High-resolution modeling approach is increasingly being considered as a necessary step for improving the monitoring and predictions of regional air quality. This is especially true for highly urbanized region with com...High-resolution modeling approach is increasingly being considered as a necessary step for improving the monitoring and predictions of regional air quality. This is especially true for highly urbanized region with complex terrain and land-use. This study uses Community Multiscale Air Quality （CMAQ） model coupled with MM5 mesoscale model for a comprehensive analysis to assess the suitability of such high-resolution modeling system in predicting ozone air quality in the complex terrains of Osaka, Japan. The 1-km and 3-kin grid domains were nested inside a 9-km domain and the domain with 1-km grid covered the Osaka region. High-resolution Grid Point Value-Mesoscale Model （GPV-MSM） data were used after suitable validation. The simulated ozone concentrations were validated and evaluated using statistical metrics using performance criteria set for ozone. Daily maxima of ozone were found better simulated by the 1-krn grid domain than the coarser 9-km and 3-km domains, with the maximum improvement in the mean absolute gross error about 3 ppbv. In addition, 1-km grid results fared better than other grids at most of the observation stations that showed noticeable differences in gross error as well as correlation. These results amply justify the use of the integrated high-resolution MM5-CMAQ modeling system in the highly urbanized region, such as the Osaka region, which has complex terrain and land-use.展开更多
Mesoamerica and the Caribbean are low-latitude regions at risk for the effects of climate change. Global climate models provide large-scale assessment of climate drivers, but, at a horizontal resolution of 100 km, can...Mesoamerica and the Caribbean are low-latitude regions at risk for the effects of climate change. Global climate models provide large-scale assessment of climate drivers, but, at a horizontal resolution of 100 km, cannot resolve the effects of topography and land use as they impact the local temperature and precipitation that are keys to climate impacts. We developed a robust dynamical downscaling strategy that used the WRF regional climate model to downscale at 4 - 12 km resolution GCM results. Model verification demonstrates the need for such resolution of topography in order to properly simulate temperatures. Precipitation is more difficult to evaluate, being highly variable in time and space. Overall, a 36 km resolution is inadequate;12 km appears reasonable, especially in regions of low topography, but the 4 km resolution provides the best match with observations. This represents a tradeoff between model resolution and the computational effort needed to make simulations. A key goal is to provide climate change specialists in each country with the information they need to evaluate possible future climate change impacts.展开更多
Under global warming,extreme weather events and air pollution are becoming increasingly critical challenges.Both pose serious risks to human health,economies,and societal stability,and their complex interactions can f...Under global warming,extreme weather events and air pollution are becoming increasingly critical challenges.Both pose serious risks to human health,economies,and societal stability,and their complex interactions can further amplify these impacts.Numerical models are essential tools for studying these phenomena;however,traditional low-resolution Earth system models often fail to accurately capture the dynamics of extreme weather and air pollution.This limitation hinders our mechanistic understanding,reduces the reliability of future projections,and constrains the development of effective adaptation strategies.Dynamical downscaling—an approach that uses highresolution regional models nested within global models—offers a partial solution.However,this method inherits biases from the parent global models and often fails to adequately represent multi-scale and cross-sphere interactions involving the atmosphere,land,and oceans.These shortcomings underscore the growing need for developing and applying high-resolution Earth system models that can more comprehensively and accurately depict land-sea-atmosphere interactions,including heat and material exchanges and their spatial heterogeneity.This article explores the current challenges,recent advances,and future opportunities in understanding the interplay between extreme weather events and air pollution,with a focus on the critical role of high-resolution modeling.展开更多
Continental silicate weathering acts as a crucial negative feedback mechanism for removing atmospheric CO_(2) and maintaining Earth's long-term climate stability.However,quantifying continental silicate weathering...Continental silicate weathering acts as a crucial negative feedback mechanism for removing atmospheric CO_(2) and maintaining Earth's long-term climate stability.However,quantifying continental silicate weathering rates and fluxes continues to pose a fundamental challenge in Earth system science.This study utilizes the GEOCLIM carbon cycle model,which integrates modern high-resolution(0.1°×0.1°)datasets on surface temperature,runoff,topography,and lithology to model the spatial distribution of global silicate weathering fluxes.Results indicate a strong correlation between modeled basin-scale outputs and hydrological observations,with weathering rates falling within consistent error margins.Silicate weathering fluxes exhibit distinct latitudinal patterns,with the highest values concentrated within 30°of the equator,accounting for 76.9%of the global total.Continental contributions differ significantly,with Asian river basins representing 36.9%of global fluxes,primarily from Southeast Asia(17.4%),South Asia(8.2%),and East Asia(6.6%).They are followed by South America(29.2%)and Africa(21.7%).Tectonically active regions contribute 21.9%of global silicate weathering,while stable regions account for 72.6%.Multivariate regression analyses using RF and XGBoost machine learning algorithms identify runoff as the primary controlling factor of weathering on a global scale.Weathering in stable regions is jointly regulated by runoff and erosion rates,whereas temperature is the prevailing factor in tectonically active zones.The GEOCLIM model offers a robust framework for quantifying continental weathering processes.Future studies should incorporate organic carbon oxidation,burial,and sulfide oxidation dynamics to clarify carbon cycle interactions and reveal climate-dependent mechanisms for weathering responses and feedback.展开更多
Accurately counting dense objects in complex and diverse backgrounds is a significant challenge in computer vision,with applications ranging from crowd counting to various other object counting tasks.To address this,w...Accurately counting dense objects in complex and diverse backgrounds is a significant challenge in computer vision,with applications ranging from crowd counting to various other object counting tasks.To address this,we propose HUANNet(High-Resolution Unified Attention Network),a convolutional neural network designed to capture both local features and rich semantic information through a high-resolution representation learning framework,while optimizing computational distribution across parallel branches.HUANNet introduces three core modules:the High-Resolution Attention Module(HRAM),which enhances feature extraction by optimizing multiresolution feature fusion;the Unified Multi-Scale Attention Module(UMAM),which integrates spatial,channel,and convolutional kernel information through an attention mechanism applied across multiple levels of the network;and the Grid-Assisted Point Matching Module(GPMM),which stabilizes and improves point-to-point matching by leveraging grid-based mechanisms.Extensive experiments show that HUANNet achieves competitive results on the ShanghaiTech Part A/B crowd counting datasets and sets new state-of-the-art performance on dense object counting datasets such as CARPK and XRAY-IECCD,demonstrating the effectiveness and versatility of HUANNet.展开更多
Background:Diabetic foot,a severe complication of diabetes,is characterized by chronic refractory wounds.Sanhuang Oil,a topical herbal formula,demonstrates significant therapeutic effects including antibacterial,anti-...Background:Diabetic foot,a severe complication of diabetes,is characterized by chronic refractory wounds.Sanhuang Oil,a topical herbal formula,demonstrates significant therapeutic effects including antibacterial,anti-inflammatory,and immunomodulatory activities.However,its active constituents and mechanisms of action against diabetic foot remain to be elucidated.Methods:In this study,the chemical constituents of Sanhuang Oil were identified using UPLC-QE-Orbitrap-MS.Subsequently,the mechanism by which Sanhuang Oil promotes diabetic foot ulcer healing was predicted by integrating network pharmacology and molecular docking.Additionally,diabetic mouse model was established in ICR mice using a combination of a high-fat diet(HFD)and streptozotocin(STZ)chemical induction.A full-thickness skin defect was created on the dorsum of the mice.Wound healing and the healing rate were observed following Sanhuang Oil intervention.The mechanism underlying Sanhuang Oil’s promotion of diabetic ulcer healing was further investigated using transcriptomics and histopathological examination(H&E staining).Results:A total of 97 active ingredients were identified from Sanhuang Oil.Network pharmacology analysis predicted 543 common targets,and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis identified 203 relevant pathways.Molecular docking further confirmed high binding affinity(binding energy≤−5.0 kcal/mol)between specific active components in Sanhuang Oil(e.g.,coptisine,phellodendrine,baicalein)and key targets associated with diabetic foot ulcers(e.g.,EGFR,AKT1,STAT3).In vivo experimental results demonstrated that the wound healing rate was significantly higher in Sanhuang Oil-treated groups compared to the model group(P<0.001).HE staining revealed that the high-dose Sanhuang Oil group exhibited more pronounced epithelial tissue coverage over the wound,reduced inflammatory cell infiltration,and increased collagen deposition and fibroblast proliferation.transcriptomic analysis identified Pdk4,Ttn,Csrp3,Actn2,Myoz2,Tnnc2,Myod1,Myog,Myot,and Myf6 as key regulatory proteins involved in promoting wound healing.Conclusion:Sanhuang Oil promotes wound healing in diabetic ulcer mice,potentially by mitigating inflammation and regulating key targets such as Pdk4 to enhance fibroblast function.These findings provide novel insights into the multi-target,multi-pathway mechanism of Sanhuang Oil for treating diabetic foot ulcers.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
To address the issues of frequent identity switches(IDs)and degraded identification accuracy in multi object tracking(MOT)under complex occlusion scenarios,this study proposes an occlusion-robust tracking framework ba...To address the issues of frequent identity switches(IDs)and degraded identification accuracy in multi object tracking(MOT)under complex occlusion scenarios,this study proposes an occlusion-robust tracking framework based on face-pedestrian joint feature modeling.By constructing a joint tracking model centered on“intra-class independent tracking+cross-category dynamic binding”,designing a multi-modal matching metric with spatio-temporal and appearance constraints,and innovatively introducing a cross-category feature mutual verification mechanism and a dual matching strategy,this work effectively resolves performance degradation in traditional single-category tracking methods caused by short-term occlusion,cross-camera tracking,and crowded environments.Experiments on the Chokepoint_Face_Pedestrian_Track test set demonstrate that in complex scenes,the proposed method improves Face-Pedestrian Matching F1 area under the curve(F1 AUC)by approximately 4 to 43 percentage points compared to several traditional methods.The joint tracking model achieves overall performance metrics of IDF1:85.1825%and MOTA:86.5956%,representing improvements of 0.91 and 0.06 percentage points,respectively,over the baseline model.Ablation studies confirm the effectiveness of key modules such as the Intersection over Area(IoA)/Intersection over Union(IoU)joint metric and dynamic threshold adjustment,validating the significant role of the cross-category identity matching mechanism in enhancing tracking stability.Our_model shows a 16.7%frame per second(FPS)drop vs.fairness of detection and re-identification in multiple object tracking(FairMOT),with its cross-category binding module adding aboute 10%overhead,yet maintains near-real-time performance for essential face-pedestrian tracking at small resolutions.展开更多
In weather forecasting,generating atmospheric variables for regions with complex topography,such as the Andean regions with peaks reaching 6500 m above sea level,poses significant challenges.Traditional regional clima...In weather forecasting,generating atmospheric variables for regions with complex topography,such as the Andean regions with peaks reaching 6500 m above sea level,poses significant challenges.Traditional regional climate models often struggle to accurately represent the atmospheric behavior in such areas.Furthermore,the capability to produce high spatio-temporal resolution data(less than 27 km and hourly)is limited to a few institutions globally due to the substantial computational resources required.This study presents the results of atmospheric data generated using a new type of artificial intelligence(AI)models,aimed to reduce the computational cost of generating downscaled climate data using climate regional models like the Weather Research and Forecasting(WRF)model over the Andes.The WRF model was selected for this comparison due to its frequent use in simulating atmospheric variables in the Andes.Our results demonstrate a higher downscaling performance for the four target weather variables studied(temperature,relative humidity,zonal and meridional wind)over coastal,mountain,and jungle regions.Moreover,this AI model offers several advantages,including lower computational costs compared to dynamic models like WRF and continuous improvement potential with additional training data.展开更多
A down-scaled operational oceanographic system is developed for the coastal waters of Korea using a re- gional ocean modeling system （ROMS）. The operational oceanographic modeling system consists of at- mospheric an...A down-scaled operational oceanographic system is developed for the coastal waters of Korea using a re- gional ocean modeling system （ROMS）. The operational oceanographic modeling system consists of at- mospheric and hydrodynamic models. The hydrodynamic model, ROMS, is coupled with wave, sediment transport, and water quality modules. The system forecasts the predicted results twice a day on a 72 h basis, including sea surface elevation, currents, temperature, salinity, storm surge height, and wave information for the coastal waters of Korea. The predicted results are exported to the web-GIS-based coastal informa- tion system for real-time dissemination to the public and validation with real-time monitoring data using visualization technologies. The ROMS is two-way coupled with a simulating waves nearshore model, SWAN, for the hydrodynamics and waves, nested with the meteorological model, WRE for the atmospheric surface forcing, and externally nested with the eutrophication model, CE-QUAL-ICM, for the water quality. The op- erational model, ROMS, was calibrated with the tidal surface observed with a tide-gage and verified with current data observed by bottom-mounted ADCP or AWAC near the coastal waters of Korea. To validate the predicted results, we used real-time monitoring data derived from remote buoy system, HF-radar, and geostationary ocean color imager （GOCI）. This down-scaled operational coastal forecasting system will be used as a part of the Korea operational oceanographic system （KOOS） with other operational oceanographic systems.展开更多
With the increasing availability of precipitation radar data from space,enhancement of the resolution of spaceborne precipitation observations is important,particularly for hazard prediction and climate modeling at lo...With the increasing availability of precipitation radar data from space,enhancement of the resolution of spaceborne precipitation observations is important,particularly for hazard prediction and climate modeling at local scales relevant to extreme precipitation intensities and gradients.In this paper,the statistical characteristics of radar precipitation reflectivity data are studied and modeled using a hidden Markov tree(HMT)in the wavelet domain.Then,a high-resolution interpolation algorithm is proposed for spaceborne radar reflectivity using the HMT model as prior information.Owing to the small and transient storm elements embedded in the larger and slowly varying elements,the radar precipitation data exhibit distinct multiscale statistical properties,including a non-Gaussian structure and scale-to-scale dependency.An HMT model can capture well the statistical properties of radar precipitation,where the wavelet coefficients in each sub-band are characterized as a Gaussian mixture model(GMM),and the wavelet coefficients from the coarse scale to fine scale are described using a multiscale Markov process.The state probabilities of the GMM are determined using the expectation maximization method,and other parameters,for instance,the variance decay parameters in the HMT model are learned and estimated from high-resolution ground radar reflectivity images.Using the prior model,the wavelet coefficients at finer scales are estimated using local Wiener filtering.The interpolation algorithm is validated using data from the precipitation radar onboard the Tropical Rainfall Measurement Mission satellite,and the reconstructed results are found to be able to enhance the spatial resolution while optimally reproducing the local extremes and gradients.展开更多
This study consists of hydrological simulations of the Muriaé river watershed with the topography-based hydrological model (TOPMODEL) and available stream gauge and rain measurements between 2009 and 2013 for two...This study consists of hydrological simulations of the Muriaé river watershed with the topography-based hydrological model (TOPMODEL) and available stream gauge and rain measurements between 2009 and 2013 for two subbasins, namely </span><i><span style="font-family:Verdana;">Carangola</span></i><span style="font-family:Verdana;"> and </span><i><span style="font-family:Verdana;">Patrocínio do Muriaé</span></i><span style="font-family:Verdana;">. The simulations were carried out with the Climate Prediction Center morphing method (CMORPH) precipitation estimates and rain gauge measurements integrated into CM- ORPH by the Statistical Objective Analysis Scheme (SOAS). TOPMODEL calibration was performed with the shuffled complex evolution (SCE-UA) method with Nash-Sutcliffe efficiency (NSE). The best overall results were obtained with CMORPH (NSE ~ 0.6) for both subbasins. The simulations with SOAS resulted in an NSE ~ 0.2. However, in an analysis of days with high- level stages, SOAS simulations resulted in a better hit rate (23%) compared to CMORPH (10%). CMORPH simulations underestimated the flows at the flood periods, which indicates the importance to use multi-sensor precipitation data. The results with TOPMODEL allow an estimate of future discharges, which allows for better planning of a flood warning system and discharge measurement schedule.展开更多
In the phase of field evaluation, the changing of interwell reservoir may be out of control if the geological model was built only on well data due to few existing wells. The uncertainty of the interwell reservoir int...In the phase of field evaluation, the changing of interwell reservoir may be out of control if the geological model was built only on well data due to few existing wells. The uncertainty of the interwell reservoir interpolation based only on well data can be decreased by comprehensive utilization of geological, logging and seismic data, especially by using highly relative seismic properties from 3D seismic data adjusted by well point data to restrict interpolation of geological properties. A 3D-geological model which takes the sand body as the direct modeling object was built through stacking the structure, reservoir and water/oil/gas properties together in 3D space.展开更多
In view of the importance of ocean component for representing climate change,efforts are underway to implement a high-resolution nesting model system in Model for Interdisciplinary Research on Climate(MIROC) for the N...In view of the importance of ocean component for representing climate change,efforts are underway to implement a high-resolution nesting model system in Model for Interdisciplinary Research on Climate(MIROC) for the North Pacific using the same ocean model as used in the coupled model MIROC5. By comparing double(10 km for the northwestern Pacific,50 km for the rest of the Pacific) and triple(double nesting plus 2 km resolution near Japan) nesting,it turns out that relative vorticity is drastically enhanced near Japan with 2 km resolution. It is hoped that such an elaborated nesting system will reveal detailed processes for the ocean heat uptake by,e.g.,intermediate water and mode water formation for which the"perturbed region"near Japan is the key region.展开更多
Current data-driven deep learning(DL)methods typically reconstruct subsurface velocity models directly from pre-stack seismic records.However,these purely data-driven methods are often less robust and produce results ...Current data-driven deep learning(DL)methods typically reconstruct subsurface velocity models directly from pre-stack seismic records.However,these purely data-driven methods are often less robust and produce results that are less physically interpretative.Here,the authors propose a new method that uses migration images as input,combined with convolutional neural networks to construct high-resolution velocity models.Compared to directly using pre-stack seismic records as input,the nonlinearity between migration images and velocity models is significantly reduced.Additionally,the advantage of using migration images lies in its ability to more comprehensively capture the reflective properties of the subsurface medium,including amplitude and phase information,thereby to provide richer physical information in guiding the reconstruction of the velocity model.This approach not only improves the accuracy and resolution of the reconstructed velocity models,but also enhances the physical interpretability and robustness.Numerical experiments on synthetic data show that the proposed method has superior reconstruction performance and strong generalization capability when dealing with complex geological structures,and shows great potential in providing efficient solutions for the task of reconstructing high-wavenumber components.展开更多
Predicting tropical cyclone(TC)genesis is of great societal importance but scientifically challenging.It requires fineresolution coupled models that properly represent air−sea interactions in the atmospheric responses...Predicting tropical cyclone(TC)genesis is of great societal importance but scientifically challenging.It requires fineresolution coupled models that properly represent air−sea interactions in the atmospheric responses to local warm sea surface temperatures and feedbacks,with aid from coherent coupled initialization.This study uses three sets of highresolution regional coupled models(RCMs)covering the Asia−Pacific(AP)region initialized with local observations and dynamically downscaled coupled data assimilation to evaluate the predictability of TC genesis in the West Pacific.The APRCMs consist of three sets of high-resolution configurations of the Weather Research and Forecasting−Regional Ocean Model System(WRF-ROMS):27-km WRF with 9-km ROMS,and 9-km WRF with 3-km ROMS.In this study,a 9-km WRF with 9-km ROMS coupled model system is also used in a case test for the predictability of TC genesis.Since the local sea surface temperatures and wind shear conditions that favor TC formation are better resolved,the enhanced-resolution coupled model tends to improve the predictability of TC genesis,which could be further improved by improving planetary boundary layer physics,thus resolving better air−sea and air−land interactions.展开更多
Meso-scale eddies are important features in the South China Sea（SCS）. The eddies with diameters of 50–200 km can greatly impact the transport of heat, momentum, and tracers. A high-resolution wave-tide-circulation ...Meso-scale eddies are important features in the South China Sea（SCS）. The eddies with diameters of 50–200 km can greatly impact the transport of heat, momentum, and tracers. A high-resolution wave-tide-circulation coupled model was developed to simulate the meso-scale eddy in the SCS in this study. The aim of this study is to examine the model ability to simulate the meso-scale eddy in the SCS without data assimilations The simulated Sea Surface Height（SSH） anomalies agree with the observed the AVISO SSH anomalies well. The simulated subsurface temperature profiles agree with the CTD observation data from the ROSE（Responses of Marine Hazards to climate change in the Western Pacific） project. The simulated upper-ocean currents also agree with the main circulation based on observations. A warm eddy is identified in winter in the northern SCS. The position and domain of the simulated eddy are confirmed by the observed sea surface height data from the AVISO. The result shows that the model has the ability to simulate the meso-scale eddy in the SCS without data assimilation.The three-dimensional structure of the meso-scale eddy in the SCS is analyzed using the model result. It is found that the eddy center is tilted vertically, which agrees with the observation. It is also found that the velocity center of the eddy does not coincide with the temperature center of the eddy. The result shows that the model has the ability to simulate the meso-scale eddy in the SCS without data assimilations. Further study on the forming mechanism and the three-dimensional structure of the meso-scale eddies will be carried out using the model result and cruise observation data in the near future.展开更多
Projections of future precipitation change over China are studied based on the output of a global AGCM, ECHAM5, with a high resolution of T319 （equivalent to 40 km）. Evaluation of the model’s performance in simulat...Projections of future precipitation change over China are studied based on the output of a global AGCM, ECHAM5, with a high resolution of T319 （equivalent to 40 km）. Evaluation of the model’s performance in simulating present-day precipitation shows encouraging results. The spatial distributions of both mean and extreme precipitation, especially the locations of main precipitation centers, are reproduced reasonably. The simulated annual cycle of precipitation is close to the observed. The performance of the model over eastern China is generally better than that over western China. A weakness of the model is the overestimation of precipitation over northern and western China. Analyses on the potential change in precipitation projected under the A1B scenario show that both annual mean precipitation intensity and extreme precipitation would increase significantly over southeastern China. The percentage increase in extreme precipitation is larger than that of mean precipitation. Meanwhile, decreases in mean and extreme precipitation are evident over the southern Tibetan Plateau. For precipitation days, extreme precipitation days are projected to increase over all of China. Both consecutive dry days over northern China and consecutive wet days over southern China would decrease.展开更多
This paper describes the model speed and model In/Out （I/O） efficiency of the high-resolution atmospheric general circulation model FAMIL （Finite- volume Atmospheric Model of IAP/LASG） at the National Supercompute...This paper describes the model speed and model In/Out （I/O） efficiency of the high-resolution atmospheric general circulation model FAMIL （Finite- volume Atmospheric Model of IAP/LASG） at the National Supercomputer Center in Tianjin, China, on its Tianhe-lA supercomputer platform. A series of three- model-day simulations were carried out with standard Aqua Planet Experiment （APE） designed within FAMIL to obtain the time stamp for the calculation of model speed, simulation cost, and model 1/O efficiency. The results of the simulation demonstrate that FAMIL has remarkable scalability below 3456 and 6144 cores, and the lowest simulation costs are 1536 and 3456 cores for 12.5 km and 6.25 krn resolutions, respectively. Furthermore, FAMIL has excellent I/O scalability and an efficiency of more than 80% on 6 I/Os and more than 99% on 1536 I/Os.展开更多
Using the Community Earth System Model framework, the authors build a very-high-resolution quasi-global coupled model by coupling an eddy-resolving quasi-global ocean model with a high-resolution atmospheric model. Th...Using the Community Earth System Model framework, the authors build a very-high-resolution quasi-global coupled model by coupling an eddy-resolving quasi-global ocean model with a high-resolution atmospheric model. The model is successfully run for six years under present climate conditions, and the simulations are evaluated against observational and reanalysis data.The model is capable of simulating large-scale oceanic and atmospheric circulation patterns, sea surface temperature(SST) fronts, oceanic eddy kinetic energy, and fine-scale structures of surface winds. The ocean mesoscale structure–induced air–sea interaction characteristics are explored in detail. The model can effectively reproduce positive correlations between SST and surface wind stress induced by mesoscale structures through comparison with observations. The positive correlation is particularly significant over regions with strong oceanic fronts and eddies.However, the responses of wind stress to eddy-induced SST are weaker in the simulation than in the observations, although different magnitudes exist in different areas. Associated with weak wind responses, surface sensible heat flux responses to eddy-induced SST are underestimated slightly, while surface latent heat flux responses are overestimated because of the drier atmospheric boundary layers in the model. Both momentum mixing and pressure adjustment mechanisms play important roles in surface wind changes over oceanic fronts and eddies in the high-resolution model.展开更多
文摘High-resolution modeling approach is increasingly being considered as a necessary step for improving the monitoring and predictions of regional air quality. This is especially true for highly urbanized region with complex terrain and land-use. This study uses Community Multiscale Air Quality （CMAQ） model coupled with MM5 mesoscale model for a comprehensive analysis to assess the suitability of such high-resolution modeling system in predicting ozone air quality in the complex terrains of Osaka, Japan. The 1-km and 3-kin grid domains were nested inside a 9-km domain and the domain with 1-km grid covered the Osaka region. High-resolution Grid Point Value-Mesoscale Model （GPV-MSM） data were used after suitable validation. The simulated ozone concentrations were validated and evaluated using statistical metrics using performance criteria set for ozone. Daily maxima of ozone were found better simulated by the 1-krn grid domain than the coarser 9-km and 3-km domains, with the maximum improvement in the mean absolute gross error about 3 ppbv. In addition, 1-km grid results fared better than other grids at most of the observation stations that showed noticeable differences in gross error as well as correlation. These results amply justify the use of the integrated high-resolution MM5-CMAQ modeling system in the highly urbanized region, such as the Osaka region, which has complex terrain and land-use.
文摘Mesoamerica and the Caribbean are low-latitude regions at risk for the effects of climate change. Global climate models provide large-scale assessment of climate drivers, but, at a horizontal resolution of 100 km, cannot resolve the effects of topography and land use as they impact the local temperature and precipitation that are keys to climate impacts. We developed a robust dynamical downscaling strategy that used the WRF regional climate model to downscale at 4 - 12 km resolution GCM results. Model verification demonstrates the need for such resolution of topography in order to properly simulate temperatures. Precipitation is more difficult to evaluate, being highly variable in time and space. Overall, a 36 km resolution is inadequate;12 km appears reasonable, especially in regions of low topography, but the 4 km resolution provides the best match with observations. This represents a tradeoff between model resolution and the computational effort needed to make simulations. A key goal is to provide climate change specialists in each country with the information they need to evaluate possible future climate change impacts.
基金supported by the National Natural Science Foundation of China(Nos.42122039 and 42375189)the Science and Technology Innovation Project of Laoshan Laboratory(China)(Nos.LSKJ202300401 and LSKJ202202201)+1 种基金Hainan Provincial Joint Project of Sanya Yazhou Bay Science and Technology City(China)(No.2021JJLH0050)Deliang Chen was supported by Tsinghua University(China)(No.100008001).
文摘Under global warming,extreme weather events and air pollution are becoming increasingly critical challenges.Both pose serious risks to human health,economies,and societal stability,and their complex interactions can further amplify these impacts.Numerical models are essential tools for studying these phenomena;however,traditional low-resolution Earth system models often fail to accurately capture the dynamics of extreme weather and air pollution.This limitation hinders our mechanistic understanding,reduces the reliability of future projections,and constrains the development of effective adaptation strategies.Dynamical downscaling—an approach that uses highresolution regional models nested within global models—offers a partial solution.However,this method inherits biases from the parent global models and often fails to adequately represent multi-scale and cross-sphere interactions involving the atmosphere,land,and oceans.These shortcomings underscore the growing need for developing and applying high-resolution Earth system models that can more comprehensively and accurately depict land-sea-atmosphere interactions,including heat and material exchanges and their spatial heterogeneity.This article explores the current challenges,recent advances,and future opportunities in understanding the interplay between extreme weather events and air pollution,with a focus on the critical role of high-resolution modeling.
基金supported by the National Key Research and Development Program of China(Grant No.2022YFF0800504)the Major Program of the National Natural Science Foundation of China(Grant No.41991324)the Major Research Plan of the National Natural Science Foundation of China(Grant No.92479106)。
文摘Continental silicate weathering acts as a crucial negative feedback mechanism for removing atmospheric CO_(2) and maintaining Earth's long-term climate stability.However,quantifying continental silicate weathering rates and fluxes continues to pose a fundamental challenge in Earth system science.This study utilizes the GEOCLIM carbon cycle model,which integrates modern high-resolution(0.1°×0.1°)datasets on surface temperature,runoff,topography,and lithology to model the spatial distribution of global silicate weathering fluxes.Results indicate a strong correlation between modeled basin-scale outputs and hydrological observations,with weathering rates falling within consistent error margins.Silicate weathering fluxes exhibit distinct latitudinal patterns,with the highest values concentrated within 30°of the equator,accounting for 76.9%of the global total.Continental contributions differ significantly,with Asian river basins representing 36.9%of global fluxes,primarily from Southeast Asia(17.4%),South Asia(8.2%),and East Asia(6.6%).They are followed by South America(29.2%)and Africa(21.7%).Tectonically active regions contribute 21.9%of global silicate weathering,while stable regions account for 72.6%.Multivariate regression analyses using RF and XGBoost machine learning algorithms identify runoff as the primary controlling factor of weathering on a global scale.Weathering in stable regions is jointly regulated by runoff and erosion rates,whereas temperature is the prevailing factor in tectonically active zones.The GEOCLIM model offers a robust framework for quantifying continental weathering processes.Future studies should incorporate organic carbon oxidation,burial,and sulfide oxidation dynamics to clarify carbon cycle interactions and reveal climate-dependent mechanisms for weathering responses and feedback.
基金funded by the National Natural Science Foundation of China(62273213,62472262,62572287)Natural Science Foundation of Shandong Province(ZR2024MF144)+1 种基金Natural Science Foundation of Shandong Province for Innovation and Development Joint Funds(ZR2022LZH001)Taishan Scholarship Construction Engineering.
文摘Accurately counting dense objects in complex and diverse backgrounds is a significant challenge in computer vision,with applications ranging from crowd counting to various other object counting tasks.To address this,we propose HUANNet(High-Resolution Unified Attention Network),a convolutional neural network designed to capture both local features and rich semantic information through a high-resolution representation learning framework,while optimizing computational distribution across parallel branches.HUANNet introduces three core modules:the High-Resolution Attention Module(HRAM),which enhances feature extraction by optimizing multiresolution feature fusion;the Unified Multi-Scale Attention Module(UMAM),which integrates spatial,channel,and convolutional kernel information through an attention mechanism applied across multiple levels of the network;and the Grid-Assisted Point Matching Module(GPMM),which stabilizes and improves point-to-point matching by leveraging grid-based mechanisms.Extensive experiments show that HUANNet achieves competitive results on the ShanghaiTech Part A/B crowd counting datasets and sets new state-of-the-art performance on dense object counting datasets such as CARPK and XRAY-IECCD,demonstrating the effectiveness and versatility of HUANNet.
基金supported by the Natural Science Foundation of Hubei Provincial Department of Education(D20232101)Shandong Second Medical University 2024 Affiliated Hospital(Teaching Hospital)Scientific Research Development Fund Project(2024FYQ026)+3 种基金the innovative Research Programme of Xiangyang No.1 People’s Hospital(XYY2023ZY01)Faculty Development Grants of Xiangyang No.1 People’s Hospital Affiliated to Hubei University of Medicine(XYY2023D05)Joint supported by Hubei Provincial Natural Science Foundation and Xiangyang of China(2025AFD091)Traditional Chinese Medicine Scientific Research Project of Hubei Provincial Administration of Traditional Chinese Medicine(ZY2025D019).
文摘Background:Diabetic foot,a severe complication of diabetes,is characterized by chronic refractory wounds.Sanhuang Oil,a topical herbal formula,demonstrates significant therapeutic effects including antibacterial,anti-inflammatory,and immunomodulatory activities.However,its active constituents and mechanisms of action against diabetic foot remain to be elucidated.Methods:In this study,the chemical constituents of Sanhuang Oil were identified using UPLC-QE-Orbitrap-MS.Subsequently,the mechanism by which Sanhuang Oil promotes diabetic foot ulcer healing was predicted by integrating network pharmacology and molecular docking.Additionally,diabetic mouse model was established in ICR mice using a combination of a high-fat diet(HFD)and streptozotocin(STZ)chemical induction.A full-thickness skin defect was created on the dorsum of the mice.Wound healing and the healing rate were observed following Sanhuang Oil intervention.The mechanism underlying Sanhuang Oil’s promotion of diabetic ulcer healing was further investigated using transcriptomics and histopathological examination(H&E staining).Results:A total of 97 active ingredients were identified from Sanhuang Oil.Network pharmacology analysis predicted 543 common targets,and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis identified 203 relevant pathways.Molecular docking further confirmed high binding affinity(binding energy≤−5.0 kcal/mol)between specific active components in Sanhuang Oil(e.g.,coptisine,phellodendrine,baicalein)and key targets associated with diabetic foot ulcers(e.g.,EGFR,AKT1,STAT3).In vivo experimental results demonstrated that the wound healing rate was significantly higher in Sanhuang Oil-treated groups compared to the model group(P<0.001).HE staining revealed that the high-dose Sanhuang Oil group exhibited more pronounced epithelial tissue coverage over the wound,reduced inflammatory cell infiltration,and increased collagen deposition and fibroblast proliferation.transcriptomic analysis identified Pdk4,Ttn,Csrp3,Actn2,Myoz2,Tnnc2,Myod1,Myog,Myot,and Myf6 as key regulatory proteins involved in promoting wound healing.Conclusion:Sanhuang Oil promotes wound healing in diabetic ulcer mice,potentially by mitigating inflammation and regulating key targets such as Pdk4 to enhance fibroblast function.These findings provide novel insights into the multi-target,multi-pathway mechanism of Sanhuang Oil for treating diabetic foot ulcers.
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.
基金supported by the confidential research grant No.a8317。
文摘To address the issues of frequent identity switches(IDs)and degraded identification accuracy in multi object tracking(MOT)under complex occlusion scenarios,this study proposes an occlusion-robust tracking framework based on face-pedestrian joint feature modeling.By constructing a joint tracking model centered on“intra-class independent tracking+cross-category dynamic binding”,designing a multi-modal matching metric with spatio-temporal and appearance constraints,and innovatively introducing a cross-category feature mutual verification mechanism and a dual matching strategy,this work effectively resolves performance degradation in traditional single-category tracking methods caused by short-term occlusion,cross-camera tracking,and crowded environments.Experiments on the Chokepoint_Face_Pedestrian_Track test set demonstrate that in complex scenes,the proposed method improves Face-Pedestrian Matching F1 area under the curve(F1 AUC)by approximately 4 to 43 percentage points compared to several traditional methods.The joint tracking model achieves overall performance metrics of IDF1:85.1825%and MOTA:86.5956%,representing improvements of 0.91 and 0.06 percentage points,respectively,over the baseline model.Ablation studies confirm the effectiveness of key modules such as the Intersection over Area(IoA)/Intersection over Union(IoU)joint metric and dynamic threshold adjustment,validating the significant role of the cross-category identity matching mechanism in enhancing tracking stability.Our_model shows a 16.7%frame per second(FPS)drop vs.fairness of detection and re-identification in multiple object tracking(FairMOT),with its cross-category binding module adding aboute 10%overhead,yet maintains near-real-time performance for essential face-pedestrian tracking at small resolutions.
文摘In weather forecasting,generating atmospheric variables for regions with complex topography,such as the Andean regions with peaks reaching 6500 m above sea level,poses significant challenges.Traditional regional climate models often struggle to accurately represent the atmospheric behavior in such areas.Furthermore,the capability to produce high spatio-temporal resolution data(less than 27 km and hourly)is limited to a few institutions globally due to the substantial computational resources required.This study presents the results of atmospheric data generated using a new type of artificial intelligence(AI)models,aimed to reduce the computational cost of generating downscaled climate data using climate regional models like the Weather Research and Forecasting(WRF)model over the Andes.The WRF model was selected for this comparison due to its frequent use in simulating atmospheric variables in the Andes.Our results demonstrate a higher downscaling performance for the four target weather variables studied(temperature,relative humidity,zonal and meridional wind)over coastal,mountain,and jungle regions.Moreover,this AI model offers several advantages,including lower computational costs compared to dynamic models like WRF and continuous improvement potential with additional training data.
基金The project entitled Cooperation on the Development of Basic Technologies for the Yellow Sea and East China Sea Operational Oceanographic System funded by the China-Korea Joint Ocean Research Centerthe project entitled"Development of Korea Operational Oceanographic System"funded by the Ministry of Oceans and Fisheries,Koreathe project Functional Improvement of Korea Ocean Satellite Center and Development of the Marine Environment Impact Prediction Program funded by the Korea Institute of Ocean Science and Technology
文摘A down-scaled operational oceanographic system is developed for the coastal waters of Korea using a re- gional ocean modeling system （ROMS）. The operational oceanographic modeling system consists of at- mospheric and hydrodynamic models. The hydrodynamic model, ROMS, is coupled with wave, sediment transport, and water quality modules. The system forecasts the predicted results twice a day on a 72 h basis, including sea surface elevation, currents, temperature, salinity, storm surge height, and wave information for the coastal waters of Korea. The predicted results are exported to the web-GIS-based coastal informa- tion system for real-time dissemination to the public and validation with real-time monitoring data using visualization technologies. The ROMS is two-way coupled with a simulating waves nearshore model, SWAN, for the hydrodynamics and waves, nested with the meteorological model, WRE for the atmospheric surface forcing, and externally nested with the eutrophication model, CE-QUAL-ICM, for the water quality. The op- erational model, ROMS, was calibrated with the tidal surface observed with a tide-gage and verified with current data observed by bottom-mounted ADCP or AWAC near the coastal waters of Korea. To validate the predicted results, we used real-time monitoring data derived from remote buoy system, HF-radar, and geostationary ocean color imager （GOCI）. This down-scaled operational coastal forecasting system will be used as a part of the Korea operational oceanographic system （KOOS） with other operational oceanographic systems.
基金This study was funded by the National Natural Science Foundation of China(Grant No.41975027)the Natural Science Foundation of Jiangsu Province(Grant No.BK20171457)the National Key R&D Program on Monitoring,Early Warning and Prevention of Major Natural Disasters(Grant No.2017YFC1501401).
文摘With the increasing availability of precipitation radar data from space,enhancement of the resolution of spaceborne precipitation observations is important,particularly for hazard prediction and climate modeling at local scales relevant to extreme precipitation intensities and gradients.In this paper,the statistical characteristics of radar precipitation reflectivity data are studied and modeled using a hidden Markov tree(HMT)in the wavelet domain.Then,a high-resolution interpolation algorithm is proposed for spaceborne radar reflectivity using the HMT model as prior information.Owing to the small and transient storm elements embedded in the larger and slowly varying elements,the radar precipitation data exhibit distinct multiscale statistical properties,including a non-Gaussian structure and scale-to-scale dependency.An HMT model can capture well the statistical properties of radar precipitation,where the wavelet coefficients in each sub-band are characterized as a Gaussian mixture model(GMM),and the wavelet coefficients from the coarse scale to fine scale are described using a multiscale Markov process.The state probabilities of the GMM are determined using the expectation maximization method,and other parameters,for instance,the variance decay parameters in the HMT model are learned and estimated from high-resolution ground radar reflectivity images.Using the prior model,the wavelet coefficients at finer scales are estimated using local Wiener filtering.The interpolation algorithm is validated using data from the precipitation radar onboard the Tropical Rainfall Measurement Mission satellite,and the reconstructed results are found to be able to enhance the spatial resolution while optimally reproducing the local extremes and gradients.
文摘This study consists of hydrological simulations of the Muriaé river watershed with the topography-based hydrological model (TOPMODEL) and available stream gauge and rain measurements between 2009 and 2013 for two subbasins, namely </span><i><span style="font-family:Verdana;">Carangola</span></i><span style="font-family:Verdana;"> and </span><i><span style="font-family:Verdana;">Patrocínio do Muriaé</span></i><span style="font-family:Verdana;">. The simulations were carried out with the Climate Prediction Center morphing method (CMORPH) precipitation estimates and rain gauge measurements integrated into CM- ORPH by the Statistical Objective Analysis Scheme (SOAS). TOPMODEL calibration was performed with the shuffled complex evolution (SCE-UA) method with Nash-Sutcliffe efficiency (NSE). The best overall results were obtained with CMORPH (NSE ~ 0.6) for both subbasins. The simulations with SOAS resulted in an NSE ~ 0.2. However, in an analysis of days with high- level stages, SOAS simulations resulted in a better hit rate (23%) compared to CMORPH (10%). CMORPH simulations underestimated the flows at the flood periods, which indicates the importance to use multi-sensor precipitation data. The results with TOPMODEL allow an estimate of future discharges, which allows for better planning of a flood warning system and discharge measurement schedule.
文摘In the phase of field evaluation, the changing of interwell reservoir may be out of control if the geological model was built only on well data due to few existing wells. The uncertainty of the interwell reservoir interpolation based only on well data can be decreased by comprehensive utilization of geological, logging and seismic data, especially by using highly relative seismic properties from 3D seismic data adjusted by well point data to restrict interpolation of geological properties. A 3D-geological model which takes the sand body as the direct modeling object was built through stacking the structure, reservoir and water/oil/gas properties together in 3D space.
文摘In view of the importance of ocean component for representing climate change,efforts are underway to implement a high-resolution nesting model system in Model for Interdisciplinary Research on Climate(MIROC) for the North Pacific using the same ocean model as used in the coupled model MIROC5. By comparing double(10 km for the northwestern Pacific,50 km for the rest of the Pacific) and triple(double nesting plus 2 km resolution near Japan) nesting,it turns out that relative vorticity is drastically enhanced near Japan with 2 km resolution. It is hoped that such an elaborated nesting system will reveal detailed processes for the ocean heat uptake by,e.g.,intermediate water and mode water formation for which the"perturbed region"near Japan is the key region.
文摘Current data-driven deep learning(DL)methods typically reconstruct subsurface velocity models directly from pre-stack seismic records.However,these purely data-driven methods are often less robust and produce results that are less physically interpretative.Here,the authors propose a new method that uses migration images as input,combined with convolutional neural networks to construct high-resolution velocity models.Compared to directly using pre-stack seismic records as input,the nonlinearity between migration images and velocity models is significantly reduced.Additionally,the advantage of using migration images lies in its ability to more comprehensively capture the reflective properties of the subsurface medium,including amplitude and phase information,thereby to provide richer physical information in guiding the reconstruction of the velocity model.This approach not only improves the accuracy and resolution of the reconstructed velocity models,but also enhances the physical interpretability and robustness.Numerical experiments on synthetic data show that the proposed method has superior reconstruction performance and strong generalization capability when dealing with complex geological structures,and shows great potential in providing efficient solutions for the task of reconstructing high-wavenumber components.
基金supported by the National Key Research&Development Program of China(Grant Nos.2017YFC1404100 and 2017YFC1404104)the National Natural Science Foundation of China(Grant Nos.41775100 and 41830964)。
文摘Predicting tropical cyclone(TC)genesis is of great societal importance but scientifically challenging.It requires fineresolution coupled models that properly represent air−sea interactions in the atmospheric responses to local warm sea surface temperatures and feedbacks,with aid from coherent coupled initialization.This study uses three sets of highresolution regional coupled models(RCMs)covering the Asia−Pacific(AP)region initialized with local observations and dynamically downscaled coupled data assimilation to evaluate the predictability of TC genesis in the West Pacific.The APRCMs consist of three sets of high-resolution configurations of the Weather Research and Forecasting−Regional Ocean Model System(WRF-ROMS):27-km WRF with 9-km ROMS,and 9-km WRF with 3-km ROMS.In this study,a 9-km WRF with 9-km ROMS coupled model system is also used in a case test for the predictability of TC genesis.Since the local sea surface temperatures and wind shear conditions that favor TC formation are better resolved,the enhanced-resolution coupled model tends to improve the predictability of TC genesis,which could be further improved by improving planetary boundary layer physics,thus resolving better air−sea and air−land interactions.
基金The National Basic Research Program(973 Program) of China under contract No.2014CB745004China-Korea Cooperation Project on the development of oceanic monitoring and prediction system on nuclear safety+2 种基金the National Natural Science Foundation of China under contract No.41206025NSFC-Shandong Joint Fund for Marine Science Research Centers under contract No.U1406404supported by China-Korea Joint Ocean Research Center
文摘Meso-scale eddies are important features in the South China Sea（SCS）. The eddies with diameters of 50–200 km can greatly impact the transport of heat, momentum, and tracers. A high-resolution wave-tide-circulation coupled model was developed to simulate the meso-scale eddy in the SCS in this study. The aim of this study is to examine the model ability to simulate the meso-scale eddy in the SCS without data assimilations The simulated Sea Surface Height（SSH） anomalies agree with the observed the AVISO SSH anomalies well. The simulated subsurface temperature profiles agree with the CTD observation data from the ROSE（Responses of Marine Hazards to climate change in the Western Pacific） project. The simulated upper-ocean currents also agree with the main circulation based on observations. A warm eddy is identified in winter in the northern SCS. The position and domain of the simulated eddy are confirmed by the observed sea surface height data from the AVISO. The result shows that the model has the ability to simulate the meso-scale eddy in the SCS without data assimilation.The three-dimensional structure of the meso-scale eddy in the SCS is analyzed using the model result. It is found that the eddy center is tilted vertically, which agrees with the observation. It is also found that the velocity center of the eddy does not coincide with the temperature center of the eddy. The result shows that the model has the ability to simulate the meso-scale eddy in the SCS without data assimilations. Further study on the forming mechanism and the three-dimensional structure of the meso-scale eddies will be carried out using the model result and cruise observation data in the near future.
基金supported by the National Key Technologies R&D Program(Grant No. 2007BAC29B03)China-UK-Swiss Adaptingto Climate Change in China Project (ACCC)-Climate Sciencethe National Natural Science Foundation of China (Grant No. 40890054)
文摘Projections of future precipitation change over China are studied based on the output of a global AGCM, ECHAM5, with a high resolution of T319 （equivalent to 40 km）. Evaluation of the model’s performance in simulating present-day precipitation shows encouraging results. The spatial distributions of both mean and extreme precipitation, especially the locations of main precipitation centers, are reproduced reasonably. The simulated annual cycle of precipitation is close to the observed. The performance of the model over eastern China is generally better than that over western China. A weakness of the model is the overestimation of precipitation over northern and western China. Analyses on the potential change in precipitation projected under the A1B scenario show that both annual mean precipitation intensity and extreme precipitation would increase significantly over southeastern China. The percentage increase in extreme precipitation is larger than that of mean precipitation. Meanwhile, decreases in mean and extreme precipitation are evident over the southern Tibetan Plateau. For precipitation days, extreme precipitation days are projected to increase over all of China. Both consecutive dry days over northern China and consecutive wet days over southern China would decrease.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDA05110303)the National Basic Research Program of China (973Program, Grant Nos. 2012CB417203 and 2010CB950404)+1 种基金the National High Technology Research and Development Program of China (863 Program, Grant No. 2010AA012305)the National Natural Science Foundation of China (Grant No. 41023002)
文摘This paper describes the model speed and model In/Out （I/O） efficiency of the high-resolution atmospheric general circulation model FAMIL （Finite- volume Atmospheric Model of IAP/LASG） at the National Supercomputer Center in Tianjin, China, on its Tianhe-lA supercomputer platform. A series of three- model-day simulations were carried out with standard Aqua Planet Experiment （APE） designed within FAMIL to obtain the time stamp for the calculation of model speed, simulation cost, and model 1/O efficiency. The results of the simulation demonstrate that FAMIL has remarkable scalability below 3456 and 6144 cores, and the lowest simulation costs are 1536 and 3456 cores for 12.5 km and 6.25 krn resolutions, respectively. Furthermore, FAMIL has excellent I/O scalability and an efficiency of more than 80% on 6 I/Os and more than 99% on 1536 I/Os.
基金supported by the National Key R&D Program for Developing Basic Sciences [grant numbers2016YFC1401401 and 2016YFC1401601]the National Natural Science Foundation of China [grant numbers41376026 and 41576025]
文摘Using the Community Earth System Model framework, the authors build a very-high-resolution quasi-global coupled model by coupling an eddy-resolving quasi-global ocean model with a high-resolution atmospheric model. The model is successfully run for six years under present climate conditions, and the simulations are evaluated against observational and reanalysis data.The model is capable of simulating large-scale oceanic and atmospheric circulation patterns, sea surface temperature(SST) fronts, oceanic eddy kinetic energy, and fine-scale structures of surface winds. The ocean mesoscale structure–induced air–sea interaction characteristics are explored in detail. The model can effectively reproduce positive correlations between SST and surface wind stress induced by mesoscale structures through comparison with observations. The positive correlation is particularly significant over regions with strong oceanic fronts and eddies.However, the responses of wind stress to eddy-induced SST are weaker in the simulation than in the observations, although different magnitudes exist in different areas. Associated with weak wind responses, surface sensible heat flux responses to eddy-induced SST are underestimated slightly, while surface latent heat flux responses are overestimated because of the drier atmospheric boundary layers in the model. Both momentum mixing and pressure adjustment mechanisms play important roles in surface wind changes over oceanic fronts and eddies in the high-resolution model.
