The static correction of a near-surface model may be improved by using travel time tomographic inversion.We discuss unfavorable factors in the inversion of surface seismic waves that have been analyzed by the first br...The static correction of a near-surface model may be improved by using travel time tomographic inversion.We discuss unfavorable factors in the inversion of surface seismic waves that have been analyzed by the first break.These factors show that sources and geophones arranged on the surface,or close to the surface,give a first break that only includes the direct wave and the up going wave from the down going to up going transition.These up going waves have weak directivity when they arrive at a geophone and so the rays passing through the grids have small directional differences and a narrow azimuth.Drawing lessons from the advantages of Vertical Seismic Profiling(VSP) acquisition mode we describe a pseudo well-surface simultaneous travel time tomographic inversion of a near-surface model.The well depth should be increased in the surface seismic study to produce a pure up going wave,to enhance the verticality of the rays and to increase the azimuth and shorten path length of the rays.Simulations of the effect of well depth on a pseudo well-surface simultaneous travel time tomographic inversion model are reported.The results show that the static corrections are improved significantly when the well depth extends below the weathered or sub-weathered layers.The root mean square error of the statics is 1.14 or 0.93 ms for these two situations,respectively.展开更多
Global deforestation has been recognized as an important factor influencing climate change over the past century.However, uncertainties remain regarding its biophysical impacts on temperature across China. Utilizing m...Global deforestation has been recognized as an important factor influencing climate change over the past century.However, uncertainties remain regarding its biophysical impacts on temperature across China. Utilizing monthly data from eight global climate models of the Land Use Model Intercomparison Project, a multimodel comparison was conducted to quantitatively analyze the biophysical impacts of global deforestation on near-surface air temperature in China, using a surface energy balance decomposition method. Results show a 38%(29% to 45%) reduction in forest cover in China(ensemble mean and range across eight models) relative to pre-industrial levels, and an annual cooling of 0.6 K(0.05 to1.4 K) accompanied by global deforestation. Notably, surface albedo causes a cooling effect of 0.6 K(0.2 to 2.0 K), while surface latent and sensible heat fluxes partially offset this cooling by 0.2 K(-0.2 to 0.5 K) and 0.2 K(-0.04 to 0.6 K),respectively. These effects are more pronounced in winter and spring in deforested regions. Furthermore, the separation of atmospheric feedbacks under clear-sky and cloudy conditions show that the cloud radiative effect only accounts for 0.1 K(-0.1 to 0.4 K), while the clear-sky surface downward radiation is a significant cooling factor, contributing up to-0.5 K(-1.2 to 0.004 K), particularly in summer. However, the consistency of these models in simulating the impact of surface latent heat flux and albedo on surface temperature in China in response to deforestation is somewhat poor, highlighting the need to improve these related processes.展开更多
In tomographic statics seismic data processing, it 1s crucial to cletermme an optimum base for a near-surface model. In this paper, we consider near-surface model base determination as a global optimum problem. Given ...In tomographic statics seismic data processing, it 1s crucial to cletermme an optimum base for a near-surface model. In this paper, we consider near-surface model base determination as a global optimum problem. Given information from uphole shooting and the first-arrival times from a surface seismic survey, we present a near-surface velocity model construction method based on a Monte-Carlo sampling scheme using a layered equivalent medium assumption. Compared with traditional least-squares first-arrival tomography, this scheme can delineate a clearer, weathering-layer base, resulting in a better implementation of damming correction. Examples using synthetic and field data are used to demonstrate the effectiveness of the proposed scheme.展开更多
In order to improve the efficiency of 3D near-surface velocity model building, we develop a layer-stripping method using seismic first-arrival times. The velocity model within a Common Mid-Point （CMP） gather is assu...In order to improve the efficiency of 3D near-surface velocity model building, we develop a layer-stripping method using seismic first-arrival times. The velocity model within a Common Mid-Point （CMP） gather is assumed to be stratified into thin layers, and the velocity of each layer var- ies linearly with depth. The thickness and velocity of the top layer are estimated using minimum-offset first-arrival data in a CMP gather. Then the top layer is stripped and the second layer becomes a new top layer. After removing the effect of the top layer from the former first-arrival data, the new first-arrival data are obtained and then used to estimate the parameters of the second layer. In this manner, the velocity model, being regarded as that at a CMP location, is built layer-by-layer from the top to the bottom. A 3D near-surface velocity model is then formed using the velocity models at all CMP locations. The tests on synthetic and observed seismic data show that the layer-stripping method can be used to build good near-surface velocity models for static correction, and its computation speed is approximately hundred times faster than that of grid tomography.展开更多
The results from a hybrid approach that combines a mesoscale meteorological model with a diagnostic model to produce high-resolution wind fields in complex coastal topography are evaluated.The diagnostic wind model(Ca...The results from a hybrid approach that combines a mesoscale meteorological model with a diagnostic model to produce high-resolution wind fields in complex coastal topography are evaluated.The diagnostic wind model(California Meteorological Model,CALMET) with 100-m horizontal spacing was driven with outputs from the Weather Research and Forecasting(WRF) model to obtain near-surface winds for the 1-year period from 12 September 2003 to 11 September 2004.Results were compared with wind observations at four sites.Traditional statistical scores,including correlation coefficients,standard deviations(SDs) and mean absolute errors(MAEs),indicate that the wind estimates from the WRF/CALMET modeling system are produced reasonably well.The correlation coefficients are relatively large,ranging from 0.5 to 0.7 for the zonal wind component and from 0.75 to 0.85 for the meridional wind component.MAEs for wind speed range from 1.5 to 2.0 m s-1 at 10 meters above ground level(AGL) and from 2.0 to 2.5 m s-1 at 60 m AGL.MAEs for wind direction range from 30 to 40 degrees at both levels.A spectral decomposition of the time series of wind speed shows positive impacts of CALMET in improving the mesoscale winds.Moreover,combining the CALMET model with WRF significantly improves the spatial variability of the simulated wind fields.It can be concluded that the WRF/CALMET modeling system is capable of providing a detailed near-surface wind field,but the physics in the diagnostic CALMET model needs to be further improved.展开更多
The seismoacoustic analysis method has broad potential applications to source parameter estimation for near-surface explosion events such as industrial explosions and terrorist attacks.In this study,current models wer...The seismoacoustic analysis method has broad potential applications to source parameter estimation for near-surface explosion events such as industrial explosions and terrorist attacks.In this study,current models were improved by modifying the acoustic model and adopting the Bayesian Markov-chain-Monte-Carlo inversion method.The source parameters of near-surface small-yield chemical explosions were analyzed via the improved seismoacoustic analysis model and by the estimation accuracy of seismoacoustic joint inversion.Estimation and analysis results showed that the improved seismoacoustic analysis model considered ground shock coupling and the impact of explosion products ejecting from the surface so that the improved acoustic impulse relation was more consistent with the measured data than the Ford impulse relation.It is suitable for deep-burial,shallow-burial,and near-surface aerial explosions.Furthermore,trade-off relationships were declined through the application of the improved model to source parameter inversion for near-surface small-yield chemical explosions,and source parameter estimation accuracy was improved.展开更多
The simulated Arctic sea ice drift and its relationship with the near-surface wind and surface ocean current during 1979-2014 in nine models from China that participated in the sixth phase of the Coupled Model Interco...The simulated Arctic sea ice drift and its relationship with the near-surface wind and surface ocean current during 1979-2014 in nine models from China that participated in the sixth phase of the Coupled Model Intercomparison Project(CMIP6)are examined by comparison with observational and reanalysis datasets.Most of the models reasonably represent the Beaufort Gyre(BG)and Transpolar Drift Stream(TDS)in the spatial patterns of their long-term mean sea ice drift,while the detailed location,extent,and strength of the BG and TDS vary among the models.About two-thirds of the models agree with the observation/reanalysis in the sense that the sea ice drift pattern is consistent with the near-surface wind pattern.About the same proportion of models shows that the sea ice drift pattern is consistent with the surface ocean current pattern.In the observation/reanalysis,however,the sea ice drift pattern does not match well with the surface ocean current pattern.All nine models missed the observational widespread sea ice drift speed acceleration across the Arctic.For the Arctic basin-wide spatial average,five of the nine models overestimate the Arctic long-term(1979-2014)mean sea ice drift speed in all months.Only FGOALS-g3 captures a significant sea ice drift speed increase from 1979 to 2014 both in spring and autumn.The increases are weaker than those in the observation.This evaluation helps assess the performance of the Arctic sea ice drift simulations in these CMIP6 models from China.展开更多
Gravity anomalies reflect the geophysical response to subsurface density structures.Traditionally,the terrain density is assumed to be a constant when calculating Bouguer gravity anomaly.But deviations from this assum...Gravity anomalies reflect the geophysical response to subsurface density structures.Traditionally,the terrain density is assumed to be a constant when calculating Bouguer gravity anomaly.But deviations from this assumption may induce high-frequency signals in the Bouguer gravity anomaly.This study introduces a Bayesian method for computing Bouguer gravity anomaly.It incorporates a smoothness prior for the Bouguer gravity anomaly and estimates near-surface density parameters to minimize the Akaike's Bayesian Information Criterion(ABIC)value.The effectiveness of this method is validated through theoretical model tests and calculations on two observed gravity profiles in Yunnan.The results indicate that the Bouguer gravity anomaly profiles estimated using the Bayesian approach need no extra filtering,exhibit correlations with the crustal structure along the profiles,and effectively reveal subsurface crustal density variations.Moreover,the obtained density variations offer insights into the near-surface rock density in different geological periods.Specifically,Cenozoic formations have a density of roughly 2.65–2.90 g·cm^(-3),Mesozoic formations 2.61-2.91 g·cm^(-3),and Paleozoic formations 2.61–2.92 g·cm^(-3).Magmatic rock regions generally show higher density values.Additionally,these estimated densities show a positive correlation with the global VS30 seismic velocity estimates,suggesting a new geophysical approach for seismic site classification.The findings of this study are significantly valuable for near-surface density estimation and Bouguer gravity anomaly calculations.展开更多
Wind speed extremes in the sub-Arctic realm of the North-East Pacific region were investigated through extreme value analysis of wind speed obtained from wind simulations of the COSMO-CLM (Consortium for Small-scale M...Wind speed extremes in the sub-Arctic realm of the North-East Pacific region were investigated through extreme value analysis of wind speed obtained from wind simulations of the COSMO-CLM (Consortium for Small-scale Modelling, climate version) mesoscale model, as well as using observed data. The analysis showed that the set of wind speed extremes obtained from observations is a mixture of two different subsets each neatly described by the Weibull distribution. Using special metaphoric terminology, they are labelled as “Black Swans” and “Dragons”. The “Dragons” are responsible for strongest extremes. It has been shown that both reanalysis and GCM (general circulation model) data have no “Dragons”. This means that such models underestimate wind speed maxima, and the important circulation process generating the anomalies is not simulated. The COSMO-CLM data have both “Black Swans” and “Dragons”. This evidence provides a clue that an atmospheric model with a detailed spatial resolution (we used in this work the data from domain with 13.2 km spatial resolution) does reproduce the special mechanism responsible for the generation of the largest wind speed extremes. However, a more thorough analysis shows that the differences in the parameters of the cumulative distribution functions are still significant. The ratio between the modelled Dragons and Black Swans can reach up to only 10%. It is much less than 30%, which was the level established for observations.展开更多
The regional Weather and Research Forecast (WRF) Model was run for the 2000-2010 period over the Northern Patagonia Icefield (NPI) with an horizontal resolution of 5 km. The regional model was initialized using the NC...The regional Weather and Research Forecast (WRF) Model was run for the 2000-2010 period over the Northern Patagonia Icefield (NPI) with an horizontal resolution of 5 km. The regional model was initialized using the NCEP/NCAR atmospheric Reanalysis database. The simulation results, centered over the NPI, were validated against the observed data from the local surface stations in order to evaluate the improvement of the model results due to its increased horizontal resolution with respect to the lower resolution from Global Climate Model simulations. Interest in the NPI is due to 1) the large body of frozen water exposed to the impact of the warming planet, 2) the scarce availability of observed meteorological and glaciological information in this large and remote icefield, and 3) the need to validate the model behavior in simulating the current climate and its variability in complex terrain. The results will shed light on the degree of confidence in simulating future climate scenarios in the region and also in similar geographical settings. Based on this study subsequent model runs will allow to model future climate changes in Patagonia, which is basic information for estimating glacier variations to be expected during this century.展开更多
Model evaluation using benchmark datasets is an important method to measure the capability of large language models(LLMs)in specific domains,and it is mainly used to assess the knowledge and reasoning abilities of LLM...Model evaluation using benchmark datasets is an important method to measure the capability of large language models(LLMs)in specific domains,and it is mainly used to assess the knowledge and reasoning abilities of LLMs.Therefore,in order to better assess the capability of LLMs in the agricultural domain,Agri-Eval was proposed as a benchmark for assessing the knowledge and reasoning ability of LLMs in agriculture.The assessment dataset used in Agri-Eval covered seven major disciplines in the agricultural domain:crop science,horticulture,plant protection,animal husbandry,forest science,aquaculture science,and grass science,and contained a total of 2283 questions.Among domestic general-purpose LLMs,DeepSeek R1 performed best with an accuracy rate of 75.49%.In the realm of international general-purpose LLMs,Gemini 2.0 pro exp 0205 standed out as the top performer,achieving an accuracy rate of 74.28%.As an LLMs in agriculture vertical,Shennong V2.0 outperformed all the LLMs in China,and the answer accuracy rate of agricultural knowledge exceeded that of all the existing general-purpose LLMs.The launch of Agri-Eval helped the LLM developers to comprehensively evaluate the model's capability in the field of agriculture through a variety of tasks and tests to promote the development of the LLMs in the field of agriculture.展开更多
In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asy...In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asymptotic stability of the trivial solution and the positive periodic solution.Finally,numerical simulations are presented to validate our results.Our results show that age-selective harvesting is more conducive to sustainable population survival than non-age-selective harvesting.展开更多
In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and cha...In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and change.Likewise,this period has seen a significant increase in our understanding of the physical processes and mechanisms that drive precipitation and its variability across different regions of Africa.By leveraging a large volume of climate model outputs,numerous studies have investigated the model representation of African precipitation as well as underlying physical processes.These studies have assessed whether the physical processes are well depicted and whether the models are fit for informing mitigation and adaptation strategies.This paper provides a review of the progress in precipitation simulation overAfrica in state-of-the-science climate models and discusses the major issues and challenges that remain.展开更多
Utilizing finite element analysis,the ballistic protection provided by a combination of perforated D-shaped and base armor plates,collectively referred to as radiator armor,is evaluated.ANSYS Explicit Dynamics is empl...Utilizing finite element analysis,the ballistic protection provided by a combination of perforated D-shaped and base armor plates,collectively referred to as radiator armor,is evaluated.ANSYS Explicit Dynamics is employed to simulate the ballistic impact of 7.62 mm armor-piercing projectiles on Aluminum AA5083-H116 and Steel Secure 500 armors,focusing on the evaluation of material deformation and penetration resistance at varying impact points.While the D-shaped armor plate is penetrated by the armor-piercing projectiles,the combination of the perforated D-shaped and base armor plates successfully halts penetration.A numerical model based on the finite element method is developed using software such as SolidWorks and ANSYS to analyze the interaction between radiator armor and bullet.The perforated design of radiator armor is to maintain airflow for radiator function,with hole sizes smaller than the bullet core diameter to protect radiator assemblies.Predictions are made regarding the brittle fracture resulting from the projectile core′s bending due to asymmetric impact,and the resulting fragments failed to penetrate the perforated base armor plate.Craters are formed on the surface of the perforated D-shaped armor plate due to the impact of projectile fragments.The numerical model accurately predicts hole growth and projectile penetration upon impact with the armor,demonstrating effective protection of the radiator assemblies by the radiator armor.展开更多
The National Geophysical Data Center(NGDC)of the United States has collected aeromagnetic data for input into a series of geomagnetic models to improve model resolution;however,in the Tibetan Plateau region,ground-bas...The National Geophysical Data Center(NGDC)of the United States has collected aeromagnetic data for input into a series of geomagnetic models to improve model resolution;however,in the Tibetan Plateau region,ground-based observations remain insufficient to clearly reflect the characteristics of the region’s lithospheric magnetism.In this study,we evaluate the lithospheric magnetism of the Tibetan Plateau by using a 3D surface spline model based on observations from>200 newly constructed repeat stations(portable stations)to determine the spatial distribution of plateau geomagnetism,as well as its correlation with the tectonic features of the region.We analyze the relationships between M≥5 earthquakes and lithospheric magnetic field variations on the Tibetan Plateau and identify regions susceptible to strong earthquakes.We compare the geomagnetic results with those from an enhanced magnetic model(EMM2015)developed by the NGDC and provide insights into improving lithospheric magnetic field calculations in the Tibetan Plateau region.Further research reveals that these magnetic anomalies exhibit distinct differences from the magnetic-seismic correlation mechanisms observed in other tectonic settings;here,they are governed primarily by the combined effects of compressional magnetism,thermal magnetism,and deep thermal stress.This study provides new evidence of geomagnetic anomalies on the Tibetan Plateau,interprets them physically,and demonstrates their potential for identifying seismic hazard zones on the Plateau.展开更多
Climate model prediction has been improved by enhancing model resolution as well as the implementation of sophisticated physical parameterization and refinement of data assimilation systems[section 6.1 in Wang et al.(...Climate model prediction has been improved by enhancing model resolution as well as the implementation of sophisticated physical parameterization and refinement of data assimilation systems[section 6.1 in Wang et al.(2025)].In relation to seasonal forecasting and climate projection in the East Asian summer monsoon season,proper simulation of the seasonal migration of rain bands by models is a challenging and limiting factor[section 7.1 in Wang et al.(2025)].展开更多
Oil spills continue to generate various issues and concerns regarding their effect and behavior in the marine environment,owing to the related potential for detrimental environmental,economic and social implications.I...Oil spills continue to generate various issues and concerns regarding their effect and behavior in the marine environment,owing to the related potential for detrimental environmental,economic and social implications.It is essential to have a solid understanding of the ways in which oil interacts with the water and the coastal ecosystems that are located nearby.This study proposes a simplified model for predicting the plume-like transport behavior of heavy Bunker C fuel oil discharging downward from an acutely-angled broken pipeline located on the water surface.The results show that the spill overall profile is articulated in three major flow areas.The first,is the source field,i.e.,a region near the origin of the initial jet,followed by the intermediate or transport field,namely,the region where the jet oil flow transitions into an underwater oil plume flow and starts to move horizontally,and finally,the far-field,where the oil re-surface and spreads onto the shore at a significant distance from the spill site.The behavior of the oil in the intermediate field is investigated using a simplified injection-type oil spill model capable of mimicking the undersea trapping and lateral migration of an oil plume originating from a negatively buoyant jet spill.A rectangular domain with proper boundary conditions is used to implement the model.The Projection approach is used to discretize a modified version of the Navier-Stokes equations in two dimensions.A benchmark fluid flow issue is used to verify the model and the results indicate a reasonable relationship between specific gravity and depth as well as agreement with the aerial data and a vertical temperature profile plot.展开更多
To investigate the influence of coarse aggregate parent rock properties on the elastic modulus of concrete,the mineralogical properties and stress-strain curves of granite and dolomite parent rocks,as well as the stre...To investigate the influence of coarse aggregate parent rock properties on the elastic modulus of concrete,the mineralogical properties and stress-strain curves of granite and dolomite parent rocks,as well as the strength and elastic modulus of mortar and concrete prepared with mechanism aggregates of the corresponding lithology,and the stress-strain curves of concrete were investigated.In this paper,a coarse aggregate and mortar matrix bonding assumption is proposed,and a prediction model for the elastic modulus of mortar is established by considering the lithology of the mechanism sand and the slurry components.An equivalent coarse aggregate elastic modulus model was established by considering factors such as coarse aggregate particle size,volume fraction,and mortar thickness between coarse aggregates.Based on the elastic modulus of the equivalent coarse aggregate and the remaining mortar,a prediction model for the elastic modulus of the two and three components of concrete in series and then in parallel was established,and the predicted values differed from the measured values within 10%.It is proposed that the coarse aggregate elastic modulus in highstrength concrete is the most critical factor affecting the elastic modulus of concrete,and as the coarse aggregate elastic modulus increases by 27.7%,the concrete elastic modulus increases by 19.5%.展开更多
Kinetic impact is the most practical planetary-defense technique,with momentum-transfer efficiency central to deflection design.We present a Monte Carlo photometric framework that couples ejecta sampling,dynamical evo...Kinetic impact is the most practical planetary-defense technique,with momentum-transfer efficiency central to deflection design.We present a Monte Carlo photometric framework that couples ejecta sampling,dynamical evolution,and image synthesis to compare directly with HST,LICIACube,ground-based and Lucy observations of the DART impact.Decomposing ejecta into(1)a highvelocity(~1600 m/s)plume exhibiting Na/K resonance,(2)a low-velocity(~1 m/s)conical component shaped by binary gravity and solar radiation pressure,and(3)meter-scale boulders,we quantify each component’s mass and momentum.Fitting photometric decay curves and morphological evolution yields size-velocity distributions and,via scaling laws,estimates of Dimorphos’bulk density,cratering parameters,and cohesive strength that agree with dynamical constraints.Photometric ejecta modeling therefore provides a robust route to constrain momentum enhancement and target properties,improving predictive capability for kinetic-deflection missions.展开更多
Customer churn is the rate at which customers discontinue doing business with a company over a given time period.It is an essential measure for businesses to monitor high churn rates,as they often indicate underlying ...Customer churn is the rate at which customers discontinue doing business with a company over a given time period.It is an essential measure for businesses to monitor high churn rates,as they often indicate underlying issues with services,products,or customer experience,resulting in considerable income loss.Prediction of customer churn is a crucial task aimed at retaining customers and maintaining revenue growth.Traditional machine learning(ML)models often struggle to capture complex temporal dependencies in client behavior data.To address this,an optimized deep learning(DL)approach using a Regularized Bidirectional Long Short-Term Memory(RBiLSTM)model is proposed to mitigate overfitting and improve generalization error.The model integrates dropout,L2-regularization,and early stopping to enhance predictive accuracy while preventing over-reliance on specific patterns.Moreover,this study investigates the effect of optimization techniques on boosting the training efficiency of the developed model.Experimental results on a recent public customer churn dataset demonstrate that the trained model outperforms the traditional ML models and some other DL models,such as Long Short-Term Memory(LSTM)and Deep Neural Network(DNN),in churn prediction performance and stability.The proposed approach achieves 96.1%accuracy,compared with LSTM and DNN,which attain 94.5%and 94.1%accuracy,respectively.These results confirm that the proposed approach can be used as a valuable tool for businesses to identify at-risk consumers proactively and implement targeted retention strategies.展开更多
文摘The static correction of a near-surface model may be improved by using travel time tomographic inversion.We discuss unfavorable factors in the inversion of surface seismic waves that have been analyzed by the first break.These factors show that sources and geophones arranged on the surface,or close to the surface,give a first break that only includes the direct wave and the up going wave from the down going to up going transition.These up going waves have weak directivity when they arrive at a geophone and so the rays passing through the grids have small directional differences and a narrow azimuth.Drawing lessons from the advantages of Vertical Seismic Profiling(VSP) acquisition mode we describe a pseudo well-surface simultaneous travel time tomographic inversion of a near-surface model.The well depth should be increased in the surface seismic study to produce a pure up going wave,to enhance the verticality of the rays and to increase the azimuth and shorten path length of the rays.Simulations of the effect of well depth on a pseudo well-surface simultaneous travel time tomographic inversion model are reported.The results show that the static corrections are improved significantly when the well depth extends below the weathered or sub-weathered layers.The root mean square error of the statics is 1.14 or 0.93 ms for these two situations,respectively.
基金supported by the National Natural Science Foundation of China (Grant No.42305041)the Natural Science Foundation of Hubei Province of China (Grant No.2020CFB331)supported by the National Key Scientific and Technological Infrastructure project “Earth System Numerical Simulation Facility” (Earth Lab)。
文摘Global deforestation has been recognized as an important factor influencing climate change over the past century.However, uncertainties remain regarding its biophysical impacts on temperature across China. Utilizing monthly data from eight global climate models of the Land Use Model Intercomparison Project, a multimodel comparison was conducted to quantitatively analyze the biophysical impacts of global deforestation on near-surface air temperature in China, using a surface energy balance decomposition method. Results show a 38%(29% to 45%) reduction in forest cover in China(ensemble mean and range across eight models) relative to pre-industrial levels, and an annual cooling of 0.6 K(0.05 to1.4 K) accompanied by global deforestation. Notably, surface albedo causes a cooling effect of 0.6 K(0.2 to 2.0 K), while surface latent and sensible heat fluxes partially offset this cooling by 0.2 K(-0.2 to 0.5 K) and 0.2 K(-0.04 to 0.6 K),respectively. These effects are more pronounced in winter and spring in deforested regions. Furthermore, the separation of atmospheric feedbacks under clear-sky and cloudy conditions show that the cloud radiative effect only accounts for 0.1 K(-0.1 to 0.4 K), while the clear-sky surface downward radiation is a significant cooling factor, contributing up to-0.5 K(-1.2 to 0.004 K), particularly in summer. However, the consistency of these models in simulating the impact of surface latent heat flux and albedo on surface temperature in China in response to deforestation is somewhat poor, highlighting the need to improve these related processes.
基金funded by the National Science VIP specialized project of China(Grant No.2011ZX05025-001-03)by the National Science Foundation of China(Grant No.41274117)
文摘In tomographic statics seismic data processing, it 1s crucial to cletermme an optimum base for a near-surface model. In this paper, we consider near-surface model base determination as a global optimum problem. Given information from uphole shooting and the first-arrival times from a surface seismic survey, we present a near-surface velocity model construction method based on a Monte-Carlo sampling scheme using a layered equivalent medium assumption. Compared with traditional least-squares first-arrival tomography, this scheme can delineate a clearer, weathering-layer base, resulting in a better implementation of damming correction. Examples using synthetic and field data are used to demonstrate the effectiveness of the proposed scheme.
基金supported by the National Natural Science Foundation of China(Nos.41230318,41074077)the Specialized Research Fund for the Doctoral Program of Higher Education(No.20130132110023)the Fundamental Research Funds for the Central Universities of China(No.201413004)
文摘In order to improve the efficiency of 3D near-surface velocity model building, we develop a layer-stripping method using seismic first-arrival times. The velocity model within a Common Mid-Point （CMP） gather is assumed to be stratified into thin layers, and the velocity of each layer var- ies linearly with depth. The thickness and velocity of the top layer are estimated using minimum-offset first-arrival data in a CMP gather. Then the top layer is stripped and the second layer becomes a new top layer. After removing the effect of the top layer from the former first-arrival data, the new first-arrival data are obtained and then used to estimate the parameters of the second layer. In this manner, the velocity model, being regarded as that at a CMP location, is built layer-by-layer from the top to the bottom. A 3D near-surface velocity model is then formed using the velocity models at all CMP locations. The tests on synthetic and observed seismic data show that the layer-stripping method can be used to build good near-surface velocity models for static correction, and its computation speed is approximately hundred times faster than that of grid tomography.
基金National Public Benefit Research Foundation of China (2008416048GYHY201006035)
文摘The results from a hybrid approach that combines a mesoscale meteorological model with a diagnostic model to produce high-resolution wind fields in complex coastal topography are evaluated.The diagnostic wind model(California Meteorological Model,CALMET) with 100-m horizontal spacing was driven with outputs from the Weather Research and Forecasting(WRF) model to obtain near-surface winds for the 1-year period from 12 September 2003 to 11 September 2004.Results were compared with wind observations at four sites.Traditional statistical scores,including correlation coefficients,standard deviations(SDs) and mean absolute errors(MAEs),indicate that the wind estimates from the WRF/CALMET modeling system are produced reasonably well.The correlation coefficients are relatively large,ranging from 0.5 to 0.7 for the zonal wind component and from 0.75 to 0.85 for the meridional wind component.MAEs for wind speed range from 1.5 to 2.0 m s-1 at 10 meters above ground level(AGL) and from 2.0 to 2.5 m s-1 at 60 m AGL.MAEs for wind direction range from 30 to 40 degrees at both levels.A spectral decomposition of the time series of wind speed shows positive impacts of CALMET in improving the mesoscale winds.Moreover,combining the CALMET model with WRF significantly improves the spatial variability of the simulated wind fields.It can be concluded that the WRF/CALMET modeling system is capable of providing a detailed near-surface wind field,but the physics in the diagnostic CALMET model needs to be further improved.
基金the National Natural Science Foundation of China(No.12072290).
文摘The seismoacoustic analysis method has broad potential applications to source parameter estimation for near-surface explosion events such as industrial explosions and terrorist attacks.In this study,current models were improved by modifying the acoustic model and adopting the Bayesian Markov-chain-Monte-Carlo inversion method.The source parameters of near-surface small-yield chemical explosions were analyzed via the improved seismoacoustic analysis model and by the estimation accuracy of seismoacoustic joint inversion.Estimation and analysis results showed that the improved seismoacoustic analysis model considered ground shock coupling and the impact of explosion products ejecting from the surface so that the improved acoustic impulse relation was more consistent with the measured data than the Ford impulse relation.It is suitable for deep-burial,shallow-burial,and near-surface aerial explosions.Furthermore,trade-off relationships were declined through the application of the improved model to source parameter inversion for near-surface small-yield chemical explosions,and source parameter estimation accuracy was improved.
基金supported by the National Key R&D Program of China(Grant No.2018YFA0605904)the National Natural Science Foundation of China(Grant No.41701411).
文摘The simulated Arctic sea ice drift and its relationship with the near-surface wind and surface ocean current during 1979-2014 in nine models from China that participated in the sixth phase of the Coupled Model Intercomparison Project(CMIP6)are examined by comparison with observational and reanalysis datasets.Most of the models reasonably represent the Beaufort Gyre(BG)and Transpolar Drift Stream(TDS)in the spatial patterns of their long-term mean sea ice drift,while the detailed location,extent,and strength of the BG and TDS vary among the models.About two-thirds of the models agree with the observation/reanalysis in the sense that the sea ice drift pattern is consistent with the near-surface wind pattern.About the same proportion of models shows that the sea ice drift pattern is consistent with the surface ocean current pattern.In the observation/reanalysis,however,the sea ice drift pattern does not match well with the surface ocean current pattern.All nine models missed the observational widespread sea ice drift speed acceleration across the Arctic.For the Arctic basin-wide spatial average,five of the nine models overestimate the Arctic long-term(1979-2014)mean sea ice drift speed in all months.Only FGOALS-g3 captures a significant sea ice drift speed increase from 1979 to 2014 both in spring and autumn.The increases are weaker than those in the observation.This evaluation helps assess the performance of the Arctic sea ice drift simulations in these CMIP6 models from China.
基金supported by the National Key Research and Development Program of China(2023YFE0101800)the National Natural Science Foundation of China(Young Scientists Fund,42450233,General Program,42474120)+3 种基金the Basic Scientific Research Fund Special Project of the Institute of Geophysics,China Earthquake Administration(DQJB24B20)the Natural Science Foundation of Beijing(Grant No.1242033)the Natural Science Foundation of Tianjin(25JCQNJC00540)the National Science and Technology Major Project for Deep Earth Probe and Mineral Resources Exploration(2024ZD1002700).
文摘Gravity anomalies reflect the geophysical response to subsurface density structures.Traditionally,the terrain density is assumed to be a constant when calculating Bouguer gravity anomaly.But deviations from this assumption may induce high-frequency signals in the Bouguer gravity anomaly.This study introduces a Bayesian method for computing Bouguer gravity anomaly.It incorporates a smoothness prior for the Bouguer gravity anomaly and estimates near-surface density parameters to minimize the Akaike's Bayesian Information Criterion(ABIC)value.The effectiveness of this method is validated through theoretical model tests and calculations on two observed gravity profiles in Yunnan.The results indicate that the Bouguer gravity anomaly profiles estimated using the Bayesian approach need no extra filtering,exhibit correlations with the crustal structure along the profiles,and effectively reveal subsurface crustal density variations.Moreover,the obtained density variations offer insights into the near-surface rock density in different geological periods.Specifically,Cenozoic formations have a density of roughly 2.65–2.90 g·cm^(-3),Mesozoic formations 2.61-2.91 g·cm^(-3),and Paleozoic formations 2.61–2.92 g·cm^(-3).Magmatic rock regions generally show higher density values.Additionally,these estimated densities show a positive correlation with the global VS30 seismic velocity estimates,suggesting a new geophysical approach for seismic site classification.The findings of this study are significantly valuable for near-surface density estimation and Bouguer gravity anomaly calculations.
文摘Wind speed extremes in the sub-Arctic realm of the North-East Pacific region were investigated through extreme value analysis of wind speed obtained from wind simulations of the COSMO-CLM (Consortium for Small-scale Modelling, climate version) mesoscale model, as well as using observed data. The analysis showed that the set of wind speed extremes obtained from observations is a mixture of two different subsets each neatly described by the Weibull distribution. Using special metaphoric terminology, they are labelled as “Black Swans” and “Dragons”. The “Dragons” are responsible for strongest extremes. It has been shown that both reanalysis and GCM (general circulation model) data have no “Dragons”. This means that such models underestimate wind speed maxima, and the important circulation process generating the anomalies is not simulated. The COSMO-CLM data have both “Black Swans” and “Dragons”. This evidence provides a clue that an atmospheric model with a detailed spatial resolution (we used in this work the data from domain with 13.2 km spatial resolution) does reproduce the special mechanism responsible for the generation of the largest wind speed extremes. However, a more thorough analysis shows that the differences in the parameters of the cumulative distribution functions are still significant. The ratio between the modelled Dragons and Black Swans can reach up to only 10%. It is much less than 30%, which was the level established for observations.
文摘The regional Weather and Research Forecast (WRF) Model was run for the 2000-2010 period over the Northern Patagonia Icefield (NPI) with an horizontal resolution of 5 km. The regional model was initialized using the NCEP/NCAR atmospheric Reanalysis database. The simulation results, centered over the NPI, were validated against the observed data from the local surface stations in order to evaluate the improvement of the model results due to its increased horizontal resolution with respect to the lower resolution from Global Climate Model simulations. Interest in the NPI is due to 1) the large body of frozen water exposed to the impact of the warming planet, 2) the scarce availability of observed meteorological and glaciological information in this large and remote icefield, and 3) the need to validate the model behavior in simulating the current climate and its variability in complex terrain. The results will shed light on the degree of confidence in simulating future climate scenarios in the region and also in similar geographical settings. Based on this study subsequent model runs will allow to model future climate changes in Patagonia, which is basic information for estimating glacier variations to be expected during this century.
文摘Model evaluation using benchmark datasets is an important method to measure the capability of large language models(LLMs)in specific domains,and it is mainly used to assess the knowledge and reasoning abilities of LLMs.Therefore,in order to better assess the capability of LLMs in the agricultural domain,Agri-Eval was proposed as a benchmark for assessing the knowledge and reasoning ability of LLMs in agriculture.The assessment dataset used in Agri-Eval covered seven major disciplines in the agricultural domain:crop science,horticulture,plant protection,animal husbandry,forest science,aquaculture science,and grass science,and contained a total of 2283 questions.Among domestic general-purpose LLMs,DeepSeek R1 performed best with an accuracy rate of 75.49%.In the realm of international general-purpose LLMs,Gemini 2.0 pro exp 0205 standed out as the top performer,achieving an accuracy rate of 74.28%.As an LLMs in agriculture vertical,Shennong V2.0 outperformed all the LLMs in China,and the answer accuracy rate of agricultural knowledge exceeded that of all the existing general-purpose LLMs.The launch of Agri-Eval helped the LLM developers to comprehensively evaluate the model's capability in the field of agriculture through a variety of tasks and tests to promote the development of the LLMs in the field of agriculture.
基金Supported by the National Natural Science Foundation of China(12261018)Universities Key Laboratory of Mathematical Modeling and Data Mining in Guizhou Province(2023013)。
文摘In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asymptotic stability of the trivial solution and the positive periodic solution.Finally,numerical simulations are presented to validate our results.Our results show that age-selective harvesting is more conducive to sustainable population survival than non-age-selective harvesting.
基金the World Climate Research Programme(WCRP),Climate Variability and Predictability(CLIVAR),and Global Energy and Water Exchanges(GEWEX)for facilitating the coordination of African monsoon researchsupport from the Center for Earth System Modeling,Analysis,and Data at the Pennsylvania State Universitythe support of the Office of Science of the U.S.Department of Energy Biological and Environmental Research as part of the Regional&Global Model Analysis(RGMA)program area。
文摘In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and change.Likewise,this period has seen a significant increase in our understanding of the physical processes and mechanisms that drive precipitation and its variability across different regions of Africa.By leveraging a large volume of climate model outputs,numerous studies have investigated the model representation of African precipitation as well as underlying physical processes.These studies have assessed whether the physical processes are well depicted and whether the models are fit for informing mitigation and adaptation strategies.This paper provides a review of the progress in precipitation simulation overAfrica in state-of-the-science climate models and discusses the major issues and challenges that remain.
文摘Utilizing finite element analysis,the ballistic protection provided by a combination of perforated D-shaped and base armor plates,collectively referred to as radiator armor,is evaluated.ANSYS Explicit Dynamics is employed to simulate the ballistic impact of 7.62 mm armor-piercing projectiles on Aluminum AA5083-H116 and Steel Secure 500 armors,focusing on the evaluation of material deformation and penetration resistance at varying impact points.While the D-shaped armor plate is penetrated by the armor-piercing projectiles,the combination of the perforated D-shaped and base armor plates successfully halts penetration.A numerical model based on the finite element method is developed using software such as SolidWorks and ANSYS to analyze the interaction between radiator armor and bullet.The perforated design of radiator armor is to maintain airflow for radiator function,with hole sizes smaller than the bullet core diameter to protect radiator assemblies.Predictions are made regarding the brittle fracture resulting from the projectile core′s bending due to asymmetric impact,and the resulting fragments failed to penetrate the perforated base armor plate.Craters are formed on the surface of the perforated D-shaped armor plate due to the impact of projectile fragments.The numerical model accurately predicts hole growth and projectile penetration upon impact with the armor,demonstrating effective protection of the radiator assemblies by the radiator armor.
基金supported by the CAS Pioneer Hundred Talents Program and Second Tibetan Plateau Scientific Expedition Research Program(2019QZKK0708)as well as the Basic Research Program of Qinghai Province:Lithospheric Geomagnetic Field of the Qinghai‒Tibet Plateau and the Relationship with Strong Earthquakes(2021-ZJ-969Q).
文摘The National Geophysical Data Center(NGDC)of the United States has collected aeromagnetic data for input into a series of geomagnetic models to improve model resolution;however,in the Tibetan Plateau region,ground-based observations remain insufficient to clearly reflect the characteristics of the region’s lithospheric magnetism.In this study,we evaluate the lithospheric magnetism of the Tibetan Plateau by using a 3D surface spline model based on observations from>200 newly constructed repeat stations(portable stations)to determine the spatial distribution of plateau geomagnetism,as well as its correlation with the tectonic features of the region.We analyze the relationships between M≥5 earthquakes and lithospheric magnetic field variations on the Tibetan Plateau and identify regions susceptible to strong earthquakes.We compare the geomagnetic results with those from an enhanced magnetic model(EMM2015)developed by the NGDC and provide insights into improving lithospheric magnetic field calculations in the Tibetan Plateau region.Further research reveals that these magnetic anomalies exhibit distinct differences from the magnetic-seismic correlation mechanisms observed in other tectonic settings;here,they are governed primarily by the combined effects of compressional magnetism,thermal magnetism,and deep thermal stress.This study provides new evidence of geomagnetic anomalies on the Tibetan Plateau,interprets them physically,and demonstrates their potential for identifying seismic hazard zones on the Plateau.
文摘Climate model prediction has been improved by enhancing model resolution as well as the implementation of sophisticated physical parameterization and refinement of data assimilation systems[section 6.1 in Wang et al.(2025)].In relation to seasonal forecasting and climate projection in the East Asian summer monsoon season,proper simulation of the seasonal migration of rain bands by models is a challenging and limiting factor[section 7.1 in Wang et al.(2025)].
文摘Oil spills continue to generate various issues and concerns regarding their effect and behavior in the marine environment,owing to the related potential for detrimental environmental,economic and social implications.It is essential to have a solid understanding of the ways in which oil interacts with the water and the coastal ecosystems that are located nearby.This study proposes a simplified model for predicting the plume-like transport behavior of heavy Bunker C fuel oil discharging downward from an acutely-angled broken pipeline located on the water surface.The results show that the spill overall profile is articulated in three major flow areas.The first,is the source field,i.e.,a region near the origin of the initial jet,followed by the intermediate or transport field,namely,the region where the jet oil flow transitions into an underwater oil plume flow and starts to move horizontally,and finally,the far-field,where the oil re-surface and spreads onto the shore at a significant distance from the spill site.The behavior of the oil in the intermediate field is investigated using a simplified injection-type oil spill model capable of mimicking the undersea trapping and lateral migration of an oil plume originating from a negatively buoyant jet spill.A rectangular domain with proper boundary conditions is used to implement the model.The Projection approach is used to discretize a modified version of the Navier-Stokes equations in two dimensions.A benchmark fluid flow issue is used to verify the model and the results indicate a reasonable relationship between specific gravity and depth as well as agreement with the aerial data and a vertical temperature profile plot.
基金Funded by State Railway Administration Research Project(No.2023JS007)National Natural Science Foundation of China(No.52438002)+1 种基金Research and Development Programs for Science and Technology of China Railways Corporation(No.J2023G003)New Cornerstone Science Foundation through the XPLORER PRIZE。
文摘To investigate the influence of coarse aggregate parent rock properties on the elastic modulus of concrete,the mineralogical properties and stress-strain curves of granite and dolomite parent rocks,as well as the strength and elastic modulus of mortar and concrete prepared with mechanism aggregates of the corresponding lithology,and the stress-strain curves of concrete were investigated.In this paper,a coarse aggregate and mortar matrix bonding assumption is proposed,and a prediction model for the elastic modulus of mortar is established by considering the lithology of the mechanism sand and the slurry components.An equivalent coarse aggregate elastic modulus model was established by considering factors such as coarse aggregate particle size,volume fraction,and mortar thickness between coarse aggregates.Based on the elastic modulus of the equivalent coarse aggregate and the remaining mortar,a prediction model for the elastic modulus of the two and three components of concrete in series and then in parallel was established,and the predicted values differed from the measured values within 10%.It is proposed that the coarse aggregate elastic modulus in highstrength concrete is the most critical factor affecting the elastic modulus of concrete,and as the coarse aggregate elastic modulus increases by 27.7%,the concrete elastic modulus increases by 19.5%.
基金supported by the National Natural Science Foundation of China(Grant No.12272018)the National Key Basic Research Project(2022JCJQZD20600).
文摘Kinetic impact is the most practical planetary-defense technique,with momentum-transfer efficiency central to deflection design.We present a Monte Carlo photometric framework that couples ejecta sampling,dynamical evolution,and image synthesis to compare directly with HST,LICIACube,ground-based and Lucy observations of the DART impact.Decomposing ejecta into(1)a highvelocity(~1600 m/s)plume exhibiting Na/K resonance,(2)a low-velocity(~1 m/s)conical component shaped by binary gravity and solar radiation pressure,and(3)meter-scale boulders,we quantify each component’s mass and momentum.Fitting photometric decay curves and morphological evolution yields size-velocity distributions and,via scaling laws,estimates of Dimorphos’bulk density,cratering parameters,and cohesive strength that agree with dynamical constraints.Photometric ejecta modeling therefore provides a robust route to constrain momentum enhancement and target properties,improving predictive capability for kinetic-deflection missions.
文摘Customer churn is the rate at which customers discontinue doing business with a company over a given time period.It is an essential measure for businesses to monitor high churn rates,as they often indicate underlying issues with services,products,or customer experience,resulting in considerable income loss.Prediction of customer churn is a crucial task aimed at retaining customers and maintaining revenue growth.Traditional machine learning(ML)models often struggle to capture complex temporal dependencies in client behavior data.To address this,an optimized deep learning(DL)approach using a Regularized Bidirectional Long Short-Term Memory(RBiLSTM)model is proposed to mitigate overfitting and improve generalization error.The model integrates dropout,L2-regularization,and early stopping to enhance predictive accuracy while preventing over-reliance on specific patterns.Moreover,this study investigates the effect of optimization techniques on boosting the training efficiency of the developed model.Experimental results on a recent public customer churn dataset demonstrate that the trained model outperforms the traditional ML models and some other DL models,such as Long Short-Term Memory(LSTM)and Deep Neural Network(DNN),in churn prediction performance and stability.The proposed approach achieves 96.1%accuracy,compared with LSTM and DNN,which attain 94.5%and 94.1%accuracy,respectively.These results confirm that the proposed approach can be used as a valuable tool for businesses to identify at-risk consumers proactively and implement targeted retention strategies.
