Global Wave Research Articles

Talking about security in the era of high-tech and green-tech: China’s empathy with Russia and the rare earths trade with the West

ABSTRACT As high technology and green transition gain momentum in modern life, global supply chains of resources like rare earths become vital. China is the dominant actor in this market, Russia already holds a strategic niche albeit as an emerging actor, whereas the West is a “latecomer”, lagging considerably behind. Against the backdrop of ever deepening geopolitical fault lines, the article views the China/Russia – West rare earths trade through the lenses of weaponized interdependence. In particular, it employs this theoretical account for the first time from a non-Western angle and proves that in the recent wave of globalization not all the most central nodes are territorially concentrated in the advanced economies of the West. Moreover, it demonstrates that the West’s domination of relevant innovation cycles is not as absolute and autonomous as propounded by the theory. The conclusions summarize China’s (and Russia’s) panopticon effects on the rare earths trade with the West, and show that should their security concerns be overlooked, they are likely to escalate to chokepoint effects to the detriment of the global economy.

Two Effective Degrees of Freedom Can Represent the Dominant Features of Global Rayleigh Wave Dispersion Maps

AbstractObjectively exploring global variations in crust and upper mantle structure helps constrain fundamental aspects of Earth's plate tectonic and convective processes. Here we adopted a Variational Auto‐Encoder to explore the degrees of freedom of global Rayleigh wave dispersion maps at 4–40 mHz. We found that two latent variables sufficiently represent the global variations, suggesting inherent coupling between crustal and mantle seismic properties. We propose that the two extracted latent variables mostly correspond with crustal thickness and upper mantle thermal structure. The first variable shows low values for continental mountain belts and ocean spreading ridges, contrasted by high values for abyssal plains. The second variable shows low values for most oceanic lithosphere and Phanerozoic continental areas, contrasted by high values for Archean cratons. Latent space correlations indicate that continental lithosphere has more strongly coupled depth features than beneath the oceans, which might be a consequence of its longevity.

Introducing bimodal sea-states in a hybrid model for nearshore wave processes

HySwash has been recently developed as a fast and effective hybrid method to predict nearshore wave processes under unimodal wave conditions. However, global wave climates, and especially those in the tropical regions where coral reefs are hosted, are usually exposed to multiple incoming wave systems, resulting in several energy peaks corresponding to coexisting swells and wind seas. Moreover, although the full distribution of wave runup can have a significant impact on the assessment of vulnerable low-lying tropical regions, predictive models of flooding usually synthesize wave runups to an extreme percentile value, overlooking its full distribution. To enhance the capabilities of HySwash, in the present work, the inclusion of bimodality, as well as the prediction of the complete wave runup distribution is presented. This involves adapting the sampling, selection, and interpolation algorithms together with the hydrodynamic modeling that constitutes the original HySwash methodology. The positive mathematical validation reinforces the applicability of HySwash for a variety of coastal applications. Furthermore, a comparison is conducted between extreme wave runups induced by bimodal sea states and unimodal sea states, providing insights into the impact of multimodality on wave runup extremes.

GWSM4C: A global wave surrogate model for climate simulation based on a convolutional architecture

Accurate and rapid ocean surface wave simulations are essential for navigation safety, marine activity, and climate change research. However, traditional numerical wave models incur substantial computational costs, especially in long-term simulations for climatology research. Deep-learning methods have shown promise in enabling faster simulations with fewer computational resources. However, the cumulative error in current deep-learning wave models limits their use as surrogate component models in climate modeling. In this work, a deep-learning model, named the Global Wave Surrogate Model for Climate simulation (GWSM4C), was developed based on a convolutional architecture, which accounts for the physical processes (wind waves and swells) of waves. Because GWSM4C can automatically generate initial conditions for each simulation moment depending only on historical wind fields, the accumulation of errors from previous simulated wave states can be avoided. The experimental results demonstrated that simulated global significant wave height produced by GWSM4C exhibited a correlation coefficient of 0.94 and a root-mean-square error of 0.21 m compared with the traditional numerical wave model. Furthermore, the generalization test of the GWSM4C indicates that it is feasible to use GWSM4C for long-term wave simulation in climatology-related studies or to integrate it into a coupled climate model as a surrogate wave component model.

Toward a Japanese paradigm of settler-colonial urbanism?

Abstract The city of Sapporo, founded in 1869 by the Japanese government as a colonial headquarters in Hokkaido, developed as part of a global wave of settler-colonial urbanism. Like counterparts in North America and Australia, Sapporo facilitated economic, environmental and political transformations across Hokkaido that led to the displacement of Indigenous Ainu society by a soon overwhelming number of ethnically Japanese settlers. However, several historical factors distinguish Sapporo’s settler-colonial urbanism from its peers, including the long history of relations between the Ainu and Japanese; the heavy role of the Japanese state in Sapporo; and the lack of mass relocations of the Ainu to reservations far from their traditional homes.

Hybrid Modernity in ‘K-Culture’ : The Non-simultaneous Cultural Politics of the Global Korean Wave and Its Landscapes

Hybrid Modernity in ‘K-Culture’ : The Non-simultaneous Cultural Politics of the Global Korean Wave and Its Landscapes

Echo of the Arab Spring in Asia: A Quantitative Analysis

There is no doubt that the Arab Spring triggered a global wave of social and political destabilization which significantly exceeded the scale of the Arab Spring itself and affected all the world-system zones, including Asian countries.2 The analysis suggests that in the Asian region there were two waves of destabilization caused by the Arab Spring. The first started in 2011 and included a series of mostly peaceful protests, which had some features similar to the Middle Eastern revolutions in their organizational forms and communication methods. The second wave, in turn, took place in 2012–2014, when protest movements in Asia began to follow their own path, adding local discontent to their agenda. It was also connected with a sharp increase in terrorist activity in the Middle East, due to the weakening of several authoritarian governments and the emergence of consolidated terrorist organizations. Some Islamist groups in some Muslim-majority Asian countries, in their turn, pledged allegiance to these organizations (first of all, to ISIS/Daesh). Terrorist activity spread from the Arab world to Asia through various channels: the internationalization of jihadist ideas by militarized groups; ISIS propaganda on the Internet; refugees and jihadists returning to the region from the battlefields of the Arab World.

Effect of background wind and dissipation processes on the semidiurnal component of atmospheric solar tides

The equations governing the neutral wind velocities and temperature, which depict the oscillations of atmospheric tides, incorporate various elements of the atmosphere. These factors comprise background wind, temperature profiles, and the atmosphere’s composition, including ozone, oxygen, carbon dioxide, water, etc. The current work describes the method of solution of the atmospheric tidal model and investigates the effects of background wind and dissipation processes on the migrating semidiurnal tides during the March equinox. Thermal heating due to water vapour absorption in the troposphere, ozone in the stratosphere and oxygen absorption in the thermosphere is considered in this model. Furthermore, the model takes into account the various dissipation processes (i.e. ion drag and Hall coefficients, Newtonian cooling, divergence of momentum and heat fluxes due to molecular and eddy diffusion) and background wind. The semidiurnal tidal features obtained from the present model match well with the Global Scale Wave Model (GSWM-98). The bar charts are presented to quantify the effects of different parameters on horizontal winds for altitudes below 100 km and above 100 km, separately. It reveals that the background wind plays a vital role in deciding the semidiurnal tidal amplitudes of zonal and meridional winds. Momentum and heat flux coefficients also have a significant influence on semidiurnal tides. At higher altitudes (>100 km), the ion drag reduces the amplitude of semidiurnal tides considerably.

The multiscale variability of global extreme wind and wave events and their relationships with climate modes

Extreme winds and waves threaten human life, property security, infrastructure, and marine engineering. Persistent extreme wind events (EWiEs) and extreme wave events (EWaEs) can cause more significant impacts and destruction than short-term or instantaneous extreme events. This study defines an EWiE (EWaE) as a prolonged discrete event characterized by abnormally high wind speeds (significant wave heights). The climatological characteristics, spatiotemporal variability, and long-term trends of EWaEs and EWiEs globally are studied utilizing ERA5 reanalysis datasets from 1940 to 2021. The climatological mean characteristics of EWiEs and EWaEs are generally similar: extratropical regions exhibit high intensities, high counts, and short durations, whereas tropical regions are characterized by weak intensities, low counts, and long durations. The count and duration of EWaEs have significantly increased globally, with the greatest rate in the equatorial Pacific Ocean, where the count of events has increased by more than 2.1/decade and the duration by more than 7.2 h/decade. Furthermore, the Southern Annular Mode (SAM) exhibits a significant positive correlation with the count and duration of EWaEs in the eastern Pacific and Southern Oceans. In the Southern Hemisphere at 0–30°S, the Atlantic Multidecadal Oscillation (AMO) shows a significant positive correlation with the count of EWaEs and EWiEs.

Emergent effects of synaptic connectivity on the dynamics of global and local slow waves in a large-scale thalamocortical network model of the human brain.

Slow-wave sleep (SWS), characterized by slow oscillations (SO, <1Hz) of alternating active and silent states in the thalamocortical network, is a primary brain state during Non-Rapid Eye Movement (NREM) sleep. In the last two decades, the traditional view of SWS as a global and uniform whole-brain state has been challenged by a growing body of evidence indicating that SO can be local and can coexist with wake-like activity. However, the understanding of how global and local SO emerges from micro-scale neuron dynamics and network connectivity remains unclear. We developed a multi-scale, biophysically realistic human whole-brain thalamocortical network model capable of transitioning between the awake state and slow-wave sleep, and we investigated the role of connectivity in the spatio-temporal dynamics of sleep SO. We found that the overall strength and a relative balance between long and short-range synaptic connections determined the network state. Importantly, for a range of synaptic strengths, the model demonstrated complex mixed SO states, where periods of synchronized global slow-wave activity were intermittent with the periods of asynchronous local slow-waves. Increase of the overall synaptic strength led to synchronized global SO, while decrease of synaptic connectivity produced only local slow-waves that would not propagate beyond local area. These results were compared to human data to validate probable models of biophysically realistic SO. The model producing mixed states provided the best match to the spatial coherence profile and the functional connectivity estimated from human subjects. These findings shed light on how the spatio-temporal properties of SO emerge from local and global cortical connectivity and provide a framework for further exploring the mechanisms and functions of SWS in health and disease.

The hidden cost of corporate tax cuts: Evidence from worker health in China

Despite extensive research on the impact of corporate tax cuts on firm-level outcomes, their effects on worker health have yet to be examined. This study aims to address this research gap by utilizing individual-level panel data from the China Family Panel Studies between 2010 and 2018, and by exploiting exogenous shock in the corporate effective tax burden stemming from accelerated depreciation. Our results yield three key findings: first, that corporate tax cuts significantly reduce worker health; second, that this effect may be driven by increased working hours and poor health behaviors; third, that corporate tax cuts exacerbate health inequalities based on gender, education level, executive positions, and employed company. These findings shed light on the wider implications of tax incentives for corporate investment and contribute to stimulating interest in the welfare of workers in a global wave of tax cuts.

International comparison of China's digitalization level and its enlightenment.

The global digital wave has flourished in recent years, and the digital technology revolution has emerged. Digitalization plays an undeniable role in promoting modern economic and social development in multiple aspects such as economy, society, innovation, public services and sustainable development, China's digitalization application is also developing rapidly. In order to better measure the current situation of China's digitalization development level, this paper constructs a comprehensive evaluation index system of digitalization development from four dimensions of talents in the digital field, digital infrastructure construction, digitalization innovation ability and international competitiveness, and tests the index system. The entropy method is used to measure the level of digitalization development between China and the United States, the United Kingdom, France and other major developed countries in the world, and the coefficient of variation method, kernel density estimation and Dagum Gini coefficient method are used to analyze the temporal and spatial characteristics and regional differences of digitalization development level of seven countries. This paper makes a comparative analysis between China and major developed countries from the historical perspective of the evolution of the techno-economic paradigm. With a view to summarizing and exploring from it and drawing on the advanced experiences accumulated by the developed countries over a long period of time, so as to provide China with useful insights and bases for further enhancing its digitalization development level.

Coupled connectivity in the global complex network: the case of United Kingdom (1880–1925)

The main objective of this research is to analyse the connectivity of cities in a coupled network composed of planar (railways) and non-planar (maritime) topologies. It examines the state of the network during the 1880–1925 period, namely in the context of the first globalization wave (1880–1914), when trade and urban development were closely tied to progress in communications systems and steam propulsion especially. Edges represent intercity physical infrastructure on land, and inter-port ship voyages at sea. We tested several hypotheses in terms of inter-network specialisation and urban hierarchies with an application in the United Kingdom. The main results reveal that the networks are highly interdependent, whereas combined centrality is closely associated with city size and urban growth. We discuss the key results in light of network science, spatial science, maritime history, and transport research.

Educational Innovations in the Fundamentals of Marxism in the Context of the New Era

In the historical context of the new era, socialist education with Chinese characteristics faces many opportunities and challenges. With the further deepening of globalisation and informatisation, traditional economic, cultural and technological boundaries are becoming blurred, while bringing about social challenges such as intensified global competition and the polarisation of the rich and the poor. As the world's second largest economy, China is striving to find a development path suitable for itself in the wave of globalisation. In the age of information technology, cutting-edge technologies such as artificial intelligence and big data are reshaping the economy and society, while the Internet and mobile communication technologies have made the flow of information more rapid, which not only facilitates the dissemination of knowledge, but also has a significant impact on the mode of education and the way of work. By promoting the "Internet Plus" action plan and the development of the digital economy, the Chinese government aims to improve governance capacity and efficiency, and draw up a blueprint for a digital China and a smart society. In the new era of ideological pluralism, China faces the challenges and opportunities of both socialist core values and traditional cultural heritage. China is trying to find a balance between inheritance and innovation, and to strengthen citizens' moral construction and cultural confidence. Such an endeavour not only enhances the country's cultural soft power, but is also a positive response to the changes of the times. At the same time, socialist education with Chinese characteristics is also placing greater emphasis on people's livelihoods and fairness and justice in the new era, and the public's pursuit of a high quality of life has become more intense. The rising demand for education, health, housing and the environment requires the government to pay more attention to livelihood improvement and social equity while promoting economic development. The concept of environmental protection and green development has become a social consensus, pointing to the goal of sustainable development. China's economic system is transforming into a more globally competitive modernisation and is seeking a broader space for development under the new pattern of globalisation. The changes brought about by this new era to Chinese education are not only challenges, but also opportunities. China not only needs to play an important role in the international arena, but also needs to deepen its internal reforms in order to raise the level of national education and contribute to the grand blueprint of high-quality economic development and national rejuvenation. Marxist education, as a guiding ideology, will continue to play an important role in this process, aiming to cultivate the talents needed by the times, promote the internalisation and practice of socialist core values, and ultimately realise socialist modernisation and the overall revitalization of the country.

Ocean waves in the southwestern Atlantic Ocean: An evaluation of global wave models

AbstractIn situ wave observations are essential for implementing coastal management strategies, designing coastal and offshore structures and understanding many processes related to sedimentology and marine biology. Despite their importance, these observations are rather scarce in the coastal areas of southeastern South America. Moreover, the existing observations are discontinuous, with several gaps and no simultaneity. Today, global wave models have improved their performance by providing reliable wave parameters with high resolution and coverage even at near‐shore areas. In this work, wave parameters from five global models were compared with significant wave heights (HS), peak periods (T) and propagation direction at nine sites located at the Southwestern South Atlantic Ocean. The global products used were WAVERYS (Global Reanalysis Wav 001 032), IOWAGA (WAVEWATCH III Hindcast – WW3 – Global grid – CFSR), ERA5 (ECMWF reanalysis), NOAA WW3 – 30‐year Hindcast Phase 2 and NCEP/EMC Operational global wave model GFS – Wave. Mean arithmetic error (Bias), root mean square deviation, scatter index and the Pearson linear correlation coefficient (r) were assessed at each location where wave observations were available. The best agreements for HS were obtained at the deepest sites located farther from the coast. Lower statistical metrics were achieved at coastal sites where the bathymetry is roughly represented by the global models. The calculated correlation coefficients were found to be lower for T than for HS. Overall, T was slightly underestimated by global models. Wave propagation directions were excellently represented by global models at offshore sites. The WAVERYS model is the global product that best represents the wave parameters in the study area, probably due to its higher spatial resolution (0.2°) and more realistic atmospheric forcing (ERA5). In addition, it satisfactorily represents the temporal variability of HS in open water as well as swell characteristics at the outer the Río de la Plata.

Heme oxygenase 1-mediated ferroptosis in Kupffer cells initiates liver injury during heat stroke

With the escalating prevalence of global heat waves, heat stroke has become a prominent health concern, leading to substantial liver damage. Unlike other forms of liver injury, heat stroke-induced damage is characterized by heat cytotoxicity and heightened inflammation, directly contributing to elevated mortality rates. While clinical assessments have identified elevated bilirubin levels as indicative of Kupffer cell dysfunction, their specific correlation with heat stroke liver injury remains unclear. Our hypothesis proposes the involvement of Kupffer cell ferroptosis during heat stroke, initiating IL-1β-mediated inflammation. Using single-cell RNA sequencing of murine macrophages, a distinct and highly susceptible Kupffer cell subtype, Clec4F+/CD206+, emerged, with heme oxygenase 1 (HMOX-1) playing a pivotal role. Mechanistically, heat-induced HMOX-1, regulated by early growth response factor 1, mediated ferroptosis in Kupffer cells, specifically in the Clec4F+/CD206+ subtype (KC2), activating phosphatidylinositol 4-kinase beta and promoting PI4P production. This cascade triggered NLRP3 inflammasome activation and maturation of IL-1β. These findings underscore the critical role of targeted therapy against HMOX-1 in ferroptosis within Kupffer cells, particularly in Clec4F+/CD206+ KCs. Such an approach has the potential to mitigate inflammation and alleviate acute liver injury in the context of heat stroke, offering a promising avenue for future therapeutic interventions.

Estimating stratospheric polar vortex strength using ambient ocean‐generated infrasound and stochastics‐based machine learning

AbstractThere are sparse opportunities for direct measurement of upper stratospheric winds, yet improving their representation in subseasonal‐to‐seasonal prediction models can have significant benefits. There is solid evidence from previous research that global atmospheric infrasound waves are sensitive to stratospheric dynamics. However, there is a lack of results providing a direct mapping between infrasound recordings and polar‐cap upper stratospheric winds. The global International Monitoring System (IMS), which monitors compliance with the Comprehensive Nuclear‐Test‐Ban Treaty, includes ground‐based stations that can be used to characterize the infrasound soundscape continuously. In this study, multi‐station IMS infrasound data were utilized along with a machine‐learning supported stochastic model, Delay‐SDE‐net, to demonstrate how a near‐real‐time estimate of the polar‐cap averaged zonal wind at 1‐hPa pressure level can be found from infrasound data. The infrasound was filtered to a temporal low‐frequency regime dominated by microbaroms, which are ambient‐noise infrasonic waves continuously radiated into the atmosphere from nonlinear interaction between counter‐propagating ocean surface waves. Delay‐SDE‐net was trained on 5 years (2014–2018) of infrasound data from three stations and the ERA5 reanalysis 1‐hPa polar‐cap averaged zonal wind. Using infrasound in 2019–2020 for validation, we demonstrate a prediction of the polar‐cap averaged zonal wind, with an error standard deviation of around 12 m·s compared with ERA5. These findings highlight the potential of using infrasound data for near‐real‐time measurements of upper stratospheric dynamics. A long‐term goal is to improve high‐top atmospheric model accuracy, which can have significant implications for weather and climate prediction.

Cross-Shore Modeling Features: Calibration and Impacts of Wave Climate Uncertainties

Numerical models can be powerful tools for evaluating the best scenarios for the construction of artificial nourishments to mitigate coastal erosion. Until recent decades, when looking at medium- to long-term simulations, cross-shore and alongshore processes have been studied separately. Accounting for both processes in a shoreline evolution numerical model would improve the understanding and predictive capacity of future changes in coastline evolution. The AX-COAST project aims to develop new capacities in modeling cross-shore sediment transport processes by adding the CS-Model, a cross-shore numerical model, into the existing LTC (Long-Term Configuration) model. The LTC model is a shoreline evolution numerical model which is a module of the cost–benefit assessment tool COAST. This work presents the first steps of the CS-Model implementation, which involve evaluating its performance by calibrating the model with extensive measured datasets of wave climate, beach profiles, tide levels, etc., from coastal areas in IJmuiden and Sand Motor in the Netherlands. The results show good agreement between modeled and observed values. Additionally, wave climate datasets derived from global and regional wave models were considered to evaluate modeling performance at IJmuiden. Using derived timeseries from the wave models did not significantly lead to different results compared to using measured data. The obtained mean absolute and relative errors for each profile were low for both types of datasets. Calibration processes with consistent data are important in modeling simulations to accurately represent the study area and ensure the credibility of future simulations.

Simulating influences of land use/land cover composition and configuration on urban heat island using machine learning

Urban heat island (UHI) has become a worldwide concern under global warming and urbanization waves, which pose significant threats to human health and urban sustainability. Despite Land Use/Land Cover (LULC) being regarded as a crucial factor influencing UHI, few studies simulated the nonlinear influences from LULC compositions and configurations, especially considering the difference between monocentric and polycentric cities. Therefore, we measured the patterns of LULC and UHI from 2006 to 2022 using cases of a monocentric city (Chengdu) and a polycentric city (Chongqing). Further, we simulated future and land surface temperature (LST) using Machine Learning (ML) models, and further calculated the simulated UHI in 2030 by urban-rural LST differences. The results showed that Chengdu had prominent UHI intensity in cores and the surrounding satellite towns. Chongqing's main center and subcenters had high UHI intensity under clustered patterns. ML results indicated that built-up percentage was the most crucial factor driving LST. Configuration factors dominated in impacting Chengdu's LST, while composition factors were more critical in Chongqing. Moreover, future UHI is estimated to decrease in Chongqing's core, compared with the remaining high UHI in Chengdu's core. These results might provide insights for understanding and mitigating future UHI effects.

An investigation of sea state conditions at the time of ship accidents in Indonesia

ABSTRACT In this study, we investigate the sea state conditions during the two cases of ship accidents that have recently occurred in the Indonesian ocean. The first accident case occurred in the middle part of Indonesia at the end of May 2022 resulted in fatalities. Similarly, another incident was in the eastern part of Indonesia in the middle of July 2022, killing 12 people. For both cases, we observed the maximum wave height, significant wave height, and wind speed during the respective accident periods. The observations were carried out using the global ocean wave model, WAVEWATCH III, in conjunction with Altimeters and ASCAT scatterometers. Specifically, the study employed data from Cryosat-2, Jason-3, Saral, Sentinel-3B, Sentinel-6A, Metop-B and Metop-C. The resultant satellite observations are consistent with the model, meaning that the wave heights at the time of the accident were very high. The first case clearly shows that strong wind and high waves most likely triggered the accident. As a result, all stakeholders who run their ocean transport business must consider the warning from the related agency, which is, in this case meteorological, climatological, and geophysical agency. Such proactive measures have the potential to mitigate marine accidents stemming from adverse weather conditions.