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The VIRTIS (Visible, Infrared and Thermal Imaging Spectrometer) instrument aboard the Rosetta spacecraft has performed extensive spectral mapping of the surface of comet 67P/Churyumov-Gerasimenko in the range 0.3-5 mu m. The reflectance spectra collected across the surface display a low reflectance factor over the whole spectral range, two spectral slopes in the visible and near-infrared ranges and a broad absorption band centered at 3.2 mu m. The first two of these characteristics are typical of dark small bodies of the Solar System and are difficult to interpret in terms of composition. Moreover, solar wind irradiation may modify the structure and composition of surface materials and there is no unequivocal interpretation of these spectra devoid of vibrational bands. To circumvent these problems, we consider the composition of cometary grains analyzed in the laboratory to constrain the nature of the cometary materials and consider results on surface rejuvenation and solar wind processing provided by the OSIRIS and ROSINA instruments, respectively. Our results lead to five main conclusions: (i) The low albedo of comet 67P/CG is accounted for by a dark refractory polyaromatic carbonaceous component mixed with opaque minerals. VIRTIS data do not provide direct insights into the nature of these opaque minerals. However, according to the composition of cometary grains analyzed in the laboratory, we infer that they consist of Fe-Ni alloys and FeS sulfides. (ii) A semi-volatile component, consisting of a complex mix of low weight molecular species not volatilized at T similar to 220 K, is likely a major carrier of the 3.2 p.m band. Water ice contributes significantly to this feature in the neck region but not in other regions of the comet. COOH in carboxylic acids is the only chemical group that encompasses the broad width of this feature. It appears as a highly plausible candidate along with the NH4+ ion. (iii) Photolytic/thermal residues, produced in the laboratory from interstellar ice analogs, are potentially good spectral analogs. (iv) No hydrated minerals were identified and our data support the lack of genetic links with the CI, CR and CM primitive chondrites. This concerns in particular the Orgueil chondrite, previously suspected to have been of cometary origin. (v) The comparison between fresh and aged terrains revealed no effect of solar wind irradiation on the 3.2 mu m band. This is consistent with the presence of efficient resurfacing processes such as dust transport from the interior to the surface, as revealed by the OSIRIS camera. (C) 2016 Elsevier Inc. All rights reserved.
In the last few years the method of cosmic-ray neutron sensing (CRNS) has gained popularity among hydrologists, physicists, and land-surface modelers. The sensor provides continuous soil moisture data, averaged over several hectares and tens of decimeters in depth. However, the signal still may contain unidentified features of hydrological processes, and many calibration datasets are often required in order to find reliable relations between neutron intensity and water dynamics. Recent insights into environmental neutrons accurately described the spatial sensitivity of the sensor and thus allowed one to quantify the contribution of individual sample locations to the CRNS signal. Consequently, data points of calibration and validation datasets are suggested to be averaged using a more physically based weighting approach. In this work, a revised sensitivity function is used to calculate weighted averages of point data. The function is different from the simple exponential convention by the extraordinary sensitivity to the first few meters around the probe, and by dependencies on air pressure, air humidity, soil moisture, and vegetation. The approach is extensively tested at six distinct monitoring sites: two sites with multiple calibration datasets and four sites with continuous time series datasets. In all cases, the revised averaging method improved the performance of the CRNS products. The revised approach further helped to reveal hidden hydrological processes which otherwise remained unexplained in the data or were lost in the process of overcalibration. The presented weighting approach increases the overall accuracy of CRNS products and will have an impact on all their applications in agriculture, hydrology, and modeling.
In the last few years the method of cosmic-ray neutron sensing (CRNS) has gained popularity among hydrologists, physicists, and land-surface modelers. The sensor provides continuous soil moisture data, averaged over several hectares and tens of decimeters in depth. However, the signal still may contain unidentified features of hydrological processes, and many calibration datasets are often required in order to find reliable relations between neutron intensity and water dynamics. Recent insights into environmental neutrons accurately described the spatial sensitivity of the sensor and thus allowed one to quantify the contribution of individual sample locations to the CRNS signal. Consequently, data points of calibration and validation datasets are suggested to be averaged using a more physically based weighting approach. In this work, a revised sensitivity function is used to calculate weighted averages of point data. The function is different from the simple exponential convention by the extraordinary sensitivity to the first few meters around the probe, and by dependencies on air pressure, air humidity, soil moisture, and vegetation. The approach is extensively tested at six distinct monitoring sites: two sites with multiple calibration datasets and four sites with continuous time series datasets. In all cases, the revised averaging method improved the performance of the CRNS products. The revised approach further helped to reveal hidden hydrological processes which otherwise remained unexplained in the data or were lost in the process of overcalibration. The presented weighting approach increases the overall accuracy of CRNS products and will have an impact on all their applications in agriculture, hydrology, and modeling.