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Zhang, Yang ; Huang, Wentao ; Huang, Baochun ; van Hinsbergen, Douwe J. J. ; Yang, Tao ; Dupont-Nivet, Guillaume ; Guo, Zhaojie
The Gongjue basin from the eastern Qiangtang terrane is located in the transition region where the regional structural lineation curves from east-west-oriented in Tibet to north-south-oriented in Yunnan. In this study, we sampled the red beds in the basin from the lower Gongjue to upper Ranmugou formations for the first time covering the entire stratigraphic profile. The stratigraphic ages are bracketed within 53-43Ma by new detrital zircon U-Pb ages constraining the maximum deposition age to 52.51.5Ma. Rock magnetic and petrographic studies indicate that detrital magnetite and hematite are the magnetic carriers. Positive reversals and fold tests demonstrate that the characteristic remanent magnetization has a primary origin. The Gongjue and Ranmugou formations yield mean characteristic remanent magnetization directions of D-s/I-s=31.0 degrees/21.3 degrees and D-s/I-s=15.9 degrees/22.0 degrees, respectively. The magnetic inclination of these characteristic remanent magnetizations is significantly shallowed compared to the expected inclination for the locality. However, the elongation/inclination correction method does not provide a meaningful correction, likely because of syn-depositional rotation. Rotations relative to the Eurasian apparent polar wander path occurred in three stages: Stage I, 33.33.4 degrees clockwise rotation during the deposition of the Gongjue and lower Ranmugou formations; Stage II, 26.93.7 degrees counterclockwise rotation during deposition of the lower and middle Ranmugou formation; and Stage III, 17.73.3 degrees clockwise rotation after 43Ma. The complex rotation history recorded in the basin is possibly linked to sinistral shear along the Qiangtang block during India indentation into Asia and the early stage of the extrusion of the northwestern Indochina blocks away from eastern Tibet.
Risk-based insurance is a commonly proposed and discussed flood risk adaptation mechanism in policy debates across the world such as in the United Kingdom and the United States of America. However, both risk-based premiums and growing risk pose increasing difficulties for insurance to remain affordable. An empirical concept of affordability is required as the affordability of adaption strategies is an important concern for policymakers, yet such a concept is not often examined. Therefore, a robust metric with a commonly acceptable affordability threshold is required. A robust metric allows for a previously normative concept to be quantified in monetary terms, and in this way, the metric is rendered more suitable for integration into public policy debates. This paper investigates the degree to which risk-based flood insurance premiums are unaffordable in Europe. In addition, this paper compares the outcomes generated by three different definitions of unaffordability in order to investigate the most robust definition. In doing so, the residual income definition was found to be the least sensitive to changes in the threshold. While this paper focuses on Europe, the selected definition can be employed elsewhere in the world and across adaption measures in order to develop a common metric for indicating the potential unaffordability problem.
The literature contains a sizable number of publications where weather types are used to decompose climate shifts or trends into contributions of frequency and mean of those types. They are all based on the product rule, that is, a transformation of a product of sums into a sum of products, the latter providing the decomposition. While there is nothing to argue about the transformation itself, its interpretation as a climate shift or trend decomposition is bound to fail. While the case of a climate shift may be viewed as an incomplete description of a more complex behaviour, trend decomposition indeed produces bogus trends, as demonstrated by a synthetic counterexample with well-defined trends in type frequency and mean. Consequently, decompositions based on that transformation, be it for climate shifts or trends, must not be used.
Earthquake localization is both a necessity within the field of seismology, and a prerequisite for further analysis such as source studies and hazard assessment. Traditional localization methods often rely on manually picked phases. We present an alternative approach using deep learning that once trained can predict hypocenter locations efficiently. In seismology, neural networks have typically been trained with either single-station records or based on features that have been extracted previously from the waveforms. We use three-component full-waveform records of multiple stations directly. This means no information is lost during preprocessing and preparation of the data does not require expert knowledge. The first convolutional layer of our deep convolutional neural network (CNN) becomes sensitive to features that characterize the waveforms it is trained on. We show that this layer can therefore additionally be used as an event detector. As a test case, we trained our CNN using more than 2000 earthquake swarm events from West Bohemia, recorded by nine local three-component stations. The CNN successfully located 908 validation events with standard deviations of 56.4 m in east-west, 123.8 m in north-south, and 136.3 m in vertical direction compared to a double-difference relocated reference catalog. The detector is sensitive to events with magnitudes down to M-L = -0.8 with 3.5% false positive detections.
Hartman, Jan F. ; Gentz, Torben ; Schiller, Amanda ; Greule, Markus ; Grossart, Hans-Peter ; Ionescu, Danny ; Keppler, Frank ; Martinez-Cruz, Karla ; Sepulveda-Jauregui, Armando ; Isenbeck-Schroeter, Margot
A fast and sensitive method for the continuous determination of methane (CH4) and its stable carbon isotopic values (delta C-13-CH4) in surface waters was developed by applying a vacuum to a gas/liquid exchange membrane and measuring the extracted gases by a portable cavity ring-down spectroscopy analyser (M-CRDS). The M-CRDS was calibrated and characterized for CH4 concentration and delta C-13-CH4 with synthetic water standards. The detection limit of the M-CRDS for the simultaneous determination of CH4 and delta C-13-CH4 is 3.6 nmol L-1 CH4. A measurement precision of CH4 concentrations and delta C-13-CH4 in the range of 1.1%, respectively, 1.7 parts per thousand (1 sigma) and accuracy (1.3%, respectively, 0.8 parts per thousand [1 sigma]) was achieved for single measurements and averaging times of 10 min. The response time tau of 57 +/- 5 s allow determination of delta C-13-CH4 values more than twice as fast than other methods. The demonstrated M-CRDS method was applied and tested for Lake Stechlin (Germany) and compared with the headspace-gas chromatography and fast membrane CH4 concentration methods. Maximum CH4 concentrations (577 nmol L-1) and lightest delta C-13-CH4 (-35.2 parts per thousand) were found around the thermocline in depth profile measurements. The M-CRDS-method was in good agreement with other methods. Temporal variations in CH4 concentration and delta C-13-CH4 obtained in 24 h measurements indicate either local methane production/oxidation or physical variations in the thermocline. Therefore, these results illustrate the need of fast and sensitive analyses to achieve a better understanding of different mechanisms and pathways of CH4 formation in aquatic environments.
With increasing amount of strong motion data, Ground Motion Prediction Equation (GMPE) developers are able to quantify empirical site amplification functions (delta S2S(s)) from GMPE residuals, for use in site-specific Probabilistic Seismic Hazard Assessment. In this study, we first derive a GMPE for 5% damped Pseudo Spectral Acceleration (g) of Active Shallow Crustal earthquakes in Japan with 3.4 <= M-w <= 7.3 and 0 <= R-JB <= 600km. Using k-mean spectral clustering technique, we then classify our estimated delta S2S(s)(T = 0.01 - 2s) of 588 wellcharacterized sites, into 8 site clusters with distinct mean site amplification functions, and within-cluster site-tosite variability similar to 50% smaller than the overall dataset variability (phi(S2S)). Following an evaluation of existing schemes, we propose a revised data-driven site classification characterized by kernel density distributions of V-s30, V-s10, H-800, and predominant period (T-G) of the site clusters.
Quantitative estimates of sea-level rise in the Mediterranean Basin become increasingly accurate thanks to detailed satellite monitoring. However, such measuring campaigns cover several years to decades, while longer-term sea-level records are rare for the Mediterranean. We used a data archeological approach to reanalyze monthly mean sea-level data of the Antalya-I (1935–1977) tide gauge to fill this gap. We checked the accuracy and reliability of these data before merging them with the more recent records of the Antalya-II (1985–2009) tide gauge, accounting for an eight-year hiatus. We obtain a composite time series of monthly and annual mean sea levels spanning some 75 years, providing the longest record for the eastern Mediterranean Basin, and thus an essential tool for studying the region's recent sea-level trends. We estimate a relative mean sea-level rise of 2.2 ± 0.5 mm/year between 1935 and 2008, with an annual variability (expressed here as the standard deviation of the residuals, σresiduals = 41.4 mm) above that at the closest tide gauges (e.g., Thessaloniki, Greece, σresiduals = 29.0 mm). Relative sea-level rise accelerated to 6.0 ± 1.5 mm/year at Antalya-II; we attribute roughly half of this rate (~3.6 mm/year) to tectonic crustal motion and anthropogenic land subsidence. Our study highlights the value of data archeology for recovering and integrating historic tide gauge data for long-term sea-level and climate studies.
Sulfur is an important component in volcanic gases at the Earth surface but also present in the deep Earth in hydrothermal or magmatic fluids. Little is known about the evolution of such fluids during ascent in the crust. A new optical cell was developed for in situ Raman spectroscopic investigations on fluids allowing abrupt or continuous changes of pressure up to 200 MPa at temperatures up to 750 degrees C. The concept is based on a flexible gold bellow, which separates the sample fluid from the pressure medium water. To avoid reactions between aggressive fluids and the pressure cell, steel components in contact with the fluid are shielded by gold foil. The cell was tested to study redox reactions in fluids using aqueous ammonium sulfate solutions as a model system. During heating at constant pressure of 130 MPa, sulfate ions transform first to HSO4- ions and then to molecular units such as H2SO4. Variation of pressure shows that the stability of sulfate species relies on fluid density, i.e., highly charged species are stable only in high-density fluids. Partial decomposition of ammonium was evident above 550 degrees C by the occurrence of a nitrogen peak in the Raman spectra. Reduced sulfur species were observed above 700 degrees C by Raman signals near 2590 cm(-1) assigned to HS- and H2S. No clear evidence for the formation of sulfur dioxide was found in contrary to previous studies on aqueous H2SO4, suggesting very reducing conditions in our experiments. Fluid-mineral interaction was studied by inserting into the cell a small, semi-open capsule filled with a mixture of pyrite and pyrrhotite. Oxidation of the sample assembly was evident by transformation of pyrite to pyrrhotite. As a consequence, sulfide species were observed in the fluid already at temperatures of similar to 600 degrees C.
Woutersen, Amber ; Jardine, Phillip E. ; Giovanni Bogota-Angel, Raul ; Zhang, Hong-Xiang ; Silvestro, Daniele ; Antonelli, Alexandre ; Gogna, Elena ; Erkens, Roy H. J. ; Gosling, William D. ; Dupont-Nivet, Guillaume ; Hoorn, Carina
Nitraria is a halophytic taxon (i.e., adapted to saline environments) that belongs to the plant family Nitrariaceae and is distributed from the Mediterranean, across Asia into the south-eastern tip of Australia. This taxon is thought to have originated in Asia during the Paleogene (66-23 Ma), alongside the proto-Paratethys epicontinental sea. The evolutionary history of Nitraria might hold important clues on the links between climatic and biotic evolution but limited taxonomic documentation of this taxon has thus far hindered this line of research. Here we investigate if the pollen morphology and the chemical composition of the pollen wall are informative of the evolutionary history of Nitraria and could explain if origination along the proto-Paratethys and dispersal to the Tibetan Plateau was simultaneous or a secondary process. To answer these questions, we applied a novel approach consisting of a combination of Fourier Transform Infrared spectroscopy (FTIR), to determine the chemical composition of the pollen wall, and pollen morphological analyses using Light Microscopy (LM) and Scanning Electron Microscopy (SEM). We analysed our data using ordinations (principal components analysis and non-metric multidimensional scaling), and directly mapped it on the Nitrariaceae phylogeny to produce a phylomorphospace and a phylochemospace. Our LM, SEM and FTIR analyses show clear morphological and chemical differences between the sister groups Peganum and Nitraria. Differences in the morphological and chemical characteristics of highland species (Nitraria schoberi, N. sphaerocarpa, N. sibirica and N. tangutorum) and lowland species (Nitraria billardierei and N. retusa) are very subtle, with phylogenetic history appearing to be a more important control on Nitraria pollen than local environmental conditions. Our approach shows a compelling consistency between the chemical and morphological characteristics of the eight studied Nitrariaceae species, and these traits are in agreement with the phylogenetic tree. Taken together, this demonstrates how novel methods for studying fossil pollen can facilitate the evolutionary investigation of living and extinct taxa, and the environments they represent.
Python is at the forefront of scientific computation for seismologists and therefore should be introduced to students interested in becoming seismologists. On its own, Python is open source and well designed with extensive libraries. However, Python code can also be executed, visualized, and communicated to others with "Jupyter Notebooks". Thus, Jupyter Notebooks are ideal for teaching students Python and scientific computation. In this article, we designed an openly available Python library and collection of Jupyter Notebooks based on defined scientific computation learning goals for seismology students. The Notebooks cover topics from an introduction to Python to organizing data, earthquake catalog statistics, linear regression, and making maps. Our Python library and collection of Jupyter Notebooks are meant to be used as course materials for an upper-division data analysis course in an Earth Science Department, and the materials were tested in a Probabilistic Seismic Hazard course. However, seismologists or anyone else who is interested in Python for data analysis and map making can use these materials.