The Probability Density Function Related to Shallow Cumulus Entrainment Rate and Its Influencing Factors in a Large-Eddy Simulation

The process of entrainment-mixing between cumulus clouds and the ambient air is important for the development of cumulus clouds.Accurately obtaining the entrainment rate(λ)is particularly important for its parameterization within the overall cumulus parameterization scheme.In this study,an improved bulk-plume method is proposed by solving the equations of two conserved variables simultaneously to calculateλof cumulus clouds in a large-eddy simulation.The results demonstrate that the improved bulk-plume method is more reliable than the traditional bulk-plume method,becauseλ,as calculated from the improved method,falls within the range ofλvalues obtained from the traditional method using different conserved variables.The probability density functions ofλfor all data,different times,and different heights can be well-fitted by a log-normal distribution,which supports the assumed stochastic entrainment process in previous studies.Further analysis demonstrate that the relationship betweenλand the vertical velocity is better than other thermodynamic/dynamical properties;thus,the vertical velocity is recommended as the primary influencing factor for the parameterization ofλin the future.The results of this study enhance the theoretical understanding ofλand its influencing factors and shed new light on the development ofλparameterization.

Approximation approach to the SRM based on root decomposition in the simulation of spatially varying ground motions

The spectral representation method （SRM） is widely used to simulate spatially varying ground motions. This study focuses on the approximation approach to the SRM based on root decomposition, which can improve the efficiency of the simulation. The accuracy of the approximation approach may be affected by three factors： matrix for decomposition, distribution of frequency interpolation nodes and elements for interpolation. The influence of these factors on the accuracy of this approach is examined and the following conclusions are drawn. The SRM based on the root decomposition of the lagged coherency matrix exhibits greater accuracy than the SRM based on the root decomposition of the cross spectral matrix. The equal energy distribution of frequency interpolation nodes proposed in this study is more effective than the counter pith with an equal spacing. Elements for interpolation do not have much of an effect on the accuracy, so interpolation of the elements of the decomposed matrix is recommended because it is less complicated from a computational efficiency perspective.

Simulation Analysis on Spatial Pattern of Urban Population in Shenyang City,China in Late 20th Century

The spatial distribution of urban population can reflect significantly urban functions and development status. Shenyang, as a typical old industrial city in China, has experienced considerable changes in spatial distribution of population in the process of urban transformation, resulting in the change of urban spatial structure. Based on the sub-district data of Chinese national population censuses in 1982, 1990 and 2000, this study simulates the evolution pattern of spatial distribution of urban population in Shenyang City. Using statistical method and exploratory spatial data analysis (ESDA), we found that the population distribution, on the whole, has presented a balanced and decentralized trend since the 1980s, which characterizes with Chinese suburbanization. Furthermore, based on the investigation of the pattern of population distribution, it is concluded that the negative exponential model fitted the distribution best, and population concentration in the inner suburb kept increasing gradually, meanwhile, the spatial structure of population distribution has presented a polycentric feature since the 1980s. The parameters of the model show that population in the urban core concentrate significantly all the time. The increase of population in the inner suburb influences the population distribution pattern more and more importantly, but the concentration intensity of population cores in inner suburb is still low.

Dependence of the Accuracy of Precipitation and Cloud Simulation on Temporal and Spatial Scales

Precipitation and associated cloud hydrometeors have large temporal and spatial variability, which makes accurate quantitative precipitation forecasting difficult. Thus, dependence of accurate precipitation and associated cloud simulation on temporal and spatial scales becomes an important issue. We report a cloud- resolving modeling analysis on this issue by comparing the control experiment with experiments perturbed by initial temperature, water vapor, and cloud conditions. The simulation is considered to be accurate only if the root-mean-squared difference between the perturbation experiments and the control experiment is smaller than the standard deviation. The analysis may suggest that accurate precipitation and cloud simulations cannot be obtained on both fine temporal and spatial scales simultaneously, which limits quanti- tative precipitation forecasting. The accurate simulation of water vapor convergence could lead to accurate precipitation and cloud simulations on daily time scales, but it may not be beneficial to precipitation and cloud simulations on hourly time scales due to the dominance of cloud processes.

Evaluation of the performance of alternative assessment configurations to account for the spatial heterogeneity in age-structure: a simulation study based on Indian Ocean albacore tuna

Various population structures or spatial heterogeneities in population distribution have been an important source of model misspecification and have had an impact on estimation performance in fisheries stock assessment.In this study,we simulated the Indian Ocean albacore spatial heterogeneity in age-structure using Stock Synthesis according to the stage-dependent migration rate and region-dependent fishing mortality rate and generated the stock assessment data.Based on these data,we investigated the performances of different spatial configurations,selectivity curves and selections of CPUE(catch per unit effort)indices of the assessment models which were used to account for spatial heterogeneity.The results showed:(1)although the spatially explicit configurations,which exactly matched the operating model,provided unbiased and accurate estimates of relative spawning biomass,relative fishing mortality rate and maximum sustainable yield in all simulation scenarios,their performance may be very poor if there were mismatches between them and the operating model due to gaps in knowledge and data;(2)for spatially explicit assessment configuration,the correct boundary was required,but for non-spatially explicit assessment configuration,it seemed more important for analysts to partition the area to properly reflect the transition in field data and to effectively account for the impacts of ignoring the spatial structure by using the additional spatially referenced parameters;(3)although the areas-as-fleets methods and flexible time-varying selectivity curves could be used as better alternative approaches to account for spatial structure,these configurations could not completely eliminate the impacts of model misspecification and the quality of estimates of different quantities from the same assessment model may be inconsistent or the performance of the same assessment configuration may fluctuate significantly between simulation scenarios;(4)although the worst estimates could generally be avoided by using multiple CPUE indices,there were no best solutions to select or regenerate the CPUE indices to account for the impacts of the ignored spatial structure to obviously improve the quality of stock assessment.Compared with the results of assessment model configurations which are used to account for the spatial structure by different modelers,the performances of the configurations are always casespecific except for spatially explicit configurations which exactly match the operating model.In this sense,our study will not only provide some insights into the current Indian Ocean albacore stock assessment but also enrich existing knowledge regarding the performance of assessment configurations to account for spatial structure.

Study on Simulation of Remotely Operated Underwater Vehicle Spatial Motion

In order to analyze the spatial maneuverability of the remotely operated underwater vehicle(ROV),the 6-DOF motion mathematic model of the ROV was founded.Hydrodynamics were analyzed by using the Taylor series.The thrusters on the ROV were discussed.This paper considers three cases of motion simulation:vertical motion,rotational motion and Z-shape motion.A series of simulation experiments showed that the 6-DOF motion mathematic model was correct and reliable,and also fit with the scene simulation.

Large Eddy Simulation of Vertical Structure and Size Density of Deep Layer Clouds

In a convective scheme featuring a discretized cloud size density, the assumed lateral mixing rate is inversely proportional to the exponential coefficient of plume size. This follows a typical assumption of-1, but it has unveiled inherent uncertainties, especially for deep layer clouds. Addressing this knowledge gap, we conducted comprehensive large eddy simulations and comparative analyses focused on terrestrial regions. Our investigation revealed that cloud formation adheres to the tenets of Bernoulli trials, illustrating power-law scaling that remains consistent regardless of the inherent deep layer cloud attributes existing between cloud size and the number of clouds. This scaling paradigm encompasses liquid, ice, and mixed phases in deep layer clouds. The exponent characterizing the interplay between cloud scale and number in the deep layer cloud, specifically for liquid, ice, or mixed-phase clouds, resembles that of shallow convection,but converges closely to zero. This convergence signifies a propensity for diminished cloud numbers and sizes within deep layer clouds. Notably, the infusion of abundant moisture and the release of latent heat by condensation within the lower atmospheric strata make substantial contributions. However, this role in ice phase formation is limited. The emergence of liquid and ice phases in deep layer clouds is facilitated by the latent heat and influenced by the wind shear inherent in the middle levels. These interrelationships hold potential applications in formulating parameterizations and post-processing model outcomes.

Monte Carlo simulations of biaxial structure in thin hybrid nematic film based upon spatially anisotropic pair potential

Hybrid nematic films have been studied by Monte Carlo simulations using a lattice spin model, in which the pair potential is spatially anisotropic and dependent on elastic constants of liquid crystals. We confirm in the thin hybrid nematic film the existence of a biaxially nonbent structure and the structure transition from the biaxial to the bent-director structure, which is similar to the result obtained using the Lebwoh-Lasher model. However, the step-like director＇s profile, characteristic for the biaxial structure, is spatially asymmetric in the film because the pair potential leads to K1 ≠ K3. We estimate the upper cell thickness to be 69 spin layers, in which the biaxial structure can be found.

Simulation of temporal and spatial change of N_2O emissions in the Yangtze River Delta

A biogeochemical model(DNDC) is combined with a plant ecological model to estimate N_2O emission from rice paddy fields in the Yangtze River Delta region. The model is driven by local meteorological, soil, and physiological data and is validated for 1999 and 2000 at a site in the region, which showed that the simulated N_2O emissions agree fairly well with the observed data. This adds some confidence in the estimated N_2O emissions during 1950 and 2000 in the Hangzhou Region. A significant correlation between the N_2O emissions and the population for the Hangzhou Region is found, which is due to a combination of increased application of fertilizers and cultivated area. Such a correlation can not be established for the whole Yangtze River Delta region when the data of both urban and rural areas are included. However, when the data from the heavily urbanized areas are excluded, a significant correlation between population and N_2O emissions emerges. The results show clearly that both the temporal and the spatial N_2O emissions have significant positive relationship with population under traditional farming practice. These results have implications for suitable mitigation options towards a sustainable agriculture and environment in this region.

Spatial Modeling of Soil Lime Requirements with Uncertainty Assessment Using Geostatistical Sequential Indicator Simulation

This work presents and analyses a geostatistical methodology for spatial modelling of Soil Lime Requirements (SLR) considering punctual samples of Cation Exchange Capacity (CEC) and Base Saturation (BS) soil properties. Geostatistical Sequential Indicator Simulation is used to draw realizations from the joint uncertainty distributions of the CEC and the BS input variables. The joint distributions are accomplished applying the Principal Component Analyses (PCA) approach. The Monte Carlo method for handling error propagations is used to obtain realization values of the SLR model which are considered to compute and store statistics from the output uncertainty model. From these statistics, it is obtained predictions and uncertainty maps that represent the spatial variation of the output variable and the propagated uncertainty respectively. Therefore, the prediction map of the output model is qualified with uncertainty information that should be used on decision making activities related to the planning and management of environmental phenomena. The proposed methodology for SLR modelling presented in this article is illustrated using CEC and BS input sample sets obtained in a farm located in Ponta Grossa city, Paraná state, Brazil.

Spatial Pattern Change Simulation of Land Use in Yongchuan District of Chongqing City

In order to study the county scale land use structure during the rapid urbanization and more accurately grasp the dynamic process of land use and cover change,we combine GIS technology with CLUE-S model to research the spatial pattern change of land use in Yongchuan District of Chongqing City. The results show that the forest and farmland were main land use types going through changes in Yongchuan District during 2000-2010,accounting for more than 90% of the total area in each year; during 2000- 2010,the urban area was significantly increased,an increase of 16. 11%,and the urban area during 2005- 2010 was changed more dramatically than during 2000- 2005; forest area was slightly increased and farmland area was reduced by 1660 ha in 10 years. We set three scenarios on land use change in Yongchuan District for simulation and compare the predicted results. It can be concluded that driven by rapid urbanization,the change in land use landscape pattern in Yongchuan District is mainly focused on forest and farmland,the urban area is substantially increased,and the forest area also shows an increasing trend while the farmland area is reduced accordingly. Under ecological protection scenarios,the land use type having a protective effect on the ecological environment achieves better control effect.

Numerical Simulation of Spatial Distribution of Wave Overtopping on Non-reshaping Berm Breakwaters

This study presents the results of a 2D numerical modeling investigation on the performance of non-reshaping berm breakwaters with a special look at the spatial distribution of irregular wave overtopping using FLOW-3D CFD code.The numerical model is based on Reynolds-Averaged Navier-Stokes solver(RANS)and volume of fluid(VOF)surface capturing scheme(RANS-VOF).The numerical model has been validated using experimental data.The armor and core porosities have been used as calibration factors to reproduce the wave overtopping distribution.The computed distributions of wave overtopping behind the structure agree well with the measurements for a non-reshaping berm breakwater.A formula is derived to relate the spatial distribution of wave overtopping water behind non-reshaping berm breakwaters to non-dimensional forms of wave height,wave period,berm width,berm height,and armor freeboard based on numerical results.This formula model agreed reasonably well with numerical model results.

High-resolution simulation of upper-ocean submesoscale variability in the South China Sea:Spatial and seasonal dynamical regimes

Submesoscale processes in marginal seas usually have complex generating mechanisms,highly dependent on the local background flow and forcing.This numerical study investigates the spatial and seasonal differences of submesoscale activities in the upper ocean of the South China Sea(SCS)and the different dynamical regimes for sub-regions.The spatial and seasonal variations of vertical vorticity,horizontal convergence,lateral buoyancy gradient,and strain rate are analyzed to compare the submesoscale phenomenon within four sub-regions,the northern region near the Luzon Strait(R1),the middle ocean basin(R2),the western SCS(R3),and the southern SCS(R4).The results suggest that the SCS submesoscale processes are highly heterogeneous in space,with different seasonalities in each sub-region.The submesoscale activities in the northern sub-regions(R1,R2)are active in winter but weak in summer,while there appears an almost seasonal anti-phase in the western region(R3)compared to R1 and R2.Interestingly,no clear seasonality of submesoscale features is shown in the southern region(R4).Further analysis of Ertel potential vorticity reveals different generating mechanisms of submesoscale processes in different sub-regions.Correlation analyses also show the vertical extent of vertical velocity and the role of monsoon in generating submesoscale activities in the upper ocean of sub-regions.All these results suggest that the sub-regions have different regimes for submesoscale processes,e.g.,Kuroshio intrusion(R1),monsoon modulation(R2),frontal effects(R3),topography wakes(R4).

Evolution and Simulation of Spatial-temporal Heterogeneities in Ecological Background Quality of Changsha City

By GIS and ENVI,TM/ETM remote sensing images of five districts(Yuelu District,Furong District,Yuhua District,Tianxin District and Kaifu District) in Changsha City center in 2005,2010 and 2015 were interpreted.Moreover,distribution chart for ecological background factors in 2020 was simulated by using CA-Markov module in IDRISI.Using principal component analysis,evaluation model for ecological background quality of the city was established.Via circle analysi s,GS+semi variance function analysis,hot spot area analysis and grey correlation analysis,integrated analysis and evaluation on spatial heterogeneity evolution of ecological background quality in research region were conducted.Results showed that firstly Changsha overall has formed ecological pattern of landscape island city,but ecological background started to show the evolution trend of high heterogeneity and fragmentation under the construction land expansion,and ecological background quality of the city declined from 0.300,6 to 0.257,1 during 2005-2020.Secondly,ecological background quality of Changsha City had typical circle and axial gradient structure,and "eco tone" had the most violent evolution.Thirdly,spatial structure of ecological background quality had region,time and direction heterogeneities,and spatial heterogeneity of region was the most important.Fourthly,hot spot area distribution of ecological background quality evolution showed the "frog jump" trend of gathering in marginal zone and diffusing to peripheral zone.Fifthly,in driving factors of ecological background quality,industrialization rate had the highest grey correlation degree(0.842,1),and grey absolute correlation degree between ecological background quality in Yuelu District and industrialization rate was the highest(0.603,1).

A Simulation Study of Hierarchical Bayesian Fusion Spatial Small Area Model for Binary Outcome under Spatial Misalignment

Simulation (stochastic) methods are based on obtaining random samples θ5 from the desired distribution p(θ) and estimating the expectation of any function h(θ). Simulation methods can be used for high-dimensional distributions, and there are general algorithms which work for a wide variety of models. Markov chain Monte Carlo (MCMC) methods have been important in making Bayesian inference practical for generic hierarchical models in small area estimation. Small area estimation is a method for producing reliable estimates for small areas. Model based Bayesian small area estimation methods are becoming popular for their ability to combine information from several sources as well as taking account of spatial prediction of spatial data. In this study, detailed simulation algorithm is given and the performance of a non-trivial extension of hierarchical Bayesian model for binary data under spatial misalignment is assessed. Both areal level and unit level latent processes were considered in modeling. The process models generated from the predictors were used to construct the basis so as to alleviate the problem of collinearity between the true predictor variables and the spatial random process. The performance of the proposed model was assessed using MCMC simulation studies. The performance was evaluated with respect to root mean square error (RMSE), Mean absolute error (MAE) and coverage probability of corresponding 95% CI of the estimate. The estimates from the proposed model perform better than the direct estimate.

Using autologistic spatial models to simulate the distribution of land-use patterns in Zhangjiajie, Hunan Province

Nowadays, spatial simulation on land use patterns is one of the key contents of LUCC. Modeling is an important tool for simulating land use patterns due to its ability to integrate measurements of changes in land cover and the associated drivers. The conventional regression model can only analyze the correlation between land use types and driving factors but cannot depict the spatial autocorrelation characteristics. Land uses in Yongding County, which is located in the typical karst mountain areas in northwestern Hunan province, were investigated by means of modeling the spatial autocorrelation of land use types with the purpose of deriving better spatial land use patterns on the basis of terrain characteristics and infrastructural conditions. Through incorporating components describing the spatial autocorrelation into a conventional logistic model, we constructed a regression model （Autologistic model）, and used this model to simulate and analyze the spatial land use patterns in Yongding County. According to the comparison with the conventional logistic model without considering the spatial autocorrelation, this model showed better goodness and higher accuracy of fitting. The distribution of arable land, wood land, built-up land and unused land yielded areas under the ROC curves （AUC） was improved to 0.893, 0.940, 0.907 and 0.863 respectively with the autologistic model. It is argued that the improved model based on autologistic method was reasonable to a certain extent. Meanwhile, these analysis results could provide valuable information for modeling future land use change scenarios with actual conditions of local and regional land use, and the probability maps of land use types obtained from this study could also support government decision-making on land use management for Yongding County and other similar areas.

Simulation of multi-support depth-varying earthquake ground motions within heterogeneous onshore and offshore sites

This paper presents a novel approach to model and simulate the multi-support depth-varying seismic motions（MDSMs） within heterogeneous offshore and onshore sites.Based on 1 D wave propagation theory,the three-dimensional ground motion transfer functions on the surface or within an offshore or onshore site are derived by considering the effects of seawater and porous soils on the propagation of seismic P waves.Moreover,the depth-varying and spatial variation properties of seismic ground motions are considered in the ground motion simulation.Using the obtained transfer functions at any locations within a site,the offshore or onshore depth-varying seismic motions are stochastically simulated based on the spectral representation method（SRM）.The traditional approaches for simulating spatially varying ground motions are improved and extended to generate MDSMs within multiple offshore and onshore sites.The simulation results show that the PSD functions and coherency losses of the generated MDSMs are compatible with respective target values,which fully validates the effectiveness of the proposed simulation method.The synthesized MDSMs can provide strong support for the precise seismic response prediction and performance-based design of both offshore and onshore large-span engineering structures.

Hydrological Simulation Using TRMM and CHIRPS Precipitation Estimates in the Lower Lancang-Mekong River Basin

Satellite-based products with high spatial and temporal resolution provide useful precipitation information for data-sparse or ungauged large-scale watersheds. In the Lower Lancang-Mekong River Basin, rainfall stations are sparse and unevenly distributed, and the transboundary characteristic makes the collection of precipitation data more difficult, which has restricted hydrological processes simulation. In this study, daily precipitation data from four datasets(gauge observations, inverse distance weighted(IDW) data, Tropical Rainfall Measuring Mission(TRMM) estimates, and Climate Hazards Group InfraRed Precipitation with Stations(CHIRPS) estimates), were applied to drive the Soil and Water Assessment Tool(SWAT) model, and then their capability for hydrological simulation in the Lower Lancang-Mekong River Basin were examined. TRMM and CHIRPS data showed good performances on precipitation estimation in the Lower Lancang-Mekong River Basin, with the better performance for TRMM product. The Nash-Sutcliffe efficiency(NSE) values of gauge, IDW, TRMM, and CHIRPS simulations during the calibration period were 0.87, 0.86, 0.95, and 0.93 for monthly flow, respectively, and those for daily flow were 0.75, 0.77, 0.86, and 0.84, respectively. TRMM and CHIRPS data were superior to rain gauge and IDW data for driving the hydrological model, and TRMM data produced the best simulation performance. Satellite-based precipitation estimates could be suitable data sources when simulating hydrological processes for large data-poor or ungauged watersheds, especially in international river basins for which precipitation observations are difficult to collect. CHIRPS data provide long precipitation time series from 1981 to near present and thus could be used as an alternative precipitation input for hydrological simulation, especially for the period without TRMM data. For satellite-based precipitation products, the differences in the occurrence frequencies and amounts of precipitation with different intensities would affect simulation results of water balance components, which should be comprehensively considered in water resources estimation and planning.

A STUDY ON CELLULAR AUTOMATA BASED ON RELATIONAL DATABASES AND SPATIO-TE MPORAL SIMULATIONS OF CULTURE DIFFUSION

This paper presents a development o f the extended Cellular Automata9CA),based on relational databases(RDB),to model dynamic interactions amon g spatial objects.The integration o f Geographical Information System(GIS)and CA has the great advantage of simu lationg geographical processes.But standard CA has some restrictions i n cellular shape and neighbourhood and neighbour rules,which restrict the CA’ s ability to simulate complex,real world environ-ments.This paper discusses a cell’ s spatialrelationbasedonthe spatialobject’ s geometricalandmon -geometricalc haracter-istics,and extends the cell’ s neighbour definition,and considers that the cell’ s neighbour lies in the forms of not on ly spa-tial adjacency but also attribute co rrelation.This paper then puts forw ard that spatial relations between t wo different cells can be divided into three types,including spatial adjacency,neighbour hood and complicated separation.Ba sed on tradition-al ideas,it is impossible to settle CA’ s restrictions completely.RDB -based CA is an academic experiment,in which some fields ard desighed to describe the essential information needed to define and select a cell’ s neighbour.The culture innovation diffusion system has mul tiple forms of space diffusion and in herited characteristics that the RD B -based CA is capable of simulating more effectiv ely.Finally this paper details a successful case study on the diffusion o f fashion wear trends.Compared to the original CA,the RDB -based CA is a more natural and efficient representation of human k nowl-edge over space,and is an effective t ol in simulation complex systems that have multiple forms of spatial diff usion.

Spatio-temporal Dynamic Simulation of Land use and Ecological Risk in the Yangtze River Delta Urban Agglomeration,China

Rapid urbanization leads to dramatic changes in land use patterns,and the land use/cover change(LUCC)can reflect the spatial impact of urbanization on the ecological environment.Simulating the process of LUCC and predicting the ecological risk future changes can provide supports for urban ecological management.Taking the Yangtze River Delta Urban Agglomeration(YRDUA),China as the study area,four developmental scenarios were set on the basis of the land use data from 2005 to 2015.The temporal land use changes were predicted by the integration of the system dynamic and the future land use simulation(SD-FLUS)model,and the geographically weighted regression(GWR)model was used to identify the spatial heterogeneity and evolution characteristics between ecological risk index(ERI)and socio-economic driving forces.Results showed that:1)From 2005 to 2015,the expansion of construction land(7670.24 km^(2))mainly came from the occupation of cultivated land(7854.22 km2).The Kappa coefficient of the SD-FLUS model was 0.886,indicating that this model could be used to predict the future land use changes in the YRDUA.2)Gross domestic production(GDP)and population density(POP)showed a positive effect on the ERI,and the impact of POP exceeded that of GDP.The ERI showed the characteristics of zonal diffusion and a slight upward trend,and the high ecological risk region increased by 6.09%,with the largest increase.3)Under different developmental scenarios,the land use and ecological risk patterns varied.The construction land is increased by 5.76%,7.41%,5.25%and 6.06%,respectively.And the high ecological risk region accounted for 12.71%,15.06%,11.89%,and 12.94%,correspondingly.In Scenario D,the structure of land use and ecological risk pattern was better compared with other scenarios considering the needs of rapid economic and ecological protection.This study is helpful to understand the spatio-temporal pattern and demand of land use types,grasp the ecological security pattern of large-scale areas,and provide scientific basis for the territory development of urban agglomeration in the future.