Transport Modeling System Research Articles

Modeling and dynamic analysis of integral vertical transport system for deep-sea mining in three-dimensional space

This paper proposed a new three-dimensional numerical model of the integral vertical transport system (VTS) in deep-sea mining using the vector form intrinsic finite element (VFIFE) method. The method shows great advantages in solving complex dynamic behavior problems of VTS with large differences in mechanical properties and strong geometric nonlinearity. The governing equations are established according to Newton's second law and solved in the time domain by the central difference method. The simulation program for predicting the nonlinear dynamic behavior of VTS is developed with MATLAB and verified with the results of relevant literature. Then, a parameter sensitivity analysis is conducted to investigate the influences of the amplitude and period of the top vessel motion, current velocity, internal flow velocity and buffer mass on the VTS dynamic characteristics. The results show that the heave motions of the vessel are the most adverse motion state to the rigid pipe stress. The influence of the internal flow velocity on the system tension is significantly greater than the bending moment. The rigid pipe, which exhibits a higher sensitivity to each parameter than the flexible pipe, is the weakest area that needs more attention in the design.

Industrial and oil ports: case studies and theoretical approaches

Industrial and oil ports have been mainly developed, after the Second World War, with the birth of large industrial systems and they established during the second half of 20th century. Large ports are built close to the industrial areas. Heavy and oil industrial sectors need huge loading capacity, direct connections without constraints on shapes, lengths and unit of loads. The iron and steel industry, the petrochemical, the power plants, etc., determine the birth of the so-called second-generation ports, as defined by UNCTAD. The technical characteristics are the following: large yards close to the quays, oil terminals with sophisticated security systems, starting points for oil pipelines and power lines. The paradigm of the second-generation ports is: firstly, the industrial plant was settled and, then, the port was built for serving the industrial plant. The ships that arrive at the industrial ports are specialized. The oil tankers are born, with the subsequent variations of hull and technology, they evolve up to the LNG ships. The economic system is therefore defined in a simple way: eliminating the distances between the heavy industry plants and the loading/unloading points that allow international connections. The economic model has not been enough studied in its basic components given by the flows of goods from the port to the industries and vice versa.The paper is articulated into two main parts. The first one presents a critical analysis of some representative case studies of industrial and oil ports for each continental area. The second one presents the proposed theoretical approaches, based on Transport System Models (TSMs) introducing the multi-modal approach considering that in the examined ports there is a pipeline network other than a road network. The multi-modal TSM explains the relationship of industrial and oil ports with trade partners who have built their cargo transformation facilities in the closer industrial area. The approach can be extended to the sea and land networks used for the oil transport. The work may be considered a step able to open several directions to study the characteristics of oil and petrochemical ports and their connection with the industrial areas by means of TSMs. The use of TSMs allows transport planners to integrate industrial ports into land development plans and researchers to investigate the structure of TSMs applied to freight transport during which physical and economic (value modification) changes occur in goods.

Учет сложности в задачах транспортного спроса

The article describes the theoretical basis for taking into account the complexity in solving problems of transport demand, the analysis of the concept of “self-organized criticality” is carried out. The problems of describing complex conduct in transport systems are solved, the prerequisites or causes of complex behavior are indicated, the traditional definitions of a “complex transport system” are formalized. Examples of some models demonstrating complex behavior in transport systems are given. Objective: formulation of research directions in the theory of transport systems, which should be developed with the help of conceptual and mathematical devices of individual sciences, such as complexity theory, nonlinear dynamics, to solve problems of transport demand, accompanied by flows of various events and elements in transport macrosystems, to take into account the complexity of problems in the theory of transport systems in modeling the dynamics of transport demand. Approaches used: development of mathematical models of nonlinear transport systems demonstrating complex behavior, including models with power-law distribution of system characteristics within the framework of self-organized criticality, as well as models demonstrating bifurcations. Methods and (or) methodological apparatus of research: methods of the theory of self-organized criticality and synergetics, allowing to take into account the properties of a complex system. The scientific novelty lies in the use of methods and approaches of the theory of self-organized criticality and complexity theory for a wide class of models of transport systems used in problems of transport demand and based on traffic flow models. Directions for further research, recommendations: it is required to analyze real statistics of the behavior of transport systems that correspond to various states of the transport system, including complex behavior, as well as the formulation and solution of problems of the theory of transport macrosystems.

Port-city interactions: models and case studies

Historically ports are directly connected with the cities. Even more: ancient cities were born where ports were. Firstly, the port is born and, then, the city around, which grows in symbiosis with the port. This element remains an indissoluble union over the centuries. Cities are fed by ports and urban productions are sent to other cities via ports.The territorial model, defined as “first-generation” port by UNCTAD, remains constant through the millennia. It has been variously treated in the scientific literature with different approaches using aggregate models. The territorial model has not been studied in depth in its founding variables, which are those connected to the flow of goods and passengers.The paper is articulated into some parts. The first one presents the theoretical approaches proposed to explain interactions between port and city using as explicative variables, the flows of passengers and goods. The second one presents a comparative analysis of some representative case studies of port-city interactions, in order to aggregate the observed processes in some macro-classes.The work may be considered a step able to open several directions to study the port-city interaction process and the connection with transport by means of Transport System Models (TSMs). The use of TSMs could allow to extend the consolidated quantitative methods developed in the field of passengers’ mobility and freight distribution in urban transport networks to the larger field of port-city interactions.The proposed modelling approaches can be of great interest to traffic and transport planners because they allow to integrate the port economic system inside the traffic or transport plans of the city. This integration is even more necessary inside plans with sustainability objectives.

Optimization of Market Behavior of a Transportation Company

The relevance of optimizing the interaction of participants in manufacture and transport systems is due to the growth of the scale of social production, the development of transnational companies and international trade at the present stage of market transformations, economic integration and development of transport corridors. In this paper we will optimize the market behavior of a transport enterprise in the manufacture and transportation chain. Objectives: To determine the best option for coordinating the actions of participants in the manufacture and transport chain and to optimize the mechanism for granting discounts on the tariff of the transport company. Research methods: economic and mathematical modeling, construction and mathematical analysis of models of manufacture and transport systems, optimization computer calculations, economic interpretation of the results. In this paper it will also be analyzed how full or partial integration of the participants of manufacture and transportation chains, such as coordination of actions, unification of interests can ensure not only a significant increase in the profits of each participant, but also an increase in production volumes and delivery of products to consumers with a corresponding decrease in prices. The paper also portrays how every participant in the manufacture and transportation chain can paradoxically benefit from the established mechanism that would provide discounts on the tariff of a transport company depending on the volume of cargo flow followed by principle the more cargo, the greater the discount. It will be shown how manufacturer benefits by reducing transportation costs, while the transport company earns less per container, but the outstripping growth in the number of these containers provides it with a higher profit. Consequently, the conditions for the feasibility of applying such a mechanism of tariff discounts will also be established.

Этапы создания транспортных моделей и их построение в PTV Visum

The article analyzes various aspects of the use of computer modeling for the development of transport infrastructure. The levels of modeling, the main stages of preparation and creation of transport models of systems are considered. The overview of specialized software for modeling transport processes is given. The advantages of the PTV Visum software product, which is widely used in transport planning and analysis to build accurate and detailed models of transport systems, are specified.

Simulation of rates of traffic accidents involving unmanned ground vehicles within a transportation system for the ‘smart city’

This article presents an approach to simulation of the rates of road traffic accidents involving unmanned ground vehicles within a multi-agent intelligent transportation system for the ‘smart city.’ A new simulation model of an intelligent transport system has been developed which makes it possible to significantly reduce the number of potential road traffic accidents (TAs) and implements the concept of socially-centered management of the urban economy. The software implementation of such a large-scale agent-based model was carried out using the FLAME GPU framework, which allows us to effectively parallelize the agents’ behaviour logic and consider their individual decision-making systems when modelling the spacial dynamics of an ensemble of unmanned ground vehicles (UGVs) interacting with other road users: the usual manned ground vehicles (MGVs), unexpected obstacles (e.g., pedestrians, etc.). Various scenarios of such agents’ behaviour in an intelligent transportation system are studied, including the occurrence of an accident under certain conditions (e.g., under the high speed and traffic intensity of UGVs, etc.) and various configurations of the digital road network (DRN). We determine the parameter values that provide for the individual decision-making system of UGVs remaining stable with respect to the characteristics of the external environment (including in extreme situations), ensuring the safety of other road users on the scale of the ‘smart city.’

Improvement of local ozone phytotoxicity modelling for autochthonous grape cultivars

The grapevine is a key crop for Mediterranean environments and is both sensitive to climate warming and air pollutants, of which ozone is the most damaging to crop yield and quality. Ambient ozone effects on the grapevine have been noticed since the late fifties but risk assessments are still impaired by the lack of information concerning differences in cultivar sensitivity, and adaptation capacity to environmental factors including drought conditions. This study develops a specific parametrization for autochthonous grape cultivars within a leaf-level stomatal flux model, the DO3SE model, coupled with a meteorological and atmospheric chemical transport modelling system, the WRF-CHIMERE, by using a renowned wine producing area, the Douro wine region of Portugal, as case study. The DO3SE model parametrization introduced in this study included phenology, photosynthetic active radiation, air temperature, air vapour pressure deficit, and leaf water potential as a proxy of soil water content. The modelling experiments, which included simulations with the current default Convention on Long-Range Transboundary Air Pollution DO3SE parametrization and with the proposed parametrization, covered a reference grapevine growing season (from April to September 2017), during which a measuring campaign was carried out. Simulation results show that the proposed parametrization succeeded to replicate the observed grapevine leaf-level stomatal flux gradient in the region. Both field and modified DO3SE model values indicate that considerable areas in the Douro wine region of Portugal can exceed critical phytotoxic ozone dose (POD) values, although with a lower and different spatial extent when compared to the default DO3SE parametrization for the grapevine. However, under irrigated conditions, the POD values increase, and the values are close to those obtained with the default parametrization. Overall, the research results indicate that air quality management, in particular the reduction of ozone levels in the ambient air, must also be considered to define sustainable grape and wine production strategies in the context of climate and wine production management change.

Analysis of the National Air Pollutant Emissions Inventory (CAPSS 2018) Data and Assessment of Emissions Based on Air Quality Modeling in the Republic of Korea

According to the 2018 National Air Pollutant Emissions Inventory (NEI), air pollutant emissions in the Republic of Korea comprised 808,801 tons of CO, 1,153,265 tons of NOX, 300,979 tons of SOX, 617,481 tons of TSP, 232,993 tons of PM10, 98,388 tons of PM2.5, 15,562 tons of black carbon (BC), 1,035,636 tons of VOCs, and 315,975 tons of NH3. As for national emission contributions to primary PM2.5 and PM precursors (NOX, SOX, VOCs, and NH3), major source categories were the road sector for NOX, the industry sector for SOX and PM2.5, and the everyday activities and others sector for VOCs and NH3. In the case of emissions by region, the largest amount of NOX was emitted from the Seoul Metropolitan Areas (SMA; Seoul, Incheon, and Gyeonggi-do, hereafter SMA) and the largest amounts of SOX, PM2.5, VOCs, and NH3 were from the Yeongnam region. A 3D chemical transport modeling system was used to examine the uncertainty of the national air pollutant emissions based on the National Emission and Air Quality Assessment System (NEAS). Air quality was simulated using CAPSS 2018, and the simulation data were compared with observed concentrations to examine the uncertainties of the current emissions. These data show that emissions from five si (cities) (Pohang, Yeosu, Gwangyang, Dangjin, and Ulsan) need to be improved. Most of all, it is necessary to examine the emissions from places of business that use anthracite, which is the major PM2.5 emission source, as fuel in these areas.

Analysis of Intelligent Transportation System Application Based on Internet of Things and Big Data Technology under the Background of Information Society

With the growth of national economic strength, urban modernization has become an indispensable part. Among them, urban road traffic congestion has become the main problem affecting work and traffic. Traffic pressure promotes the massive use of Internet of Things and other technologies in the transportation system. The integration of computer, Internet of Things and transportation system forms a new intelligent transportation concept. With the advent of intelligent information society, the application of intelligent transportation is imminent. In view of the shortcomings of urban intelligent transportation, this paper uses Internet of Things technology and big data technology to study it. Firstly, it analyzes the function and value of IoT intelligent transportation, analyzes the system components from the construction principle, and makes full use of intelligent technology to improve the transportation system. Secondly, the optimal path algorithm is proposed in the IoT urban intelligent transportation system model. The advantages and disadvantages of genetic algorithm and heuristic algorithm are analyzed, and ant colony algorithm is used for further optimization. In order to verify the feasibility of the intelligent transportation system, technologies such as big data edge computing are also used to comprehensively evaluate and study the use of the system. Finally, we analyze the results of the practical application of the intelligent transportation system under the Internet of Things technology. The research results show that the urban intelligent transportation system, supported by the Internet of Things technology, can realize the dynamic planning of the optimal route, help the people to improve their driving experience in the high safety and intellectualization, and greatly avoid a series of problems caused by congestion.

Evaluation and bias correction of probabilistic volcanic ash forecasts

Abstract. Satellite retrievals of column mass loading of volcanic ash are incorporated into the HYSPLIT transport and dispersion modeling system for source determination, bias correction, and forecast verification of probabilistic ash forecasts of a short eruption of Bezymianny in Kamchatka. The probabilistic forecasts are generated with a dispersion model ensemble created by driving HYSPLIT with 31 members of the NOAA global ensemble forecast system (GEFS). An inversion algorithm is used for source determination. A bias correction procedure called cumulative distribution function (CDF) matching is used to very effectively reduce bias. Evaluation is performed with rank histograms, reliability diagrams, fractions skill score, and precision recall curves. Particular attention is paid to forecasting the end of life of the ash cloud when only small areas are still detectable in satellite imagery. We find indications that the simulated dispersion of the ash cloud does not represent the observed dispersion well, resulting in difficulty simulating the observed evolution of the ash cloud area. This can be ameliorated with the bias correction procedure. Individual model runs struggle to capture the exact placement and shape of the small areas of ash left near the end of the clouds lifetime. The ensemble tends to be overconfident but does capture the range of possibilities of ash cloud placement. Probabilistic forecasts such as ensemble-relative frequency of exceedance and agreement in percentile levels are suited to strategies in which areas with certain concentrations or column mass loadings of ash need to be avoided with a chosen amount of confidence.

A Numerical Investigation of Hurricane Florence‐Induced Compound Flooding in the Cape Fear Estuary Using a Dynamically Coupled Hydrological‐Ocean Model

AbstractHurricane‐induced compound flooding is a combined result of multiple processes, including overland runoff, precipitation, and storm surge. This study presents a dynamical coupling method applied at the boundary of a processes‐based hydrological model (the hydrological modeling extension package of the Weather Research and Forecasting model) and the two‐dimensional Regional Ocean Modeling System on the platform of the Coupled‐Ocean‐Atmosphere‐Wave‐Sediment Transport Modeling System. The coupled model was adapted to the Cape Fear River Basin and adjacent coastal ocean in North Carolina, United States, which suffered severe losses due to the compound flood induced by Hurricane Florence in 2018. The model's robustness was evaluated via comparison against observed water levels in the watershed, estuary, and along the coast. With a series of sensitivity experiments, the contributions from different processes to the water level variations in the estuary were untangled and quantified. Based on the temporal evolution of wind, water flux, water level, and water‐level gradient, compound flooding in the estuary was categorized into four stages: (I) swelling, (II) local‐wind‐dominated, (III) transition, and (IV) overland‐runoff‐dominated. A nonlinear effect was identified between overland runoff and water level in the estuary, which indicated the estuary could serve as a buffer for surges from the ocean side by reducing the maximum surge height. Water budget analysis indicated that water in the estuary was flushed 10 times by overland runoff within 23 days after Florence's landfall.

Effects of swell waves on the dynamics of the estuarine turbidity maximum in an idealized convergent partially mixed estuary

The dynamics of estuarine sediments plays a key role in the morphological evolution, water quality, and ecosystem health of estuaries. Estuarine turbidity maxima (ETMs) are ubiquitous in estuaries worldwide and have drawn enormous attention from researchers. Here, we use a coupled ocean–atmosphere–wave–sediment transport modeling system to examine the effects of swell waves on the location, extent, and suspended sediment concentration (SSC) of ETMs in a convergent partially mixed estuary. Our results reveal that swell waves influence the residual circulation, mixing, and bottom stress in the estuary. The wave–current interaction increases the bottom stress in the estuary but reduces mixing in the lower to middle reaches of the estuary, owing to the enhanced landward salt transport, and the increased stratification. The reduced mixing enhances the estuarine circulation in the middle reach of the estuary. These changes cause a landward shift of the primary ETM and an increase in the SSC in the lower estuary. Moreover, the Coriolis force changes the ETM distribution and influences the wave effects. Overall, the findings of this study further elucidate ETM dynamics in an estuary. • Swell wave advects more saline water in the estuary and increases stratification. • Wave-current interaction increases the bottom stress in the lower estuary. • Swell wave causes a landward shift of the primary estuarine turbidity maxima (ETM).

Variational multiscale reinforcement learning for discovering reduced order closure models of nonlinear spatiotemporal transport systems

A central challenge in the computational modeling and simulation of a multitude of science applications is to achieve robust and accurate closures for their coarse-grained representations due to underlying highly nonlinear multiscale interactions. These closure models are common in many nonlinear spatiotemporal systems to account for losses due to reduced order representations, including many transport phenomena in fluids. Previous data-driven closure modeling efforts have mostly focused on supervised learning approaches using high fidelity simulation data. On the other hand, reinforcement learning (RL) is a powerful yet relatively uncharted method in spatiotemporally extended systems. In this study, we put forth a modular dynamic closure modeling and discovery framework to stabilize the Galerkin projection based reduced order models that may arise in many nonlinear spatiotemporal dynamical systems with quadratic nonlinearity. However, a key element in creating a robust RL agent is to introduce a feasible reward function, which can be constituted of any difference metrics between the RL model and high fidelity simulation data. First, we introduce a multi-modal RL to discover mode-dependant closure policies that utilize the high fidelity data in rewarding our RL agent. We then formulate a variational multiscale RL (VMRL) approach to discover closure models without requiring access to the high fidelity data in designing the reward function. Specifically, our chief innovation is to leverage variational multiscale formalism to quantify the difference between modal interactions in Galerkin systems. Our results in simulating the viscous Burgers equation indicate that the proposed VMRL method leads to robust and accurate closure parameterizations, and it may potentially be used to discover scale-aware closure models for complex dynamical systems.

Influence of sea surface wave-dependent roughness on summer precipitation over the Southeastern United States

To study the influence of ocean surface roughness on summer precipitation over the southeastern United States, we perform singular value decomposition (SVD) analysis between the mean summer precipitations and the significant wave height from 1979 to 2017 over the Gulf of Mexico (GOM). The first dominant mode shows that the swell energy in the northern GOM is larger than that in the southern GOM, especially over the region adjacent to the southeastern United States (SE-US). Meanwhile, the precipitation in the SE-US is much heavier than the other regions. Composite analysis shows that when the first pattern takes place, the wind speed is small near the region of the SE-US, swell dominates. There is a cyclonic wind anomaly at 850 hPa over the SE-US, which results in strong upward motion, therefore heavy rainfall in this region. To further study the effect of the swell on the precipitation in the SE-US, we also design two numerical experiments using the Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) Modelling System. In the control (CTL) experiment, the popular Charnock aerodynamical roughness length parameterization is adopted. In the other experiment, a wave-dependent roughness scheme is used. The precipitation in the SE-US is better simulated in the wave-dependent roughness experiment than in the CTL experiment. In summer, the 10-m wind speed is weak in the northeastern Gulf of Mexico, and that means the swell is dominant in this region. The wave-dependent surface roughness strengthens the wind, which means that the momentum is transferred from the wave to the atmosphere under swell dominant conditions. The increase of the shear term and the cyclonic wind anomaly in the lower layers of the atmosphere leads to a stronger upward motion which drives heavier rainfall in the SE-US.

The Impact of Fuel Cell Electric Freight Vehicles on Fuel Consumption and CO2 Emissions: The Case of Italy

The Italian Recovery and Resilience Plan promotes, among its many actions, the use of hydrogen by the deployment of refuelling stations for heavy-duty vehicles, predicting a 5–7% penetration rate of fuel cell electric vehicles (FCEVs) for long-distance freight transport. In this work, the impact of this action on the reduction of greenhouse gas emissions and consumption was estimated, assuming the plan’s objectives are met. To achieve this aim, a national simulation model of the road freight transport system was implemented, consisting of a graph of the national road network and an inter-provincial origin-destination matrix; the graph was based on data available from OpenStreetMap, while the interprovincial matrix was estimated from the interregional matrix with the use of two linear regression models, one for emitted goods and one for attracted goods. The simulation of the system made it possible to estimate the impact of this action on CO2 emissions and fuel consumption under three different scenarios. From 2025 to 2040, a reduction in CO2 emissions ranging from around 9 to around 16.5 million tonnes was estimated, and a reduction in consumption ranging from around 3 billion to around 5.6 billion litres of diesel. These results show how this action can be seen as one of the bricks contributing to the fight against global warming.

Activity-based integrated modelling for assessing COVID-19 impacts on transport operations and emissions

ABSTRACT This study combines an integrated transport, land-use, and energy (iTLE) modeling system with traffic microsimulation model and emission simulator for a holistic analysis of COVID-19 pandemic related changes in traffic flows and emissions. An activity-based travel demand model within iTLE informs pandemic traffic operation scenarios for traffic microsimulation modeling. Link-based simulation outputs inform a finer-grained emission estimation process within a MOtor Vehicle Emission Simulator. Results suggest that the overall network performance improves during lockdown as average delays and queue time decrease by 42.04% and 5.9% respectively compared to pre-COVID condition. Emission results reveal that GHG emissions significantly decrease (64%) in lockdown while it starts increasing gradually in post-pandemic period. Link-based emission analysis indicates that major arterial streets achieve a significant reduction in air pollutant emission. The findings of this study will help transportation planners, engineers, and policymakers to devise effective policies for the improvement of transport operations and emissions.

Flow Structure Investigation of a Truck under Crosswinds

This paper investigates the flow structures on the near- and far-wake of a 1/8th scaled simplified heavy vehicle model called Ground Transportation System (GTS) model using a steady-state Reynolds-averaged Navier-Stokes (RANS) with k-ω Shear Stress Transport (SST) turbulence model at Reynolds number (Re) of 1.6 × 106 and yaw angles (Ψ) = 0o-14o. The current CFD results have been validated using experimental data from the literature. Two crosswind conditions based on the crosswind incidence angle (β) are adopted; β < 90o is called crosswind, and β = 90o (perpendicular to the GTS side surface) is called pure crosswind. Vortex detection scheme based on Ω method and total pressure coefficient (Cpt) contours is used to visualize the wake structure. With Ψ, vortices on the GTS roof take birth as a result of pressure differences between the windward and leeward sides. These vortices grow in size as they travel downstream. The growth in size is related to the Helmholtz theorem of vorticity and Kelvin’s Circulation Theorem. The vortices merged at Z/W > -4 (Z/W = 0 is the GTS rear surface) downstream of the GTS for Ψ = 7.5o and 14o. The merged vortex dissipates at Z/W > -6 and Z/W > -8 for Ψ = 7.5o and 14o, respectively. In the pure crosswind condition, the merged vortex attaches to the ground due to the velocity difference between the freestream and the moving computational ground used in the present simulation. At Ψ = 14o, surface streamlines on the GTS surface show the creation of two co-rotating vortices on the windward roof. For the present Ψ, similar flow structures between the two crosswind conditions are shown. Initial results show that the aerodynamic crosswind stability of a truck is related to the spanwise pressure difference between the windward and leeward surfaces of the truck.

Sustainable Mobility as a Service: Demand Analysis and Case Studies

Urban mobility is evolving today towards the concept of Mobility as a Service (MaaS). MaaS allows passengers to use different transport services as a single option, by using a digital platform. Therefore, according to the MaaS concept, the mobility needs of passengers are the central element of the transport service. The objective of this paper is to build an updated state-of-the-art of the main disaggregated and aggregated variables connected to travel demand in presence of MaaS. According to the above objective, this paper deals with methods and case studies to analyze passengers’ behaviour in the presence of MaaS. The methods described rely on the Transportation System Models (TSMs), in particular with the travel demand modelling component. The travel demand may be estimated by means of disaggregated, or sample, surveys (e.g., individual choices) and of aggregate surveys (e.g., characteristics of the area, traffic flows). The surveys are generally supported by Information Communication System (ICT) tools, such as: smartphones; smartcards; Global Position Systems (GPS); points of interest. The analysis of case studies allows to aggregate the existing scientific literature according to some criteria: the choice dimension of users (e.g., mode, bundle and path, or a combination of them); the characteristics of the survey (e.g., revealed preferences or stated preferences); the presence of behavioural theoretical background and of calibrated choice model(s).

Multi-instrument observations of microseisms generated by typhoon Kalmaegi (2014) over the Northwestern Pacific

The typhoon-generated microseisms, originating from the complex energy coupling and transferring among the Atmosphere-Ocean-Solid Earth spheres, can be detected remotely by seismometers as the strongest ambient seismic noise. The lack of in situ observations during the passage of typhoons has hampered numerical modeling of wind fields and ocean waves, and limited our understanding of the generation mechanisms of microseisms associated with typhoons. Here we present a comprehensive investigation of microseisms generated by typhoon Kalmaegi (September 2014) based on multiple-instrument constraints from observations including terrestrial and ocean-bottom seismic stations as well as ocean buoys. To understand the generation mechanisms, we apply an improved frequency-domain beamforming method to seismic array data leading to successful location of double-frequency (DF) microseism source regions. For comparison, we calculate the typhoon-induced ocean waves and theoretical source regions of the DF microseisms using the coupled ocean–atmosphere–wave–sediment transport modeling system with validation by ocean buoy observations. Both observations and numerical modeling results reveal two different generation mechanisms for typhoon-induced DF microseisms during the lifespan of Kalmaegi. When over the Philippine Sea, the DF microseisms were generated mainly by opposing ocean waves from two distinct storms. After Kalmaegi entered the South China Sea, the DF microseisms were generated mainly by the fast-moving typhoon with source regions just trailing behind, with the minimum frequencies determined by the typhoon translation speed. DF microseisms generated in coastal source regions were not detected by ocean bottom seismometers, suggesting that DF microseisms might not effectively propagate across the ocean-basin seafloor covered by thick sediments, owing to severe seismic attenuation and spreading losses. This information is crucial for the use of DF microseisms for future tracking and monitoring of typhoons.