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The analytical solutions of the radiative transfer equation are needed for the solution of various applied atmospheric and snow optics problems. In this paper, we propose a simple analytical equation for the top-of-atmosphere (TOA) spectral reflectance. To simplify the problem under study we consider the case of Antarctica, where both snow and atmosphere are almost free of pollutants. This work is focused on the simulation of the moderate spectral resolution TOA measurements (1 nm or so) and the spectral range 400–1000 nm. The values of the coefficient of variance (CV) between the measured by the Ocean and Land Colour Instrument (OLCI) on board Sentinel-3A and modelled spectra are smaller than 10% for most cases in Antarctica. There are regions in Eastern Antarctica, where the values of CV are smaller than 5%. The areas with larger deviations between measured and retrieved spectra could be due to the presence of clouds or structures on the snow surface not captured by the proposed model.

The paper presents the first retrievals of clean snow properties using spaceborne hyperspectral observations via the Environmental Mapping and Analysis Program (EnMAP). The location close to the Concordia station at the Dome C Plateau (Antarctica) was selected. At this location, the atmospheric effects (except molecular light scattering and absorption) are weak, and the simplified atmospheric correction scheme could be applied. The ice grain size, snow specific surface area, and snow spectral and broadband albedos were retrieved using single-view EnMAP measurements. In addition, we propose a technique to retrieve trace gas concentrations (e.g., water vapor and ozone) from EnMAP observations over the snow surfaces. A close correspondence of satellite and ground-measured parameters was found.

The severity of wildfires is increasing globally. In this study, we used data from the Global Change Observation Mission-Climate/Second-generation Global Imager (GCOM-C/SGLI) to characterize the biomass burning aerosols that are generated by large-scale wildfires. We used data from the September 2020 wildfires in western North America. The target area had a complex topography, comprising a basin among high mountains along a coastal region. The SGLI was essential for dealing with the complex topographical changes in terrain that we encountered, as it contains 19 polarization channels ranging from near ultraviolet (380 nm and 412 nm) to thermal infrared (red at 674 nm and near-infrared at 869 nm) and has a fine spatial resolution (1 km). The SGLI also proved to be efficient in the radiative transfer simulations of severe wildfires through the mutual use of polarization and radiance. We used a regional numerical model SCALE (Scalable Computing for Advanced Library and Environment) to account for variations in meteorological conditions and/or topography. Ground-based aerosol measurements in the target area were sourced from the National Aeronautics and Space Administration-Aerosol Robotic Network; currently, official satellite products typically do not provide the aerosol properties for very optically thick cases of wildfires. This paper used satellite observations, ground-based observations, and a meteorological model to define an algorithm for retrieving the aerosol properties caused by severe wildfire events.

The Global Ozone Monitoring Experiment-2 (GOME-2) flies on the Metop series of satellites, the space component of the EUMETSAT Polar System. In this paper we will provide an overview of the instrument design, the on-ground calibration and characterization activities, in-flight calibration, and level 0 to 1 data processing. The current status of the level 1 data is presented and points of specific relevance to users are highlighted. Long-term level 1 data consistency is also discussed and plans for future work are outlined. The information contained in this paper summarizes a large number of technical reports and related documents containing information that is not currently available in the published literature. These reports and documents are however made available on the EUMETSAT web pages and readers requiring more details than can be provided in this overview paper will find appropriate references at relevant points in the text.

In this work, we develop a software suite for studies of atmosphere–underlying SNOW-spaceborne optical receiver light TRANsmission calculations (SNOWTRAN) with applications for the solution of forward and inverse radiative transfer problems in polar regions. Assuming that the aerosol load is extremely low, the proposed theory does not require the numerical procedures for the solution of the radiative transfer equation and is based on analytical equations for the spectral nadir reflectance and simple approximations for the local optical properties of atmosphere and snow. The developed model is validated using EnMAP and PRISMA spaceborne imaging spectroscopy data close to the Concordia research station in Antarctica. A new, fast technique for the determination of the snow grain size and assessment of the snowpack vertical inhomogeneity is then proposed and further demonstrated on EnMAP imagery over the Aviator Glacier and in the vicinity of the Concordia research station in Antarctica. The results revealed a large increase in precipitable water vapor at the Concordia research station in February 2023 that was linked to a warming event and a four times larger grain size at Aviator Glacier compared with Dome C.

The optical diameter of the surface snow grains impacts the amount of energy absorbed by the surface and therefore the onset and magnitude of surface melt. Snow grains respond to surface heating through grain metamorphism and growth. During melt, liquid water between the grains markedly increases the optical grain size, as wet snow grain clusters are optically equivalent to large grains. We present daily surface snow grain optical diameters (dopt) retrieved from the Greenland ice sheet at 1 km resolution for 2017–2019 using observations from Ocean and Land Colour Instrument (OLCI) onboard Sentinel-3A. The retrieved dopt are evaluated against 3 years of in situ measurements in Northeast Greenland. We show that higher dopt are indicative of surface melt as calculated from meteorological measurements at four PROMICE automatic weather stations. We deduce a threshold value of 0.64 mm in dopt allowing categorization of the days either as melting or nonmelting. We apply this simple melt detection technique in Northeast Greenland and compare the derived melting areas with the conventional passive microwave MEaSUREs melt flag for June 2019. The two flags show generally consistent evolution of the melt extent although we highlight areas where large grain diameters are strong indicators of melt but are missed by the MEaSUREs melt flag. While spatial resolution of the optical grain diameter-based melt flag is higher than passive microwave, it is hampered by clouds. Our retrieval remains suitable to study melt at a local to regional scales and could be in the future combined with passive microwave melt flags for increased coverage.

We proposed a simple algorithm to retrieve the total ozone column and snow properties (spectral albedo and effective light absorption path) using the high spatial resolution single–view MSI/S-2 measurements over Antarctica. In addition, the algorithm allows the retrieval of the snow grain size on a scale of 10–20 m. This algorithm should be useful for the understanding of intra-pixel total ozone and snow albedo variability in complement to satellite observations performed on a much coarser spatial resolution scale (0.3–1 km and even larger spatial scales).

In this paper, we present a simplified algorithm to retrieve snow grain size, dust mass absorption coefficient and dust mass concentration from spectral diffuse reflectance measurements at three wavelengths located in the visible and near infrared. The theoretical model is then compared with field spectroscopy data collected in different days from an automated spectrometer in the Alps.

In this work, we propose simple and robust technique for the retrieval of underlying surface spectral reflectance using spaceborne observations. It can be used to process both multispectral moderate resolution satellite data and also multi-zone high spatial resolution data. The technique can work automatically for different types of land surfaces without using huge databases accumulated in advance. The new cloud discrimination and retrieval of the water vapor content in atmosphere procedures are presented. The key point of the proposed atmospheric correction technique is the suggested single-wavelength method for determining the atmospheric aerosol optical thickness without reference to a specific type of underlying surface spectrum. The retrievals of spectral reflectance for various land surfaces with developed technique, performed using computer simulation and experimental data, have demonstrated a high retrieval accuracy.

In this paper, we made use of PRISMA imaging spectroscopy data for retrieving surface snow properties in the Nansen Ice Shelf (East Antarctica). PRISMA satellite mission has been launched in 2019 and it features 239 spectral bands covering the 400-2500 nm interval. These data are promising for cryospheric applications, since several snow and ice parameters can be derived from reflectance in the Visible Near InfraRed - Short Wave InfraRed (VNIR-SWIR) wavelength interval. Here we analyze, for the first time, PRISMA data collected in Antarctica. Our scene was acquired on December 2020 over the Nansen Ice Shelf (NIS). Using PRISMA data we estimated various snow parameters (effective grain diameter, snow specific surface area, snow spectral and broadband albedo, bottom of atmosphere snow reflectance, type of impurities in snow and their concentration), and we compared them with data presented in the scientific literature.