coarse particles.

Comparison of full-sky polarization and radiance observations to radiative transfer simulations which employ AERONET products

Visible-band and near infrared polarization and radiance images measured with a ground-based full-sky polarimeter are compared against a successive orders of scattering (SOS) radiative transfer model for 2009 summer cloud-free days in Bozeman, Montana, USA. The polarimeter measures radiance and polarization in 10-nm bands centered at 450 nm, 490 nm, 530 nm, 630 nm, and 700 nm. AERONET products are used to represent aerosols in the SOS model, while MISR satellite BRF products are used for the surface reflectance. While model results generally agree well with observation, the simulated degree of polarization is typically higher than observed data. Potential sources of this difference may include cloud contamination and/or underestimation of the AERONET-retrieved aerosol real refractive index. Problems with the retrieved parameters are not unexpected given the low aerosol optical depth range (0.025 to 0.17 at 500 nm) during the study and the corresponding difficulties that these conditions pose to the AERONET inversion algorithm.

Measuring the influence of aerosols and albedo on sky polarization

All-sky distributions of the polarized radiance are measured using an automated fish-eye camera system with a rotating polarizer. For a large range of aerosol and surface albedo situations, the influence on the degree of polarization and sky radiance is investigated. The range of aerosol optical depth and albedo is 0.05–0.5 and 0.1–0.75, respectively. For this range of parameters, a reduction of the degree of polarization from about 0.7 to 0.4 was observed. The analysis is done for 90° scattering angle in the principal plane under clear sky conditions for a broadband channel of 450±25nm and solar zenith angles between 55° and 60°. Radiative transfer calculations considering three different aerosol mixtures are performed and and agree with the measurements within the statistical error.

Aerosols and their influence on radiation partitioning and savanna productivity in northern Australia

Aerosols have been shown to affect the quantity and quality of solar radiation on the Earth’s surface. Savanna regions are subject to frequent burning and release of aerosols that may impact on radiation components and possibly vegetation productivity in this region. Therefore, in this study, we have analyzed the optical properties of aerosols (aerosol optical depth (AOD) and Angstrom coefficient) from the Atmospheric Radiation Measurement site in Darwin for the periods from April 2002 to June 2005 as measured by a multifilter rotating shadowband radiometer. The influence of aerosols and their effect on surface shortwave incoming solar radiation and savanna productivity were examined for the dry season using sky radiation collection of radiometers and eddy covariance measurements from the Howard Springs flux site. Results indicated that aerosol concentrations in the region were relatively low compared to other savanna regions with the maximum monthly average AOD over the period being the greatest in October (0.29 ± 0.003 standard error at 500 nm). The highest monthly average Angstrom exponent was also found in October (1.38 ± 0.008). The relatively low aerosol concentration in this region can be attributed to the mixture of smoke aerosols with humidity haze and local circulations. Over a range of AODs from 0.1 to 0.4, we found a modest increase in the fraction of diffuse radiation to total radiation from 11% to 21%. This small increase in diffuse fraction did not affect the carbon flux significantly. However, because the current range of AOD in the region is relatively low, the region could be sensitive to increases in aerosols and diffuse fraction in the future.