The Zebiak–Cane(ZC) model, renowned as a coupled ocean-atmosphere model specifically designed to simulate and predict El Ni??o-Southern Oscillation(ENSO), is an indispensable tool for ENSO studies. However, the origi...The Zebiak–Cane(ZC) model, renowned as a coupled ocean-atmosphere model specifically designed to simulate and predict El Ni??o-Southern Oscillation(ENSO), is an indispensable tool for ENSO studies. However, the original ZC model exhibits certain biases in reproducing the ENSO–related sea surface temperature anomalies and heating anomalies, limiting its broader applicability. To improve the accuracy of ENSO simulation, we propose a modified ZC model based on Xie et al.(2015), named the MZC_XJH model, through refining the heating parameterization scheme. The performance in simulating the nonlinear SST–precipitation relationship in the MZC_XJH model is firstly elaborated. Then, we investigate the impacts of three key atmospheric parameters on ENSO simulation by conducting experiments with the MZC_XJH model. Through assessing the performance in simulating five fundamental ENSO metrics(amplitude, periodicity,seasonality, diversity, and skewness), we uncover that the sensitivities of simulated ENSO behaviors to different parameters are distinct. Moreover, we explain why a particular parameter greatly affects some simulated ENSO behaviors while others exert minor influence. We also reveal that the nonlinear effect due to the covariation of multi-parameters on ENSO simulation warrants careful consideration when tuning multi-parameters synchronously. Lastly, we present an updated version of the MZC_XJH model, in which some biases have been mitigated but some remain obvious. Although there are no universally optimal parameters that would ensure flawless performance in simulating every aspect of ENSO, this study provides a valuable reference for tuning atmospheric parameters in the MZC_XJH model, rendering the MZC_XJH model applicable to some research objectives.展开更多
In this study,the Betts-Miller-Janjic(BMJ)convective adjustment scheme in the Weather Research and Forecasting(WRF)model version 4.0 was used to investigate the effect of itsα-parameter,which influences the first-gue...In this study,the Betts-Miller-Janjic(BMJ)convective adjustment scheme in the Weather Research and Forecasting(WRF)model version 4.0 was used to investigate the effect of itsα-parameter,which influences the first-guess potential temperature reference profile on the Madden-Julian oscillation(MJO)propagation and structure.This study diagnosed the MJO active phase composites of the MJO-filtered outgoing longwave radiation(OLR)during the December-to-February(DJF)period of 2006-2016 over the Indian Ocean(IO),Maritime Continent(MC),and western Pacific(WP).The results show that the MJO-filtered OLR intensity,propagation pattern,and MJO classification(standing,jumping,and propagating clusters)are sensitive to theα-value,but the phase speeds of propagating MJOs are not.Overall,with an increasingα-value,the simulated MJO-filtered OLR intensity increases,and the simulated propagation pattern is improved.Results also show that the intensity and propagation pattern of an eastward-propagating MJO are associated with MJO circulation structures and thermodynamic structures.Asαincreases,the front Walker cell and the low-level easterly anomaly are enhanced,which premoistens the lower troposphere and triggers more active shallow and congestus clouds.The enhanced shallow and congestus convection preconditions the lower to middle troposphere,accelerating the transition from congestus to deep convection,thereby facilitating eastward propagation of the MJO.Therefore,the simulated MJO tends to transfer from standing to eastward propagating asαincreases.In summary,increasing theα-value is a possible way to improve the simulation of the structure and propagation of the MJO.展开更多
Taking short-duration heavy rainfall and convective wind gusts as examples, the present study examined the characteristics of radar reflectivity and several convective parameters. We analyzed nowcasting techniques by ...Taking short-duration heavy rainfall and convective wind gusts as examples, the present study examined the characteristics of radar reflectivity and several convective parameters. We analyzed nowcasting techniques by integrating a high-resolution numerical weather prediction model with these convective parameters. Based on the CMA-GD 1-km model and its assimilation system, we conducted repeated tests on radar reflectivity data assimilation and analyzed their impact on nowcasting accuracy. Based on these analyses, we proposed a method to improve model forecasts using the useful indicative information provided by high-frequency radar reflectivity data and convective parameters. The improved method was applied to the CMA-GD 1-km model for nowcasting tests. Evaluations from batch tests and case analysis show that the proposed method significantly reduced the model's false alarm rates and improved its nowcasting performance.展开更多
This study introduces a new ocean surface friction velocity scheme and a modified Thompson cloud microphysics parameterization scheme into the CMA-TYM model.The impact of these two parameterization schemes on the pred...This study introduces a new ocean surface friction velocity scheme and a modified Thompson cloud microphysics parameterization scheme into the CMA-TYM model.The impact of these two parameterization schemes on the prediction of the movement track and intensity of Typhoon Kompasu in 2021 is examined.Additionally,the possible reasons for their effects on tropical cyclone(TC)intensity prediction are analyzed.Statistical results show that both parameterization schemes improve the predictions of Typhoon Kompasu’s track and intensity.The influence on track prediction becomes evident after 60 h of model integration,while the significant positive impact on intensity prediction is observed after 66 h.Further analysis reveals that these two schemes affect the timing and magnitude of extreme TC intensity values by influencing the evolution of the TC’s warm-core structure.展开更多
As blockchain technology rapidly evolves,smart contracts have seen widespread adoption in financial transactions and beyond.However,the growing prevalence of malicious Ponzi scheme contracts presents serious security ...As blockchain technology rapidly evolves,smart contracts have seen widespread adoption in financial transactions and beyond.However,the growing prevalence of malicious Ponzi scheme contracts presents serious security threats to blockchain ecosystems.Although numerous detection techniques have been proposed,existing methods suffer from significant limitations,such as class imbalance and insufficient modeling of transaction-related semantic features.To address these challenges,this paper proposes an oversampling-based detection framework for Ponzi smart contracts.We enhance the Adaptive Synthetic Sampling(ADASYN)algorithm by incorporating sample proximity to decision boundaries and ensuring realistic sample distributions.This enhancement facilitates the generation of high-quality minority class samples and effectively mitigates class imbalance.In addition,we design a Contract Transaction Graph(CTG)construction algorithm to preserve key transactional semantics through feature extraction from contract code.A graph neural network(GNN)is then applied for classification.This study employs a publicly available dataset from the XBlock platform,consisting of 318 verified Ponzi contracts and 6498 benign contracts.Sourced from real Ethereum deployments,the dataset reflects diverse application scenarios and captures the varied characteristics of Ponzi schemes.Experimental results demonstrate that our approach achieves an accuracy of 96%,a recall of 92%,and an F1-score of 94%in detecting Ponzi contracts,outperforming state-of-the-art methods.展开更多
Hepatocellular carcinoma presents with three distinct immune phenotypes,including immune-desert,immune-excluded,and immune-inflamed,indicating various treatment responses and prognostic outcomes.The clinical applicati...Hepatocellular carcinoma presents with three distinct immune phenotypes,including immune-desert,immune-excluded,and immune-inflamed,indicating various treatment responses and prognostic outcomes.The clinical application of multi-omics parameters is still restricted by the expensive and less accessible assays,although they accurately reflect immune status.A comprehensive evaluation framework based on“easy-to-obtain”multi-model clinical parameters is urgently required,incorporating clinical features to establish baseline patient profiles and disease staging;routine blood tests assessing systemic metabolic and functional status;immune cell subsets quantifying subcluster dynamics;imaging features delineating tumor morphology,spatial configuration,and perilesional anatomical relationships;immunohistochemical markers positioning qualitative and quantitative detection of tumor antigens from the cellular and molecular level.This integrated phenomic approach aims to improve prognostic stratification and clinical decision-making in hepatocellular carcinoma management conveniently and practically.展开更多
Electrochemical models,characterized by high fidelity and physical interpretability,have been applied in var-ious fields such as fast charging,battery state estimation,and battery material design.Currently,widely util...Electrochemical models,characterized by high fidelity and physical interpretability,have been applied in var-ious fields such as fast charging,battery state estimation,and battery material design.Currently,widely utilized single particle-based model exhibits high computational efficiency but suffers from low simulation accuracy under high-rate charge/discharge conditions.In this work,an electrochemical model for lithium-ion batteries based on multi-particle hypothesis is developed.Two particles are employed to represent the electrode char-acteristics of the positive and negative electrodes,respectively.Through theoretical derivation,mathematical equations are established to describe various processes within the battery,including solid-phase diffusion,li-quidphase diffusion,reaction polarization,and ohmic polarization.In addition,a method for obtaining model parameters is proposed.Finally,the model is experimentally validated by using lithium iron phosphate and nickel-cobalt-manganese lithium-ion batteries under constant current conditions.The identified battery elec-trochemical model parameters are within reasonable accuracy as evidenced by the experimental validation results.展开更多
In this paper,we present a finite volume trigonometric weighted essentially non-oscillatory(TWENO)scheme to solve nonlinear degenerate parabolic equations that may exhibit non-smooth solutions.The present method is de...In this paper,we present a finite volume trigonometric weighted essentially non-oscillatory(TWENO)scheme to solve nonlinear degenerate parabolic equations that may exhibit non-smooth solutions.The present method is developed using the trigonometric scheme,which is based on zero,first,and second moments,and the direct discontinuous Galerkin(DDG)flux is used to discretize the diffusion term.Moreover,the DDG method directly applies the weak form of the parabolic equation to each computational cell,which can better capture the characteristics of the solution,especially the discontinuous solution.Meanwhile,the third-order TVD-Runge-Kutta method is applied for temporal discretization.Finally,the effectiveness and stability of the method constructed in this paper are evaluated through numerical tests.展开更多
(Quasi-)closed-form results for the statistical properties of unmanned aerial vehicle(UAV)airto-ground channels are derived for the first time using a novel spatial-vector-based method from a threedimensional(3-D)arbi...(Quasi-)closed-form results for the statistical properties of unmanned aerial vehicle(UAV)airto-ground channels are derived for the first time using a novel spatial-vector-based method from a threedimensional(3-D)arbitrary-elevation one-cylinder model.The derived results include a closed-form expression for the space-time correlation function and some quasi-closed-form ones for the space-Doppler power spectrum density,the level crossing rate,and the average fading duration,which are shown to be the generalizations of those previously obtained from the two-dimensional(2-D)one-ring model and the 3-D low-elevation one-cylinder model for terrestrial mobile-to-mobile channels.The close agreements between the theoretical results and the simulations as well as the measurements validate the utility of the derived channel statistics.Based on the derived expressions,the impacts of some parameters on the channel characteristics are investigated in an effective,efficient,and explicable way,which leads to a general guideline on the manual parameter estimation from the measurement description.展开更多
The shale gas development in China faces challenges such as complex reservoir conditions and high development costs.Based on the pore pressure and geostress coupling theory,this paper studies the geostress evolution l...The shale gas development in China faces challenges such as complex reservoir conditions and high development costs.Based on the pore pressure and geostress coupling theory,this paper studies the geostress evolution laws and fracture network characteristics of shale gas infill wells.A mechanism model of CN platform logging data and geomechanical parameters is established to simulate the influence of parent well’s production on the geostress in the infill well area.It is suggested that with the increase of production time,normal fault stress state and horizontal stress deflection will occur.The smaller the parent well spacing and the longer the production time,the earlier the normal fault stress state appears and the larger the range.Based on the model,the fracture network morphology and construction parameters of infill wells are optimized.parentparentparentparent The results indicate that:1:A well spacing of 500 m achieves a Pareto optimum between“full reserve coverage”and“stress barrier”;2:A parent well recovery degree of 30%corresponds to the critical point of stress reversal,where the lateral deflection rate of the infill fracture is less than 8%and the SRV loss is minimized;3:6-cluster intensive completion with twice the liquid intensity increases the fracture complexity index by 1.7 times,enhances well group EUR by 15.4%,and reduces single-well cost by 22%.This research fills the theoretical gap in the collaborative optimization of“multi-parameter,multi-objective and multi-constraint”and provide parameter optimization basis for shale gas infill well development in China and help to improve the development efficiency and economic benefits.展开更多
Accurate estimation of photovoltaic(PV)parameters is essential for optimizing solar module perfor-mance and enhancing resource efficiency in renewable energy systems.This study presents a process innovation by introdu...Accurate estimation of photovoltaic(PV)parameters is essential for optimizing solar module perfor-mance and enhancing resource efficiency in renewable energy systems.This study presents a process innovation by introducing,for the first time,the Triangulation Topology Aggregation Optimizer(TTAO)integrated with parallel computing to address PV parameter estimation challenges.The effectiveness and robustness of TTAO are rigorously evaluated using two standard benchmark datasets(KC200GT and R.T.C.France solar cells)and a real-world dataset(Poly70W solar module)under single-,double-,and triple-diode configurations.Results show that TTAO consistently achieves superior accuracy by producing the lowest RMSE values and faster convergence compared to state-of-the-art metaheuristic algorithms.In addition,the integration of parallel computing significantly enhances computational efficiency,reducing execution time by up to 85%without compromising accuracy.Validation using real-world data further demonstrates TTAO’s adaptability and practical relevance in renewable energy systems,effectively bridging the gap between theoretical modeling and real-world implementation for PV system monitoring and optimization,contributing to climate mitigation through improved solar energy performance.展开更多
Load frequency control(LFC)is a critical function to balance the power consumption and generation.Thegrid frequency is a crucial indicator for maintaining balance.However,the widely used information and communication ...Load frequency control(LFC)is a critical function to balance the power consumption and generation.Thegrid frequency is a crucial indicator for maintaining balance.However,the widely used information and communication infrastructure for LFC increases the risk of being attacked by malicious actors.The dynamic load altering attack(DLAA)is a typical attack that can destabilize the power system,causing the grid frequency to deviate fromits nominal value.Therefore,in this paper,we mathematically analyze the impact of DLAA on the stability of the grid frequency and propose the network parameter regulation(NPR)to mitigate the impact.To begin with,the dynamic LFC model is constructed by highlighting the importance of the network parameter.Then,we model the DLAA and analyze its impact on LFC using the theory of second-order dynamic systems.Finally,we model the NPR and prove its effect in mitigating the DLAA.Besides,we construct a least-effort NPR considering its infrastructure cost and aim to reduce the operation cost.Finally,we carry out extensive simulations to demonstrate the impact of the DLAA and evaluate the mitigation performance of NPR.The proposed cost-benefit NPR approach can not only mitigate the impact of DLAA with 100%and also save 41.18$/MWh in terms of the operation cost.展开更多
Accurate parameter extraction of photovoltaic(PV)models plays a critical role in enabling precise performance prediction,optimal system sizing,and effective operational control under diverse environmental conditions.W...Accurate parameter extraction of photovoltaic(PV)models plays a critical role in enabling precise performance prediction,optimal system sizing,and effective operational control under diverse environmental conditions.While a wide range of metaheuristic optimisation techniques have been applied to this problem,many existing methods are hindered by slow convergence rates,susceptibility to premature stagnation,and reduced accuracy when applied to complex multi-diode PV configurations.These limitations can lead to suboptimal modelling,reducing the efficiency of PV system design and operation.In this work,we propose an enhanced hybrid optimisation approach,the modified Spider Wasp Optimization(mSWO)with Opposition-Based Learning algorithm,which integrates the exploration and exploitation capabilities of the Spider Wasp Optimization(SWO)metaheuristic with the diversityenhancing mechanism of Opposition-Based Learning(OBL).The hybridisation is designed to dynamically expand the search space coverage,avoid premature convergence,and improve both convergence speed and precision in highdimensional optimisation tasks.The mSWO algorithm is applied to three well-established PV configurations:the single diode model(SDM),the double diode model(DDM),and the triple diode model(TDM).Real experimental current-voltage(I-V)datasets from a commercial PV module under standard test conditions(STC)are used for evaluation.Comparative analysis is conducted against eighteen advanced metaheuristic algorithms,including BSDE,RLGBO,GWOCS,MFO,EO,TSA,and SCA.Performance metrics include minimum,mean,and maximum root mean square error(RMSE),standard deviation(SD),and convergence behaviour over 30 independent runs.The results reveal that mSWO consistently delivers superior accuracy and robustness across all PV models,achieving the lowest RMSE values of 0.000986022(SDM),0.000982884(DDM),and 0.000982529(TDM),with minimal SD values,indicating remarkable repeatability.Convergence analyses further show that mSWO reaches optimal solutions more rapidly and with fewer oscillations than all competing methods,with the performance gap widening as model complexity increases.These findings demonstrate that mSWO provides a scalable,computationally efficient,and highly reliable framework for PV parameter extraction.Its adaptability to models of growing complexity suggests strong potential for broader applications in renewable energy systems,including performance monitoring,fault detection,and intelligent control,thereby contributing to the optimisation of next-generation solar energy solutions.展开更多
The internal flow fields within a three-dimensional inward-tunning combined inlet are extremely complex,especially during the engine mode transition,where the tunnel changes may impact the flow fields significantly.To...The internal flow fields within a three-dimensional inward-tunning combined inlet are extremely complex,especially during the engine mode transition,where the tunnel changes may impact the flow fields significantly.To develop an efficient flow field reconstruction model for this,we present an Improved Conditional Denoising Diffusion Generative Adversarial Network(ICDDGAN),which integrates Conditional Denoising Diffusion Probabilistic Models(CDDPMs)with Style GAN,and introduce a reconstruction discrimination mechanism and dynamic loss weight learning strategy.We establish the Mach number flow field dataset by numerical simulation at various backpressures for the mode transition process from turbine mode to ejector ramjet mode at Mach number 2.5.The proposed ICDDGAN model,given only sparse parameter information,can rapidly generate high-quality Mach number flow fields without a large number of samples for training.The results show that ICDDGAN is superior to CDDGAN in terms of training convergence and stability.Moreover,the interpolation and extrapolation test results during backpressure conditions show that ICDDGAN can accurately and quickly reconstruct Mach number fields at various tunnel slice shapes,with a Structural Similarity Index Measure(SSIM)of over 0.96 and a Mean-Square Error(MSE)of 0.035%to actual flow fields,reducing time costs by 7-8 orders of magnitude compared to Computational Fluid Dynamics(CFD)calculations.This can provide an efficient means for rapid computation of complex flow fields.展开更多
In this study, we mainly introduce two salinity parameterization schemes used in Sea Ice Simulator （SIS）, that is, isosaline scheme and salinity profile scheme. Comparing the equation of isosaline scheme with that o...In this study, we mainly introduce two salinity parameterization schemes used in Sea Ice Simulator （SIS）, that is, isosaline scheme and salinity profile scheme. Comparing the equation of isosaline scheme with that of salinity profile scheme, we found that there was one different term between the two schemes named the salinity different term. The thermodynamic effect of the salinity difference term on sea ice thickness and sea ice concentration showed that： in the freezing processes from November to next May, the sea ice temperature could rise on the influence of the salinity difference term and restrain sea ice freezing; at the first melting phase from June to August, the upper ice melting rate was faster than the lower ice melting rate. Then sea ice temperature could rise and accelerate the sea ice melting; at the second melting phase from September to October, the upper ice melting rate was slower than the lower ice melting rate, then sea ice temperature could decrease and restrain sea ice melting. However, the effect of the salinity difference term on the sea ice thickness and sea ice concentration was weak. To analyze the impacts of the salinity different term on Arctic sea ice thickness and sea ice concentration, we also designed several experiments by introducing the two salinity parameterizations to the ice-ocean coupled model, Modular Ocean Model （MOM4）, respectively. The simulated results confirmed the previous results of formula derivation.展开更多
Improving and validating land surface models based on integrated observations in deserts is one of the challenges in land modeling. Particularly, key parameters and parameterization schemes in desert regions need to b...Improving and validating land surface models based on integrated observations in deserts is one of the challenges in land modeling. Particularly, key parameters and parameterization schemes in desert regions need to be evaluated in-situ to improve the models. In this study, we calibrated the land-surface key parameters and evaluated several formulations or schemes for thermal roughness length （z 0h ） in the common land model （CoLM）. Our parameter calibration and scheme evaluation were based on the observed data during a torrid summer （29 July to 11 September 2009） over the Taklimakan Desert hinterland. First, the importance of the key parameters in the experiment was evaluated based on their physics principles and the significance of these key parameters were further validated using sensitivity test. Second, difference schemes （or physics-based formulas） of z 0h were adopted to simulate the variations of energy-related variables （e.g., sensible heat flux and surface skin temperature） and the simulated variations were then compared with the observed data. Third, the z 0h scheme that performed best （i.e., Y07） was then selected to replace the defaulted one （i.e., Z98）; the revised scheme and the superiority of Y07 over Z98 was further demonstrated by comparing the simulated results with the observed data. Admittedly, the revised model did a relatively poor job of simulating the diurnal variations of surface soil heat flux, and nighttime soil temperature was also underestimated, calling for further improvement of the model for desert regions.展开更多
We use the Wind Farm Parameterization(WFP) scheme coupled with the Weather Research and Forecasting model under multiple resolution regimes to simulate turbulent wake dynamics generated by a real onshore wind farm and...We use the Wind Farm Parameterization(WFP) scheme coupled with the Weather Research and Forecasting model under multiple resolution regimes to simulate turbulent wake dynamics generated by a real onshore wind farm and their influence at the local meteorological scale. The model outputs are compared with earlier modeling and observation studies. It is found that higher vertical and horizontal resolutions have great impacts on the simulated wake flow dynamics. The corresponding wind speed deficit and turbulent kinetic energy results match well with previous studies. In addition, the effect of horizontal resolution on near-surface meteorology is significantly higher than that of vertical resolution. The wake flow field extends from the start of the wind farm to downstream within 10 km, where the wind speed deficit may exceed 4%. For a height of 150 m or at a distance of about 25 km downstream, the wind speed deficit is around 2%. This indicates that, at a distance of more than 25 km downstream, the impact of the wind turbines can be ignored. Analysis of near-surface meteorology indicates a night and early morning warming near the surface, and increase in near-surface water vapor mixing ratio with decreasing surface sensible and latent heat fluxes. During daytime, a slight cooling near the surface and decrease in the near-surface water vapor mixing ratio with increasing surface sensible and latent heat fluxes is noticed over the wind farm area.展开更多
The formation and development of typhoons are closely related to the disturbed low vortexes at the planetary boundary layer(PBL). The effects of five PBL parameterization schemes(PBL schemes hereinafter) on the trajec...The formation and development of typhoons are closely related to the disturbed low vortexes at the planetary boundary layer(PBL). The effects of five PBL parameterization schemes(PBL schemes hereinafter) on the trajectory,intensity, and distribution of physical quantities are studied using the mesoscale WRF model on Super Typhoon Sanba(2012) during its initial stage. Results show that the five PBL schemes exhibit significant different effects on the simulated intensity and path. The results simulated by QNSE and ACM2 without the Bogus method are close to the best track data in the numerical experiments. When the Bogus method is adopted, the simulated trajectories improve significantly because the initial field is close to the true data. Among the five PBL schemes, QNSE and ACM2 with the Bogus method present improved simulated path and intensity compared with the three other schemes. This finding indicates that the two schemes deal with the initial PBL process satisfactorily, especially in the formation and development of disturbed low vortexes. The differences in the treatment methods of the five PBL schemes affect the surface layer physical quantities and the middle and upper atmospheres during the middle to late periods of the typhoon.Although QNSE and ACM2 present better simulation results than other schemes, they exhibit a few differences in the internal structure of the typhoon. The results simulated by MYJ are worse, and this method may be unsuitable for studying the formation and development of typhoons.展开更多
This study discusses the sensitivity of convective parameterization schemes（CPSs） in the Regional Climate Model（version 4.3）（Reg CM4.3） over East/South Asia. The simulations using different CPSs in Reg CM are co...This study discusses the sensitivity of convective parameterization schemes（CPSs） in the Regional Climate Model（version 4.3）（Reg CM4.3） over East/South Asia. The simulations using different CPSs in Reg CM are compared to discover a suitable scheme for this region, as the performance of different schemes is greatly influenced by region and seasonality. Over Southeast China and the Bay of Bengal, the Grell scheme exhibits the lowest RMSEs of summer precipitation compared to observed data. Moreover, the Emanuel over land and Grell over ocean（ELGO） scheme enhances the simulation, in comparison with any single CPS（Grell/Emanuel） over Western Ghats, Sri Lanka, and Southeast India. Over the Huang–Huai–Hai Plain（3H） and Tibetan Plateau（TP） regions of China, the Tiedtke scheme simulates the more reasonable summer precipitation with high correlation coefficient and comparable amplitude. Especially, it reproduces a minimum convective precipitation bias of 8 mm d^-1and the lowest RMSEs throughout the year over East/South Asia. Furthermore, for seasonal variation of precipitation, the Tiedtke scheme results are closer to the observed data over the 3H and TP regions. However, none of the CPSs is able to simulate the seasonal variation over North Pakistan（NP）. In comparison with previous research, the results of this study support the Grell scheme over South Asia. However, the Tiedtke scheme shows superiority for the 3H, TP and NP regions. The thicker PBL, less surface latent heat flux, the unique ability of deep convection and the entrainment process in the Tiedtke scheme are responsible for reducing the wet bias.展开更多
基金supported by the National Key Research and Development Program of China (Grant No.2022YFF0802004)the Excellent Youth Natural Science Foundation of Jiangsu Province (BK20230061)+1 种基金the Joint Open Project of KLME&CIC-FEMD (Grant No.KLME202501)Jiangsu Innovation Research Group (Grant No.JSSCTD 202346)。
文摘The Zebiak–Cane(ZC) model, renowned as a coupled ocean-atmosphere model specifically designed to simulate and predict El Ni??o-Southern Oscillation(ENSO), is an indispensable tool for ENSO studies. However, the original ZC model exhibits certain biases in reproducing the ENSO–related sea surface temperature anomalies and heating anomalies, limiting its broader applicability. To improve the accuracy of ENSO simulation, we propose a modified ZC model based on Xie et al.(2015), named the MZC_XJH model, through refining the heating parameterization scheme. The performance in simulating the nonlinear SST–precipitation relationship in the MZC_XJH model is firstly elaborated. Then, we investigate the impacts of three key atmospheric parameters on ENSO simulation by conducting experiments with the MZC_XJH model. Through assessing the performance in simulating five fundamental ENSO metrics(amplitude, periodicity,seasonality, diversity, and skewness), we uncover that the sensitivities of simulated ENSO behaviors to different parameters are distinct. Moreover, we explain why a particular parameter greatly affects some simulated ENSO behaviors while others exert minor influence. We also reveal that the nonlinear effect due to the covariation of multi-parameters on ENSO simulation warrants careful consideration when tuning multi-parameters synchronously. Lastly, we present an updated version of the MZC_XJH model, in which some biases have been mitigated but some remain obvious. Although there are no universally optimal parameters that would ensure flawless performance in simulating every aspect of ENSO, this study provides a valuable reference for tuning atmospheric parameters in the MZC_XJH model, rendering the MZC_XJH model applicable to some research objectives.
基金supported by the National Natural Science Foundation of China(Grant Nos.41975090,U2242201,42075077)the Natural Science Foundation of Hunan Province,China(2022JJ20043)the Science and Technology Innovation Program of Hunan Province,China(2022RC1239)。
文摘In this study,the Betts-Miller-Janjic(BMJ)convective adjustment scheme in the Weather Research and Forecasting(WRF)model version 4.0 was used to investigate the effect of itsα-parameter,which influences the first-guess potential temperature reference profile on the Madden-Julian oscillation(MJO)propagation and structure.This study diagnosed the MJO active phase composites of the MJO-filtered outgoing longwave radiation(OLR)during the December-to-February(DJF)period of 2006-2016 over the Indian Ocean(IO),Maritime Continent(MC),and western Pacific(WP).The results show that the MJO-filtered OLR intensity,propagation pattern,and MJO classification(standing,jumping,and propagating clusters)are sensitive to theα-value,but the phase speeds of propagating MJOs are not.Overall,with an increasingα-value,the simulated MJO-filtered OLR intensity increases,and the simulated propagation pattern is improved.Results also show that the intensity and propagation pattern of an eastward-propagating MJO are associated with MJO circulation structures and thermodynamic structures.Asαincreases,the front Walker cell and the low-level easterly anomaly are enhanced,which premoistens the lower troposphere and triggers more active shallow and congestus clouds.The enhanced shallow and congestus convection preconditions the lower to middle troposphere,accelerating the transition from congestus to deep convection,thereby facilitating eastward propagation of the MJO.Therefore,the simulated MJO tends to transfer from standing to eastward propagating asαincreases.In summary,increasing theα-value is a possible way to improve the simulation of the structure and propagation of the MJO.
基金Key-Area Research and Development Program of Guangdong (2020B1111200001)National Natural Science Foundation of China (42230105, U2142213, 42175167)。
文摘Taking short-duration heavy rainfall and convective wind gusts as examples, the present study examined the characteristics of radar reflectivity and several convective parameters. We analyzed nowcasting techniques by integrating a high-resolution numerical weather prediction model with these convective parameters. Based on the CMA-GD 1-km model and its assimilation system, we conducted repeated tests on radar reflectivity data assimilation and analyzed their impact on nowcasting accuracy. Based on these analyses, we proposed a method to improve model forecasts using the useful indicative information provided by high-frequency radar reflectivity data and convective parameters. The improved method was applied to the CMA-GD 1-km model for nowcasting tests. Evaluations from batch tests and case analysis show that the proposed method significantly reduced the model's false alarm rates and improved its nowcasting performance.
基金supported by the National Key R&D Program of China[grant number 2023YFC3008004]。
文摘This study introduces a new ocean surface friction velocity scheme and a modified Thompson cloud microphysics parameterization scheme into the CMA-TYM model.The impact of these two parameterization schemes on the prediction of the movement track and intensity of Typhoon Kompasu in 2021 is examined.Additionally,the possible reasons for their effects on tropical cyclone(TC)intensity prediction are analyzed.Statistical results show that both parameterization schemes improve the predictions of Typhoon Kompasu’s track and intensity.The influence on track prediction becomes evident after 60 h of model integration,while the significant positive impact on intensity prediction is observed after 66 h.Further analysis reveals that these two schemes affect the timing and magnitude of extreme TC intensity values by influencing the evolution of the TC’s warm-core structure.
基金supported by the Key Project of Joint Fund of the National Natural Science Foundation of China“Research on Key Technologies and Demonstration Applications for Trusted and Secure Data Circulation and Trading”(U24A20241)the National Natural Science Foundation of China“Research on Trusted Theories and Key Technologies of Data Security Trading Based on Blockchain”(62202118)+4 种基金the Major Scientific and Technological Special Project of Guizhou Province([2024]014)Scientific and Technological Research Projects from the Guizhou Education Department(Qian jiao ji[2023]003)the Hundred-Level Innovative Talent Project of the Guizhou Provincial Science and Technology Department(Qiankehe Platform Talent-GCC[2023]018)the Major Project of Guizhou Province“Research and Application of Key Technologies for Trusted Large Models Oriented to Public Big Data”(Qiankehe Major Project[2024]003)the Guizhou Province Computational Power Network Security Protection Science and Technology Innovation Talent Team(Qiankehe Talent CXTD[2025]029).
文摘As blockchain technology rapidly evolves,smart contracts have seen widespread adoption in financial transactions and beyond.However,the growing prevalence of malicious Ponzi scheme contracts presents serious security threats to blockchain ecosystems.Although numerous detection techniques have been proposed,existing methods suffer from significant limitations,such as class imbalance and insufficient modeling of transaction-related semantic features.To address these challenges,this paper proposes an oversampling-based detection framework for Ponzi smart contracts.We enhance the Adaptive Synthetic Sampling(ADASYN)algorithm by incorporating sample proximity to decision boundaries and ensuring realistic sample distributions.This enhancement facilitates the generation of high-quality minority class samples and effectively mitigates class imbalance.In addition,we design a Contract Transaction Graph(CTG)construction algorithm to preserve key transactional semantics through feature extraction from contract code.A graph neural network(GNN)is then applied for classification.This study employs a publicly available dataset from the XBlock platform,consisting of 318 verified Ponzi contracts and 6498 benign contracts.Sourced from real Ethereum deployments,the dataset reflects diverse application scenarios and captures the varied characteristics of Ponzi schemes.Experimental results demonstrate that our approach achieves an accuracy of 96%,a recall of 92%,and an F1-score of 94%in detecting Ponzi contracts,outperforming state-of-the-art methods.
文摘Hepatocellular carcinoma presents with three distinct immune phenotypes,including immune-desert,immune-excluded,and immune-inflamed,indicating various treatment responses and prognostic outcomes.The clinical application of multi-omics parameters is still restricted by the expensive and less accessible assays,although they accurately reflect immune status.A comprehensive evaluation framework based on“easy-to-obtain”multi-model clinical parameters is urgently required,incorporating clinical features to establish baseline patient profiles and disease staging;routine blood tests assessing systemic metabolic and functional status;immune cell subsets quantifying subcluster dynamics;imaging features delineating tumor morphology,spatial configuration,and perilesional anatomical relationships;immunohistochemical markers positioning qualitative and quantitative detection of tumor antigens from the cellular and molecular level.This integrated phenomic approach aims to improve prognostic stratification and clinical decision-making in hepatocellular carcinoma management conveniently and practically.
基金Supported by the National Natural Science Foundation of China(Grant Nos.52407238,52177210)the Youth Foundation of Shandong Provincial Natural Science Foundation(Grant No.ZR2023QE036).
文摘Electrochemical models,characterized by high fidelity and physical interpretability,have been applied in var-ious fields such as fast charging,battery state estimation,and battery material design.Currently,widely utilized single particle-based model exhibits high computational efficiency but suffers from low simulation accuracy under high-rate charge/discharge conditions.In this work,an electrochemical model for lithium-ion batteries based on multi-particle hypothesis is developed.Two particles are employed to represent the electrode char-acteristics of the positive and negative electrodes,respectively.Through theoretical derivation,mathematical equations are established to describe various processes within the battery,including solid-phase diffusion,li-quidphase diffusion,reaction polarization,and ohmic polarization.In addition,a method for obtaining model parameters is proposed.Finally,the model is experimentally validated by using lithium iron phosphate and nickel-cobalt-manganese lithium-ion batteries under constant current conditions.The identified battery elec-trochemical model parameters are within reasonable accuracy as evidenced by the experimental validation results.
基金The Natural Science Foundation of Xinjiang Uygur Autonomous Region of China“RBF-Hermite difference scheme for the time-fractional kdv-Burgers equation”(2024D01C43)。
文摘In this paper,we present a finite volume trigonometric weighted essentially non-oscillatory(TWENO)scheme to solve nonlinear degenerate parabolic equations that may exhibit non-smooth solutions.The present method is developed using the trigonometric scheme,which is based on zero,first,and second moments,and the direct discontinuous Galerkin(DDG)flux is used to discretize the diffusion term.Moreover,the DDG method directly applies the weak form of the parabolic equation to each computational cell,which can better capture the characteristics of the solution,especially the discontinuous solution.Meanwhile,the third-order TVD-Runge-Kutta method is applied for temporal discretization.Finally,the effectiveness and stability of the method constructed in this paper are evaluated through numerical tests.
基金supported in part by the National Key Research and Development Program of China(2021YFB2900501)in part by the Shaanxi Science and Technology Innovation Team(2023-CX-TD-03)+3 种基金in part by the Science and Technology Program of Shaanxi Province(2021GXLH-Z-038)in part by the Natural Science Foundation of Hunan Province(2023JJ40607 and 2023JJ50045)in part by the Scientific Research Foundation of Hunan Provincial Education Department(23B0713 and 24B0603)in part by the National Natural Science Foundation of China(62401371,62101275,and 62372070).
文摘(Quasi-)closed-form results for the statistical properties of unmanned aerial vehicle(UAV)airto-ground channels are derived for the first time using a novel spatial-vector-based method from a threedimensional(3-D)arbitrary-elevation one-cylinder model.The derived results include a closed-form expression for the space-time correlation function and some quasi-closed-form ones for the space-Doppler power spectrum density,the level crossing rate,and the average fading duration,which are shown to be the generalizations of those previously obtained from the two-dimensional(2-D)one-ring model and the 3-D low-elevation one-cylinder model for terrestrial mobile-to-mobile channels.The close agreements between the theoretical results and the simulations as well as the measurements validate the utility of the derived channel statistics.Based on the derived expressions,the impacts of some parameters on the channel characteristics are investigated in an effective,efficient,and explicable way,which leads to a general guideline on the manual parameter estimation from the measurement description.
文摘The shale gas development in China faces challenges such as complex reservoir conditions and high development costs.Based on the pore pressure and geostress coupling theory,this paper studies the geostress evolution laws and fracture network characteristics of shale gas infill wells.A mechanism model of CN platform logging data and geomechanical parameters is established to simulate the influence of parent well’s production on the geostress in the infill well area.It is suggested that with the increase of production time,normal fault stress state and horizontal stress deflection will occur.The smaller the parent well spacing and the longer the production time,the earlier the normal fault stress state appears and the larger the range.Based on the model,the fracture network morphology and construction parameters of infill wells are optimized.parentparentparentparent The results indicate that:1:A well spacing of 500 m achieves a Pareto optimum between“full reserve coverage”and“stress barrier”;2:A parent well recovery degree of 30%corresponds to the critical point of stress reversal,where the lateral deflection rate of the infill fracture is less than 8%and the SRV loss is minimized;3:6-cluster intensive completion with twice the liquid intensity increases the fracture complexity index by 1.7 times,enhances well group EUR by 15.4%,and reduces single-well cost by 22%.This research fills the theoretical gap in the collaborative optimization of“multi-parameter,multi-objective and multi-constraint”and provide parameter optimization basis for shale gas infill well development in China and help to improve the development efficiency and economic benefits.
基金funded by the Malaysian Ministry of Higher Education through the Fundamental Research Grant Scheme(FRGS/1/2024/ICT02/UCSI/02/1).
文摘Accurate estimation of photovoltaic(PV)parameters is essential for optimizing solar module perfor-mance and enhancing resource efficiency in renewable energy systems.This study presents a process innovation by introducing,for the first time,the Triangulation Topology Aggregation Optimizer(TTAO)integrated with parallel computing to address PV parameter estimation challenges.The effectiveness and robustness of TTAO are rigorously evaluated using two standard benchmark datasets(KC200GT and R.T.C.France solar cells)and a real-world dataset(Poly70W solar module)under single-,double-,and triple-diode configurations.Results show that TTAO consistently achieves superior accuracy by producing the lowest RMSE values and faster convergence compared to state-of-the-art metaheuristic algorithms.In addition,the integration of parallel computing significantly enhances computational efficiency,reducing execution time by up to 85%without compromising accuracy.Validation using real-world data further demonstrates TTAO’s adaptability and practical relevance in renewable energy systems,effectively bridging the gap between theoretical modeling and real-world implementation for PV system monitoring and optimization,contributing to climate mitigation through improved solar energy performance.
基金supported by the project Major Scientific and Technological Special Project of Guizhou Province([2024]014).
文摘Load frequency control(LFC)is a critical function to balance the power consumption and generation.Thegrid frequency is a crucial indicator for maintaining balance.However,the widely used information and communication infrastructure for LFC increases the risk of being attacked by malicious actors.The dynamic load altering attack(DLAA)is a typical attack that can destabilize the power system,causing the grid frequency to deviate fromits nominal value.Therefore,in this paper,we mathematically analyze the impact of DLAA on the stability of the grid frequency and propose the network parameter regulation(NPR)to mitigate the impact.To begin with,the dynamic LFC model is constructed by highlighting the importance of the network parameter.Then,we model the DLAA and analyze its impact on LFC using the theory of second-order dynamic systems.Finally,we model the NPR and prove its effect in mitigating the DLAA.Besides,we construct a least-effort NPR considering its infrastructure cost and aim to reduce the operation cost.Finally,we carry out extensive simulations to demonstrate the impact of the DLAA and evaluate the mitigation performance of NPR.The proposed cost-benefit NPR approach can not only mitigate the impact of DLAA with 100%and also save 41.18$/MWh in terms of the operation cost.
基金funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R442)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Accurate parameter extraction of photovoltaic(PV)models plays a critical role in enabling precise performance prediction,optimal system sizing,and effective operational control under diverse environmental conditions.While a wide range of metaheuristic optimisation techniques have been applied to this problem,many existing methods are hindered by slow convergence rates,susceptibility to premature stagnation,and reduced accuracy when applied to complex multi-diode PV configurations.These limitations can lead to suboptimal modelling,reducing the efficiency of PV system design and operation.In this work,we propose an enhanced hybrid optimisation approach,the modified Spider Wasp Optimization(mSWO)with Opposition-Based Learning algorithm,which integrates the exploration and exploitation capabilities of the Spider Wasp Optimization(SWO)metaheuristic with the diversityenhancing mechanism of Opposition-Based Learning(OBL).The hybridisation is designed to dynamically expand the search space coverage,avoid premature convergence,and improve both convergence speed and precision in highdimensional optimisation tasks.The mSWO algorithm is applied to three well-established PV configurations:the single diode model(SDM),the double diode model(DDM),and the triple diode model(TDM).Real experimental current-voltage(I-V)datasets from a commercial PV module under standard test conditions(STC)are used for evaluation.Comparative analysis is conducted against eighteen advanced metaheuristic algorithms,including BSDE,RLGBO,GWOCS,MFO,EO,TSA,and SCA.Performance metrics include minimum,mean,and maximum root mean square error(RMSE),standard deviation(SD),and convergence behaviour over 30 independent runs.The results reveal that mSWO consistently delivers superior accuracy and robustness across all PV models,achieving the lowest RMSE values of 0.000986022(SDM),0.000982884(DDM),and 0.000982529(TDM),with minimal SD values,indicating remarkable repeatability.Convergence analyses further show that mSWO reaches optimal solutions more rapidly and with fewer oscillations than all competing methods,with the performance gap widening as model complexity increases.These findings demonstrate that mSWO provides a scalable,computationally efficient,and highly reliable framework for PV parameter extraction.Its adaptability to models of growing complexity suggests strong potential for broader applications in renewable energy systems,including performance monitoring,fault detection,and intelligent control,thereby contributing to the optimisation of next-generation solar energy solutions.
文摘The internal flow fields within a three-dimensional inward-tunning combined inlet are extremely complex,especially during the engine mode transition,where the tunnel changes may impact the flow fields significantly.To develop an efficient flow field reconstruction model for this,we present an Improved Conditional Denoising Diffusion Generative Adversarial Network(ICDDGAN),which integrates Conditional Denoising Diffusion Probabilistic Models(CDDPMs)with Style GAN,and introduce a reconstruction discrimination mechanism and dynamic loss weight learning strategy.We establish the Mach number flow field dataset by numerical simulation at various backpressures for the mode transition process from turbine mode to ejector ramjet mode at Mach number 2.5.The proposed ICDDGAN model,given only sparse parameter information,can rapidly generate high-quality Mach number flow fields without a large number of samples for training.The results show that ICDDGAN is superior to CDDGAN in terms of training convergence and stability.Moreover,the interpolation and extrapolation test results during backpressure conditions show that ICDDGAN can accurately and quickly reconstruct Mach number fields at various tunnel slice shapes,with a Structural Similarity Index Measure(SSIM)of over 0.96 and a Mean-Square Error(MSE)of 0.035%to actual flow fields,reducing time costs by 7-8 orders of magnitude compared to Computational Fluid Dynamics(CFD)calculations.This can provide an efficient means for rapid computation of complex flow fields.
基金supported by the National Natural Science Foundation of China(No.41075030,41106004,41106159 and 41206013)the Ocean Public Welfare Science Research Project,State Oceanic Administration,People's Republic of China(No.201005019)
文摘In this study, we mainly introduce two salinity parameterization schemes used in Sea Ice Simulator （SIS）, that is, isosaline scheme and salinity profile scheme. Comparing the equation of isosaline scheme with that of salinity profile scheme, we found that there was one different term between the two schemes named the salinity different term. The thermodynamic effect of the salinity difference term on sea ice thickness and sea ice concentration showed that： in the freezing processes from November to next May, the sea ice temperature could rise on the influence of the salinity difference term and restrain sea ice freezing; at the first melting phase from June to August, the upper ice melting rate was faster than the lower ice melting rate. Then sea ice temperature could rise and accelerate the sea ice melting; at the second melting phase from September to October, the upper ice melting rate was slower than the lower ice melting rate, then sea ice temperature could decrease and restrain sea ice melting. However, the effect of the salinity difference term on the sea ice thickness and sea ice concentration was weak. To analyze the impacts of the salinity different term on Arctic sea ice thickness and sea ice concentration, we also designed several experiments by introducing the two salinity parameterizations to the ice-ocean coupled model, Modular Ocean Model （MOM4）, respectively. The simulated results confirmed the previous results of formula derivation.
基金jointly funded by the National Natural Science Foundation of China(GrantNo40775019)Desert Meteorology Science Foundation of China(Grant NoSqj2009012)Project of Key Laboratory of Oasis Ecology(Xinjiang University)Ministry of Education(Grant NoXJDX0206-2009-08)
文摘Improving and validating land surface models based on integrated observations in deserts is one of the challenges in land modeling. Particularly, key parameters and parameterization schemes in desert regions need to be evaluated in-situ to improve the models. In this study, we calibrated the land-surface key parameters and evaluated several formulations or schemes for thermal roughness length （z 0h ） in the common land model （CoLM）. Our parameter calibration and scheme evaluation were based on the observed data during a torrid summer （29 July to 11 September 2009） over the Taklimakan Desert hinterland. First, the importance of the key parameters in the experiment was evaluated based on their physics principles and the significance of these key parameters were further validated using sensitivity test. Second, difference schemes （or physics-based formulas） of z 0h were adopted to simulate the variations of energy-related variables （e.g., sensible heat flux and surface skin temperature） and the simulated variations were then compared with the observed data. Third, the z 0h scheme that performed best （i.e., Y07） was then selected to replace the defaulted one （i.e., Z98）; the revised scheme and the superiority of Y07 over Z98 was further demonstrated by comparing the simulated results with the observed data. Admittedly, the revised model did a relatively poor job of simulating the diurnal variations of surface soil heat flux, and nighttime soil temperature was also underestimated, calling for further improvement of the model for desert regions.
基金the National Key Research and Development Program of China (Grant No.2017YFA0604501)the National Natural Science Foundation of China (Grant No.41475013) for the funding support
文摘We use the Wind Farm Parameterization(WFP) scheme coupled with the Weather Research and Forecasting model under multiple resolution regimes to simulate turbulent wake dynamics generated by a real onshore wind farm and their influence at the local meteorological scale. The model outputs are compared with earlier modeling and observation studies. It is found that higher vertical and horizontal resolutions have great impacts on the simulated wake flow dynamics. The corresponding wind speed deficit and turbulent kinetic energy results match well with previous studies. In addition, the effect of horizontal resolution on near-surface meteorology is significantly higher than that of vertical resolution. The wake flow field extends from the start of the wind farm to downstream within 10 km, where the wind speed deficit may exceed 4%. For a height of 150 m or at a distance of about 25 km downstream, the wind speed deficit is around 2%. This indicates that, at a distance of more than 25 km downstream, the impact of the wind turbines can be ignored. Analysis of near-surface meteorology indicates a night and early morning warming near the surface, and increase in near-surface water vapor mixing ratio with decreasing surface sensible and latent heat fluxes. During daytime, a slight cooling near the surface and decrease in the near-surface water vapor mixing ratio with increasing surface sensible and latent heat fluxes is noticed over the wind farm area.
基金National Natural Science Foundation of China(41375033,41225018)National Basic Research Program of China(973 Program)(2013CB430100)Fundamental Research Funds for Central Universities of Lanzhou University(LZUJBKY-2013-K16)
文摘The formation and development of typhoons are closely related to the disturbed low vortexes at the planetary boundary layer(PBL). The effects of five PBL parameterization schemes(PBL schemes hereinafter) on the trajectory,intensity, and distribution of physical quantities are studied using the mesoscale WRF model on Super Typhoon Sanba(2012) during its initial stage. Results show that the five PBL schemes exhibit significant different effects on the simulated intensity and path. The results simulated by QNSE and ACM2 without the Bogus method are close to the best track data in the numerical experiments. When the Bogus method is adopted, the simulated trajectories improve significantly because the initial field is close to the true data. Among the five PBL schemes, QNSE and ACM2 with the Bogus method present improved simulated path and intensity compared with the three other schemes. This finding indicates that the two schemes deal with the initial PBL process satisfactorily, especially in the formation and development of disturbed low vortexes. The differences in the treatment methods of the five PBL schemes affect the surface layer physical quantities and the middle and upper atmospheres during the middle to late periods of the typhoon.Although QNSE and ACM2 present better simulation results than other schemes, they exhibit a few differences in the internal structure of the typhoon. The results simulated by MYJ are worse, and this method may be unsuitable for studying the formation and development of typhoons.
基金supported by the Knowledge Innovation Program of the Chinese Academy of Sciences (KZCX2EW-QN208)a project of the National Natural Science Foundation of China (Grant No. 41275082)+1 种基金the National Basic Research Program of China (Grant Nos. 2010CB428502 and 2011CB952003)the R&D Special Fund for Public Welfare Industry (meteorology) of the Ministry of Finance and the Ministry of Science and Technology (GYHY201006014-04)
文摘This study discusses the sensitivity of convective parameterization schemes（CPSs） in the Regional Climate Model（version 4.3）（Reg CM4.3） over East/South Asia. The simulations using different CPSs in Reg CM are compared to discover a suitable scheme for this region, as the performance of different schemes is greatly influenced by region and seasonality. Over Southeast China and the Bay of Bengal, the Grell scheme exhibits the lowest RMSEs of summer precipitation compared to observed data. Moreover, the Emanuel over land and Grell over ocean（ELGO） scheme enhances the simulation, in comparison with any single CPS（Grell/Emanuel） over Western Ghats, Sri Lanka, and Southeast India. Over the Huang–Huai–Hai Plain（3H） and Tibetan Plateau（TP） regions of China, the Tiedtke scheme simulates the more reasonable summer precipitation with high correlation coefficient and comparable amplitude. Especially, it reproduces a minimum convective precipitation bias of 8 mm d^-1and the lowest RMSEs throughout the year over East/South Asia. Furthermore, for seasonal variation of precipitation, the Tiedtke scheme results are closer to the observed data over the 3H and TP regions. However, none of the CPSs is able to simulate the seasonal variation over North Pakistan（NP）. In comparison with previous research, the results of this study support the Grell scheme over South Asia. However, the Tiedtke scheme shows superiority for the 3H, TP and NP regions. The thicker PBL, less surface latent heat flux, the unique ability of deep convection and the entrainment process in the Tiedtke scheme are responsible for reducing the wet bias.
