To reveal the influence of coupled effects of dry-wet cycling and precompression stress(CEDWCPS)on the damage evolution of limestone with horizontal fissure(LHF),a series of degradation and uniaxial compression tests ...To reveal the influence of coupled effects of dry-wet cycling and precompression stress(CEDWCPS)on the damage evolution of limestone with horizontal fissure(LHF),a series of degradation and uniaxial compression tests were conducted,and a corresponding piecewise damage constitutive model(PDCM)was established.We found that both dry-wet cycling and precompression stress deteriorate the physical properties,alter the microscopic characteristics,and reduce the mechanical properties of the LHF.These degradations are particularly pronounced under the CEDWCPS,although the magnitude of these changes gradually diminishes with the progression of dry-wet cycling.Meanwhile,they also reduce the deformation degree,prolong the micropore compaction stage,shorten the unstable crack propagation stage,lower the frequency and intensity of AE events,decrease the high-amplitude and high-frequency AE signals,enlarge crack scales,and shorten the crack initiation time.Among the changes of these indicators,the dry-wet cycling plays a dominant role.The crack types of LHF under the CEDWCPS(LHFCEDWCPS)are predominantly tensile cracks,supplemented by shear cracks.The failure mode can be defined as tensileshear composite failure.Finally,the established PDCM effectively captures the nonlinear deformation of micropore and the linear deformation of the matrix in LHFCEDWCPS,with all corresponding R^(2) consistently exceeding 0.97.展开更多
Developing sensorless techniques for estimating battery expansion is essential for effective mechanical state monitoring,improving the accuracy of digital twin simulation and abnormality detection.Therefore,this paper...Developing sensorless techniques for estimating battery expansion is essential for effective mechanical state monitoring,improving the accuracy of digital twin simulation and abnormality detection.Therefore,this paper presents a data-driven approach to expansion estimation using electromechanical coupled models with machine learning.The proposed method integrates reduced-order impedance models with data-driven mechanical models,coupling the electrochemical and mechanical states through the state of charge(SOC)and mechanical pressure within a state estimation framework.The coupling relationship was established through experimental insights into pressure-related impedance parameters and the nonlinear mechanical behavior with SOC and pressure.The data-driven model was interpreted by introducing a novel swelling coefficient defined by component stiffnesses to capture the nonlinear mechanical behavior across various mechanical constraints.Sensitivity analysis of the impedance model shows that updating model parameters with pressure can reduce the mean absolute error of simulated voltage by 20 mV and SOC estimation error by 2%.The results demonstrate the model's estimation capabilities,achieving a root mean square error of less than 1 kPa when the maximum expansion force is from 30 kPa to 120 kPa,outperforming calibrated stiffness models and other machine learning techniques.The model's robustness and generalizability are further supported by its effective handling of SOC estimation and pressure measurement errors.This work highlights the importance of the proposed framework in enhancing state estimation and fault diagnosis for lithium-ion batteries.展开更多
Numerical models are crucial for quantifying the ocean-atmosphere interactions associated with the El Niño-Southern Oscillation(ENSO)phenomenon in the tropical Pacific.Current coupled models often exhibit signifi...Numerical models are crucial for quantifying the ocean-atmosphere interactions associated with the El Niño-Southern Oscillation(ENSO)phenomenon in the tropical Pacific.Current coupled models often exhibit significant biases and inter-model differences in simulating ENSO,underscoring the need for alternative modeling approaches.The Regional Ocean Modeling System(ROMS)is a sophisticated ocean model widely used for regional studies and has been coupled with various atmospheric models.However,its application in simulating ENSO processes on a basin scale in the tropical Pacific has not been explored.For the first time,this study presents the development of a basin-scale hybrid coupled model(HCM)for the tropical Pacific,integrating ROMS with a statistical atmospheric model that captures the interannual relationships between sea surface temperature(SST)and wind stress anomalies.The HCM is evaluated for its capability to simulate the annual mean,seasonal,and interannual variations of the oceanic state in the tropical Pacific.Results demonstrate that the model effectively reproduces the ENSO cycle,with a dominant oscillation period of approximately two years.The ROMS-based HCM developed here offers an efficient and robust tool for investigating climate variability in the tropical Pacific.展开更多
Improving plasma uniformity is a critical issue in the development of large-area radio-frequency(RF)inductively coupled plasma(ICP)sources.In this work,the effects of coil structure and electromagnetic shielding on th...Improving plasma uniformity is a critical issue in the development of large-area radio-frequency(RF)inductively coupled plasma(ICP)sources.In this work,the effects of coil structure and electromagnetic shielding on the spatial distribution and uniformity of the plasma are systematically investigated using a three-dimensional fluid model.The model integrates plasma and electromagnetic field modules to simulate the discharge characteristics of a large-area RF ICP source with dimensions of 100 cm×50 cm.The results reveal that the electron density distribution varies significantly with the coil structure.For the rotating and translating coil structures,the electron density is high at off-axis positions and low at the center.In contrast,the mirror coil structure exhibits a significantly higher electron density at the chamber center,resulting in a high-center and low-edge density distribution.Among the three configurations,the rotating coil structure provides the best plasma uniformity.The incorporation of electromagnetic shielding further improves plasma uniformity,particularly for the mirror coil structure.For the rotating and translating coil structures,the electron density exhibits a saddle-shaped distribution regardless of electromagnetic shielding.However,introducing electromagnetic shielding into the mirror coil structure reduces the electron density at the chamber center and decreases the non-uniformity degree by 18.4%.Overall,the mirror coil structure with electromagnetic shielding achieves the highest uniformity,with an exceptional plasma uniformity of 94%.This work offers valuable insights for the design of large-area ICP sources in advanced plasma processing systems.展开更多
A coupled thermal-hydro-mechanical cohesive phase-field model for hydraulic fracturing in deep coal seams is presented.Heat exchange between the cold fluid and the hot rock is considered,and the thermal contribution t...A coupled thermal-hydro-mechanical cohesive phase-field model for hydraulic fracturing in deep coal seams is presented.Heat exchange between the cold fluid and the hot rock is considered,and the thermal contribution terms between the cold fluid and the hot rock are derived.Heat transfer obeys Fourier's law,and porosity is used to relate the thermodynamic parameters of the fracture and matrix domains.The net pressure difference between the fracture and the matrix is neglected,and thus the fluid flow is modeled by the unified fluid-governing equations.The evolution equations of porosity and Biot's coefficient during hydraulic fracturing are derived from their definitions.The effect of coal cleats is considered and modeled by Voronoi polygons,and this approach is shown to have high accuracy.The accuracy of the proposed model is verified by two sets of fracturing experiments in multilayer coal seams.Subsequently,the differences in fracture morphology,fluid pressure response,and fluid pressure distribution between direct fracturing of coal seams and indirect fracturing of shale interlayers are explored,and the effects of the cluster number and cluster spacing on fracture morphology for multi-cluster fracturing are also examined.The numerical results show that the proposed model is expected to be a powerful tool for the fracturing design and optimization of deep coalbed methane.展开更多
Deep rock engineering is affected by coupled thermo-hydro-mechanical(THM)-dynamic fields,necessitating the elucidation of the dynamic mechanical behavior and failure mechanisms.This study utilized a Multi-field Couple...Deep rock engineering is affected by coupled thermo-hydro-mechanical(THM)-dynamic fields,necessitating the elucidation of the dynamic mechanical behavior and failure mechanisms.This study utilized a Multi-field Coupled Controlled Split Hopkinson Pressure Bar(MCC-SHPB)system to elucidate the cross-scale dynamic responses of rocks and the boundaries of failure modes under THM coupling.Impact tests were conducted on green sandstone under coupled conditions of temperature(25℃-80℃),confining pressure(0-15 MPa),and seepage water pressure(0-15 MPa).Scanning electron microscopy(SEM)microstructural characterization and COMSOL Multiphysics numerical simulations were conducted,and a dynamic constitutive theoretical framework and failure-prediction methodology were established.We investigated the impact toughness index(I_(t)),dynamic modulus(E_(d)),dynamic triaxial compressive strength(TCS_(d)),fragmentation degree(W),and failure modes of green sandstone under thermo-confining pressure-seepage-impact loading conditions.The key findings reveal that the(I_(t))reflects different energy regulation mechanisms across different confining pressure regimes.Thermal-microcrack interactions dominate at low pressure,and energy absorption prevails at high pressure.A triphasic dynamic modulus model captures stiffness evolution under energy-driven conditions,revealing cross-scale crack nucleation-propagation and fragment reorganization.The TCSd inflection point signifies energy dissipation shifts,causing nonlinear skeleton bearing-capacity degradation.A critical criterion based on the W was established to distinguish between the two failure modes and predict the unstable failure initiation.Numerical simulations were used to elucidate the effects of inertia-dominated crack propagation and stress wave interference,validating the critical criterion and the predictive accuracy of the theoretical model during cross-scale failure.This study provides a theoretical foundation for assessing the dynamic stability of rock masses subjected to multi-field coupling during deep resource exploitation.展开更多
Timely and accurate forecasting of storm surges can effectively prevent typhoon storm surges from causing large economic losses and casualties in coastal areas.At present,numerical model forecasting consumes too many ...Timely and accurate forecasting of storm surges can effectively prevent typhoon storm surges from causing large economic losses and casualties in coastal areas.At present,numerical model forecasting consumes too many resources and takes too long to compute,while neural network forecasting lacks regional data to train regional forecasting models.In this study,we used the DUAL wind model to build typhoon wind fields,and constructed a typhoon database of 75 processes in the northern South China Sea using the coupled Advanced Circulation-Simulating Waves Nearshore(ADCIRC-SWAN)model.Then,a neural network with a Res-U-Net structure was trained using the typhoon database to forecast the typhoon processes in the validation dataset,and an excellent storm surge forecasting effect was achieved in the Pearl River Estuary region.The storm surge forecasting effect of stronger typhoons was improved by adding a branch structure and transfer learning.展开更多
Using observation and reanalysis data throughout 1961-1990, the East Asian surface air temperature, precipitation and sea level pressure climatology as simulated by seven fully coupled atmosphere-ocean models, namely ...Using observation and reanalysis data throughout 1961-1990, the East Asian surface air temperature, precipitation and sea level pressure climatology as simulated by seven fully coupled atmosphere-ocean models, namely CCSR/NIES, CGCM2, CSIRO-Mk2, ECHAM4/OPYC3, GFDL-R30, HadCM3, and NCAR-PCM, are systematically evaluated in this study. It is indicated that the above models can successfully reproduce the annual and seasonal surface air temperature and precipitation climatology in East Asia, with relatively good performance for boreal autumn and annual mean. The models' ability to simulate surface air temperature is more reliable than precipitation. In addition, the models can dependably capture the geographical distribution pattern of annual, boreal winter, spring and autumn sea level pressure in East Asia. In contrast, relatively large simulation errors are displayed when simulated boreal summer sea level pressure is compared with reanalysis data in East Asia. It is revealed that the simulation errors for surface air temperature, precipitation and sea level pressure are generally large over and around the Tibetan Plateau. No individual model is best in every aspect. As a whole, the ECHAM4/OPYC3 and HadCM3 performances are much better, whereas the CGCM2 is relatively poorer in East Asia. Additionally, the seven-model ensemble mean usually shows a relatively high reliability.展开更多
A review is presented about the development and application of climate ocean models and oceanatmosphere coupled models developed in China as well as a review of climate variability and climate change studies performed...A review is presented about the development and application of climate ocean models and oceanatmosphere coupled models developed in China as well as a review of climate variability and climate change studies performed with these models. While the history of model development is briefly reviewed, emphasis has been put on the achievements made in the last five years. Advances in model development are described along with a summary on scientific issues addressed by using these models. The focus of the review is the climate ocean models and the associated coupled models, including both global and regional models, developed at the Institute of Atmospheric Physics, Chinese Academy of Sciences. The progress of either coupled model development made by other institutions or climate modeling using internationally developed models also is reviewed.展开更多
Nonuniform track support and differential settlements are commonly observed in bridge approaches where the ballast layer can develop gaps at crosstie-ballast interfaces often referred to as a hanging crosstie conditio...Nonuniform track support and differential settlements are commonly observed in bridge approaches where the ballast layer can develop gaps at crosstie-ballast interfaces often referred to as a hanging crosstie condition.Hanging crossties usually yield unfavorable dynamic effects such as higher wheel loads,which negatively impact the serviceability and safety of railway operations.Hence,a better understanding of the mechanisms that cause hanging crossties and their effects on the ballast layer load-deformation characteristics is necessary.Since the ballast layer is a particulate medium,the discrete element method(DEM),which simulates ballast particle interactions individually,is ideal to explore the interparticle contact forces and ballast movements under dynamic wheel loading.Accurate representations of the dynamic loads from the train and track superstructure are needed for high-fidelity DEM modeling.This paper introduces an integrated modeling approach,which couples a single-crosstie DEM ballast model with a train–track–bridge(TTB)model using a proportional–integral–derivative control loop.The TTB–DEM model was validated with field measurements,and the coupled model calculates similar crosstie displacements as the TTB model.The TTB–DEM provided new insights into the ballast particle-scale behavior,which the TTB model alone cannot explore.The TTB–DEM coupling approach identified detrimental effects of hanging crossties on adjacent crossties,which were found to experience drastic vibrations and large ballast contact force concentrations.展开更多
In this study, the relationship between the limit of predictability and initial error was investigated using two simple chaotic systems： the Lorenz model, which possesses a single characteristic time scale, and the c...In this study, the relationship between the limit of predictability and initial error was investigated using two simple chaotic systems： the Lorenz model, which possesses a single characteristic time scale, and the coupled Lorenz model, which possesses two different characteristic time scales. The limit of predictability is defined here as the time at which the error reaches 95% of its saturation level; nonlinear behaviors of the error growth are therefore involved in the definition of the limit of predictability. Our results show that the logarithmic function performs well in describing the relationship between the limit of predictability and initial error in both models, although the coefficients in the logarithmic function were not constant across the examined range of initial errors. Compared with the Lorenz model, in the coupled Lorenz model in which the slow dynamics and the fast dynamics interact with each other--there is a more complex relationship between the limit of predictability and initial error. The limit of predictability of the Lorenz model is unbounded as the initial error becomes infinitesimally small; therefore, the limit of predictability of the Lorenz model may be extended by reducing the amplitude of the initial error. In contrast, if there exists a fixed initial error in the fast dynamics of the coupled Lorenz model, the slow dynamics has an intrinsic finite limit of predictability that cannot be extended by reducing the amplitude of the initial error in the slow dynamics, and vice versa. The findings reported here reveal the possible existence of an intrinsic finite limit of predictability in a coupled system that possesses many scales of time or motion.展开更多
Coupled thermo-hydro-mechanical(THM)processes in fractured rock are playing a crucial role in geoscience and geoengineering applications.Diverse and conceptually distinct approaches have emerged over the past decades ...Coupled thermo-hydro-mechanical(THM)processes in fractured rock are playing a crucial role in geoscience and geoengineering applications.Diverse and conceptually distinct approaches have emerged over the past decades in both continuum and discontinuum perspectives leading to significant progress in their comprehending and modeling.This review paper offers an integrated perspective on existing modeling methodologies providing guidance for model selection based on the initial and boundary conditions.By comparing various models,one can better assess the uncertainties in predictions,particularly those related to the conceptual models.The review explores how these methodologies have significantlyenhanced the fundamental understanding of how fractures respond to fluid injection and production,and improved predictive capabilities pertaining to coupled processes within fractured systems.It emphasizes the importance of utilizing advanced computational technologies and thoroughly considering fundamental theories and principles established through past experimental evidence and practical experience.The selection and calibration of model parameters should be based on typical ranges and applied to the specificconditions of applications.The challenges arising from inherent heterogeneity and uncertainties,nonlinear THM coupled processes,scale dependence,and computational limitations in representing fieldscale fractures are discussed.Realizing potential advances on computational capacity calls for methodical conceptualization,mathematical modeling,selection of numerical solution strategies,implementation,and calibration to foster simulation outcomes that intricately reflectthe nuanced complexities of geological phenomena.Future research efforts should focus on innovative approaches to tackle the hurdles and advance the state-of-the-art in this critical fieldof study.展开更多
The El Niño-Southern Oscillation(ENSO)is a naturally recurring interannual climate fluctuation that affects the global climate system.The advent of deep learning-based approaches has led to transformative changes...The El Niño-Southern Oscillation(ENSO)is a naturally recurring interannual climate fluctuation that affects the global climate system.The advent of deep learning-based approaches has led to transformative changes in ENSO forecasts,resulting in significant progress.Most deep learning-based ENSO prediction models which primarily rely solely on reanalysis data may lead to challenges in intensity underestimation in long-term forecasts,reducing the forecasting skills.To this end,we propose a deep residual-coupled model prediction(Res-CMP)model,which integrates historical reanalysis data and coupled model forecast data for multiyear ENSO prediction.The Res-CMP model is designed as a lightweight model that leverages only short-term reanalysis data and nudging assimilation prediction results of the Community Earth System Model(CESM)for effective prediction of the Niño 3.4 index.We also developed a transfer learning strategy for this model to overcome the limitations of inadequate forecast data.After determining the optimal configuration,which included selecting a suitable transfer learning rate during training,along with input variables and CESM forecast lengths,Res-CMP demonstrated a high correlation ability for 19-month lead time predictions(correlation coefficients exceeding 0.5).The Res-CMP model also alleviated the spring predictability barrier(SPB).When validated against actual ENSO events,Res-CMP successfully captured the temporal evolution of the Niño 3.4 index during La Niña events(1998/99 and 2020/21)and El Niño events(2009/10 and 2015/16).Our proposed model has the potential to further enhance ENSO prediction performance by using coupled models to assist deep learning methods.展开更多
To thoroughly examine the complex relationships between tire and pavement vibrations,a sophisticated vehicle-pavement coupled system is proposed,incorporating a non-uniform dynamic friction force between the tire and ...To thoroughly examine the complex relationships between tire and pavement vibrations,a sophisticated vehicle-pavement coupled system is proposed,incorporating a non-uniform dynamic friction force between the tire and the pavement.According to the Timoshenko beam theory,a dynamic model of pavement structure with a finite length beam was formulated on a nonlinear Pasternak foundation.To more accurately describe the coupling relationship between the tire and the pavement,and to take into account the vibration state under vehicle-pavement interaction,the load distribution between the tire and the pavement is modeled as a dynamic non-uniform contact.Combined with the classic LuGre tire model,the adhesion between the tire and the pavement is calculated.The Galerkin truncation method is employed to transform the pavement vibration partial differential equation into a finite ordinary differential equation,and the integral expression of the nonlinear foundation beam term is derived using the product to sum formula.By using the Runge-Kutta method,the tire-road coupled system can be numerically calculated,thus determining tire adhesion.This research demonstrates that compared with tire force under the traditional static load distribution,load distribution has a significant influence on adhesion.This study offers valuable insights for pavement structure design and vehicle performance control.展开更多
Inspired by the crucial role of the tail in crocodile locomotion,we propose a novel rigid-flexible coupled tail structure design.The tail design reduces the number of required actuators,enables undulatory propulsion i...Inspired by the crucial role of the tail in crocodile locomotion,we propose a novel rigid-flexible coupled tail structure design.The tail design reduces the number of required actuators,enables undulatory propulsion in swimming,and provides additional support during terrestrial crawling.However,when the tail lifts off the ground during land crawling,its flexible underactuated structure tends to oscillate randomly due to minimal damping.These oscillations impart disruptive reaction torques to the body,critically impairing locomotion stability.To tackle this issue,we employed the standard Denavit-Hartenberg(DH)method and Newton-Euler equations to formulate a rigid-flexible coupled dynamic model for the tail,in which distributed elastic forces are embedded as internal forces in the force balance equations.Based on this model,we propose an oscillation suppression strategy based on an energy-optimized Nonlinear Model Predictive Controller(NMPC)with a single joint torque as the control input.This controller solves a constrained multi-objective optimization problem to effectively suppress the underactuated oscillations of the tail.Finally,experimental comparisons validate the accuracy of the dynamic model,and simulations based on this model substantiate the effectiveness of the oscillation suppression strategy.展开更多
With the miniaturization of devices and the development of modern heating technologies,the generalization of heat conduction and thermoelastic coupling has become crucial,effectively emulating the thermodynamic behavi...With the miniaturization of devices and the development of modern heating technologies,the generalization of heat conduction and thermoelastic coupling has become crucial,effectively emulating the thermodynamic behavior of materials in ultrashort time scales.Theoretically,generalized heat conductive models are considered in this work.By analogy with mechanical viscoelastic models,this paper further enriches the heat conduction models and gives their one-dimensional physical expression.Numerically,the transient thermoelastic response of the slim strip material under thermal shock is investigated by applying the proposed models.First,the analytical solution in the Laplace domain is obtained by the Laplace transform.Then,the numerical results of the transient responses are obtained by the numerical inverse Laplace transform.Finally,the transient responses of different models are analyzed and compared,and the effects of material parameters are discussed.This work not only opens up new research perspectives on generalized heat conductive and thermoelastic coupling theories,but also is expected to be beneficial for the deeper understanding of the heat wave theory.展开更多
A mechanistic understanding and modeling of the coupled human and natural systems(CHANS)are frontier of geographical sciences and essential for promoting regional sustainability.Modeling regional CHANS in the Yellow R...A mechanistic understanding and modeling of the coupled human and natural systems(CHANS)are frontier of geographical sciences and essential for promoting regional sustainability.Modeling regional CHANS in the Yellow River Basin(YRB)featuring high water stress,intense human interference,and a fragile ecosystem has always been a complex challenge.Here,we propose a conceptual modeling framework to capture key human-natural components and their interactions,focusing on human-water dynamics.The modeling framework encompasses five human(Population,Economy,Energy,Food,and Water Demand)and five natural sectors(Water Supply,Sediment,Land,Carbon,and Climate)that can be either fully interactive or standalone.The modeling framework,implemented using the system dynamics(SD)approach,can well reproduce the basin's historical evolution in human-natural processes and predict future dynamics under various scenarios.The flexibility,adaptability,and potential for integration with diverse methods position the framework as an instructive tool for guiding regional CHANS modeling.Our insights highlight pathways to advance regional CHANS modeling and its application to address regional sustainability challenges.展开更多
This paper provides a comparative analysis of the performance of a high-resolution regional ocean-atmosphere coupled model in predicting tropical cyclone(TC)gales over the northern South China Sea.The atmosphere and o...This paper provides a comparative analysis of the performance of a high-resolution regional ocean-atmosphere coupled model in predicting tropical cyclone(TC)gales over the northern South China Sea.The atmosphere and ocean components of the coupled system are represented by the China Meteorological Administration’s Tropical Regional Atmosphere Model for the South China Sea(CMA-TRAMS)and the LASG/IAP Climate system Ocean Model(LICOM),respectively.The Ocean Atmosphere Sea Ice Soil VersionH 3(OASIS3)software has been utilized for the exchange of momentum,heat,and freshwater fluxes between these two components.An assessment of the coupled model’s three-day predictions for five TCs’gales was conducted.Preliminary findings indicate that the predicted TC tracks show less sensitivity to oceanic influences than the predicted TC intensities.Significant improvement in predicting the surface TC gales has been achieved through coupling the ocean model.This improvement is attributed to the impact of the warmer ocean’s effect on TC intensification,counteracting the cooling effect of the cold wake.In summary,coupling has enhanced the model’s predictive capabilities for TC gales.A detailed assessment of the coupled model’s performance in predicting other tropical weather phenomena is forthcoming.展开更多
Arctic sea ice is an important component of the global climate system and has experienced rapid changes during in the past few decades,the prediction of which is a significant application for climate models.In this st...Arctic sea ice is an important component of the global climate system and has experienced rapid changes during in the past few decades,the prediction of which is a significant application for climate models.In this study,a Localized Error Subspace Transform Kalman Filter is employed in a coupled climate system model(the Flexible Global Ocean–Atmosphere–Land System Model,version f3-L(FGOALS-f3-L))to assimilate sea-ice concentration(SIC)and sea-ice thickness(SIT)data for melting-season ice predictions.The scheme is applied through the following steps:(1)initialization for generating initial ensembles;(2)analysis for assimilating observed data;(3)adoption for dividing ice states into five thickness categories;(4)forecast for evolving the model;(5)resampling for updating model uncertainties.Several experiments were conducted to examine its results and impacts.Compared with the control experiment,the continuous assimilation experiments(CTNs)indicate assimilations improve model SICs and SITs persistently and generate realistic initials.Assimilating SIC+SIT data better corrects overestimated model SITs spatially than when only assimilating SIC data.The continuous assimilation restart experiments indicate the initials from the CTNs correct the overestimated marginal SICs and overall SITs remarkably well,as well as the cold biases in the oceanic and atmospheric models.The initials with SIC+SIT assimilated show more reasonable spatial improvements.Nevertheless,the SICs in the central Arctic undergo abnormal summer reductions,which is probably because overestimated SITs are reduced in the initials but the strong seasonal cycle(summer melting)biases are unchanged.Therefore,since systematic biases are complicated in a coupled system,for FGOALS-f3-L to make better ice predictions,oceanic and atmospheric assimilations are expected required.展开更多
This study evaluates the 1995-2020 global ocean-sea ice simulation using the unstructured-mesh model for prediction across scales(MPAS)-ocean/sea ice model within energy exascale earth system model(E3SM)version 2.1(E3...This study evaluates the 1995-2020 global ocean-sea ice simulation using the unstructured-mesh model for prediction across scales(MPAS)-ocean/sea ice model within energy exascale earth system model(E3SM)version 2.1(E3SMv2-MPAS)at 60 km to 10 km resolution.Multi-source observational data are utilized to validate sea surface temperature/salinity,sea ice,three-dimensional thermal-saline structures,mixed layer depth,ocean heat content,and sea surface height.Key results show the following:(1)E3SMv2-MPAS captures seasonal-to-decadal variability in surface fields and sea ice,but shows systematic biases in sea surface temperature of western boundary currents(inadequate eddy parameterization)and Arctic sea surface salinity(misrepresented freshwater fluxes and mixing processes).(2)The model robustly represents three-dimensional climate variability,yet underestimates mixed layer depth in key regions(Antarctic Circumpolar Current and North Atlantic),revealing deficiencies in extreme mixing.(3)Ocean heat content distributions are well-simulated.(4)Sea surface height spatial patterns and interannual variability are accurately reproduced.This work identifies critical refinements for unstructured-mesh models:mesoscale eddy parameterization,polar ocean-sea ice coupling,and multi-scale energy processes,advancing high-resolution climate model development and laying the groundwork for improved ocean forecasting systems.展开更多
基金supported by the Yunnan Province Science and Technology Plan Project(No.202403AA080001-4)the Key Research and Development Project of Guangxi,China(No.guikeAB24010144)the National Key Research and Development Project of China(Nos.2021YFB3901402 and 2018YFC1504802)。
文摘To reveal the influence of coupled effects of dry-wet cycling and precompression stress(CEDWCPS)on the damage evolution of limestone with horizontal fissure(LHF),a series of degradation and uniaxial compression tests were conducted,and a corresponding piecewise damage constitutive model(PDCM)was established.We found that both dry-wet cycling and precompression stress deteriorate the physical properties,alter the microscopic characteristics,and reduce the mechanical properties of the LHF.These degradations are particularly pronounced under the CEDWCPS,although the magnitude of these changes gradually diminishes with the progression of dry-wet cycling.Meanwhile,they also reduce the deformation degree,prolong the micropore compaction stage,shorten the unstable crack propagation stage,lower the frequency and intensity of AE events,decrease the high-amplitude and high-frequency AE signals,enlarge crack scales,and shorten the crack initiation time.Among the changes of these indicators,the dry-wet cycling plays a dominant role.The crack types of LHF under the CEDWCPS(LHFCEDWCPS)are predominantly tensile cracks,supplemented by shear cracks.The failure mode can be defined as tensileshear composite failure.Finally,the established PDCM effectively captures the nonlinear deformation of micropore and the linear deformation of the matrix in LHFCEDWCPS,with all corresponding R^(2) consistently exceeding 0.97.
基金Fund supported this work for Excellent Youth Scholars of China(Grant No.52222708)the National Natural Science Foundation of China(Grant No.51977007)+1 种基金Part of this work is supported by the research project“SPEED”(03XP0585)at RWTH Aachen Universityfunded by the German Federal Ministry of Education and Research(BMBF)。
文摘Developing sensorless techniques for estimating battery expansion is essential for effective mechanical state monitoring,improving the accuracy of digital twin simulation and abnormality detection.Therefore,this paper presents a data-driven approach to expansion estimation using electromechanical coupled models with machine learning.The proposed method integrates reduced-order impedance models with data-driven mechanical models,coupling the electrochemical and mechanical states through the state of charge(SOC)and mechanical pressure within a state estimation framework.The coupling relationship was established through experimental insights into pressure-related impedance parameters and the nonlinear mechanical behavior with SOC and pressure.The data-driven model was interpreted by introducing a novel swelling coefficient defined by component stiffnesses to capture the nonlinear mechanical behavior across various mechanical constraints.Sensitivity analysis of the impedance model shows that updating model parameters with pressure can reduce the mean absolute error of simulated voltage by 20 mV and SOC estimation error by 2%.The results demonstrate the model's estimation capabilities,achieving a root mean square error of less than 1 kPa when the maximum expansion force is from 30 kPa to 120 kPa,outperforming calibrated stiffness models and other machine learning techniques.The model's robustness and generalizability are further supported by its effective handling of SOC estimation and pressure measurement errors.This work highlights the importance of the proposed framework in enhancing state estimation and fault diagnosis for lithium-ion batteries.
基金Supported by the Laoshan Laboratory(No.LSKJ 202202404)the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDB 42000000)+1 种基金the National Natural Science Foundation of China(NSFC)(No.42030410)the Startup Foundation for Introducing Talent of NUIST,and the Jiangsu Innovation Research Group(No.JSSCTD 202346)。
文摘Numerical models are crucial for quantifying the ocean-atmosphere interactions associated with the El Niño-Southern Oscillation(ENSO)phenomenon in the tropical Pacific.Current coupled models often exhibit significant biases and inter-model differences in simulating ENSO,underscoring the need for alternative modeling approaches.The Regional Ocean Modeling System(ROMS)is a sophisticated ocean model widely used for regional studies and has been coupled with various atmospheric models.However,its application in simulating ENSO processes on a basin scale in the tropical Pacific has not been explored.For the first time,this study presents the development of a basin-scale hybrid coupled model(HCM)for the tropical Pacific,integrating ROMS with a statistical atmospheric model that captures the interannual relationships between sea surface temperature(SST)and wind stress anomalies.The HCM is evaluated for its capability to simulate the annual mean,seasonal,and interannual variations of the oceanic state in the tropical Pacific.Results demonstrate that the model effectively reproduces the ENSO cycle,with a dominant oscillation period of approximately two years.The ROMS-based HCM developed here offers an efficient and robust tool for investigating climate variability in the tropical Pacific.
基金supported by the National Natural Science Foundation of China(Grant Nos.12075049 and 11935005)。
文摘Improving plasma uniformity is a critical issue in the development of large-area radio-frequency(RF)inductively coupled plasma(ICP)sources.In this work,the effects of coil structure and electromagnetic shielding on the spatial distribution and uniformity of the plasma are systematically investigated using a three-dimensional fluid model.The model integrates plasma and electromagnetic field modules to simulate the discharge characteristics of a large-area RF ICP source with dimensions of 100 cm×50 cm.The results reveal that the electron density distribution varies significantly with the coil structure.For the rotating and translating coil structures,the electron density is high at off-axis positions and low at the center.In contrast,the mirror coil structure exhibits a significantly higher electron density at the chamber center,resulting in a high-center and low-edge density distribution.Among the three configurations,the rotating coil structure provides the best plasma uniformity.The incorporation of electromagnetic shielding further improves plasma uniformity,particularly for the mirror coil structure.For the rotating and translating coil structures,the electron density exhibits a saddle-shaped distribution regardless of electromagnetic shielding.However,introducing electromagnetic shielding into the mirror coil structure reduces the electron density at the chamber center and decreases the non-uniformity degree by 18.4%.Overall,the mirror coil structure with electromagnetic shielding achieves the highest uniformity,with an exceptional plasma uniformity of 94%.This work offers valuable insights for the design of large-area ICP sources in advanced plasma processing systems.
基金Project supported by the National Natural Science Foundation of China(No.42202314)。
文摘A coupled thermal-hydro-mechanical cohesive phase-field model for hydraulic fracturing in deep coal seams is presented.Heat exchange between the cold fluid and the hot rock is considered,and the thermal contribution terms between the cold fluid and the hot rock are derived.Heat transfer obeys Fourier's law,and porosity is used to relate the thermodynamic parameters of the fracture and matrix domains.The net pressure difference between the fracture and the matrix is neglected,and thus the fluid flow is modeled by the unified fluid-governing equations.The evolution equations of porosity and Biot's coefficient during hydraulic fracturing are derived from their definitions.The effect of coal cleats is considered and modeled by Voronoi polygons,and this approach is shown to have high accuracy.The accuracy of the proposed model is verified by two sets of fracturing experiments in multilayer coal seams.Subsequently,the differences in fracture morphology,fluid pressure response,and fluid pressure distribution between direct fracturing of coal seams and indirect fracturing of shale interlayers are explored,and the effects of the cluster number and cluster spacing on fracture morphology for multi-cluster fracturing are also examined.The numerical results show that the proposed model is expected to be a powerful tool for the fracturing design and optimization of deep coalbed methane.
基金supported by the National Natural Science Foundation of China(Grant Nos.12272411 and 42007259).
文摘Deep rock engineering is affected by coupled thermo-hydro-mechanical(THM)-dynamic fields,necessitating the elucidation of the dynamic mechanical behavior and failure mechanisms.This study utilized a Multi-field Coupled Controlled Split Hopkinson Pressure Bar(MCC-SHPB)system to elucidate the cross-scale dynamic responses of rocks and the boundaries of failure modes under THM coupling.Impact tests were conducted on green sandstone under coupled conditions of temperature(25℃-80℃),confining pressure(0-15 MPa),and seepage water pressure(0-15 MPa).Scanning electron microscopy(SEM)microstructural characterization and COMSOL Multiphysics numerical simulations were conducted,and a dynamic constitutive theoretical framework and failure-prediction methodology were established.We investigated the impact toughness index(I_(t)),dynamic modulus(E_(d)),dynamic triaxial compressive strength(TCS_(d)),fragmentation degree(W),and failure modes of green sandstone under thermo-confining pressure-seepage-impact loading conditions.The key findings reveal that the(I_(t))reflects different energy regulation mechanisms across different confining pressure regimes.Thermal-microcrack interactions dominate at low pressure,and energy absorption prevails at high pressure.A triphasic dynamic modulus model captures stiffness evolution under energy-driven conditions,revealing cross-scale crack nucleation-propagation and fragment reorganization.The TCSd inflection point signifies energy dissipation shifts,causing nonlinear skeleton bearing-capacity degradation.A critical criterion based on the W was established to distinguish between the two failure modes and predict the unstable failure initiation.Numerical simulations were used to elucidate the effects of inertia-dominated crack propagation and stress wave interference,validating the critical criterion and the predictive accuracy of the theoretical model during cross-scale failure.This study provides a theoretical foundation for assessing the dynamic stability of rock masses subjected to multi-field coupling during deep resource exploitation.
基金supported by the National Natural Science Foundation of China(Grant No.42076214)Natural Science Foundation of Shandong Province(Grant No.ZR2024QD057).
文摘Timely and accurate forecasting of storm surges can effectively prevent typhoon storm surges from causing large economic losses and casualties in coastal areas.At present,numerical model forecasting consumes too many resources and takes too long to compute,while neural network forecasting lacks regional data to train regional forecasting models.In this study,we used the DUAL wind model to build typhoon wind fields,and constructed a typhoon database of 75 processes in the northern South China Sea using the coupled Advanced Circulation-Simulating Waves Nearshore(ADCIRC-SWAN)model.Then,a neural network with a Res-U-Net structure was trained using the typhoon database to forecast the typhoon processes in the validation dataset,and an excellent storm surge forecasting effect was achieved in the Pearl River Estuary region.The storm surge forecasting effect of stronger typhoons was improved by adding a branch structure and transfer learning.
基金This research was jointly supported by the Chinese Academy of Sciences(CAS)under Grant No.KZCX3-SW-221by the National Natural Science Foundation of China under Grant No.40405015+1 种基金by the Chinese Ministry of Science and Technology under Grant No.2001BA611B(part 1)by the CAS“Hundred Talent Project"funding awarded to Gao Yongqi.
文摘Using observation and reanalysis data throughout 1961-1990, the East Asian surface air temperature, precipitation and sea level pressure climatology as simulated by seven fully coupled atmosphere-ocean models, namely CCSR/NIES, CGCM2, CSIRO-Mk2, ECHAM4/OPYC3, GFDL-R30, HadCM3, and NCAR-PCM, are systematically evaluated in this study. It is indicated that the above models can successfully reproduce the annual and seasonal surface air temperature and precipitation climatology in East Asia, with relatively good performance for boreal autumn and annual mean. The models' ability to simulate surface air temperature is more reliable than precipitation. In addition, the models can dependably capture the geographical distribution pattern of annual, boreal winter, spring and autumn sea level pressure in East Asia. In contrast, relatively large simulation errors are displayed when simulated boreal summer sea level pressure is compared with reanalysis data in East Asia. It is revealed that the simulation errors for surface air temperature, precipitation and sea level pressure are generally large over and around the Tibetan Plateau. No individual model is best in every aspect. As a whole, the ECHAM4/OPYC3 and HadCM3 performances are much better, whereas the CGCM2 is relatively poorer in East Asia. Additionally, the seven-model ensemble mean usually shows a relatively high reliability.
基金This work was jointly supported by the National Natural Science Foundation of China （Grant Nos. 40523001, 40221503, 40675050）Major State Basic Research Development Program of China under Grant Nos. 2005CB321703, 2006CB403603the International Partnership Creative Group entitled ＂The Climate System Model Development and Application Studies＂.
文摘A review is presented about the development and application of climate ocean models and oceanatmosphere coupled models developed in China as well as a review of climate variability and climate change studies performed with these models. While the history of model development is briefly reviewed, emphasis has been put on the achievements made in the last five years. Advances in model development are described along with a summary on scientific issues addressed by using these models. The focus of the review is the climate ocean models and the associated coupled models, including both global and regional models, developed at the Institute of Atmospheric Physics, Chinese Academy of Sciences. The progress of either coupled model development made by other institutions or climate modeling using internationally developed models also is reviewed.
基金a U.S. Federal Railroad Administration (FRA)BAA project,titled “Mitigation of Differential Movement at Railway Transitions for High-Speed Passenger Rail and Joint Passenger/Freight Corridors”the financial support provided by the China Scholarship Council (CSC),which funded Zhongyi Liu’s and Wenjing Li’s time and research efforts for this study
文摘Nonuniform track support and differential settlements are commonly observed in bridge approaches where the ballast layer can develop gaps at crosstie-ballast interfaces often referred to as a hanging crosstie condition.Hanging crossties usually yield unfavorable dynamic effects such as higher wheel loads,which negatively impact the serviceability and safety of railway operations.Hence,a better understanding of the mechanisms that cause hanging crossties and their effects on the ballast layer load-deformation characteristics is necessary.Since the ballast layer is a particulate medium,the discrete element method(DEM),which simulates ballast particle interactions individually,is ideal to explore the interparticle contact forces and ballast movements under dynamic wheel loading.Accurate representations of the dynamic loads from the train and track superstructure are needed for high-fidelity DEM modeling.This paper introduces an integrated modeling approach,which couples a single-crosstie DEM ballast model with a train–track–bridge(TTB)model using a proportional–integral–derivative control loop.The TTB–DEM model was validated with field measurements,and the coupled model calculates similar crosstie displacements as the TTB model.The TTB–DEM provided new insights into the ballast particle-scale behavior,which the TTB model alone cannot explore.The TTB–DEM coupling approach identified detrimental effects of hanging crossties on adjacent crossties,which were found to experience drastic vibrations and large ballast contact force concentrations.
基金sprovided jointly by the 973 Program (Grant No.2010CB950400)National Natural Science Foundation of China (Grant Nos. 40805022 and 40821092)
文摘In this study, the relationship between the limit of predictability and initial error was investigated using two simple chaotic systems： the Lorenz model, which possesses a single characteristic time scale, and the coupled Lorenz model, which possesses two different characteristic time scales. The limit of predictability is defined here as the time at which the error reaches 95% of its saturation level; nonlinear behaviors of the error growth are therefore involved in the definition of the limit of predictability. Our results show that the logarithmic function performs well in describing the relationship between the limit of predictability and initial error in both models, although the coefficients in the logarithmic function were not constant across the examined range of initial errors. Compared with the Lorenz model, in the coupled Lorenz model in which the slow dynamics and the fast dynamics interact with each other--there is a more complex relationship between the limit of predictability and initial error. The limit of predictability of the Lorenz model is unbounded as the initial error becomes infinitesimally small; therefore, the limit of predictability of the Lorenz model may be extended by reducing the amplitude of the initial error. In contrast, if there exists a fixed initial error in the fast dynamics of the coupled Lorenz model, the slow dynamics has an intrinsic finite limit of predictability that cannot be extended by reducing the amplitude of the initial error in the slow dynamics, and vice versa. The findings reported here reveal the possible existence of an intrinsic finite limit of predictability in a coupled system that possesses many scales of time or motion.
基金funding from the European Research Council(ERC)under the European Union’s Horizon 2020 Research and Innovation Program through the Starting Grant GEoREST(grant agreement No.801809)support by MICIU/AEI/10.13039/501100011033 and by"European Union Next Generation EU/PRTR"through the‘Ramón y Cajal’fellowship(reference RYC2021-032780-I)+9 种基金funding by MICIU/AEI/10.13039/501100011033 and by“ERDF,EU”through the‘HydroPoreII’project(reference PID2022-137652NBC44)support by the Institute for Korea Spent Nuclear Fuel(iKSNF)National Research Foundation of Korea(NRF)grant funded by the Korea government(Ministry of Science and ICT,MSIT)(2021M2E1A1085196)support by the Swedish Radiation Safety(SSM),Swedish Transport Administration(Trafikverket),Swedish Rock Engineering Foundation(BeFo),and Nordic Energy Research(Grant 187658)supported by the US Department of Energy(DOE),the Officeof Nuclear Energy,Spent Fuel and Waste Science and Technology Campaign,and by the US Department of Energy(DOE),the Office of Basic Energy Sciences,Chemical Sciences,Geosciences,and Biosciences Division both under Contract Number DE-AC02-05CH11231 with Lawrence Berkeley National Laboratorysupport from the US National Science Foundation(grant CMMI-2239630)funding from the European Research Council(ERC)under the European Union’s Horizon 2020 research and innovation programme(grant agreement No.101002507)the UK Natural Environment Research Council(NERC)for funding SeisGreen Project(Grant No.NE/W009293/1)which supported this workthe Royal Society UK for supporting this research through fellowship UF160443IMEDEA is an accredited"Maria de Maeztu Excellence Unit"(Grant CEX2021-001198,funded by MICIU/AEI/10.13039/501100011033).
文摘Coupled thermo-hydro-mechanical(THM)processes in fractured rock are playing a crucial role in geoscience and geoengineering applications.Diverse and conceptually distinct approaches have emerged over the past decades in both continuum and discontinuum perspectives leading to significant progress in their comprehending and modeling.This review paper offers an integrated perspective on existing modeling methodologies providing guidance for model selection based on the initial and boundary conditions.By comparing various models,one can better assess the uncertainties in predictions,particularly those related to the conceptual models.The review explores how these methodologies have significantlyenhanced the fundamental understanding of how fractures respond to fluid injection and production,and improved predictive capabilities pertaining to coupled processes within fractured systems.It emphasizes the importance of utilizing advanced computational technologies and thoroughly considering fundamental theories and principles established through past experimental evidence and practical experience.The selection and calibration of model parameters should be based on typical ranges and applied to the specificconditions of applications.The challenges arising from inherent heterogeneity and uncertainties,nonlinear THM coupled processes,scale dependence,and computational limitations in representing fieldscale fractures are discussed.Realizing potential advances on computational capacity calls for methodical conceptualization,mathematical modeling,selection of numerical solution strategies,implementation,and calibration to foster simulation outcomes that intricately reflectthe nuanced complexities of geological phenomena.Future research efforts should focus on innovative approaches to tackle the hurdles and advance the state-of-the-art in this critical fieldof study.
基金The National Key Research and Development Program of China under contract Nos 2024YFF0808900,2023YFF0805300,and 2020YFA0608804the Civilian Space Programme of China under contract No.D040305.
文摘The El Niño-Southern Oscillation(ENSO)is a naturally recurring interannual climate fluctuation that affects the global climate system.The advent of deep learning-based approaches has led to transformative changes in ENSO forecasts,resulting in significant progress.Most deep learning-based ENSO prediction models which primarily rely solely on reanalysis data may lead to challenges in intensity underestimation in long-term forecasts,reducing the forecasting skills.To this end,we propose a deep residual-coupled model prediction(Res-CMP)model,which integrates historical reanalysis data and coupled model forecast data for multiyear ENSO prediction.The Res-CMP model is designed as a lightweight model that leverages only short-term reanalysis data and nudging assimilation prediction results of the Community Earth System Model(CESM)for effective prediction of the Niño 3.4 index.We also developed a transfer learning strategy for this model to overcome the limitations of inadequate forecast data.After determining the optimal configuration,which included selecting a suitable transfer learning rate during training,along with input variables and CESM forecast lengths,Res-CMP demonstrated a high correlation ability for 19-month lead time predictions(correlation coefficients exceeding 0.5).The Res-CMP model also alleviated the spring predictability barrier(SPB).When validated against actual ENSO events,Res-CMP successfully captured the temporal evolution of the Niño 3.4 index during La Niña events(1998/99 and 2020/21)and El Niño events(2009/10 and 2015/16).Our proposed model has the potential to further enhance ENSO prediction performance by using coupled models to assist deep learning methods.
基金financially supported by the National Natural Science Foundation of China(Grant No.12072204).
文摘To thoroughly examine the complex relationships between tire and pavement vibrations,a sophisticated vehicle-pavement coupled system is proposed,incorporating a non-uniform dynamic friction force between the tire and the pavement.According to the Timoshenko beam theory,a dynamic model of pavement structure with a finite length beam was formulated on a nonlinear Pasternak foundation.To more accurately describe the coupling relationship between the tire and the pavement,and to take into account the vibration state under vehicle-pavement interaction,the load distribution between the tire and the pavement is modeled as a dynamic non-uniform contact.Combined with the classic LuGre tire model,the adhesion between the tire and the pavement is calculated.The Galerkin truncation method is employed to transform the pavement vibration partial differential equation into a finite ordinary differential equation,and the integral expression of the nonlinear foundation beam term is derived using the product to sum formula.By using the Runge-Kutta method,the tire-road coupled system can be numerically calculated,thus determining tire adhesion.This research demonstrates that compared with tire force under the traditional static load distribution,load distribution has a significant influence on adhesion.This study offers valuable insights for pavement structure design and vehicle performance control.
基金supported by the National Key Research and Development Program of China(Grant No.2024YFB3213600).
文摘Inspired by the crucial role of the tail in crocodile locomotion,we propose a novel rigid-flexible coupled tail structure design.The tail design reduces the number of required actuators,enables undulatory propulsion in swimming,and provides additional support during terrestrial crawling.However,when the tail lifts off the ground during land crawling,its flexible underactuated structure tends to oscillate randomly due to minimal damping.These oscillations impart disruptive reaction torques to the body,critically impairing locomotion stability.To tackle this issue,we employed the standard Denavit-Hartenberg(DH)method and Newton-Euler equations to formulate a rigid-flexible coupled dynamic model for the tail,in which distributed elastic forces are embedded as internal forces in the force balance equations.Based on this model,we propose an oscillation suppression strategy based on an energy-optimized Nonlinear Model Predictive Controller(NMPC)with a single joint torque as the control input.This controller solves a constrained multi-objective optimization problem to effectively suppress the underactuated oscillations of the tail.Finally,experimental comparisons validate the accuracy of the dynamic model,and simulations based on this model substantiate the effectiveness of the oscillation suppression strategy.
基金Project supported by the Guangdong Basic and Applied Basic Research Foundation of China(No.2023A1515012809)the Natural Science Foundation of Shaanxi Province of China(No.2023-JC-YB-073)the Fundamental Research Funds for the Central Universities of China(No.D5000230066)。
文摘With the miniaturization of devices and the development of modern heating technologies,the generalization of heat conduction and thermoelastic coupling has become crucial,effectively emulating the thermodynamic behavior of materials in ultrashort time scales.Theoretically,generalized heat conductive models are considered in this work.By analogy with mechanical viscoelastic models,this paper further enriches the heat conduction models and gives their one-dimensional physical expression.Numerically,the transient thermoelastic response of the slim strip material under thermal shock is investigated by applying the proposed models.First,the analytical solution in the Laplace domain is obtained by the Laplace transform.Then,the numerical results of the transient responses are obtained by the numerical inverse Laplace transform.Finally,the transient responses of different models are analyzed and compared,and the effects of material parameters are discussed.This work not only opens up new research perspectives on generalized heat conductive and thermoelastic coupling theories,but also is expected to be beneficial for the deeper understanding of the heat wave theory.
基金supported by the National Natural Science Foundation of China(Grant No.42041007)the Fundamental Research Funds for the Central Universities。
文摘A mechanistic understanding and modeling of the coupled human and natural systems(CHANS)are frontier of geographical sciences and essential for promoting regional sustainability.Modeling regional CHANS in the Yellow River Basin(YRB)featuring high water stress,intense human interference,and a fragile ecosystem has always been a complex challenge.Here,we propose a conceptual modeling framework to capture key human-natural components and their interactions,focusing on human-water dynamics.The modeling framework encompasses five human(Population,Economy,Energy,Food,and Water Demand)and five natural sectors(Water Supply,Sediment,Land,Carbon,and Climate)that can be either fully interactive or standalone.The modeling framework,implemented using the system dynamics(SD)approach,can well reproduce the basin's historical evolution in human-natural processes and predict future dynamics under various scenarios.The flexibility,adaptability,and potential for integration with diverse methods position the framework as an instructive tool for guiding regional CHANS modeling.Our insights highlight pathways to advance regional CHANS modeling and its application to address regional sustainability challenges.
基金supported by the National Key R&D Program of China [grant number 2023YFC3008005]the Guangdong Basic and Applied Basic Research Foundation [grant numbers 2022A1515011288 and 2024A1515030210]+1 种基金the Key Innovation Team of the China Meteorological Administration [grant number CMA2023ZD08]the Guangdong Provincial Marine Meteorology Science Data Center [grant number 2024B1212070014]。
文摘This paper provides a comparative analysis of the performance of a high-resolution regional ocean-atmosphere coupled model in predicting tropical cyclone(TC)gales over the northern South China Sea.The atmosphere and ocean components of the coupled system are represented by the China Meteorological Administration’s Tropical Regional Atmosphere Model for the South China Sea(CMA-TRAMS)and the LASG/IAP Climate system Ocean Model(LICOM),respectively.The Ocean Atmosphere Sea Ice Soil VersionH 3(OASIS3)software has been utilized for the exchange of momentum,heat,and freshwater fluxes between these two components.An assessment of the coupled model’s three-day predictions for five TCs’gales was conducted.Preliminary findings indicate that the predicted TC tracks show less sensitivity to oceanic influences than the predicted TC intensities.Significant improvement in predicting the surface TC gales has been achieved through coupling the ocean model.This improvement is attributed to the impact of the warmer ocean’s effect on TC intensification,counteracting the cooling effect of the cold wake.In summary,coupling has enhanced the model’s predictive capabilities for TC gales.A detailed assessment of the coupled model’s performance in predicting other tropical weather phenomena is forthcoming.
基金jointly funded by the National Natural Science Foundation of China(NSFC)[grant number 42130608]the China Postdoctoral Science Foundation[grant number 2024M753169]。
文摘Arctic sea ice is an important component of the global climate system and has experienced rapid changes during in the past few decades,the prediction of which is a significant application for climate models.In this study,a Localized Error Subspace Transform Kalman Filter is employed in a coupled climate system model(the Flexible Global Ocean–Atmosphere–Land System Model,version f3-L(FGOALS-f3-L))to assimilate sea-ice concentration(SIC)and sea-ice thickness(SIT)data for melting-season ice predictions.The scheme is applied through the following steps:(1)initialization for generating initial ensembles;(2)analysis for assimilating observed data;(3)adoption for dividing ice states into five thickness categories;(4)forecast for evolving the model;(5)resampling for updating model uncertainties.Several experiments were conducted to examine its results and impacts.Compared with the control experiment,the continuous assimilation experiments(CTNs)indicate assimilations improve model SICs and SITs persistently and generate realistic initials.Assimilating SIC+SIT data better corrects overestimated model SITs spatially than when only assimilating SIC data.The continuous assimilation restart experiments indicate the initials from the CTNs correct the overestimated marginal SICs and overall SITs remarkably well,as well as the cold biases in the oceanic and atmospheric models.The initials with SIC+SIT assimilated show more reasonable spatial improvements.Nevertheless,the SICs in the central Arctic undergo abnormal summer reductions,which is probably because overestimated SITs are reduced in the initials but the strong seasonal cycle(summer melting)biases are unchanged.Therefore,since systematic biases are complicated in a coupled system,for FGOALS-f3-L to make better ice predictions,oceanic and atmospheric assimilations are expected required.
基金The National Key R&D Program of China under contract No.2021YFC3101503the Science and Technology Innovation Program of Hunan Province under contract No.2022RC3070+1 种基金the National Natural Science Foundation of China under contract Nos 42305176 and 42276205the Hunan Provincial Natural Science Foundation of China under contract No.2023JJ10053.
文摘This study evaluates the 1995-2020 global ocean-sea ice simulation using the unstructured-mesh model for prediction across scales(MPAS)-ocean/sea ice model within energy exascale earth system model(E3SM)version 2.1(E3SMv2-MPAS)at 60 km to 10 km resolution.Multi-source observational data are utilized to validate sea surface temperature/salinity,sea ice,three-dimensional thermal-saline structures,mixed layer depth,ocean heat content,and sea surface height.Key results show the following:(1)E3SMv2-MPAS captures seasonal-to-decadal variability in surface fields and sea ice,but shows systematic biases in sea surface temperature of western boundary currents(inadequate eddy parameterization)and Arctic sea surface salinity(misrepresented freshwater fluxes and mixing processes).(2)The model robustly represents three-dimensional climate variability,yet underestimates mixed layer depth in key regions(Antarctic Circumpolar Current and North Atlantic),revealing deficiencies in extreme mixing.(3)Ocean heat content distributions are well-simulated.(4)Sea surface height spatial patterns and interannual variability are accurately reproduced.This work identifies critical refinements for unstructured-mesh models:mesoscale eddy parameterization,polar ocean-sea ice coupling,and multi-scale energy processes,advancing high-resolution climate model development and laying the groundwork for improved ocean forecasting systems.
