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The forthcoming spaceborne Ice Cloud Imager (ICI) radiometer has 11 channels in the millimeter (mm) and sub-mm wave range from 183 up to 664 GHz. At some of these frequencies, the atmosphere is very opaque due to strong gaseous and cloud extinction, precluding the observation of the surface. We aim at investigating how to evaluate the ICI channels geolocation error using surface landmark targets. The most transparent ICI channels, i.e., those around 183.3 ± 7.0 GHz at vertical (V) polarization (ICI-1) and around 243.2 ± 2.5 GHz (ICI-4) at horizontal (H)/ V polarization, are considered. Starting from a previous work, we extend the database of the surface landmark targets to cover boreal and austral dry seasons at various latitudes. For testing the geolocation approach, we use satellite Special Sensor Microwave Imager/Sounder (SSMIS) available data at 183.31 ± 6.6 GHz at H-polarization during 2017, obtaining an overall mean error of about 5.0 km and standard deviation of about 2.2 km, well within the ICI geolocation error assessment specifications. Since no imagers are available at 243 GHz, we extrapolate SSMIS data to 243.2 ± 2.5 GHz using a model-based neural-network approach, named Blended Artificial-neural-network Microwave Imager Simulator (BAMIS). The latter is trained by radiative-transfer simulations and global-scale atmospheric reanalyses data as well as SSMIS data. Results confirm that the proposed approach can be successfully exploited for ICI-4 geolocation error assessment at 243.2 ± 2.5 GHz, with results close to those obtained for the SSMIS 183.31 ± 6.6-GHz channel. [ABSTRACT FROM AUTHOR]

A-train satellite data, acquired during the Calbuco volcano (Chile) sub-Plinian eruption in April 2015, are discussed to explore the complementarity of spaceborne observations in the microwave (MW), thermal infrared (TIR), and visible wavelengths for both near-source plume and distal ash clouds. The analysis shows that TIR-based detection techniques are not suitable near the volcanic vent where rising convective columns are associated with large optical depths. Detection and parametric estimates of near-source tephra mass loading and plume height from MW radiometric data, available 69 min after the eruption onset, are proposed. Results indicate a maximum plume altitude of about 21 km above the sea level and an ash mass of $3.65 \times 10^{10}$ kg, in agreement with mass values obtained from empirical formulas, but less than proximal–distal mass deposit of $1.86 \times 10^{11}$ kg. This discrepancy may be explained by extrapolating Advanced Technology Microwave Sounder-based estimates to 6 h, thus obtaining a total mass of about $1.90 \times 10^{11}$ kg. Distal volcanic cloud retrievals are derived from TIR imagery and results show a good agreement between Moderate-Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) retrievals of total mass taking into account the overpass time shift. If only the overlapping pixels between MODIS and VIIRS are considered, the respective estimates are $1.90 \times 10^{9}$ kg and $1.80 \times 10^{9}$ kg. TIR radiometric estimates of distal ash cloud height and mass loadings are also compared with Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations lidar retrievals. For low-to-medium optically thick ash cloud, average Cloud-Aerosol Lidar with Orthogonal Polarization-derived mass loading is about 0.8 g/m2 against 0.4 g/m2 from VIIRS and 1.4 g/m2 from MODIS. [ABSTRACT FROM AUTHOR]

The potential of satellite passive microwave sensors to provide quantitative information about near-source volcanic ash cloud parameters is assessed. To this aim, ground-based microwave weather radar and spaceborne microwave radiometer observations are used together with forward-model simulations. The latter are based on 2-D simulations with the numerical plume model Active Tracer High-Resolution Atmospheric Model (ATHAM), in conjunction with the radiative transfer model Satellite Data Simulator Unit (SDSU) that is based on the deltaEddington approximation and includes Mie scattering. The study area is the Icelandic subglacial volcanic region. The analyzed case study is that of the Grímsvötn eruption in May 2011. ATHAM input parameters are adjusted using available ground data, and sensitivity tests are conducted to investigate the observed brightness temperatures and their variance. The tests are based on the variation of environmental conditions like the terrain emissivity, water vapor, and ice in the volcanic plume. Quantitative correlation analysis between ATHAM/SDSU forward-model columnar content simulations and available microwave radiometric brightness temperature measurements, derived from the Special Sensor Microwave Imager/Sounder (SSMIS), are encouraging in terms of both dynamic range and correlation coefficient. The correlation coefficients are found to vary from -0.37 to -0.63 for SSMIS channels from 91 to 183 \pm 1 GHz, respectively. The larger sensitivity of the brightness temperature at 183 \pm 1 GHz to the columnar content, with respect to other channels, allowed us to consider this channel as the basis for a model-based polynomial relationship of volcanic plume height as a function of the measured SSMIS brightness temperature. [ABSTRACT FROM AUTHOR]

Understanding the lunar physical properties has been attracting the interest of scientists for many years. This paper is devoted to a numerical study on the capability of retrieving the thickness of the first layer of regolith as well as the temperature profile behavior from satellite-based multifrequency radiometers at frequencies ranging from 1 to 24 GHz. To this purpose, a forward thermal–electromagnetic numerical model, able to simulate the response of the lunar material in terms of upward brightness temperature (TB), has been used. The input parameters of the forward model have been set after a detailed investigation of the scientific literature and available measurements. Different choices of input parameters are possible, and their selection is carefully discussed. By exploiting a Monte Carlo approach to generate a synthetic data set of forward-model simulations, a physically based inversion methodology has been developed using a neural network technique. The latter has been designed to perform, from multifrequency TB's, the temperature estimation at the lunar surface, the discrimination of the subsurface material type, and the estimate of the near-surface regolith thickness. Results indicate that, within the simplified scenarios obtained by interposing strata of rock, ice, and regolith, the probability of detection of the presence of discontinuities beneath the lunar crust is on the order of 84%. The estimation uncertainty of the near-surface regolith thickness estimation ranges from 11 to 81 cm, whereas for the surface temperature, its estimation uncertainty ranges from about 1.5 K to 3 K, conditioned to the choice of radiometric frequencies and noise levels. [ABSTRACT FROM AUTHOR]

Abstract: The sub-glacial Plinian explosive eruption of the Grímsvötn volcano, which occurred on May 2011, is for the first time analyzed and quantitatively interpreted by using ground-based weather radar data and the Volcanic Ash Radar Retrieval (VARR) physically-based technique. The prevailing southerly winds stretched the erupted plume toward the Artic pole, thus preventing the ash cloud to move toward continental Europe and threatening the airline traffic (different from the less explosive Eyjafjöll eruption on April and May 2010). The 2011 Grímsvötn eruption has been continuously monitored by the Keflavík C-band weather radar, located at a distance of about 260km from the volcano vent. The VARR methodology is summarized and applied to available radar time series to estimate the coarse ash particle category, volume, fallout, concentration and the plume maximum height, every 5min within the volcano vent surroundings (i.e. an area of about 100×100km2 around the volcano). Due to the large distance from the volcano, fine-grained ash cannot be detected and estimated by the Keflavík C-band weather radar. Estimates of the eruption discharge rate, based on the retrieved ash plume top height, are provided together with an evaluation of the total erupted mass and volume. Deposited ash at ground is also retrieved from radar data by empirically reconstructing the vertical profile of radar reflectivity and estimating the near-surface ash fallout. Radar-based ash retrieval results can be compared with available satellite microwave radiometric imagery in order to show the potential contribution and limitations of these microwave remote sensing products to the understanding and modeling of explosive volcanic ash eruptions. Spaceborne microwave brightness temperatures show a correlation with ash columnar content, derived from VARR, depending on the millimeter-wave frequency and on the spatial averaging. Microphysical sensitivity of satellite microwave brightness temperatures to plume fine and coarse ash suggests their exploitation in synergy with satellite thermal infrared radiometer and ground-based microwave radar observations. [Copyright &y& Elsevier]