Estimation of elemental abundances of the lunar regolith using clementine UVVIS+NIR data

In this study we propose a regression model for the estimation of lunar elemental abundances from spectral features extracted from Clementine multispectral imagery in the visible and near-infrared domain. We extract a set of spectral features, including the continuum slope, the FWHM of the ferrous absorption trough near 1000 nm, and the wavelengths and relative depths of the absorption minima and inflection points present in the trough. As a “ground truth” for the elemental abundances we rely on the Lunar Prospector gamma ray spectrometer (LP GRS) data. With respect to the elemental abundances of the Apollo and Luna landing sites independently derived from returned samples, the best examined regression model is a second-order polynomial. The proposed regression-based approach allows an estimation of the elemental abundances of Ca, Al, Fe, Mg, and O at an accuracy of about 1 wt% and some tenths of a weight percent for Ti. We examine the influence of calibration of the Clementine UVVIS+NIR data and find that its effect on the results obtained with the regression approach is minor. Furthermore, we define a three-endmember model which allows the petrographic mapping of the lunar surface materials in terms of their Fe, Mg, and Al abundances. We examine the global distribution of Mg-rich rocks, the distribution of cryptomaria, and the occurrence of aluminous mare basalts in the Frigoris region. A possible regional compositional anomaly in northwestern Oceanus Procellarum is found, which corresponds to an extended area displaying spectral characteristics consistent with mare basalt containing significant amounts of olivine. On local scales, we examine in terms of our regression model the highland craters Proclus and Tycho, the compositionally anomalous central peaks of the craters Copernicus and Bullialdus, and the pyroclastic deposits on the floor of Alphonsus and on the northern rim of Petavius. As a general result, we show that the regression-based approach allows the detection of the main lunar terrain classes and rock types based on multispectral imagery in the visible and near-infrared domain.     

Thermal anomalies associated with shallow gas hydrates in the K-2 mud volcano, Lake Baikal

Thermal measurements and hydrate mapping in the vicinity of the K-2 mud volcano in Lake Baikal have revealed a particular type of association of thermal anomalies (29–121?mW?m^–2) near hydrate-forming layers. Detailed coring within K-2 showed that hydrates are restricted to two distinct zones at sub-bottom depths exceeding 70–300?cm. Temperature data from stations with hydrate recovery and degassing features all display low thermal gradients. Otherwise, the thermal gradients within the mud volcano are generally increased. These findings imply a more complicated thermal regime than often assumed for mud volcanoes, with important roles for both fluids and hydrates. The coexistence of neighbouring low and high thermal anomalies is interpreted to result from discharging and recharging fluid activity, rather than hydrate thermodynamics. It is suggested that hydrates play a key role in controlling the fluid circulation pattern at an early stage. At a later stage, the inflow of undersaturated lake water would favour the dissolution of structure I hydrates and the formation of structure II hydrates, the latter having been observed on top of structure I hydrates in the K-2 mud volcano.     

Kinematical characteristics of the factorized velocity model

The factorized velocity model that incorporates both vertical heterogeneity and constant anisotropy is one of the complicated analytical models used in seismic data processing and interpretation. In this paper, I derive the analytic equations for offset, traveltime and relative geometrical spreading for the quasi‐compressional (qP‐) waves that can be used for modelling and inversion of the traveltime parameters. I show that the presence of anelliptic anisotropy usually dominates over the vertical heterogeneity with respect to the non‐hyperbolicity of the factorized velocity model.     

Monitoring of the Arctic region: contribution of the Arkhangelsk seismic network

We evaluate the contribution of the Arkhangelsk seismic network to the recording of seismic events of the Arctic region. The evaluation is performed by means of the general analysis of the network seismic catalog, evaluation of the magnitude sensitivity, and comparative analysis of the Arkhangelsk network catalogs with NORSAR seismological data services and the Geophysical Service of the Russian Academy of Sciences. It is established that the Arkhangelsk network has a rather high sensitivity and records the intra-plate and inter-plate seismic activity in the Arctic Region. Due to the start of the seismic station operation on the Franz Josef Land Archipelago, there is a capability to record earthquakes, data on which are missing in the catalogs of well-known seismological data services.     

Holocene hydrological variability of Lake Ladoga,northwest Russia,as inferred from diatom oxygen isotopes

This article presents a new comprehensive assessment of the Holocene hydrological variability of Lake Ladoga, northwest Russia. The reconstruction is based on oxygen isotopes of lacustrine diatom silica (δ¹⁸O_diatom) preserved in sediment core Co 1309, and is complemented by a diatom assemblage analysis and a survey of modern isotope hydrology. The data indicate that Lake Ladoga has existed as a freshwater reservoir since at least 10.8 cal. ka BP. The δ¹⁸O_diatom values range from +29.8 to +35.0‰, and relatively higher δ¹⁸O_diatom values around +34.7‰ between c. 7.1 and 5.7 cal. ka BP are considered to reflect the Holocene Thermal Maximum. A continuous depletion in δ¹⁸O_diatom since c. 6.1 cal. ka BP accelerates after c. 4 cal. ka BP, indicating Middle to Late Holocene cooling that culminates during the interval 0.8–0.2 cal. ka BP, corresponding to the Little Ice Age. Lake‐level rises result in lower δ¹⁸O_diatom values, whereas lower lake levels cause higher δ¹⁸O_diatom values. The diatom isotope record gives an indication for a rather early opening of the Neva River outflow at c. 4.4–4.0 cal. ka BP. Generally, overall high δ¹⁸O_diatom values around +33.5‰ characterize a persistent evaporative lake system throughout the Holocene. As the Lake Ladoga δ¹⁸O_diatom record is roughly in line with the 60°N summer insolation, a linkage to broader‐scale climate change is likely.     

冰力学参数的超声波测试研究

利用非线性高能超声测试设备及超声波(纵波、横波)波速与物体力学参数的关系,对人造冰样进行了冰样力学参数(杨氏模量、泊松比、剪切模量、体积模量)随温度变化的研究。通过MATLAB进行所测数据曲线拟合,得到超声波波速在人造冰样中随温度的变化规律,进而由理论公式推导所测人造冰样力学参数随温度的变化规律。结果表明:冰样中超声波波速随温度降低而升高,冰样的杨氏模量、泊松比、剪切模量、体积模量也都随温度降低而升高。本研究有助于超声波检测法在冰样物理力学性质测量中的应用,为开展南极冰盖、海冰以及终年冻土等力学及流动特性研究提供理论模型和实验数据。     

Elemental diffusion and segregation processes in partially ionized solar plasma

Although diffusion is usually associated with equalizing of the chemical composition, the pressure and temperature gradients inside the Sun cause elemental diffusion segregation. While light hydrogen is flowing up to the solar envelope, helium and heavier elements are settling down to the core. The target of our simulation is an accurate estimation of the settling rate in solar plasma during the course of solar evolution. The rate of helium depletion in the envelope is a key parameter of the solar evolution and depends on position and conditions around the base of the convective mixing zone. The rate of heavy element settling is sensitive to the degree of ionization and interaction with the radiation flux. We estimate the effect of ion ionization on the settling rate for several heavy elements up to iron in the framework of the LTE assumption and the thermodynamic calculation according to SAHA-S EOS.     

Upper Ocean Temperatures Hit Record High in 2020

The long-term warming of the ocean is a critical indicator of both the past and present state of the climate system. It also provides insights about the changes to come, owing to the persistence of both decadal variations and secular trends,which the ocean records extremely well(Hansen et al., 2011;IPCC, 2013;Rhein et al., 2013;Trenberth et al., 2016;Abram et al., 2019).     

Model-based remote sensing algorithms for particulate organic carbon (POC) in the Northeastern Gulf of Mexico

Hydrographic data, including particulate organic carbon (POC) from the Northeastern Gulf of Mexico (NEGOM) study, were combined with remotely-sensed SeaWiFS data to estimate POC concentration using principal component analysis (PCA). The spectral radiance was extracted at each NEGOM station, digitized, and averaged. The mean value and spurious trends were removed from each spectrum. De-trended data included six wavelengths at 58 stations. The correlation between the weighting factors of the first six eigenvectors and POC concentration were applied using multiple linear regression. PCA algorithms based on the first three, four, and five modes accounted for 90, 95, and 98% of total variance and yielded significant correlations with POC with R ² = 0.89, 0.92, and 0.93. These full waveband approaches provided robust estimates of POC in various water types. Three different analyses (root mean square error, mean ratio and standard deviation) showed similar error estimates, and suggest that spectral variations in the modes defined by just the first four characteristic vectors are closely correlated with POC concentration, resulting in only negligible loss of spectral information from additional modes. The use of POC algorithms greatly increases the spatial and temporal resolution for interpreting POC cycling and can be extrapolated throughout and perhaps beyond the area of shipboard sampling.