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
This article explores the evolution of cloud computing, its advantages over traditional on-premises infrastructure, and its impact on information security. The study presents a comprehensive literature review covering...This article explores the evolution of cloud computing, its advantages over traditional on-premises infrastructure, and its impact on information security. The study presents a comprehensive literature review covering various cloud infrastructure offerings and security models. Additionally, it deeply analyzes real-life case studies illustrating successful cloud migrations and highlights common information security threats in current cloud computing. The article concludes by offering recommendations to businesses to protect themselves from cloud data breaches and providing insights into selecting a suitable cloud services provider from an information security perspective.展开更多
Accurate descriptions of cloud droplet spectra from aerosol activation to vapor condensation using microphysical parameterization schemes are crucial for numerical simulations of precipitation and climate change in we...Accurate descriptions of cloud droplet spectra from aerosol activation to vapor condensation using microphysical parameterization schemes are crucial for numerical simulations of precipitation and climate change in weather forecasting and climate prediction models.Hence,the latest activation and triple-moment condensation schemes were combined to simulate and analyze the evolution characteristics of a cloud droplet spectrum from activation to condensation and compared with a high-resolution Lagrangian bin model and the current double-moment condensation schemes,in which the spectral shape parameter is fixed or diagnosed by an empirical formula.The results demonstrate that the latest schemes effectively capture the evolution characteristics of the cloud droplet spectrum during activation and condensation,which is in line with the performance of the bin model.The simulation of the latest activation and condensation schemes in a parcel model shows that the cloud droplet spectrum gradually widens and exhibits a multimodal distribution during the activation process,accompanied by a decrease in the spectral shape and slope parameters over time.Conversely,during the condensation process,the cloud droplet spectrum gradually narrows,resulting in increases in the spectral shape and slope parameters.However,these double-moment schemes fail to accurately replicate the evolution of the cloud droplet spectrum and its multimodal distribution characteristics.Furthermore,the latest schemes were coupled into a 1.5D cumulus model,and an observation case was simulated.The simulations confirm that the cloud droplet spectrum appears wider at the supersaturated cloud base and cloud top due to activation,while it becomes narrower at the middle altitudes of the cloud due to condensation growth.展开更多
The cloud phase composition of cold clouds in the Antarctic atmosphere is explored using data from the Moderate Resolution Imaging Spectroradiometer （MODIS） and Cloud-Aerosol Lidar with Orthogonal Polarization （CAL...The cloud phase composition of cold clouds in the Antarctic atmosphere is explored using data from the Moderate Resolution Imaging Spectroradiometer （MODIS） and Cloud-Aerosol Lidar with Orthogonal Polarization （CALIOP） instruments for the period 2000-2006. We used the averaged fraction of liquid-phase clouds out of the total cloud amount at the cloud tops since the value is comparable in the two measurements. MODIS data for the winter months （June, July, and August） reveal liquid cloud fraction out of the total cloud amount significantly decreases with decreasing cloud-top temperature below 0°C. In addition, the CALIOP vertical profiles show that below the ice clouds, low-lying liquid clouds are distributed over ～20% of the area. With increasing latitude, the liquid cloud fraction decreases as a function of the local temperature. The MODIS-observed relation between the cloud-top liquid fraction and cloud-top temperature is then applied to evaluate the cloud phase parameterization in climate models, in which condensed cloud water is repartitioned between liquid water and ice on the basis of the grid point temperature. It is found that models assuming overly high cut-offs （ -40°C） for the separation of ice clouds from mixed-phase clouds may significantly underestimate the liquid cloud fraction in the winter Antarctic atmosphere. Correction of the bias in the liquid cloud fraction would serve to reduce the large uncertainty in cloud radiative effects.展开更多
In order to improve the efficiency of cloud-based web services,an improved plant growth simulation algorithm scheduling model.This model first used mathematical methods to describe the relationships between cloud-base...In order to improve the efficiency of cloud-based web services,an improved plant growth simulation algorithm scheduling model.This model first used mathematical methods to describe the relationships between cloud-based web services and the constraints of system resources.Then,a light-induced plant growth simulation algorithm was established.The performance of the algorithm was compared through several plant types,and the best plant model was selected as the setting for the system.Experimental results show that when the number of test cloud-based web services reaches 2048,the model being 2.14 times faster than PSO,2.8 times faster than the ant colony algorithm,2.9 times faster than the bee colony algorithm,and a remarkable 8.38 times faster than the genetic algorithm.展开更多
The impact of aerosols on clouds,which remains one of the largest aspects of uncertainty in current weather forecasting and climate change research,can be influenced by various factors,such as the underlying surface t...The impact of aerosols on clouds,which remains one of the largest aspects of uncertainty in current weather forecasting and climate change research,can be influenced by various factors,such as the underlying surface type,cloud type,cloud phase,and aerosol type.To explore the impact of different underlying surfaces on the effect of aerosols on cloud development,this study focused on the Yangtze River Delta(YRD)and its offshore regions(YRD sea)for a comparative analysis based on multi-source satellite data,while also considering the variations in cloud type and cloud phase.The results show lower cloud-top height and depth of single-layer clouds over the ocean than land,and higher liquid cloud in spring over the ocean.Aerosols are found to enhance the cumulus cloud depth through microphysical effects,which is particularly evident over the ocean.Aerosols are also found to decrease the cloud droplet effective radius in the ocean region and during the mature stage of cloud development in the land region,while opposite results are found during the early stage of cloud development in the land region.The quantitative results indicate that the indirect effect is positive(0.05)in the land region at relatively high cloud water path,which is smaller than that in the ocean region(0.11).The findings deepen our understanding of the influence aerosols on cloud development and the mechanisms involved,which could then be applied to improve the ability to simulate cloud-associated weather processes.展开更多
Cloud storage,a core component of cloud computing,plays a vital role in the storage and management of data.Electronic Health Records(EHRs),which document users’health information,are typically stored on cloud servers...Cloud storage,a core component of cloud computing,plays a vital role in the storage and management of data.Electronic Health Records(EHRs),which document users’health information,are typically stored on cloud servers.However,users’sensitive data would then become unregulated.In the event of data loss,cloud storage providers might conceal the fact that data has been compromised to protect their reputation and mitigate losses.Ensuring the integrity of data stored in the cloud remains a pressing issue that urgently needs to be addressed.In this paper,we propose a data auditing scheme for cloud-based EHRs that incorporates recoverability and batch auditing,alongside a thorough security and performance evaluation.Our scheme builds upon the indistinguishability-based privacy-preserving auditing approach proposed by Zhou et al.We identify that this scheme is insecure and vulnerable to forgery attacks on data storage proofs.To address these vulnerabilities,we enhanced the auditing process using masking techniques and designed new algorithms to strengthen security.We also provide formal proof of the security of the signature algorithm and the auditing scheme.Furthermore,our results show that our scheme effectively protects user privacy and is resilient against malicious attacks.Experimental results indicate that our scheme is not only secure and efficient but also supports batch auditing of cloud data.Specifically,when auditing 10,000 users,batch auditing reduces computational overhead by 101 s compared to normal auditing.展开更多
This study quantitatively analyzes the effects of cloud seeding on precipitation and seasonal variations over the Boryeong Dam region,which has the lowest dam storage in South Korea,based on a one-year numerical simul...This study quantitatively analyzes the effects of cloud seeding on precipitation and seasonal variations over the Boryeong Dam region,which has the lowest dam storage in South Korea,based on a one-year numerical simulation for2021.The Morrison microphysics scheme in the WRF(Weather Research and Forecasting)model was modified to estimate differences in precipitation between simulations with seeding materials(Ag I and Ca Cl2;SEED)and without them(UNSD).The effect of cloud seeding on increasing precipitation or artificial rainfall(AR)between the two simulations was highest in August(average:0.21 mm;31%of the SEED-simulated monthly mean)and lowest in January(average:0.003 mm;30%).This large AR may be attributable to a combination of abundant moisture from the summer monsoon climate and enhanced cloud droplet growth resulting from cloud seeding.In the analysis of seasonal representative cases,cloud seeding demonstrated more pronounced effects in spring and summer,with mean 180-min accumulated AR values of 0.46 and 0.43 mm,respectively,within the study area.In the spring,where an actual flight experiment was conducted,the simulated mean180-min accumulated AR(1.41 mm)in the flight experiment area was close to the observed value(1.61 mm)for the same area.Additionally,cloud seeding promoted the hygroscopic growth of water vapor,thereby reducing the cloud water mixing ratio and increasing the rain water mixing ratio.Seasonal cross-sectional analysis further highlighted the impact of cloud seeding on changes in these two mixing ratios,with the most pronounced effects observed in spring and summer.展开更多
Cloud diurnal variation is crucial for regulating cloud radiative effects and atmospheric dynamics.However,it is often overlooked in the evaluation and development of climate models.Thus,this study aims to investigate...Cloud diurnal variation is crucial for regulating cloud radiative effects and atmospheric dynamics.However,it is often overlooked in the evaluation and development of climate models.Thus,this study aims to investigate the daily mean(CFR)and diurnal variation(CDV)of cloud fraction across high-,middle-,low-level,and total clouds in the FGOALS-f3-L general circulation model.The bias of total CDV is decomposed into the model biases in CFRs and CDVs of clouds at all three levels.Results indicate that the model generally underestimates low-level cloud fraction during the daytime and high-/middle-level cloud fraction at nighttime.The simulation biases of low clouds,especially their CDV biases,dominate the bias of total CDV.Compensation effects exist among the bias decompositions,where the negative contributions of underestimated daytime low-level cloud fraction are partially offset by the opposing contributions from biases in high-/middle-level clouds.Meanwhile,the bias contributions have notable land–ocean differences and region-dependent characteristics,consistent with the model biases in these variables.Additionally,the study estimates the influences of CFR and CDV biases on the bias of shortwave cloud radiative effects.It reveals that the impacts of CDV biases can reach half of those from CFR biases,highlighting the importance of accurate CDV representation in climate models.展开更多
The cloud data centres evolved with an issue of energy management due to the constant increase in size,complexity and enormous consumption of energy.Energy management is a challenging issue that is critical in cloud d...The cloud data centres evolved with an issue of energy management due to the constant increase in size,complexity and enormous consumption of energy.Energy management is a challenging issue that is critical in cloud data centres and an important concern of research for many researchers.In this paper,we proposed a cuckoo search(CS)-based optimisation technique for the virtual machine(VM)selection and a novel placement algorithm considering the different constraints.The energy consumption model and the simulation model have been implemented for the efficient selection of VM.The proposed model CSOA-VM not only lessens the violations at the service level agreement(SLA)level but also minimises the VM migrations.The proposed model also saves energy and the performance analysis shows that energy consumption obtained is 1.35 kWh,SLA violation is 9.2 and VM migration is about 268.Thus,there is an improvement in energy consumption of about 1.8%and a 2.1%improvement(reduction)in violations of SLA in comparison to existing techniques.展开更多
The complexity of cloud environments challenges secure resource management,especially for intrusion detection systems(IDS).Existing strategies struggle to balance efficiency,cost fairness,and threat resilience.This pa...The complexity of cloud environments challenges secure resource management,especially for intrusion detection systems(IDS).Existing strategies struggle to balance efficiency,cost fairness,and threat resilience.This paper proposes an innovative approach to managing cloud resources through the integration of a genetic algorithm(GA)with a“double auction”method.This approach seeks to enhance security and efficiency by aligning buyers and sellers within an intelligent market framework.It guarantees equitable pricing while utilizing resources efficiently and optimizing advantages for all stakeholders.The GA functions as an intelligent search mechanism that identifies optimal combinations of bids from users and suppliers,addressing issues arising from the intricacies of cloud systems.Analyses proved that our method surpasses previous strategies,particularly in terms of price accuracy,speed,and the capacity to manage large-scale activities,critical factors for real-time cybersecurity systems,such as IDS.Our research integrates artificial intelligence-inspired evolutionary algorithms with market-driven methods to develop intelligent resource management systems that are secure,scalable,and adaptable to evolving risks,such as process innovation.展开更多
Efficient three-dimensional(3D)building reconstruction from drone imagery often faces data acquisition,storage,and computational challenges because of its reliance on dense point clouds.In this study,we introduced a n...Efficient three-dimensional(3D)building reconstruction from drone imagery often faces data acquisition,storage,and computational challenges because of its reliance on dense point clouds.In this study,we introduced a novel method for efficient and lightweight 3D building reconstruction from drone imagery using line clouds and sparse point clouds.Our approach eliminates the need to generate dense point clouds,and thus significantly reduces the computational burden by reconstructing 3D models directly from sparse data.We addressed the limitations of line clouds for plane detection and reconstruction by using a new algorithm.This algorithm projects 3D line clouds onto a 2D plane,clusters the projections to identify potential planes,and refines them using sparse point clouds to ensure an accurate and efficient model reconstruction.Extensive qualitative and quantitative experiments demonstrated the effectiveness of our method,demonstrating its superiority over existing techniques in terms of simplicity and efficiency.展开更多
Pronounced climatic differences occur over subtropical South China(SC)and tropical South China Sea(SCS)and understanding the key cloud-radiation characteristics is essential to simulating East Asian climate.This study...Pronounced climatic differences occur over subtropical South China(SC)and tropical South China Sea(SCS)and understanding the key cloud-radiation characteristics is essential to simulating East Asian climate.This study investigated cloud fractions and cloud radiative effects(CREs)over SC and SCS simulated by CMIP6 atmospheric models.Remarkable differences in cloud-radiation characteristics appeared over these two regions.In observations,considerable amounts of low-middle level clouds and cloud radiative cooling effect appeared over SC.In contrast,high clouds prevailed over SCS,where longwave and shortwave CREs offset each other,resulting in a weaker net cloud radiative effect(NCRE).The models underestimated NCRE over SC mainly due to weaker shortwave CRE and less cloud fractions.Conversely,most models overestimated NCRE over SCS because of stronger shortwave CRE and weaker longwave CRE.Regional CREs were closely linked to their dominant cloud fractions.Both observations and simulations showed a negative spatial correlation between total(low)cloud fraction and shortwave CRE over SC,especially in winter,and exhibited a positive correlation between high cloud fraction and longwave CRE over these two regions.Compared with SCS,most models overestimated the spatial correlation between low(high)cloud fraction and SWCRE(LWCRE)over SC,with larger bias ranges among models,indicating the exaggerated cloud radiative cooling(warming)effect caused by low(high)clouds.Moreover,most models struggled to describe regional ascent and its connection with CREs over SC while they can better reproduce these connections over SCS.This study further suggests that reasonable circulation conditions are crucial to simulating well cloud-radiation characteristics over the East Asian regions.展开更多
Airborne LiDAR(Light Detection and Ranging)is an evolving high-tech active remote sensing technology that has the capability to acquire large-area topographic data and can quickly generate DEM(Digital Elevation Model)...Airborne LiDAR(Light Detection and Ranging)is an evolving high-tech active remote sensing technology that has the capability to acquire large-area topographic data and can quickly generate DEM(Digital Elevation Model)products.Combined with image data,this technology can further enrich and extract spatial geographic information.However,practically,due to the limited operating range of airborne LiDAR and the large area of task,it would be necessary to perform registration and stitching process on point clouds of adjacent flight strips.By eliminating grow errors,the systematic errors in the data need to be effectively reduced.Thus,this paper conducts research on point cloud registration methods in urban building areas,aiming to improve the accuracy and processing efficiency of airborne LiDAR data.Meanwhile,an improved post-ICP(Iterative Closest Point)point cloud registration method was proposed in this study to determine the accurate registration and efficient stitching of point clouds,which capable to provide a potential technical support for applicants in related field.展开更多
A double-moment cloud microphysics scheme requires an assumption for cloud droplet size distributions(DSDs).However,since observations of cloud DSDs are limited,default values for shape parameters and cloud condensati...A double-moment cloud microphysics scheme requires an assumption for cloud droplet size distributions(DSDs).However,since observations of cloud DSDs are limited,default values for shape parameters and cloud condensation nuclei activation parameters are often used in numerical simulations.In this study,the effects of cloud DSDs on numerical simulations of warm stratiform precipitation around Tokyo are investigated using the Japan Meteorological Agency's non-hydrostatic model,which incorporates a double-moment cloud microphysics scheme.Simulations using the default cloud DSD showed higher cloud droplet number concentrations and lower radar reflectivity than observed data,suggesting that the default cloud DSD is too narrow.Simulations with a cloud DSD based on in situ cloud observations corrected these errors.In addition,observation-based cloud DSDs affected rainfall amounts through the autoconversion rate of cloud water and improved the threat scores.These results suggest that realistic cloud DSDs should be provided for double-moment cloud microphysics schemes in scientific studies.展开更多
During daylight laser polarization sensing of high-level clouds(HLCs),the lidar receiving system generates a signal caused by not only backscattered laser radiation,but also scattered solar radiation,the intensity and...During daylight laser polarization sensing of high-level clouds(HLCs),the lidar receiving system generates a signal caused by not only backscattered laser radiation,but also scattered solar radiation,the intensity and polarization of which depends on the Sun’s location.If a cloud contains spatially oriented ice particles,then it becomes anisotropic,that is,the coefficients of directional light scattering of such a cloud depend on the Sun’s zenith and azimuth angles.In this work,the possibility of using the effect of anisotropic scattering of solar radiation on the predictive ability of machine learning algorithms in solving the problem of predicting the HLC backscattering phase matrix(BSPM)was evaluated.The hypothesis that solar radiation scattered on HLCs has no effect on the BSPM elements of such clouds determined with a polarization lidar was tested.The operation of two algorithms for predicting the BSPM elements is evaluated.To train the first one,meteorological data were used as input parameters;for the second algorithm,the azi-muthal and zenith angles of the Sun’s position were added to the meteorological parameters.It is shown that there is no significant improvement in the predictive ability of the algorithm.展开更多
Cloud type profoundly affects precipitation,but few studies have explored its impact on precipitation scale height.The authors calculated the ratio of the volume of each cloud type to the total cloud volume and partit...Cloud type profoundly affects precipitation,but few studies have explored its impact on precipitation scale height.The authors calculated the ratio of the volume of each cloud type to the total cloud volume and partitioned the tropical region based on the dominant cloud types.Based on this,tropical regions were categorized into altocumulus control regions,stratocumulus control regions,deep convective cloud control regions,and transition regions.These regions exhibit unique characteristics:high precipitation scale heights and low surface precipitation rates in altocumulus control regions;low precipitation scale heights and low surface precipitation rates in stratocumulus control regions;and moderate precipitation scale heights with high surface precipitation rates in deep convective cloud regions.These features arise from differences in cloud characteristics,precipitation probability,and intensity,influenced by varying water vapor structures.In terms of physical mechanisms,altocumulus,stratocumulus,and deep convective cloud regions are characterized by total dryness,upper-level dryness with lower-level wetness,and total wetness,respectively.Upper-layer dryness leads to low cloud and precipitation structures,reducing the precipitation scale height,while lower-layer dryness increases it.Different humidity conditions in the upper and lower layers lead to variations in cloud type and volume distribution,ultimately affecting precipitation scale heights.This finding aids the mechanistic study of cloud precipitation physics in the tropics,providing valuable insights for developing numerical models and parameterizations.展开更多
Cloud radiative kernels(CRK)built with radiative transfer models have been widely used to analyze the cloud radiative effect on top of atmosphere(TOA)fluxes,and it is expected that the CRKs would also be useful in the...Cloud radiative kernels(CRK)built with radiative transfer models have been widely used to analyze the cloud radiative effect on top of atmosphere(TOA)fluxes,and it is expected that the CRKs would also be useful in the analyses of surface radiative fluxes,which determines the regional surface temperature change and variability.In this study,CRKs at the surface and TOA were built using the Rapid Radiative Transfer Model(RRTM).Longwave cloud radiative effect(CRE)at the surface is primarily driven by cloud base properties,while TOA CRE is primarily decided by cloud top properties.For this reason,the standard version of surface CRK is a function of latitude,longitude,month,cloud optical thickness(τ)and cloud base pressure(CBP),and the TOA CRK is a function of latitude,longitude,month,τand cloud top pressure(CTP).Considering that the cloud property histograms provided by climate models are functions of CTP instead of CBP at present,the surface CRKs on CBP-τhistograms were converted to CTP-τfields using the statistical relationship between CTP,CBP andτobtained from collocated CloudSat and MODIS observations.For both climate model outputs and satellites observations,the climatology of surface CRE and cloud-induced surface radiative anomalies calculated with the surface CRKs and cloud property histograms are well correlated with those calculated from surface radiative fluxes.The cloud-induced surface radiative anomalies reproduced by surface CRKs and MODIS cloud property histograms are not affected by spurious trends that appear in Clouds and the Earth's Radiant Energy System(CERES)surface irradiances products.展开更多
Cloud computing technology is the culmination of technical advancements in computer networks,hardware and software capabilities that collectively gave rise to computing as a utility.It offers a plethora of utilities t...Cloud computing technology is the culmination of technical advancements in computer networks,hardware and software capabilities that collectively gave rise to computing as a utility.It offers a plethora of utilities to its clients worldwide in a very cost-effective way and this feature is enticing users/companies to migrate their infrastructure to cloud platform.Swayed by its gigantic capacity and easy access clients are uploading replicated data on cloud resulting in an unnecessary crunch of storage in datacenters.Many data compression techniques came to rescue but none could serve the purpose for the capacity as large as a cloud,hence,researches were made to de-duplicate the data and harvest the space from exiting storage capacity which was going in vain due to duplicacy of data.For providing better cloud services through scalable provisioning of resources,interoperability has brought many Cloud Service Providers(CSPs)under one umbrella and termed it as Cloud Federation.Many policies have been devised for private and public cloud deployment models for searching/eradicating replicated copies using hashing techniques.Whereas the exploration for duplicate copies is not restricted to any one type of CSP but to a set of public or private CSPs contributing to the federation.It was found that even in advanced deduplication techniques for federated clouds,due to the different nature of CSPs,a single file is stored at private as well as public group in the same cloud federation which can be handled if an optimized deduplication strategy be rendered for addressing this issue.Therefore,this study has been aimed to further optimize a deduplication strategy for federated cloud environment and suggested a central management agent for the federation.It was perceived that work relevant to this is not existing,hence,in this paper,the concept of federation agent has been implemented and deduplication technique following file level has been used for the accomplishment of this approach.展开更多
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.
文摘This article explores the evolution of cloud computing, its advantages over traditional on-premises infrastructure, and its impact on information security. The study presents a comprehensive literature review covering various cloud infrastructure offerings and security models. Additionally, it deeply analyzes real-life case studies illustrating successful cloud migrations and highlights common information security threats in current cloud computing. The article concludes by offering recommendations to businesses to protect themselves from cloud data breaches and providing insights into selecting a suitable cloud services provider from an information security perspective.
基金supported by the National Natural Science Foundations of China(Grant Nos.42305163 and U22A20577)the Construction Project of Weather Modification Ability in Central China(Grant No.ZQC-H22256)+2 种基金the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB0760300)the Projects of the Earth System Numerical Simulation Facility(Grant Nos.2024-EL-PT-000707,2023-ELPT-000482,2023-EL-ZD-00026,and 2022-EL-PT-00083)the STS Program of the Inner Mongolia Meteorological Service,Chongqing Institute of Green and Intelligent Technology,Chinese Academy of Sciences,and Institute of Atmospheric Physics,Chinese Academy of Sciences(Grant No.2021CG0047)。
文摘Accurate descriptions of cloud droplet spectra from aerosol activation to vapor condensation using microphysical parameterization schemes are crucial for numerical simulations of precipitation and climate change in weather forecasting and climate prediction models.Hence,the latest activation and triple-moment condensation schemes were combined to simulate and analyze the evolution characteristics of a cloud droplet spectrum from activation to condensation and compared with a high-resolution Lagrangian bin model and the current double-moment condensation schemes,in which the spectral shape parameter is fixed or diagnosed by an empirical formula.The results demonstrate that the latest schemes effectively capture the evolution characteristics of the cloud droplet spectrum during activation and condensation,which is in line with the performance of the bin model.The simulation of the latest activation and condensation schemes in a parcel model shows that the cloud droplet spectrum gradually widens and exhibits a multimodal distribution during the activation process,accompanied by a decrease in the spectral shape and slope parameters over time.Conversely,during the condensation process,the cloud droplet spectrum gradually narrows,resulting in increases in the spectral shape and slope parameters.However,these double-moment schemes fail to accurately replicate the evolution of the cloud droplet spectrum and its multimodal distribution characteristics.Furthermore,the latest schemes were coupled into a 1.5D cumulus model,and an observation case was simulated.The simulations confirm that the cloud droplet spectrum appears wider at the supersaturated cloud base and cloud top due to activation,while it becomes narrower at the middle altitudes of the cloud due to condensation growth.
基金funded by Ko-rean Center for Atmospheric Sciences and Earthquake Re-search 2010–1178, and US Department of Energy grantDE-FG02-01ER63257
文摘The cloud phase composition of cold clouds in the Antarctic atmosphere is explored using data from the Moderate Resolution Imaging Spectroradiometer （MODIS） and Cloud-Aerosol Lidar with Orthogonal Polarization （CALIOP） instruments for the period 2000-2006. We used the averaged fraction of liquid-phase clouds out of the total cloud amount at the cloud tops since the value is comparable in the two measurements. MODIS data for the winter months （June, July, and August） reveal liquid cloud fraction out of the total cloud amount significantly decreases with decreasing cloud-top temperature below 0°C. In addition, the CALIOP vertical profiles show that below the ice clouds, low-lying liquid clouds are distributed over ～20% of the area. With increasing latitude, the liquid cloud fraction decreases as a function of the local temperature. The MODIS-observed relation between the cloud-top liquid fraction and cloud-top temperature is then applied to evaluate the cloud phase parameterization in climate models, in which condensed cloud water is repartitioned between liquid water and ice on the basis of the grid point temperature. It is found that models assuming overly high cut-offs （ -40°C） for the separation of ice clouds from mixed-phase clouds may significantly underestimate the liquid cloud fraction in the winter Antarctic atmosphere. Correction of the bias in the liquid cloud fraction would serve to reduce the large uncertainty in cloud radiative effects.
基金Shanxi Province Higher Education Science and Technology Innovation Fund Project(2022-676)Shanxi Soft Science Program Research Fund Project(2016041008-6)。
文摘In order to improve the efficiency of cloud-based web services,an improved plant growth simulation algorithm scheduling model.This model first used mathematical methods to describe the relationships between cloud-based web services and the constraints of system resources.Then,a light-induced plant growth simulation algorithm was established.The performance of the algorithm was compared through several plant types,and the best plant model was selected as the setting for the system.Experimental results show that when the number of test cloud-based web services reaches 2048,the model being 2.14 times faster than PSO,2.8 times faster than the ant colony algorithm,2.9 times faster than the bee colony algorithm,and a remarkable 8.38 times faster than the genetic algorithm.
基金supported by the National Natural Science Foundation of China(Grant No.42230601).
文摘The impact of aerosols on clouds,which remains one of the largest aspects of uncertainty in current weather forecasting and climate change research,can be influenced by various factors,such as the underlying surface type,cloud type,cloud phase,and aerosol type.To explore the impact of different underlying surfaces on the effect of aerosols on cloud development,this study focused on the Yangtze River Delta(YRD)and its offshore regions(YRD sea)for a comparative analysis based on multi-source satellite data,while also considering the variations in cloud type and cloud phase.The results show lower cloud-top height and depth of single-layer clouds over the ocean than land,and higher liquid cloud in spring over the ocean.Aerosols are found to enhance the cumulus cloud depth through microphysical effects,which is particularly evident over the ocean.Aerosols are also found to decrease the cloud droplet effective radius in the ocean region and during the mature stage of cloud development in the land region,while opposite results are found during the early stage of cloud development in the land region.The quantitative results indicate that the indirect effect is positive(0.05)in the land region at relatively high cloud water path,which is smaller than that in the ocean region(0.11).The findings deepen our understanding of the influence aerosols on cloud development and the mechanisms involved,which could then be applied to improve the ability to simulate cloud-associated weather processes.
基金supported by National Natural Science Foundation of China(No.62172436)Additionally,it is supported by Natural Science Foundation of Shaanxi Province(No.2023-JC-YB-584)Engineering University of PAP’s Funding for Scientific Research Innovation Team and Key Researcher(No.KYGG202011).
文摘Cloud storage,a core component of cloud computing,plays a vital role in the storage and management of data.Electronic Health Records(EHRs),which document users’health information,are typically stored on cloud servers.However,users’sensitive data would then become unregulated.In the event of data loss,cloud storage providers might conceal the fact that data has been compromised to protect their reputation and mitigate losses.Ensuring the integrity of data stored in the cloud remains a pressing issue that urgently needs to be addressed.In this paper,we propose a data auditing scheme for cloud-based EHRs that incorporates recoverability and batch auditing,alongside a thorough security and performance evaluation.Our scheme builds upon the indistinguishability-based privacy-preserving auditing approach proposed by Zhou et al.We identify that this scheme is insecure and vulnerable to forgery attacks on data storage proofs.To address these vulnerabilities,we enhanced the auditing process using masking techniques and designed new algorithms to strengthen security.We also provide formal proof of the security of the signature algorithm and the auditing scheme.Furthermore,our results show that our scheme effectively protects user privacy and is resilient against malicious attacks.Experimental results indicate that our scheme is not only secure and efficient but also supports batch auditing of cloud data.Specifically,when auditing 10,000 users,batch auditing reduces computational overhead by 101 s compared to normal auditing.
基金funded by the Korea Meteorological Administration Research and Development Program“Research on Weather Modification and Cloud Physics”(Grant No.KMA2018-00224)supported by Korea Institute of Marine Science&Technology Promotion(KIMST)funded by the Ministry of Oceans and Fisheries,Korea(RS-202502217872)supported by an NRF grant funded by the Korean government(MSIT)(Grant No.NRF2023R1A2C1002367)。
文摘This study quantitatively analyzes the effects of cloud seeding on precipitation and seasonal variations over the Boryeong Dam region,which has the lowest dam storage in South Korea,based on a one-year numerical simulation for2021.The Morrison microphysics scheme in the WRF(Weather Research and Forecasting)model was modified to estimate differences in precipitation between simulations with seeding materials(Ag I and Ca Cl2;SEED)and without them(UNSD).The effect of cloud seeding on increasing precipitation or artificial rainfall(AR)between the two simulations was highest in August(average:0.21 mm;31%of the SEED-simulated monthly mean)and lowest in January(average:0.003 mm;30%).This large AR may be attributable to a combination of abundant moisture from the summer monsoon climate and enhanced cloud droplet growth resulting from cloud seeding.In the analysis of seasonal representative cases,cloud seeding demonstrated more pronounced effects in spring and summer,with mean 180-min accumulated AR values of 0.46 and 0.43 mm,respectively,within the study area.In the spring,where an actual flight experiment was conducted,the simulated mean180-min accumulated AR(1.41 mm)in the flight experiment area was close to the observed value(1.61 mm)for the same area.Additionally,cloud seeding promoted the hygroscopic growth of water vapor,thereby reducing the cloud water mixing ratio and increasing the rain water mixing ratio.Seasonal cross-sectional analysis further highlighted the impact of cloud seeding on changes in these two mixing ratios,with the most pronounced effects observed in spring and summer.
基金supported by the National Natural Science Foundation of China[grant number 42275074].
文摘Cloud diurnal variation is crucial for regulating cloud radiative effects and atmospheric dynamics.However,it is often overlooked in the evaluation and development of climate models.Thus,this study aims to investigate the daily mean(CFR)and diurnal variation(CDV)of cloud fraction across high-,middle-,low-level,and total clouds in the FGOALS-f3-L general circulation model.The bias of total CDV is decomposed into the model biases in CFRs and CDVs of clouds at all three levels.Results indicate that the model generally underestimates low-level cloud fraction during the daytime and high-/middle-level cloud fraction at nighttime.The simulation biases of low clouds,especially their CDV biases,dominate the bias of total CDV.Compensation effects exist among the bias decompositions,where the negative contributions of underestimated daytime low-level cloud fraction are partially offset by the opposing contributions from biases in high-/middle-level clouds.Meanwhile,the bias contributions have notable land–ocean differences and region-dependent characteristics,consistent with the model biases in these variables.Additionally,the study estimates the influences of CFR and CDV biases on the bias of shortwave cloud radiative effects.It reveals that the impacts of CDV biases can reach half of those from CFR biases,highlighting the importance of accurate CDV representation in climate models.
文摘The cloud data centres evolved with an issue of energy management due to the constant increase in size,complexity and enormous consumption of energy.Energy management is a challenging issue that is critical in cloud data centres and an important concern of research for many researchers.In this paper,we proposed a cuckoo search(CS)-based optimisation technique for the virtual machine(VM)selection and a novel placement algorithm considering the different constraints.The energy consumption model and the simulation model have been implemented for the efficient selection of VM.The proposed model CSOA-VM not only lessens the violations at the service level agreement(SLA)level but also minimises the VM migrations.The proposed model also saves energy and the performance analysis shows that energy consumption obtained is 1.35 kWh,SLA violation is 9.2 and VM migration is about 268.Thus,there is an improvement in energy consumption of about 1.8%and a 2.1%improvement(reduction)in violations of SLA in comparison to existing techniques.
文摘The complexity of cloud environments challenges secure resource management,especially for intrusion detection systems(IDS).Existing strategies struggle to balance efficiency,cost fairness,and threat resilience.This paper proposes an innovative approach to managing cloud resources through the integration of a genetic algorithm(GA)with a“double auction”method.This approach seeks to enhance security and efficiency by aligning buyers and sellers within an intelligent market framework.It guarantees equitable pricing while utilizing resources efficiently and optimizing advantages for all stakeholders.The GA functions as an intelligent search mechanism that identifies optimal combinations of bids from users and suppliers,addressing issues arising from the intricacies of cloud systems.Analyses proved that our method surpasses previous strategies,particularly in terms of price accuracy,speed,and the capacity to manage large-scale activities,critical factors for real-time cybersecurity systems,such as IDS.Our research integrates artificial intelligence-inspired evolutionary algorithms with market-driven methods to develop intelligent resource management systems that are secure,scalable,and adaptable to evolving risks,such as process innovation.
基金Supported by the Guangdong Major Project of Basic and Applied Basic Research (2023B0303000016)the National Natural Science Foundation of China (U21A20515)。
文摘Efficient three-dimensional(3D)building reconstruction from drone imagery often faces data acquisition,storage,and computational challenges because of its reliance on dense point clouds.In this study,we introduced a novel method for efficient and lightweight 3D building reconstruction from drone imagery using line clouds and sparse point clouds.Our approach eliminates the need to generate dense point clouds,and thus significantly reduces the computational burden by reconstructing 3D models directly from sparse data.We addressed the limitations of line clouds for plane detection and reconstruction by using a new algorithm.This algorithm projects 3D line clouds onto a 2D plane,clusters the projections to identify potential planes,and refines them using sparse point clouds to ensure an accurate and efficient model reconstruction.Extensive qualitative and quantitative experiments demonstrated the effectiveness of our method,demonstrating its superiority over existing techniques in terms of simplicity and efficiency.
基金Guangdong Major Project of Basic and Applied Basic Research(2020B0301030004)National Natural Science Foundation of China(72293604,42275026)Open Grants of the State Key Laboratory of Severe Weather(2023LASW-B09)。
文摘Pronounced climatic differences occur over subtropical South China(SC)and tropical South China Sea(SCS)and understanding the key cloud-radiation characteristics is essential to simulating East Asian climate.This study investigated cloud fractions and cloud radiative effects(CREs)over SC and SCS simulated by CMIP6 atmospheric models.Remarkable differences in cloud-radiation characteristics appeared over these two regions.In observations,considerable amounts of low-middle level clouds and cloud radiative cooling effect appeared over SC.In contrast,high clouds prevailed over SCS,where longwave and shortwave CREs offset each other,resulting in a weaker net cloud radiative effect(NCRE).The models underestimated NCRE over SC mainly due to weaker shortwave CRE and less cloud fractions.Conversely,most models overestimated NCRE over SCS because of stronger shortwave CRE and weaker longwave CRE.Regional CREs were closely linked to their dominant cloud fractions.Both observations and simulations showed a negative spatial correlation between total(low)cloud fraction and shortwave CRE over SC,especially in winter,and exhibited a positive correlation between high cloud fraction and longwave CRE over these two regions.Compared with SCS,most models overestimated the spatial correlation between low(high)cloud fraction and SWCRE(LWCRE)over SC,with larger bias ranges among models,indicating the exaggerated cloud radiative cooling(warming)effect caused by low(high)clouds.Moreover,most models struggled to describe regional ascent and its connection with CREs over SC while they can better reproduce these connections over SCS.This study further suggests that reasonable circulation conditions are crucial to simulating well cloud-radiation characteristics over the East Asian regions.
基金Guangxi Key Laboratory of Spatial Information and Geomatics(21-238-21-12)Guangxi Young and Middle-aged Teachers’Research Fundamental Ability Enhancement Project(2023KY1196).
文摘Airborne LiDAR(Light Detection and Ranging)is an evolving high-tech active remote sensing technology that has the capability to acquire large-area topographic data and can quickly generate DEM(Digital Elevation Model)products.Combined with image data,this technology can further enrich and extract spatial geographic information.However,practically,due to the limited operating range of airborne LiDAR and the large area of task,it would be necessary to perform registration and stitching process on point clouds of adjacent flight strips.By eliminating grow errors,the systematic errors in the data need to be effectively reduced.Thus,this paper conducts research on point cloud registration methods in urban building areas,aiming to improve the accuracy and processing efficiency of airborne LiDAR data.Meanwhile,an improved post-ICP(Iterative Closest Point)point cloud registration method was proposed in this study to determine the accurate registration and efficient stitching of point clouds,which capable to provide a potential technical support for applicants in related field.
基金supported by Grants in Aid from the Japan Society for the Promotion of Science(JSPS)KAKENHI[grant numbers JP21H01163 and JP23H00149].
文摘A double-moment cloud microphysics scheme requires an assumption for cloud droplet size distributions(DSDs).However,since observations of cloud DSDs are limited,default values for shape parameters and cloud condensation nuclei activation parameters are often used in numerical simulations.In this study,the effects of cloud DSDs on numerical simulations of warm stratiform precipitation around Tokyo are investigated using the Japan Meteorological Agency's non-hydrostatic model,which incorporates a double-moment cloud microphysics scheme.Simulations using the default cloud DSD showed higher cloud droplet number concentrations and lower radar reflectivity than observed data,suggesting that the default cloud DSD is too narrow.Simulations with a cloud DSD based on in situ cloud observations corrected these errors.In addition,observation-based cloud DSDs affected rainfall amounts through the autoconversion rate of cloud water and improved the threat scores.These results suggest that realistic cloud DSDs should be provided for double-moment cloud microphysics schemes in scientific studies.
基金supported by the Government of the Russian Federation grant number 075-15-2025-009 of 28 February 2025 and by the Russian Science Foundation,Grant No.24-72-10127.
文摘During daylight laser polarization sensing of high-level clouds(HLCs),the lidar receiving system generates a signal caused by not only backscattered laser radiation,but also scattered solar radiation,the intensity and polarization of which depends on the Sun’s location.If a cloud contains spatially oriented ice particles,then it becomes anisotropic,that is,the coefficients of directional light scattering of such a cloud depend on the Sun’s zenith and azimuth angles.In this work,the possibility of using the effect of anisotropic scattering of solar radiation on the predictive ability of machine learning algorithms in solving the problem of predicting the HLC backscattering phase matrix(BSPM)was evaluated.The hypothesis that solar radiation scattered on HLCs has no effect on the BSPM elements of such clouds determined with a polarization lidar was tested.The operation of two algorithms for predicting the BSPM elements is evaluated.To train the first one,meteorological data were used as input parameters;for the second algorithm,the azi-muthal and zenith angles of the Sun’s position were added to the meteorological parameters.It is shown that there is no significant improvement in the predictive ability of the algorithm.
基金supported by the National Natural Science Foundation of China[grant numbers 42175099 and 42027804]The appointment of Chunsong Lu at Nanjing University of Information Science&Technology was partially supported by the Jiangsu Specially-Appointed Professor[grant number R2024T01].
文摘Cloud type profoundly affects precipitation,but few studies have explored its impact on precipitation scale height.The authors calculated the ratio of the volume of each cloud type to the total cloud volume and partitioned the tropical region based on the dominant cloud types.Based on this,tropical regions were categorized into altocumulus control regions,stratocumulus control regions,deep convective cloud control regions,and transition regions.These regions exhibit unique characteristics:high precipitation scale heights and low surface precipitation rates in altocumulus control regions;low precipitation scale heights and low surface precipitation rates in stratocumulus control regions;and moderate precipitation scale heights with high surface precipitation rates in deep convective cloud regions.These features arise from differences in cloud characteristics,precipitation probability,and intensity,influenced by varying water vapor structures.In terms of physical mechanisms,altocumulus,stratocumulus,and deep convective cloud regions are characterized by total dryness,upper-level dryness with lower-level wetness,and total wetness,respectively.Upper-layer dryness leads to low cloud and precipitation structures,reducing the precipitation scale height,while lower-layer dryness increases it.Different humidity conditions in the upper and lower layers lead to variations in cloud type and volume distribution,ultimately affecting precipitation scale heights.This finding aids the mechanistic study of cloud precipitation physics in the tropics,providing valuable insights for developing numerical models and parameterizations.
基金supported by the National Natural Science Foundation of China(Grant No.NSFC 41875095,42075127).
文摘Cloud radiative kernels(CRK)built with radiative transfer models have been widely used to analyze the cloud radiative effect on top of atmosphere(TOA)fluxes,and it is expected that the CRKs would also be useful in the analyses of surface radiative fluxes,which determines the regional surface temperature change and variability.In this study,CRKs at the surface and TOA were built using the Rapid Radiative Transfer Model(RRTM).Longwave cloud radiative effect(CRE)at the surface is primarily driven by cloud base properties,while TOA CRE is primarily decided by cloud top properties.For this reason,the standard version of surface CRK is a function of latitude,longitude,month,cloud optical thickness(τ)and cloud base pressure(CBP),and the TOA CRK is a function of latitude,longitude,month,τand cloud top pressure(CTP).Considering that the cloud property histograms provided by climate models are functions of CTP instead of CBP at present,the surface CRKs on CBP-τhistograms were converted to CTP-τfields using the statistical relationship between CTP,CBP andτobtained from collocated CloudSat and MODIS observations.For both climate model outputs and satellites observations,the climatology of surface CRE and cloud-induced surface radiative anomalies calculated with the surface CRKs and cloud property histograms are well correlated with those calculated from surface radiative fluxes.The cloud-induced surface radiative anomalies reproduced by surface CRKs and MODIS cloud property histograms are not affected by spurious trends that appear in Clouds and the Earth's Radiant Energy System(CERES)surface irradiances products.
文摘Cloud computing technology is the culmination of technical advancements in computer networks,hardware and software capabilities that collectively gave rise to computing as a utility.It offers a plethora of utilities to its clients worldwide in a very cost-effective way and this feature is enticing users/companies to migrate their infrastructure to cloud platform.Swayed by its gigantic capacity and easy access clients are uploading replicated data on cloud resulting in an unnecessary crunch of storage in datacenters.Many data compression techniques came to rescue but none could serve the purpose for the capacity as large as a cloud,hence,researches were made to de-duplicate the data and harvest the space from exiting storage capacity which was going in vain due to duplicacy of data.For providing better cloud services through scalable provisioning of resources,interoperability has brought many Cloud Service Providers(CSPs)under one umbrella and termed it as Cloud Federation.Many policies have been devised for private and public cloud deployment models for searching/eradicating replicated copies using hashing techniques.Whereas the exploration for duplicate copies is not restricted to any one type of CSP but to a set of public or private CSPs contributing to the federation.It was found that even in advanced deduplication techniques for federated clouds,due to the different nature of CSPs,a single file is stored at private as well as public group in the same cloud federation which can be handled if an optimized deduplication strategy be rendered for addressing this issue.Therefore,this study has been aimed to further optimize a deduplication strategy for federated cloud environment and suggested a central management agent for the federation.It was perceived that work relevant to this is not existing,hence,in this paper,the concept of federation agent has been implemented and deduplication technique following file level has been used for the accomplishment of this approach.
