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
The aging process is an inexorable fact throughout our lives and is considered a major factor in develo ping neurological dysfunctions associated with cognitive,emotional,and motor impairments.Aging-associated neurode...The aging process is an inexorable fact throughout our lives and is considered a major factor in develo ping neurological dysfunctions associated with cognitive,emotional,and motor impairments.Aging-associated neurodegenerative diseases are characterized by the progressive loss of neuronal structure and function.展开更多
High-resolution numerical simulation data of a rainstorm triggering debris flow in Sichuan Province of China simulated by the Weather Research and Forecasting （WRF） Model were used to study the dominant cloud microp...High-resolution numerical simulation data of a rainstorm triggering debris flow in Sichuan Province of China simulated by the Weather Research and Forecasting （WRF） Model were used to study the dominant cloud microphysical processes of the torrential rainfall.The results showed that：（1） In the strong precipitation period,particle sizes of all hydrometeors increased,and mean-mass diameters of graupel increased the most significantly,as compared with those in the weak precipitation period; （2） The terminal velocity of raindrops was the strongest among all hydrometeors,followed by graupel＇s,which was much smaller than that of raindrops.Differences between various hydrometeors＇ terminal velocities in the strong precipitation period were larger than those in the weak precipitation period,which favored relative motion,collection interaction and transformation between the particles.Absolute terminal velocity values of raindrops and graupel were significantly greater than those of air upward velocity,and the stronger the precipitation was,the greater the differences between them were; （3） The orders of magnitudes of the various hydrometeors＇ sources and sinks in the strong precipitation period were larger than those in the weak precipitation period,causing a difference in the intensity of precipitation.Water vapor,cloud water,raindrops,graupel and their exchange processes played a major role in the production of the torrential rainfall,and there were two main processes via which raindrops were generated：abundant water vapor condensed into cloud water and,on the one hand,accretion of cloud water by rain water formed rain water,while on the other hand,accretion of cloud water by graupel formed graupel,and then the melting of graupel formed rain water.展开更多
Convective processes affect large-scale environments through cloud-radiation interaction, cloud micro- physical processes, and surface rainfall processes. Over the last three decades, cloud-resolving models （CRMs） h...Convective processes affect large-scale environments through cloud-radiation interaction, cloud micro- physical processes, and surface rainfall processes. Over the last three decades, cloud-resolving models （CRMs） have demonstrated to be capable of simulating convective-radiative responses to an imposed large-scale forcing. The CRM-produced cloud and radiative properties have been utilized to study the convective- related processes and their ensemble effects on large-scale circulations. This review the recent progress on the understanding of convective processes with the use of CRM simulations, including precipitation processes; cloud microphysical and radiative processes; dynamical processes; precipitation efficiency; diurnal variations of tropical oceanic convection; local-scale atmosphere-ocean coupling processes; and tropical convective-radiative equilibrium states. Two different ongoing applications of CRMs to general circulation models （GCMs） are discussed： replacing convection and cloud schemes for studying the interaction between cloud systems and large-scale circulation, and improving the schemes for climate simulations.展开更多
Cloud micro-physical structures in a precipitation system associated with the Meiyu front are observed using the balloon-borne Precipitation Particle Image Sensor at Baoshan observatory station, Shanghai during June a...Cloud micro-physical structures in a precipitation system associated with the Meiyu front are observed using the balloon-borne Precipitation Particle Image Sensor at Baoshan observatory station, Shanghai during June and July 1999. The vertical distributions of various cloud particle size, number density, and mass density are retrieved from the observations. Analyses of observations show that ice-phase particles (ice crystals, graupel, snowflakes, and frozen drops) often exist in the cloud of torrential rain associated with the Meiyu front. Among the various particles, ice crystals and graupel are the most numerous, but graupel and snow have the highest mass density. Ice-phase particles coexist with liquid water droplets near the 0°C level. The graupel is similarly distributed with height as the ice crystals. Raindrops below the 0°C level are mainly from melted grauple, snowflakes and frozen drops. They may further grow larger by coalescence with smaller ones as they fall from the cloud base. Numerical simulations using the non-hydrostatic meso-scale model MM5 with the Reisner graupel explicit moisture scheme confirm the main observational results. Rain water at the lower level is mainly generated from the melting of snow and graupel falling from the upper level where snow and graupel are generated and grown from collection with cloud and rain water. Thus the mixed-phase cloud process, in which ice phase coexists and interacts with liquid phase (cloud and rain drops), plays the most important role in the formation and development of heavy convective rainfall in the Meiyu frontal system.展开更多
Process discovery, as one of the most challenging process analysis techniques, aims to uncover business process models from event logs. Many process discovery approaches were invented in the past twenty years;however,...Process discovery, as one of the most challenging process analysis techniques, aims to uncover business process models from event logs. Many process discovery approaches were invented in the past twenty years;however, most of them have difficulties in handling multi-instance sub-processes. To address this challenge, we first introduce a multi-instance business process model(MBPM) to support the modeling of processes with multiple sub-process instantiations. Formal semantics of MBPMs are precisely defined by using multi-instance Petri nets(MPNs)that are an extension of Petri nets with distinguishable tokens.Then, a novel process discovery technique is developed to support the discovery of MBPMs from event logs with sub-process multi-instantiation information. In addition, we propose to measure the quality of the discovered MBPMs against the input event logs by transforming an MBPM to a classical Petri net such that existing quality metrics, e.g., fitness and precision, can be used.The proposed discovery approach is properly implemented as plugins in the Pro M toolkit. Based on a cloud resource management case study, we compare our approach with the state-of-theart process discovery techniques. The results demonstrate that our approach outperforms existing approaches to discover process models with multi-instance sub-processes.展开更多
The understanding of the cloud processes of snowfall is essential to the artificial enhancement of snow and the numerical simulation of snowfall. The mesoscale model MM5 is used to simulate a moderate snowfall event i...The understanding of the cloud processes of snowfall is essential to the artificial enhancement of snow and the numerical simulation of snowfall. The mesoscale model MM5 is used to simulate a moderate snowfall event in North China that occurred during 20-21 December 2002. Thirteen experiments are performed to test the sensitivity of the simulation to the cloud physics with different cumulus parameterization schemes and different options for the Goddard cloud microphysics parameterization schemes. It is shown that the cumulus parameterization scheme has little to do with the simulation result. The results also show that there are only four classes of water substances, namely the cloud water, cloud ice, snow, and vapor, in the simulation of the moderate snowfall event. The analysis of the cloud microphysics budgets in the explicit experiment shows that the condensation of supersaturated vapor, the depositional growth of cloud ice, the initiation of cloud ice, the accretion of cloud ice by snow, the accretion of cloud water by snow, the deposition growth of snow, and the Bergeron process of cloud ice are the dominant cloud microphysical processes in the simulation. The accretion of cloud water by snow and the deposition growth of the snow are equally important in the development of the snow.展开更多
Typhoon KROSA in 2007 is simulated using GRAPES,a mesoscale numerical model,in which a two-parameter mixed-phase microphysics scheme is implanted.A series of numerical experiments are designed to test the sensitivity ...Typhoon KROSA in 2007 is simulated using GRAPES,a mesoscale numerical model,in which a two-parameter mixed-phase microphysics scheme is implanted.A series of numerical experiments are designed to test the sensitivity of landfalling typhoon structure and precipitation to varying cloud microphysics and latent heat release.It is found that typhoon track is sensitive to different microphysical processes and latent heat release.The cloud structures of simulated cyclones can be quite different with that of varying microphysical processes.Graupel particles play an important role in the formation of local heavy rainfall and the maintenance of spiral rainbands.Analysis reveals that the feedback of latent heat to dynamic fields can significantly change the content and distribution of cloud hydrometeors,thus having an impact on surface precipitation.展开更多
We analyzed cloud microphysical processes' latent heat characteristics and their influence on an autumn heavy rain event over Hainan Island,China,using the mesoscale numerical model WRF and WRF-3DVAR system.We fou...We analyzed cloud microphysical processes' latent heat characteristics and their influence on an autumn heavy rain event over Hainan Island,China,using the mesoscale numerical model WRF and WRF-3DVAR system.We found that positive latent heat occurred far above the zero layer,while negative latent heat occurred mainly under the zero layer.There was substantially more positive latent heat than negative latent heat,and the condensation heating had the most important contribution to the latent heat increase.The processes of deposition,congelation,melting and evaporation were all characterized by weakening after their intensification;however,the variations in condensation and sublimation processes were relatively small.The main cloud microphysical processes for positive latent heat were condensation of water vapor into cloud water,the condensation of rain,and the deposition increase of cloud ice,snow and graupel.The main cloud microphysical processes for negative latent heat were the evaporation of rain,the melting and enhanced melting of graupel.The latent heat releases due to different cloud microphysical processes have a significant impact on the intensity of precipitation.Without the condensation and evaporation of rain,the total latent heating would decrease and the moisture variables and precipitation would reduce significantly.Without deposition and sublimation,the heating in high levels would decrease and the precipitation would reduce.Without congelation and melting,the latent heating would enhance in the low levels,and the precipitation would reduce.展开更多
With the Reisner-2 bulk microphysical parameterization of the fifth-generation Pennsylvania State University-U.S. National Center for Atmospheric Research （PSU--NCAR） Mesoscale Model （MM5）, this paper investigates...With the Reisner-2 bulk microphysical parameterization of the fifth-generation Pennsylvania State University-U.S. National Center for Atmospheric Research （PSU--NCAR） Mesoscale Model （MM5）, this paper investigates the microphysical sensitivities of Typhoon Chanchu. Four different microphysical sensitivity experiments were designed with an objective to evaluate their respective impacts in modulating intensity forecasts and microphysics budgets of the typhoon. The set of sensitivity experiments were conducted that comprised （a） a control experiment （CTL）, （b） NEVPRW from which evaporation of rain water was suppressed, （c） NGP from which graupel was taken, and （d） NMLT from which melting of snow and graupel was removed. We studied the impacts of different cloud microphysical processes on the track, intensity and precipitation of the typhoon, as well as the kinematics, thermodynamics and vertical structural characteristics of hydrometeors in the inner core of the typhoon. Additionally, the budgets of the cloud microphysical processes in the fine domain were calculated to quantify the importance of each microphysical process for every sensitivity experiment. The primary results are as follows： （1） It is found that varying cloud microphysics parameters produce little sensitivity in typhoon track experiments. （2） The experiment of NGP produces the weakest storm, while the experiment of NMLT produces the strongest storm, and the experiment of NEVPRW also produces stronger storms than CTL. （3） Varying parameters of cloud rnicrophysics have obvious impacts on the precipitation, kinematics, and thermodynamics of the typhoon and the vertical structural characteristics of hydrometeors in the typhoon＇s inner core. （4） Most budgets of cloud microphysics in NMLT are larger than in CTL, while they are 20%-60% smaller in NEVPRW than in CTL.展开更多
The detailed surface rainfall processes associated with landfalling typhoon Kaemi（2006） are investigated based on hourly data from a two-dimensional cloud-resolving model simulation. The model is integrated for 6 da...The detailed surface rainfall processes associated with landfalling typhoon Kaemi（2006） are investigated based on hourly data from a two-dimensional cloud-resolving model simulation. The model is integrated for 6 days with imposed large-scale vertical velocity, zonal wind, horizontal temperature and vapor advection from National Center for Environmental Prediction （NCEP） / Global Data Assimilation System （GDAS） data. The simulation data are validated with observations in terms of surface rain rate. The Root-Mean-Squared （RMS） difference in surface rain rate between the simulation and the gauge observations is 0.660 mm h^-1, which is smaller than the standard deviations of both the simulated rain rate （0.753 mm h^-1） and the observed rain rate （0.833 mm h^-1）. The simulation data are then used to study the physical causes associated with the detailed surface rainfall processes during the landfall. The results show that time averaged and model domain-mean Ps mainly comes from large-scale convergence （QWVF） and local vapor loss （positive QWVT）. Large underestimation （about 15%） of Ps will occur if QWVT and QCM （cloud source/sink） are not considered as contributors to Ps ,QWVF accounts for the variation of P during most of the integration time, while it is not always a contributor to Ps,Sometimes surface rainfall could occur when divergence is dominant with local vapor loss to be a contributor to Ps - Surface rainfall is a result ofmulti-timescale interactions. QWVE possesses the longest time scale and the lowest frequeney the second and QCM of variation with time and may exert impact on P on longer time scales. QWVF possesses longest time scale and lowest frequency and can explain most of the variation of Ps. QWVT possess shorter time scales and higher frequencies, which can explain more detailed variations in Ps. Partitioning analysis shows that stratiform rainfall is dominant from the morning of 26 July till the late night of 27 July. After that, convective rainfall dominates till about 1000 LST 28 July. Before 28 July, the variations of QWVT in rainfall-free regions contribute less to that of the domain-mean QWVT while after that they contribute much, which is consistent to the corresponding variations in their fractional coverage. The variations of QWVF in rainfall regions are the main contributors to that of the domain-mean QWVF, then the main contributors to the surface rain rate before the afternoon of 28 July.展开更多
The effects of sea surface temperature（SST）,cloud radiative and microphysical processes,and diurnal variations on rainfall statistics are documented with grid data from the two-dimensional equilibrium cloud-resolvin...The effects of sea surface temperature（SST）,cloud radiative and microphysical processes,and diurnal variations on rainfall statistics are documented with grid data from the two-dimensional equilibrium cloud-resolving model simulations.For a rain rate of higher than 3 mm.h 1,water vapor convergence prevails.The rainfall amount decreases with the decrease of SST from 29℃ to 27℃,the inclusion of diurnal variation of SST,or the exclusion of microphysical effects of ice clouds and radiative effects of water clouds,which are primarily associated with the decreases in water vapor convergence.However,the amount of rainfall increases with the increase of SST from 29℃ to 31℃,the exclusion of diurnal variation of solar zenith angle,and the exclusion of the radiative effects of ice clouds,which are primarily related to increases in water vapor convergence.For a rain rate of less than 3 mm.h 1,water vapor divergence prevails.Unlike rainfall statistics for rain rates of higher than 3 mm.h 1,the decrease of SST from 29℃ to 27℃ and the exclusion of radiative effects of water clouds in the presence of radiative effects of ice clouds increase the rainfall amount,which corresponds to the suppression in water vapor divergence.The exclusion of microphysical effects of ice clouds decreases the amount of rainfall,which corresponds to the enhancement in water vapor divergence.The amount of rainfall is less sensitive to the increase of SST from 29℃ to 31℃ and to the radiative effects of water clouds in the absence of the radiative effects of ice clouds.展开更多
Cloud radiative processes are important in regulating weather and climate. Precipitation responses to radiative processes of water- and ice-clouds are investigated by analyzing mean equilibrium simulation data from a ...Cloud radiative processes are important in regulating weather and climate. Precipitation responses to radiative processes of water- and ice-clouds are investigated by analyzing mean equilibrium simulation data from a series of two-dimensional cloud-resolving model sensitivity experiments in this study. The model is imposed by zero vertical velocity.The exclusion of water radiative processes in the presence of ice radiative processes, as well as the removal of ice radiative processes, enhances tropospheric Iongwave radiative cooling and lowers air temperature and the saturation mixing ratio. The reduction in the saturation mixing ratio leads to an increase in vapor condensation and an associated release of latent heat, which increases rainfall. The elimination of water radiative processes strengthens local atmospheric warming Iongwave radiative cooling. The enhanced warming melting of graupel, which increases rainfa n the upper troposphere via a reduction in ncreases the rain source via an increase in the展开更多
The prevailing idea so far about why the rainfall occurs was that after agglutination of water droplets with condensation nuclei, the size of the particle formed by the condensation nuclei connected with droplets of w...The prevailing idea so far about why the rainfall occurs was that after agglutination of water droplets with condensation nuclei, the size of the particle formed by the condensation nuclei connected with droplets of water increased considerably and caused its fall. This idea has led to numerous scientific publications in which empirical distribution functions of clouds’ water droplets sizes were proposed. Estimates values provided by these empirical distribution functions, in most cases, were validated by comparison with UHF Radar measurements. The condensation nuclei concept has not been sufficiently exploited and this has led meteorologists to error, in their attempt to describe the clouds, thinking that clouds were formed by liquid water droplets. Indeed, MBANE BIOUELE paradox (2005) confirms this embarrassing situation. In fact, when applying Archimedes theorem to a liquid water droplet suspended in the atmosphere, we obtain a meaningless inequality ?which makes believe that the densities of pure water in liquid and solid phases are much lower than that of the atmosphere considered at the sea level. This meaningless inequality is easy to contradict: of course, if you empty a bottle of pure liquid water in the ocean (where z is equal to 0), this water will not remain suspended in the air, i.e., application of Archimedes’ theorem allows realizing that there is no liquid (or solid) water droplet, suspended in the clouds. Indeed, all liquid (or solid) water droplets which are formed in clouds, fall under the effect of gravity and produce rains. This means that our current description of the clouds is totally wrong. In this study, we describe the clouds as a gas composed of dry air and saturated water vapor whose optical properties depend on temperature, i.e., when the temperature of a cloud decreases, the color of this gaseous system tends towards white.展开更多
Cloud computing can offer a very powerful, reliable, predictable and scalable computing infrastructure for the execution of MAS （multi-agent systems） implementing complex agent-based applications such when modelling...Cloud computing can offer a very powerful, reliable, predictable and scalable computing infrastructure for the execution of MAS （multi-agent systems） implementing complex agent-based applications such when modelling, simulation and real-time running of complex systems must be provided. Multi-agent systems appears as an adequate approach to current challenges in many areas. Between important qualities of MAS also belongs to, that they are open, interoperable, and heterogenous systems. The agent is active, a program entity, has its own ideas how to perform the tasks of the own agenda. Agents： perceive, behave ＂reasonably＂, act in the environment, communicate with other agents. Cloud infrastructures can offer an ideal platform where run MAS systems simulations, applications and real-time running because of its large amount of processing and memory resources that can be dynamically configured for executing large agent-based software at unprecedented scale. Cloud computing can help chemical and food companies drive operational excellence; meet growing and changing customer demands; accelerate new product innovation and ramp-to-volume manufacturing in key markets; reduce IT spending; manage and mitigate supply chain risks; and enable faster and more flexible delivery of new IT system. Production type of SOC （service-oriented computing） can be inspired by a ＂Cloud＂, for the production of ＂Cloud＂ offers an attractive and natural solutions in several computing trends such as delivery system over the Internet, use of utilities, flexibility, virtualization, a ＂grid＂ distributed computing, outsourcing, Web 2.0, etc.. Production of the ＂Cloud＂ is also considered as a new multidisciplinary field that includes ＂network＂ production, virtual manufacturing, agile manufacturing, and of course cloud computing. Examples of cloud computing and MAS applications in food and chemistry development and industry, proposition of using multi-agent systems in the control of batch processes, modified ACO （ant colony optimization） approach for the diversified service allocation and scheduling mechanism in cloud paradigma, examples of applications in a business area were studied in the paper.展开更多
The state of the physics of convective clouds and cloud seeding is discussed briefly. It is noted that at the present time there is a transition from the stage of investigation of “elementary” processes in the cloud...The state of the physics of convective clouds and cloud seeding is discussed briefly. It is noted that at the present time there is a transition from the stage of investigation of “elementary” processes in the clouds to the stage of studying the formation of macro- and microstructural characteristics of clouds as a whole, taking into account their system properties. The main directions of the development of cloud physics at the upcoming stage of its development are discussed. The paper points out that one of these areas is the determination of the structure-forming factors for the clouds and the study of their influence on their formation and evolution. It is noted that one of such factors is the interaction of clouds with their surrounding atmosphere, and the main method of studying its role in the processes of cloud formation is mathematical modeling. A three-dimensional nonstationary model of convective clouds is presented with a detailed account of the processes of thermohydrodynamics and microphysics, which is used for research. The results of modeling the influence of the wind field structure in the atmosphere on the formation and evolution of clouds are presented. It is shown that the dynamic characteristics of the atmosphere have a significant effect on the formation of macro- and microstructural characteristics of convective clouds: the more complex the structure of the wind field in the atmosphere (i.e., the more intense the interaction of the atmosphere and the cloud), the less powerful the clouds are formed.展开更多
Large-scale point cloud datasets form the basis for training various deep learning networks and achieving high-quality network processing tasks.Due to the diversity and robustness constraints of the data,data augmenta...Large-scale point cloud datasets form the basis for training various deep learning networks and achieving high-quality network processing tasks.Due to the diversity and robustness constraints of the data,data augmentation(DA)methods are utilised to expand dataset diversity and scale.However,due to the complex and distinct characteristics of LiDAR point cloud data from different platforms(such as missile-borne and vehicular LiDAR data),directly applying traditional 2D visual domain DA methods to 3D data can lead to networks trained using this approach not robustly achieving the corresponding tasks.To address this issue,the present study explores DA for missile-borne LiDAR point cloud using a Monte Carlo(MC)simulation method that closely resembles practical application.Firstly,the model of multi-sensor imaging system is established,taking into account the joint errors arising from the platform itself and the relative motion during the imaging process.A distortion simulation method based on MC simulation for augmenting missile-borne LiDAR point cloud data is proposed,underpinned by an analysis of combined errors between different modal sensors,achieving high-quality augmentation of point cloud data.The effectiveness of the proposed method in addressing imaging system errors and distortion simulation is validated using the imaging scene dataset constructed in this paper.Comparative experiments between the proposed point cloud DA algorithm and the current state-of-the-art algorithms in point cloud detection and single object tracking tasks demonstrate that the proposed method can improve the network performance obtained from unaugmented datasets by over 17.3%and 17.9%,surpassing SOTA performance of current point cloud DA algorithms.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The aging process is an inexorable fact throughout our lives and is considered a major factor in develo ping neurological dysfunctions associated with cognitive,emotional,and motor impairments.Aging-associated neurodegenerative diseases are characterized by the progressive loss of neuronal structure and function.
基金supported by the Key Research Program of the Chinese Academy of Sciences (Grant No. KZZD-EW-05-01)the National Basic Research Program of China (973 Program) (Grant No. 2014CB441402)
文摘High-resolution numerical simulation data of a rainstorm triggering debris flow in Sichuan Province of China simulated by the Weather Research and Forecasting （WRF） Model were used to study the dominant cloud microphysical processes of the torrential rainfall.The results showed that：（1） In the strong precipitation period,particle sizes of all hydrometeors increased,and mean-mass diameters of graupel increased the most significantly,as compared with those in the weak precipitation period; （2） The terminal velocity of raindrops was the strongest among all hydrometeors,followed by graupel＇s,which was much smaller than that of raindrops.Differences between various hydrometeors＇ terminal velocities in the strong precipitation period were larger than those in the weak precipitation period,which favored relative motion,collection interaction and transformation between the particles.Absolute terminal velocity values of raindrops and graupel were significantly greater than those of air upward velocity,and the stronger the precipitation was,the greater the differences between them were; （3） The orders of magnitudes of the various hydrometeors＇ sources and sinks in the strong precipitation period were larger than those in the weak precipitation period,causing a difference in the intensity of precipitation.Water vapor,cloud water,raindrops,graupel and their exchange processes played a major role in the production of the torrential rainfall,and there were two main processes via which raindrops were generated：abundant water vapor condensed into cloud water and,on the one hand,accretion of cloud water by rain water formed rain water,while on the other hand,accretion of cloud water by graupel formed graupel,and then the melting of graupel formed rain water.
文摘Convective processes affect large-scale environments through cloud-radiation interaction, cloud micro- physical processes, and surface rainfall processes. Over the last three decades, cloud-resolving models （CRMs） have demonstrated to be capable of simulating convective-radiative responses to an imposed large-scale forcing. The CRM-produced cloud and radiative properties have been utilized to study the convective- related processes and their ensemble effects on large-scale circulations. This review the recent progress on the understanding of convective processes with the use of CRM simulations, including precipitation processes; cloud microphysical and radiative processes; dynamical processes; precipitation efficiency; diurnal variations of tropical oceanic convection; local-scale atmosphere-ocean coupling processes; and tropical convective-radiative equilibrium states. Two different ongoing applications of CRMs to general circulation models （GCMs） are discussed： replacing convection and cloud schemes for studying the interaction between cloud systems and large-scale circulation, and improving the schemes for climate simulations.
基金This study was supported by the State Key Basic Program:Research on the Formation Mechanism and Prediction Theory of Severe Synoptic Dis- asters in China No.G1998040907 and the National NaturalSciences Foundation of China under Grant No.49735180
文摘Cloud micro-physical structures in a precipitation system associated with the Meiyu front are observed using the balloon-borne Precipitation Particle Image Sensor at Baoshan observatory station, Shanghai during June and July 1999. The vertical distributions of various cloud particle size, number density, and mass density are retrieved from the observations. Analyses of observations show that ice-phase particles (ice crystals, graupel, snowflakes, and frozen drops) often exist in the cloud of torrential rain associated with the Meiyu front. Among the various particles, ice crystals and graupel are the most numerous, but graupel and snow have the highest mass density. Ice-phase particles coexist with liquid water droplets near the 0°C level. The graupel is similarly distributed with height as the ice crystals. Raindrops below the 0°C level are mainly from melted grauple, snowflakes and frozen drops. They may further grow larger by coalescence with smaller ones as they fall from the cloud base. Numerical simulations using the non-hydrostatic meso-scale model MM5 with the Reisner graupel explicit moisture scheme confirm the main observational results. Rain water at the lower level is mainly generated from the melting of snow and graupel falling from the upper level where snow and graupel are generated and grown from collection with cloud and rain water. Thus the mixed-phase cloud process, in which ice phase coexists and interacts with liquid phase (cloud and rain drops), plays the most important role in the formation and development of heavy convective rainfall in the Meiyu frontal system.
基金supported by the National Natural Science Foundation of China(61902222)the Taishan Scholars Program of Shandong Province(tsqn201909109)+1 种基金the Natural Science Excellent Youth Foundation of Shandong Province(ZR2021YQ45)the Youth Innovation Science and Technology Team Foundation of Shandong Higher School(2021KJ031)。
文摘Process discovery, as one of the most challenging process analysis techniques, aims to uncover business process models from event logs. Many process discovery approaches were invented in the past twenty years;however, most of them have difficulties in handling multi-instance sub-processes. To address this challenge, we first introduce a multi-instance business process model(MBPM) to support the modeling of processes with multiple sub-process instantiations. Formal semantics of MBPMs are precisely defined by using multi-instance Petri nets(MPNs)that are an extension of Petri nets with distinguishable tokens.Then, a novel process discovery technique is developed to support the discovery of MBPMs from event logs with sub-process multi-instantiation information. In addition, we propose to measure the quality of the discovered MBPMs against the input event logs by transforming an MBPM to a classical Petri net such that existing quality metrics, e.g., fitness and precision, can be used.The proposed discovery approach is properly implemented as plugins in the Pro M toolkit. Based on a cloud resource management case study, we compare our approach with the state-of-theart process discovery techniques. The results demonstrate that our approach outperforms existing approaches to discover process models with multi-instance sub-processes.
基金The authors benefited from discussions with Professors C.-H.Sui and Xu Huanbin.The comments of the three anonymous reviewers are acknowledged.This research was supported by the National Natural Science Foundation of China.(Grant Nos.40375036 and 40105006).
文摘The understanding of the cloud processes of snowfall is essential to the artificial enhancement of snow and the numerical simulation of snowfall. The mesoscale model MM5 is used to simulate a moderate snowfall event in North China that occurred during 20-21 December 2002. Thirteen experiments are performed to test the sensitivity of the simulation to the cloud physics with different cumulus parameterization schemes and different options for the Goddard cloud microphysics parameterization schemes. It is shown that the cumulus parameterization scheme has little to do with the simulation result. The results also show that there are only four classes of water substances, namely the cloud water, cloud ice, snow, and vapor, in the simulation of the moderate snowfall event. The analysis of the cloud microphysics budgets in the explicit experiment shows that the condensation of supersaturated vapor, the depositional growth of cloud ice, the initiation of cloud ice, the accretion of cloud ice by snow, the accretion of cloud water by snow, the deposition growth of snow, and the Bergeron process of cloud ice are the dominant cloud microphysical processes in the simulation. The accretion of cloud water by snow and the deposition growth of the snow are equally important in the development of the snow.
基金Special Found for Meteorological Research in the Public Interest(GYHY201506008)Study on Parameterization of Boundary Layer Stratocumulus Process of GRAPES Model
文摘Typhoon KROSA in 2007 is simulated using GRAPES,a mesoscale numerical model,in which a two-parameter mixed-phase microphysics scheme is implanted.A series of numerical experiments are designed to test the sensitivity of landfalling typhoon structure and precipitation to varying cloud microphysics and latent heat release.It is found that typhoon track is sensitive to different microphysical processes and latent heat release.The cloud structures of simulated cyclones can be quite different with that of varying microphysical processes.Graupel particles play an important role in the formation of local heavy rainfall and the maintenance of spiral rainbands.Analysis reveals that the feedback of latent heat to dynamic fields can significantly change the content and distribution of cloud hydrometeors,thus having an impact on surface precipitation.
基金National Natural Science Foundation of China(41275060)National Natural Science Foundation of China(41275145)+1 种基金National Key Basic Research Program of China(2014CB953903)Fundamental Research Funds for the Central Universities(131gjc03)
文摘We analyzed cloud microphysical processes' latent heat characteristics and their influence on an autumn heavy rain event over Hainan Island,China,using the mesoscale numerical model WRF and WRF-3DVAR system.We found that positive latent heat occurred far above the zero layer,while negative latent heat occurred mainly under the zero layer.There was substantially more positive latent heat than negative latent heat,and the condensation heating had the most important contribution to the latent heat increase.The processes of deposition,congelation,melting and evaporation were all characterized by weakening after their intensification;however,the variations in condensation and sublimation processes were relatively small.The main cloud microphysical processes for positive latent heat were condensation of water vapor into cloud water,the condensation of rain,and the deposition increase of cloud ice,snow and graupel.The main cloud microphysical processes for negative latent heat were the evaporation of rain,the melting and enhanced melting of graupel.The latent heat releases due to different cloud microphysical processes have a significant impact on the intensity of precipitation.Without the condensation and evaporation of rain,the total latent heating would decrease and the moisture variables and precipitation would reduce significantly.Without deposition and sublimation,the heating in high levels would decrease and the precipitation would reduce.Without congelation and melting,the latent heating would enhance in the low levels,and the precipitation would reduce.
基金National Science Foundation of China (40775066)Shanghai Typhoon Research Foundation (2008ST07)
文摘With the Reisner-2 bulk microphysical parameterization of the fifth-generation Pennsylvania State University-U.S. National Center for Atmospheric Research （PSU--NCAR） Mesoscale Model （MM5）, this paper investigates the microphysical sensitivities of Typhoon Chanchu. Four different microphysical sensitivity experiments were designed with an objective to evaluate their respective impacts in modulating intensity forecasts and microphysics budgets of the typhoon. The set of sensitivity experiments were conducted that comprised （a） a control experiment （CTL）, （b） NEVPRW from which evaporation of rain water was suppressed, （c） NGP from which graupel was taken, and （d） NMLT from which melting of snow and graupel was removed. We studied the impacts of different cloud microphysical processes on the track, intensity and precipitation of the typhoon, as well as the kinematics, thermodynamics and vertical structural characteristics of hydrometeors in the inner core of the typhoon. Additionally, the budgets of the cloud microphysical processes in the fine domain were calculated to quantify the importance of each microphysical process for every sensitivity experiment. The primary results are as follows： （1） It is found that varying cloud microphysics parameters produce little sensitivity in typhoon track experiments. （2） The experiment of NGP produces the weakest storm, while the experiment of NMLT produces the strongest storm, and the experiment of NEVPRW also produces stronger storms than CTL. （3） Varying parameters of cloud rnicrophysics have obvious impacts on the precipitation, kinematics, and thermodynamics of the typhoon and the vertical structural characteristics of hydrometeors in the typhoon＇s inner core. （4） Most budgets of cloud microphysics in NMLT are larger than in CTL, while they are 20%-60% smaller in NEVPRW than in CTL.
基金National Basic Research Program of China (973 Program) (2009CB421505)National Natural Science Foundation of China (40775036)Knowledge Innovation Program of Chinese Academy of Sciences (IAP07214)
文摘The detailed surface rainfall processes associated with landfalling typhoon Kaemi（2006） are investigated based on hourly data from a two-dimensional cloud-resolving model simulation. The model is integrated for 6 days with imposed large-scale vertical velocity, zonal wind, horizontal temperature and vapor advection from National Center for Environmental Prediction （NCEP） / Global Data Assimilation System （GDAS） data. The simulation data are validated with observations in terms of surface rain rate. The Root-Mean-Squared （RMS） difference in surface rain rate between the simulation and the gauge observations is 0.660 mm h^-1, which is smaller than the standard deviations of both the simulated rain rate （0.753 mm h^-1） and the observed rain rate （0.833 mm h^-1）. The simulation data are then used to study the physical causes associated with the detailed surface rainfall processes during the landfall. The results show that time averaged and model domain-mean Ps mainly comes from large-scale convergence （QWVF） and local vapor loss （positive QWVT）. Large underestimation （about 15%） of Ps will occur if QWVT and QCM （cloud source/sink） are not considered as contributors to Ps ,QWVF accounts for the variation of P during most of the integration time, while it is not always a contributor to Ps,Sometimes surface rainfall could occur when divergence is dominant with local vapor loss to be a contributor to Ps - Surface rainfall is a result ofmulti-timescale interactions. QWVE possesses the longest time scale and the lowest frequeney the second and QCM of variation with time and may exert impact on P on longer time scales. QWVF possesses longest time scale and lowest frequency and can explain most of the variation of Ps. QWVT possess shorter time scales and higher frequencies, which can explain more detailed variations in Ps. Partitioning analysis shows that stratiform rainfall is dominant from the morning of 26 July till the late night of 27 July. After that, convective rainfall dominates till about 1000 LST 28 July. Before 28 July, the variations of QWVT in rainfall-free regions contribute less to that of the domain-mean QWVT while after that they contribute much, which is consistent to the corresponding variations in their fractional coverage. The variations of QWVF in rainfall regions are the main contributors to that of the domain-mean QWVF, then the main contributors to the surface rain rate before the afternoon of 28 July.
基金Project supported by the National Basic Research Program of China (Grant No. 2012CB417201)the National Natural Science Foundation of China (Grant Nos. 41075034,40930950,40975034,and 41075044)
文摘The effects of sea surface temperature（SST）,cloud radiative and microphysical processes,and diurnal variations on rainfall statistics are documented with grid data from the two-dimensional equilibrium cloud-resolving model simulations.For a rain rate of higher than 3 mm.h 1,water vapor convergence prevails.The rainfall amount decreases with the decrease of SST from 29℃ to 27℃,the inclusion of diurnal variation of SST,or the exclusion of microphysical effects of ice clouds and radiative effects of water clouds,which are primarily associated with the decreases in water vapor convergence.However,the amount of rainfall increases with the increase of SST from 29℃ to 31℃,the exclusion of diurnal variation of solar zenith angle,and the exclusion of the radiative effects of ice clouds,which are primarily related to increases in water vapor convergence.For a rain rate of less than 3 mm.h 1,water vapor divergence prevails.Unlike rainfall statistics for rain rates of higher than 3 mm.h 1,the decrease of SST from 29℃ to 27℃ and the exclusion of radiative effects of water clouds in the presence of radiative effects of ice clouds increase the rainfall amount,which corresponds to the suppression in water vapor divergence.The exclusion of microphysical effects of ice clouds decreases the amount of rainfall,which corresponds to the enhancement in water vapor divergence.The amount of rainfall is less sensitive to the increase of SST from 29℃ to 31℃ and to the radiative effects of water clouds in the absence of the radiative effects of ice clouds.
基金supported by the National Natural Science Foundation of China[grant number 41475039]the National Basic Research Program of China[grant number 2015CB953601]
文摘Cloud radiative processes are important in regulating weather and climate. Precipitation responses to radiative processes of water- and ice-clouds are investigated by analyzing mean equilibrium simulation data from a series of two-dimensional cloud-resolving model sensitivity experiments in this study. The model is imposed by zero vertical velocity.The exclusion of water radiative processes in the presence of ice radiative processes, as well as the removal of ice radiative processes, enhances tropospheric Iongwave radiative cooling and lowers air temperature and the saturation mixing ratio. The reduction in the saturation mixing ratio leads to an increase in vapor condensation and an associated release of latent heat, which increases rainfall. The elimination of water radiative processes strengthens local atmospheric warming Iongwave radiative cooling. The enhanced warming melting of graupel, which increases rainfa n the upper troposphere via a reduction in ncreases the rain source via an increase in the
文摘The prevailing idea so far about why the rainfall occurs was that after agglutination of water droplets with condensation nuclei, the size of the particle formed by the condensation nuclei connected with droplets of water increased considerably and caused its fall. This idea has led to numerous scientific publications in which empirical distribution functions of clouds’ water droplets sizes were proposed. Estimates values provided by these empirical distribution functions, in most cases, were validated by comparison with UHF Radar measurements. The condensation nuclei concept has not been sufficiently exploited and this has led meteorologists to error, in their attempt to describe the clouds, thinking that clouds were formed by liquid water droplets. Indeed, MBANE BIOUELE paradox (2005) confirms this embarrassing situation. In fact, when applying Archimedes theorem to a liquid water droplet suspended in the atmosphere, we obtain a meaningless inequality ?which makes believe that the densities of pure water in liquid and solid phases are much lower than that of the atmosphere considered at the sea level. This meaningless inequality is easy to contradict: of course, if you empty a bottle of pure liquid water in the ocean (where z is equal to 0), this water will not remain suspended in the air, i.e., application of Archimedes’ theorem allows realizing that there is no liquid (or solid) water droplet, suspended in the clouds. Indeed, all liquid (or solid) water droplets which are formed in clouds, fall under the effect of gravity and produce rains. This means that our current description of the clouds is totally wrong. In this study, we describe the clouds as a gas composed of dry air and saturated water vapor whose optical properties depend on temperature, i.e., when the temperature of a cloud decreases, the color of this gaseous system tends towards white.
文摘Cloud computing can offer a very powerful, reliable, predictable and scalable computing infrastructure for the execution of MAS （multi-agent systems） implementing complex agent-based applications such when modelling, simulation and real-time running of complex systems must be provided. Multi-agent systems appears as an adequate approach to current challenges in many areas. Between important qualities of MAS also belongs to, that they are open, interoperable, and heterogenous systems. The agent is active, a program entity, has its own ideas how to perform the tasks of the own agenda. Agents： perceive, behave ＂reasonably＂, act in the environment, communicate with other agents. Cloud infrastructures can offer an ideal platform where run MAS systems simulations, applications and real-time running because of its large amount of processing and memory resources that can be dynamically configured for executing large agent-based software at unprecedented scale. Cloud computing can help chemical and food companies drive operational excellence; meet growing and changing customer demands; accelerate new product innovation and ramp-to-volume manufacturing in key markets; reduce IT spending; manage and mitigate supply chain risks; and enable faster and more flexible delivery of new IT system. Production type of SOC （service-oriented computing） can be inspired by a ＂Cloud＂, for the production of ＂Cloud＂ offers an attractive and natural solutions in several computing trends such as delivery system over the Internet, use of utilities, flexibility, virtualization, a ＂grid＂ distributed computing, outsourcing, Web 2.0, etc.. Production of the ＂Cloud＂ is also considered as a new multidisciplinary field that includes ＂network＂ production, virtual manufacturing, agile manufacturing, and of course cloud computing. Examples of cloud computing and MAS applications in food and chemistry development and industry, proposition of using multi-agent systems in the control of batch processes, modified ACO （ant colony optimization） approach for the diversified service allocation and scheduling mechanism in cloud paradigma, examples of applications in a business area were studied in the paper.
文摘The state of the physics of convective clouds and cloud seeding is discussed briefly. It is noted that at the present time there is a transition from the stage of investigation of “elementary” processes in the clouds to the stage of studying the formation of macro- and microstructural characteristics of clouds as a whole, taking into account their system properties. The main directions of the development of cloud physics at the upcoming stage of its development are discussed. The paper points out that one of these areas is the determination of the structure-forming factors for the clouds and the study of their influence on their formation and evolution. It is noted that one of such factors is the interaction of clouds with their surrounding atmosphere, and the main method of studying its role in the processes of cloud formation is mathematical modeling. A three-dimensional nonstationary model of convective clouds is presented with a detailed account of the processes of thermohydrodynamics and microphysics, which is used for research. The results of modeling the influence of the wind field structure in the atmosphere on the formation and evolution of clouds are presented. It is shown that the dynamic characteristics of the atmosphere have a significant effect on the formation of macro- and microstructural characteristics of convective clouds: the more complex the structure of the wind field in the atmosphere (i.e., the more intense the interaction of the atmosphere and the cloud), the less powerful the clouds are formed.
基金Postgraduate Innovation Top notch Talent Training Project of Hunan Province,Grant/Award Number:CX20220045Scientific Research Project of National University of Defense Technology,Grant/Award Number:22-ZZCX-07+2 种基金New Era Education Quality Project of Anhui Province,Grant/Award Number:2023cxcysj194National Natural Science Foundation of China,Grant/Award Numbers:62201597,62205372,1210456foundation of Hefei Comprehensive National Science Center,Grant/Award Number:KY23C502。
文摘Large-scale point cloud datasets form the basis for training various deep learning networks and achieving high-quality network processing tasks.Due to the diversity and robustness constraints of the data,data augmentation(DA)methods are utilised to expand dataset diversity and scale.However,due to the complex and distinct characteristics of LiDAR point cloud data from different platforms(such as missile-borne and vehicular LiDAR data),directly applying traditional 2D visual domain DA methods to 3D data can lead to networks trained using this approach not robustly achieving the corresponding tasks.To address this issue,the present study explores DA for missile-borne LiDAR point cloud using a Monte Carlo(MC)simulation method that closely resembles practical application.Firstly,the model of multi-sensor imaging system is established,taking into account the joint errors arising from the platform itself and the relative motion during the imaging process.A distortion simulation method based on MC simulation for augmenting missile-borne LiDAR point cloud data is proposed,underpinned by an analysis of combined errors between different modal sensors,achieving high-quality augmentation of point cloud data.The effectiveness of the proposed method in addressing imaging system errors and distortion simulation is validated using the imaging scene dataset constructed in this paper.Comparative experiments between the proposed point cloud DA algorithm and the current state-of-the-art algorithms in point cloud detection and single object tracking tasks demonstrate that the proposed method can improve the network performance obtained from unaugmented datasets by over 17.3%and 17.9%,surpassing SOTA performance of current point cloud DA algorithms.
