Hyperspectral Satellite Remote Sensing of Aerosol Parameters: Sensitivity Analysis and Application to TROPOMI/S5P

Precise knowledge about aerosols in the lower atmosphere (optical properties and vertical distribution) is particularly important for studying the Earth’s climatic and weather conditions. Measurements from satellite sensors in sun-synchronous and geostationary orbits can be used to map distributions of aerosol parameters in global or regional scales. The new-generation sensor Tropospheric Monitoring Instrument (TROPOMI) onboard the Copernicus Sentinel-5 Precursor (S5P) measures a wide variety of atmospheric trace gases and aerosols that are associated with climate change and air quality using a number of spectral bands between the ultraviolet and the shortwave infrared. In this study, we perform a sensitivity analysis of the forward model parameters and instrument information that are associated with the retrieval accuracy of aerosol layer height (ALH) and optical depth (AOD) using the oxygen (O2) A-band. Retrieval of aerosol parameters from hyperspectral satellite measurements requires accurate surface representation and parameterization of aerosol microphysical properties and precise radiative transfer calculations. Most potential error sources arising from satellite retrievals of aerosol parameters, including uncertainties in aerosol models, surface properties, solar/satellite viewing geometry, and wavelength shift, are analyzed. The impact of surface albedo accuracy on retrieval results can be dramatic when surface albedo values are close to the critical surface albedo. An application to the real measurements of two scenes indicates that the retrieval works reasonably in terms of retrieved quantities and fit residuals.

Earth’s Stratospheric Aerosol Parameters Reconstruction from Polarimetric Measurements of the Sky

Earth’s climate changes are the result of natural changes in the energy balance of Sun irradiation and influence of anthropogenic factors on the variations of ozone layer thickness and stratospheric aerosol abundance. It is developed a miniature polarimeter for satellite polarimetric experiments in the ultraviolet region of the sunlight spectrum. The main task of this device is to the obtain an information on the stratospheric aerosol physical properties. We tested this polarimeter on a bench specially designed and manufactured as well. It is possible to measure by it the phase dependences of the degree of linear polarization (DLP) of solar radiation scattered by the Earth’s atmosphere. A set of special computer programs was developed for comparing the spectral polarimetric measurements DLP data of cloudless sky with model calculations of DLP for the artificial gas-aerosol medium. Thus, the prototype of satellite polarimeter as well as special computer programs make it possible to study the Earth’s atmosphere aerosol physical characteristics.

Long term Spatiotemporal Variability of Atmospheric Aerosol Parameters over Western Indian sites by Satellite Remote Sensing Measurements

Long term satellite observations over more than one decade of several aerosols parameters, i.e., AOD550 nm, AE, COT, UV-AI and ASA have been analyzed to describe their overall monthly and seasonally climatology over least explored region of Western Indian sites. It has been found that maximum aerosols loading characteristics of coarse aerosols of dust mineral origin in May and minimum aerosols values in December month at selected arid sites and semi-arid site. Aerosol variables in noon hours seem to their two time higher values than their fore-noon magnitude at all selected places. Observed findings may be interpreted in view of mixed effect of increasing accumulation of regional and local aerosols emission activities. An significant long term trend in aerosols variable of positive values of more 47% in AE and 25% in AOD 550 nm itself would be indicated due to the extra-enhancement in human made activities of more than 10% in term of population growth, population density, transportation vehicles, industries as the enhancement in local anthropogenic aerosols production sources specially over western arid sites. Thus, the abundance of fine size of anthropogenic aerosols is found to be systematically enhanced in the last decade, which is serious concern to both climate and air pollution change aspect over western Indian region also in similar to other Indian regions.

Deep Learning Based Post-Process Correction of the Aerosol Parameters in the High-Resolution Sentinel-3 Level-2 Synergy Product

Satellite-based aerosol retrievals provide global spatially distributed estimates of atmospheric aerosol parameters that are commonly needed in applications such as estimation of atmospherically corrected satellite data products, climate modeling and air quality monitoring. However, a common feature of the conventional satellite aerosol retrievals is that they have reasonably low spatial resolution and poor accuracy caused by uncertainty in auxiliary model parameters, such as fixed aerosol model parameters, and the approximate forward radiative transfer models utilized to keep the computational complexity feasible. As a result, the improvement and re-processing of the operational satellite data retrieval algorithms would become a tedious and computationally excessive problem. To overcome these problems, we have developed a machine learning-based post-process correction approach to correct the existing operational satellite aerosol data products. Our approach combines the existing satellite retrieval data and a post-processing step where a machine learning algorithm is utilized to predict the approximation error in the conventional retrieval. With approximation error we refer to the discrepancy between the true aerosol parameters and the ones retrieved using the satellite data. Our hypothesis is that the prediction of the approximation error with a finite training data set is a less complex and easier task than the direct fully learned machine learning based prediction in which the aerosol parameters are directly predicted given the satellite observations and measurement geometry. With our approach, there is no need to re-run the existing retrieval algorithms and only a computationally feasible post-processing step is needed. Our approach is based on neural networks trained based on collocated satellite data and accurate ground based AERONET aerosol data. Based on our post-processing approach, we propose a post-process corrected high resolution Sentinel-3 Synergy aerosol product, which gives a spectral estimate of the aerosol optical depth at five different wavelengths with a high spatial resolution equivalent to the native resolution of the Sentinel-3 level-1 data (300 meters at nadir). With aerosol data from Sentinel-3A and 3B satellites, we demonstrate that our approach produces high-resolution aerosol data with better accuracy than the operational Sentinel-3 level-2 Synergy aerosol product or a conventional fully learned machine learning approach.

Long-term trends of black carbon and particle number concentration in the lower free troposphere in Central Europe

Background The implementation of emission mitigation policies in Europe over the last two decades has generally improved the air quality, which resulted in lower aerosol particle mass, particle number, and black carbon mass concentration. However, little is known whether the decreasing particle concentrations at a lower-altitude level can be observed in the free troposphere (FT), an important layer of the atmosphere, where aerosol particles have a longer lifetime and may affect climate dynamics. In this study, we used data from two high-Alpine observatories, Zugspitze-Schneefernerhaus (ZSF) and Jungfraujoch (JFJ), to assess the long-term trends on size-resolved particle number concentrations (PNCs) and equivalent black carbon (eBC) mass concentration separated for undisturbed lower FT conditions and under the influence of air from the planetary boundary layer (PBL) from 2009 to 2018. Results The FT and PBL-influenced conditions were segregated for both sites. We found that the FT conditions in cold months were more prevalent than in warm months, while the measured aerosol parameters showed different seasonal patterns for the FT and PBL-influenced conditions. The pollutants in the PBL-influenced condition have a higher chance to be transported to high-altitudes due to the mountainous topography, leading to a higher concentration and more distinct seasonal variation, and vice versa. The long-term trends of the measured aerosol parameters were evaluated and the decreased aerosol concentrations were observed for both FT and PBL-influenced conditions. The observed decreasing trends in eBC concentration in the PBL-influenced condition are well consistent with the reported trends in total BC emission in Germany and Switzerland. The decreased concentrations in the FT condition suggest that the background aerosol concentration in the lower FT over Central Europe has correspondingly decreased. The change of back trajectories in the FT condition at ZSF and JFJ was further evaluated to investigate the other possible drivers for the decreasing trends. Conclusions The background aerosol concentration in the lower FT over Central Europe has significantly decreased during 2009–2018. The implementation of emission mitigation policies is the most decisive factor and the decrease of the regional airmass occurrence over Central Europe also has contributed to the decreasing trends.

Interpretation of weak backscattering signals in a weakly clouded atmosphere

It is used here the lidar equation describing signals from a weakly turbid atmosphere to solve the problem of the determination of the atmospheric aerosol parameters. It is worthwhile to note that the backscattering and extinction coefficients are constant along the beam path in this case. First approximation of the exponent process can be used to describe the atmospheric extinction. The weak lidar signals were analyzed here. It is useful for calculations of the extinction coefficient the preliminary known value of this parameter. The systematic errors were analyzed for different points along the beam path. The signal power was measured at sufficiently large distance. The systematic errors of the extinction coefficient can exceed the systematic errors of the backscattering signal power. It was shown that corresponding value achieve 20. There was investigated the influence of the systematic errors of the measured signal including background light on the obtained results. It was shown that the obtained results cannot be accurate enough if we use preliminary obtained data found before the measurement. It is found that the relative error of the measured signal ˂1%. It is very important the relative error of the corresponding extinction coefficient can be ˃ 100%. There were investigated the results of measurements and the results of computations. First of all it is associated with the scattered irradiance. The cases were considered with absence and presence of water in the aerosol particles coating. It was shown that the developed models adequately describe the process of scattering by a particle. So it is possible significantly reduce the aerosol sizing error. This model can be applied in determining the pollution of the Arctic air basin.

Model Selection in Atmospheric Remote Sensing with Application to Aerosol Retrieval from DSCOVR/EPIC. Part 2: Numerical Analysis

An algorithm for retrieving aerosol parameters by taking into account the uncertainty in aerosol model selection is applied to the retrieval of aerosol optical thickness and aerosol layer height from synthetic measurements from the EPIC sensor onboard the Deep Space Climate Observatory. The synthetic measurements are generated using aerosol models derived from AERONET measurements at different sites, while other commonly used aerosol models, such as OPAC, GOCART, OMI, and MODIS databases are used in the retrieval. The numerical analysis is focused on the estimation of retrieval errors when the true aerosol model is unknown. We found that the best aerosol model is the one with a value of the asymmetry parameter and an angular variation of the phase function around the viewing direction that is close to the values corresponding to the reference aerosol model.