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Ground-motion models (GMMs) are often used to predict the random distribution of Spectral accelerations (SAs) at a site due to a nearby earthquake. In probabilistic seismic hazard and risk assessment, large earthquakes occurring close to a site are considered as critical scenarios. GMMs are expected to predict realistic SAs with low within-model uncertainty (sigma(mu)) for such rare scenarios. However, the datasets used to regress GMMs are usually deficient of data from critical scenarios. The (Kotha et al., A Regionally Adaptable Ground-Motion Model for Shallow Crustal Earthquakes in Europe Bulletin of Earthquake Engineering 18:4091-4125, 2020) GMM developed from the Engineering strong motion (ESM) dataset was found to predict decreasing short-period SAs with increasing M-W >= M-h = 6.2, and with large sigma(mu) at near-source distances <= 30km. In this study, we updated the parametrisation of the GMM based on analyses of ESM and the Near source strong motion (NESS) datasets. With M-h = 5.7, we could rectify the M-W scaling issue, while also reducing sigma(mu). at M-W >= M-h. We then evaluated the GMM against NESS data, and found that the SAs from a few large, thrust-faulting events in California, New Zealand, Japan, and Mexico are significantly higher than GMM median predictions. However, recordings from these events were mostly made on soft-soil geology, and contain anisotropic pulse-like effects. A more thorough non-ergodic treatment of NESS was not possible because most sites sampled unique events in very diverse tectonic environments. We provide an updated set of GMM coefficients,sigma(mu), and heteroscedastic variance models; while also cautioning against its application for M-W <= 4 in low-moderate seismicity regions without evaluating the homogeneity of M-W estimates between pan-European ESM and regional datasets.
Recent advances in organic solar cell performance have been mainly driven forward by combining high-performance p-type donor-acceptor copolymers (e.g.PM6) and non-fullerene small molecule acceptors (e.g.Y6) as bulk-heterojunction layers. A general observation in such devices is that the device performance, e.g., the open-circuit voltage, is strongly dependent on the processing solvent. While the morphology is a typically named key parameter, the energetics of donor-acceptor blends are equally important, but less straightforward to access in the active multicomponent layer. Here, we propose to use spectral onsets during electrochemical cycling in a systematic spectroelectrochemical study of blend films to access the redox behavior and the frontier orbital energy levels of the individual compounds. Our study reveals that the highest occupied molecular orbital offset (Delta E-HOMO) in PM6:Y6 blends is similar to 0.3 eV, which is comparable to the binding energy of Y6 excitons and therefore implies a nearly zero driving force for the dissociation of Y6 excitons. Switching the PM6 orientation in the blend films from face-on to edge-on in bulk has only a minor influence on the positions of the energy levels, but shows significant differences in the open circuit voltage of the device. We explain this phenomenon by the different interfacial molecular orientations, which are known to affect the non-radiative decay rate of the charge-transfer state. We compare our results to ultraviolet photoelectron spectroscopy data, which shows distinct differences in the HOMO offsets in the PM6:Y6 blend compared to neat films. This highlights the necessity to measure the energy levels of the individual compounds in device-relevant blend films.
Instrumental data show that the groundwater and lake levels in Northeast Germany have decreased over the past decades, and this process has accelerated over the past few years. In addition to global warming, the direct influence of humans on the local water balance is suspected to be the cause. Since the instrumental data usually go back only a few decades, little is known about the multidecadal to centennial-scale trend, which also takes long-term climate variation and the long-term influence by humans on the water balance into account. This study aims to quantitatively reconstruct the surface water areas in the Lower Havel Inner Delta and of adjacent Lake Gulpe in Brandenburg. The analysis includes the calculation of surface water areas from historical and modern maps from 1797 to 2020. The major finding is that surface water areas have decreased by approximately 30% since the pre-industrial period, with the decline being continuous. Our data show that the comprehensive measures in Lower Havel hydro-engineering correspond with groundwater lowering that started before recent global warming. Further, large-scale melioration measures with increasing water demands in the upstream wetlands beginning from the 1960s to the 1980s may have amplified the decline in downstream surface water areas.
Economic crises as critical junctures for policy and structural changes towards decarbonization
(2024)
Crises may act as tipping points for decarbonization pathways by triggering structural economic change or offering windows of opportunity for policy change. We investigate both types of effects of the global financial and COVID-19 crises on decarbonization in Spain and Germany through a quantitative Kaya-decomposition analysis of CO2 emissions and through a qualitative review of climate and energy policy changes. We show that the global financial crisis resulted in a critical juncture for Spanish CO2 emissions due to the combined effects of the deep economic recession and crisis-induced structural change, resulting in reductions in carbon and energy intensities and shifts in the economic structure. However, the crisis also resulted in a rollback of renewable energy policy, halting progress in the transition to green electricity. The impacts were less pronounced in Germany, where pre-existing decarbonization and policy trends continued after the crisis. Recovery packages had modest effects, primarily due to their temporary nature and the limited share of climate-related spending. The direct short-term impacts of the COVID-19 crisis on CO2 emissions were more substantial in Spain than in Germany. The policy responses in both countries sought to align short-term economic recovery with the long-term climate change goals of decarbonization, but it is too soon to observe their lasting effects. Our findings show that crises can affect structural change and support decarbonization but suggest that such effects depend on pre-existing trends, the severity of the crisis and political manoeuvring during the crisis.
Insights into the geographical origin and phylogeographical patterns of Paradisaea birds-of-paradise
(2022)
Birds-of-paradise represent a textbook example for geographical speciation and sexual selection. Perhaps the most iconic genus is Paradisaea, which is restricted to New Guinea and a few surrounding islands. Although several species concepts have been applied in the past to disentangle the different entities within this genus, no attempt has been made so far to uncover phylogeographical patterns based on a genetic dataset that includes multiple individuals per species. Here, we applied amplicon sequencing for the mitochondrial fragment Cytb for a total of 69 museum specimens representing all seven Paradisaea species described and inferred both phylogenetic relationships and colonization pathways across the island. Our analyses show that the most recent common ancestor of the diverging lineages within Paradisaea probably originated in the Late Miocene in the eastern part of the Central Range and suggest that tectonic processes played a key role in shaping the diversification and distribution of species. All species were recovered as monophyletic, except for those within the apoda-minor-raggiana clade, which comprises the allopatric and parapatric species P. apoda, P. minor and P. raggiana. The comparatively young divergence times, together with possible instances of mitochondrial introgression and incomplete lineage sorting, suggest recent speciation in this clade.
A dataset of 2184 field measurements reported in the literature was used to evaluate the predictive capability of eight conventional flow resistance equations to predict the mean flow velocity in gravel-bed rivers. The results reveal considerable disagreement with the observed flow velocities for relative submergence less than 4 and for the non-uniformity of the bed material greater than 7.5 for all the equations. However, the predictions made using the Smart and Jaggi (1983), Ferguson (2007), and Rickenmann and Recking (2011) equations were closer to the observed values. Furthermore, bedload sediment transport also reduces the predictive capability of the equations considered in this study except for the Recking et al. (2008) equation, which was developed consid- ering active bedload transport. The performance of flow resistance equations improves when corrected by considering the geometric standard deviation of the bed material. Here we present an empirical approach using the whole dataset and its subsets for accounting for the additional energy losses occurring due to the wake vortices, spill losses, and free surface instabilities occurring due to the protrusions from the bed. The results obtained using the validation dataset shows the importance and usefulness of this approach to account for the additional energy losses, especially for the Strickler (1923) and Keulegan (1938) equations.
Statistical distributions of flood peak discharge often show heavy tail behavior, that is, extreme floods are more likely to occur than would be predicted by commonly used distributions that have exponential asymptotic behavior.
This heavy tail behavior may surprise flood managers and citizens, as human intuition tends to expect light tail behavior, and the heaviness of the tails is very difficult to predict, which may lead to unnecessarily high flood damage.
Despite its high importance, the literature on the heavy tail behavior of flood distributions is rather fragmented.
In this review, we provide a coherent overview of the processes causing heavy flood tails and the implications for science and practice.
Specifically, we propose nine hypotheses on the mechanisms causing heavy tails in flood peak distributions related to processes in the atmosphere, the catchment, and the river system.
We then discuss to which extent the current knowledge supports or contradicts these hypotheses.
We also discuss the statistical conditions for the emergence of heavy tail behavior based on derived distribution theory and relate them to the hypotheses and flood generation mechanisms.
We review the degree to which the heaviness of the tails can be predicted from process knowledge and data. Finally, we recommend further research toward testing the hypotheses and improving the prediction of heavy tails.
Continuous pollen and chironomid records from Lake Emanda (65 degrees 17'N, 135 degrees 45'E) provide new insights into the Late Quaternary environmental history of the Yana Highlands (Yakutia). Larch forest with shrubs (alders, pines, birches) dominated during the deposition of the lowermost sediments suggesting its Early Weichselian [Marine Isotope Stage (MIS) 5] age. Pollen- and chironomid-based climate reconstructions suggest July temperatures (T-July) slightly lower than modern. Gradually increasing amounts of herb pollen and cold stenotherm chironomid head capsules reflect cooler and drier environments, probably during the termination of MIS 5. T-July dropped to 8 degrees C. Mostly treeless vegetation is reconstructed during MIS 3. Tundra and steppe communities dominated during MIS 2. Shrubs became common after similar to 14.5 ka BP but herb-dominated habitats remained until the onset of the Holocene. Larch forests with shrub alder and dwarf birch dominated after the Holocene onset, ca. 11.7 ka BP. Decreasing amounts of shrub pollen during the Lateglacial are assigned to the Older Dryas and Younger Dryas with T-July similar to 7.5 degrees C. T-July increased up to 13 degrees C. Shrub stone pine was present after similar to 7.5 ka BP. The vegetation has been similar to modern since ca. 5.8 ka BP. Chironomid diversity and concentration in the sediments increased towards the present day, indicating the development of richer hydrobiological communities in response to the Holocene thermal maximum.
Effect of temperature on the densification of silicate melts to lower earth's mantle conditions
(2022)
Physical properties of silicate melts play a key role for global planetary dynamics, controlling for example volcanic eruption styles, mantle convection and elemental cycling in the deep Earth. They are significantly modified by structural changes at the atomic scale due to external parameters such as pressure and temperature or due to chemistry. Structural rearrangements such as 4- to 6-fold coordination change of Si with increasing depth may profoundly influence melt properties, but have so far mostly been studied at ambient temperature due to experimental difficulties. In order to investigate the structural properties of silicate melts and their densification mechanisms at conditions relevant to the deep Earth's interior, we studied haplo basaltic glasses and melts (albite-diopside composition) at high pressure and temperature conditions in resistively and laser-heated diamond anvil cells using X-ray absorption near edge structure spectroscopy. Samples were doped with 10 wt% of Ge, which is accessible with this experimental technique and which commonly serves as a structural analogue for the network forming cation Si. We acquired spectra on the Ge K edge up to 48 GPa and 5000 K and derived the average Ge-O coordination number NGe-O, and bond distance RGe-O as functions of pressure. Our results demonstrate a continuous transformation from tetrahedral to octahedral coordination between ca. 5 and 30 GPa at ambient temperature. Above 1600 K the data reveal a reduction of the pressure needed to complete conversion to octahedral coordination by ca. 30 %. The results allow us to determine the influence of temperature on the Si coordination number changes in natural melts in the Earth's interior. We propose that the complete transition to octahedral coordination in basaltic melts is reached at about 40 GPa, corresponding to a depth of ca. 1200 km in the uppermost lower mantle. At the core-mantle boundary (2900 km, 130 GPa, 3000 K) the existence of non-buoyant melts has been proposed to explain observed low seismic wave velocity features. Our results highlight that the melt composition can affect the melt density at such extreme conditions and may strongly influence the structural response.
The H alpha spectral line is a well-studied absorption line revealing properties of the highly structured and dynamic solar chromosphere. Typical features with distinct spectral signatures in H alpha include filaments and prominences, bright active-region plages, superpenumbrae around sunspots, surges, flares, Ellerman bombs, filigree, and mottles and rosettes, among others. This study is based on high-spectral resolution H alpha spectra obtained with the Echelle spectrograph of the Vacuum Tower Telescope (VTT) located at Observatorio del Teide, Tenerife, Spain. The t-distributed stochastic neighbor embedding (t-SNE) is a machine-learning algorithm, which is used for nonlinear dimensionality reduction. In this application, it projects H alpha spectra onto a two-dimensional map, where it becomes possible to classify the spectra according to results of cloud model (CM) inversions. The CM parameters optical depth, Doppler width, line-of-sight velocity, and source function describe properties of the cloud material. Initial results of t-SNE indicate its strong discriminatory power to separate quiet-Sun and plage profiles from those that are suitable for CM inversions. In addition, a detailed study of various t-SNE parameters is conducted, the impact of seeing conditions on the classification is assessed, results for various types of input data are compared, and the identified clusters are linked to chromospheric features. Although t-SNE proves to be efficient in clustering high-dimensional data, human inference is required at each step to interpret the results. This exploratory study provides a framework and ideas on how to tailor a classification scheme toward specific spectral data and science questions.