Atmospheric correction of satellite optical data is based on an assessment of the optical characteristics of the atmosphere, such as the aerosol optical depth of the atmosphere and the spectral slope of its spectrum, the so-called Angstrom parameter. Inaccurate determination of these parameters is one of the causes of errors in the retrieval of the remote sensing reflectance spectra. In this work, the obtained large array of field and satellite data for the northeastern part of the Black Sea is used, including ship-based measurements of atmospheric characteristics and sea reflectance, MODIS Aqua/Terra and OLCI Sentinel-3 A/B Level 2 remote sensing reflectance and atmospheric data. The purpose of this study is to show the numerical differences between the atmospheric parameters measured from the surface level and from the satellite and demonstrate their relationship with the differences between in situ and satellite remote sensing reflectance. Based on the information received, we propose an algorithm for the additional correction of satellite Level 2 data that uses a two-parametric model of the Black Sea remote sensing reflectance as a first approximation. This method does not require any in situ information. It is shown that additional correction significantly reduces the discrepancy between in situ and retrieved remote sensing reflectance, especially in short-wave spectral bands.

This paper focuses on the atmospheric dust transport effect on the changes in chlorophyll-A concentration in the Black Sea surface layer. In order to assess the input of nutrients with atmospheric precipitations at the Crimean coast of the Black Sea, the collected samples were analyzed for the content of inorganic nitrogen, phosphates, and silicon. The samples were taken into a wet-only sampler and into a permanently open one, to assess the effect of dust on the nutrients concentration in dry depositions. Cases of multi-fold excess of the nutrients content in the open sampler collected precipitation over that in the wet-only sampler were identified. For such high concentration cases, the 7-day back-trajectories analyses was carried out using the model of the international network AERONET and the HYSPLIT model. The results of our research showed that the influx of nutrients with the atmospheric depositions can result in increasing of chlorophyll-A concentration in 11–36% in the surface layer of the Black Sea. After atmospheric depositions, concentration of phosphates in the surface layer can increase more than five times compared with the background concentration. The increase of silicon concentration can reach 30%. The influx of atmospheric precipitation containing significant amounts of nutrients into the bay can shifts the Redfield ratio compared with background value up to three times.

Atmospheric correction of satellite optical data is based on an assessment of the optical characteristics of the atmosphere, such as the aerosol optical thickness of the atmosphere and the spectral slope, the so-called Angstrom parameter. Inaccurate determination of these parameters is one of the causes of error in the retrieval of remote-sensed reflectance spectra. In this work, a large array of field and satellite data measured in Sevastopol and the northeastern part of the Black Sea were used, including ship-based measurements of atmospheric characteristics and sea reflectance, MODIS Aqua/Terra, and VIIRS NOAA/NPP Level 2 remote-sensed reflectance and atmospheric data. In total, three episodes of Saharan dust transfer over the Black Sea region were considered, mainly in the autumn-winter period. The purpose of this study was to show the numerical differences between the atmospheric parameters measured at the surface level and by satellites, and show their relationship with the differences between in situ and satellite remote-sensed reflectance. Based on the information identified, we propose an algorithm for additional correction of satellite level 2 data that uses a two-parametric model of the Black Sea remote-sensed reflectance as a first approximation. Moreover, additional correction significantly reduces the discrepancy between in situ and retrieved remote-sensed reflectance, especially in short-wave spectral bands.

Purpose. One of the most pressing problems of large cities is air pollution resulting from presence of various large and fine particles in the air. These micro-particles can be transported by the air currents over considerable distances, as well as coagulate various substances also present in the atmosphere. The purpose of the work is to study the content of particulate matter of 2.5 and 10 microns (PM2.5 and PM10) in the atmosphere of Sevastopol, as well as the processes affecting their concentration. Methods and Results. During the period from February to June, 2020, the scientists of Marine Hydrophysical Institute (MHI), RAS measured mass concentration of PM2.5 and PM10 in Sevastopol using the “Atmas” dust analyzer. A total of 180 measurements of the micro-particle concentrations in the air of Sevastopol were done, and 60 values of the PM2.5 and PM10 daily average concentrations were obtained. To analyze the preferred aerosol type for the dates with high content of suspended particles in the air, the CALIPSO satellite data were used. It is shown that the smoke recorded in the Sevastopol atmosphere on 19.02.2020 could lead to increase of the PM10 particles concentration. A day before the increased concentrations of suspended particles were revealed in the Sevastopol atmospheric air, the CALYPSO satellite data on aerosol typing over the Black Sea had shown predominance of the smoke aerosol in the atmosphere over the region under study. Conclusions. The results of the investigation shows that in the atmosphere of Sevastopol, the cases when the PM2.5 and PM10 particles contents exceeded the maximum permissible daily average concentration by up to 3.4 times were detected. It was found that the main cause of air pollution with micro-particles in Sevastopol was the transfer both of air masses from the deserts in the African continent and Asia and the burning biomass aerosol (smoke). Air pollution with the PM10 particles caused by the local source, namely soil exсavation in immediate proximity to the air sampling point, was less significant.

The main challenge that one has to face during the atmospheric correction (AC) of productive inland waters is the inability to correctly separate aerosol radiance from water-leaving radiance in the near-infrared range (NIR) bands. This leads both to incorrect estimates of the aerosol parameters and the remote-sensing reflectance (R_rs). For the Gorky Reservoir, where we are developing regional bio-optical models, the situation is complicated by the lack of field measurements of aerosol optical properties due to the significant remoteness of AERONET stations. The standard AC algorithms, as shown earlier, greatly overestimated the aerosol radiance in all spectral bands up to red bands during the period of intense cyanobacteria blooms, while the algorithm with a fixed aerosol optical depth (AOD) obtained in a clean water area gave encouraging results. Therefore, it was important to investigate the characteristics of the atmosphere above the reservoir and validate the proposed approach for regular use of Sentinel-3 imagery of the Gorky Reservoir. To solve these issues, regular in situ aerosol measurements using the handheld sun photometer SPM were performed. The measured AOD and the Angstrom exponent were compared with the estimates of these parameters from two Sentinel-3/OLCI Level-2 products, namely, Synergy (SYN) and Water Full Resolution products (OL_2_WFR). It was found that AOD and the Angstrom exponent from these standard products were overestimated by 2–3 times and almost 2 times in all cases. Atmospheric correction with fixed AOD, defined by measurements, allows us to completely get rid of negative R_rs, and its shapes and values became typical for the Gorky Reservoir. Despite the overestimation of AOD in traditional AC and its large variations in general, it was found that the minimum AOD spectrum is close to the measured spectrum. Therefore, the AOD spectra, which correspond to the two percentiles of the distribution, can be used for preliminary AC with a fixed AOD of the Sentinel-3/OLCI imaginary. The relative errors of the R_rs retrievals using the two percentile AOD compared to the measured AOD were 3–35% in the green and red bands of Sentinel-3/OLCI.