Coupling of a Regional Climate Model with a Crop Development Model and Evaluation of the Coupled Model across China

In this study, the CERES(Crop Estimation through Resource and Environment Synthesis) crop model was coupled with CLM3.5, the land module of the regional climate model RegCM4. The new coupled model was named RegCM4_CERES; and in this model, crop type was further divided into winter wheat, spring wheat, spring maize, summer maize, early rice, late rice,single rice, and other crop types based on each distribution fraction. The development of each crop sub-type was simulated by the corresponding crop model separately, with each planting and harvesting date. A simulation test using RegCM4_CERES was conducted across China from 1999 to 2008; a control test was also performed using the original RegCM4. Data on crop LAI(leaf area index), soil moisture at 10 cm depth, precipitation, and 2 m air temperature were collected to evaluate the performance of RegCM4_CERES. The evaluation provided comparison of single-station time series, regional distributions,seasonal variations, and statistical indices for RegCM4_CERES. The results revealed that the coupled model had an excellent ability to simulate the phonological changes and spatial variations in crops. The consideration of dynamic crop development in RegCM4_CERES corrected the wet bias of the original RegCM4 over North China and the cold bias over South China.However, the degree of improvement was minimal and the statistical indices for RegCM4_CERES were roughly the same as the original RegCM4.

Evaluation of East Asian Climatology as Simulated by Seven Coupled Models

Using observation and reanalysis data throughout 1961-1990, the East Asian surface air temperature, precipitation and sea level pressure climatology as simulated by seven fully coupled atmosphere-ocean models, namely CCSR/NIES, CGCM2, CSIRO-Mk2, ECHAM4/OPYC3, GFDL-R30, HadCM3, and NCAR-PCM, are systematically evaluated in this study. It is indicated that the above models can successfully reproduce the annual and seasonal surface air temperature and precipitation climatology in East Asia, with relatively good performance for boreal autumn and annual mean. The models' ability to simulate surface air temperature is more reliable than precipitation. In addition, the models can dependably capture the geographical distribution pattern of annual, boreal winter, spring and autumn sea level pressure in East Asia. In contrast, relatively large simulation errors are displayed when simulated boreal summer sea level pressure is compared with reanalysis data in East Asia. It is revealed that the simulation errors for surface air temperature, precipitation and sea level pressure are generally large over and around the Tibetan Plateau. No individual model is best in every aspect. As a whole, the ECHAM4/OPYC3 and HadCM3 performances are much better, whereas the CGCM2 is relatively poorer in East Asia. Additionally, the seven-model ensemble mean usually shows a relatively high reliability.

A Comprehensive Model for Evaluating Coalbed Methane Reservoirs in China

Coalbed methane reservoir （CBMR） evaluation is important for choosing the prospective target area for coalbed methane exploration and production. This study aims at identifying the characteristic parameters and methods to evaluate CBMR. Based on the geological surveys, laboratory measurements and field works, a four-level analytic hierarchy process （AHP） model for CBMR evaluation is proposed. In this model, different weights are prioritized and assigned on the basis of three main criteria （including reservoir physical property, storage capacity and geological characteristics）, 15 sub-criteria, and 18 technical alternatives; the later of which are discussed in detail. The model was applied to evaluate the CBMR of the Permo-Carboniferous coals in the Qinshui Basin, North China. This GIS-based fuzzy AHP comprehensive model can be used for the evaluation of CBMR of medium-high rank （mean maximum vitrinite reflectance 〉0.5 %） coal districts in China.

An optimized industry processing technology of peanut tofu and the novel prediction model for suitable peanut varieties

Peanut protein is easily digested and absorbed by the human body,and peanut tofu does not contain flatulence factors and beany flour.However,at present,there is no industrial preparation process of peanut tofu,whereas the quality of tofu prepared by different peanut varieties is quite different.This study established an industrial feasible production process of peanut tofu and optimized the key process that regulates its quality.Compared with the existing method,the production time is reduced by 53.80%,therefore the daily production output is increased by 183.33%.The chemical properties of 26 peanut varieties and the quality characteristics of tofu prepared from these 26 varieties were determined.The peanut varieties were classified based on the quality characteristics of tofu using the hierarchical cluster analysis(HCA)method,out of which 7 varieties were screened out which were suitable for preparing peanut tofu.An evaluation standard was founded based on peanut tofu qualities.Six chemical trait indexes were correlated with peanut tofu qualities(P<0.05).A logistic regressive model was developed to predict suitable peanut varieties and this prediction model was verified.This study may help broaden the peanut protein utilization,and provide guidance for breeding experts to select certain varieties for product specific cultivation of peanut.

PERFORMANCE EVALUATION METHOD FOR BUSINESS PROCESS OF MACHINERY MANUFACTURER BASED ON DEA/AHP HYBRID MODEL

A set of indices for performance evaluation for business processes with multiple inputs and multiple outputs is proposed, which are found in machinery manufacturers. Based on the traditional methods of data envelopment analysis （DEA） and analytical hierarchical process （AHP）, a hybrid model called DEA/AHP model is proposed to deal with the evaluation of business process performance. With the proposed method, the DEA is firstly used to develop a pairwise comparison matrix, and then the AHP is applied to evaluate the performance of business process using the pairwise comparison matrix. The significant advantage of this hybrid model is the use of objective data instead of subjective human judgment for performance evaluation. In the case study, a project of business process reengineering （BPR） with a hydraulic machinery manufacturer is used to demonstrate the effectiveness of the DEA/AHP model.

Modeling Hydrothermal Transfer Processes in Permafrost Regions of Qinghai-Tibet Plateau in China

Hydrothermal processes are key components in permafrost dynamics; these processes are integral to global wanning. In this study the coupled heat and mass transfer model for （CoupModel） the soil-plant-atmosphere-system is applied in high-altitude permafrost regions and to model hydrothermal transfer processes in freeze-thaw cycles. Measured meteorological forcing and soil and vegetation properties are used in the CoupModel for the period from January 1, 2009 to December 31, 2012 at the Tanggula observation site in the Qinghai-Tibet Plateau. A 24-h time step is used in the model simulation. The results show that the simulated soil temperature and water content, as well as the frozen depth compare well with the measured data. The coefficient of determination （R2） is 0.97 for the mean soil temperature and 0.73 for the mean soil water content, respectively. The simulated soil heat flux at a depth of 0-20 cm is also consistent with the monitored data. An analysis is performed on the simulated hydrothermal transfer processes from the deep soil layer to the upper one during the freezing and thawing period. At the beginning of the freezing period, the water in the deep soil layer moves upward to the freezing front and releases heat during the freezing process. When the soil layer is completely frozen, there are no vertical water ex- changes between the soil layers, and the heat exchange process is controlled by the vertical soil temperature gradient. During the thaw- ing period, the downward heat process becomes more active due to increased incoming shortwave radiation at the ground surface. The melt water is quickly dissolved in the soil, and the soil water movement only changes in the shallow soil layer. Subsequently, the model was used to provide an evaluation of the potential response of the active layer to different scenarios of initial water content and climate warming at the Tanggula site. The results reveal that the soil water content and the organic layer provide protection against active layer deepening in summer, so climate warming will cause the permafrost active layer to become deeoer and permafrost degradation.

Towards Production and Energy Coupling System Modeling and Simulation for Energy Optimization in the Process Industry

The production and energy coupling system is used to mainly present energy flow, material flow, information flow, and their coupling interaction. Through the modeling and simulation of this system, the performance of energy flow can be analyzed and optimized in the process industry. In order to study this system, the component based hybrid Petri net methodology (CpnHPN) is proposed, synthesizing a number of extended Petri net methods and using the concept of energy place, material place, and information place. Through the interface place in CpnHPN, the component based encapsulation is established, which enables the production and energy coupling system to be built, analyzed, and optimized on the multi-level framework. Considering the block and brief simulation for hybrid system, the CpnHPN model is simulated with Simulink/Stateflow. To illustrate the use of the proposed methodology, the application of CpnHPN in the energy optimization of chlorine balance system is provided.

Climate Simulations Based on a Different-GridNested and Coupled Model

An atmosphere-vegetation interaction model (AVIM) has been coupled with a nine-layer General Cir culation Model (GCM) of Institute of Atmospheic Physics / State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (IAP/ LASG), which is rhomboidally truncated at zonal wave number 15, to simulate global climatic mean states. AVIM is a model having inter-feedback between land surface processes and eco-physiological processes on land. As the first step to couple land with atmosphere completely, the physiological processes are fixed and only the physical part (generally named the SVAT (soil-vegetation-atmosphere-transfer scheme) model) of AVIM is nested into IAP/ LASG L9R15 GCM. The ocean part of GCM is prescribed and its monthly sea surface temperature (SST) is the climatic mean value. With respect to the low resolution of GCM, i.e., each grid cell having lon gitude 7.5?and latitude 4.5? the vegetation is given a high resolution of 1.5?by 1.5?to nest and couple the fine grid cells of land with the coarse grid cells of atmosphere. The coupling model has been integrated for 15 years and its last ten-year mean of outputs was chosen for analysis.Compared with observed data and NCEP reanalysis, the coupled model simulates the main characteris tics of global atmospheric circulation and the fields of temperature and moisture. In particular, the simu lated precipitation and surface air temperature have sound results. The work creates a solid base on coupling climate models with the biosphere.

Numerical Modelling for Dynamic Instability Process of Submarine Soft Clay Slopes Under Seismic Loading

Marine geological disasters occurred frequently in the deep-water slope area of the northern South China Sea,especially submarine landslides,which caused serious damage to marine facilities.The cyclic elastoplastic model that can describe the cyclic stress-strain response characteristic for soft clay,is embedded into the coupled Eulerian-Lagrangian(CEL)algorithm of ABAQUS by means of subroutine interface technology.On the basis of CEL technique and undrained cyclic elastoplastic model,a method for analyzing the dynamic instability process of marine slopes under the action of earthquake load is developed.The rationality for cyclic elastoplastic constitutive model is validated by comparing its calculated results with those of von Mises model built in Abaqus.The dynamic instability process of slopes under different conditions are analyzed.The results indicate that the deformation accumulation of soft clay have a significant effect on the dynamic instability process of submarine slopes under earthquake loading.The cumulative deformation is taken into our model and this makes the calculated final deformation of the slope under earthquake load larger than the results of conventional numerical method.When different contact conditions are used for analysis,the smaller the friction coefficient is,the larger the deformation of slopes will be.A numerical analysis method that can both reflect the dynamic properties of soft clay and display the dynamic instability process of submarine landslide is proposed,which could visually predict the topographies of the previous and post failure for submarine slope.

An Arctic Sea Ice Simulation Using an Ocean-Ice Coupled Model

This paper evaluates the simulation of Arctic sea ice states using an ocean-ice coupled model that employs LASG/IAP(the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics/the Institute of Atmospheric Physics) Climate Ocean Model(LICOM) and the sea-ice model from the Bergen Climate Model(BCM).It is shown that the coupled model can reasonably reproduce the major characteristics of the mean state,annual cycle,and interannual variability of the Arctic sea ice concentration.The coupled model also shows biases that were generally presented in other models,such as the underestimation of summer sea ice concentration and thickness as well as the unsatisfactory sea ice velocity.Sensitivity experiments indicate that the insufficient performance of the ocean model at high latitudes may be the main reason for the biases in the coupled model.The smoother and the fake "island",which had to be used due to the model's grid in the North Pole region,likely caused the ocean model's weak performance.Sea ice model thermodynamics are also responsible for the sea ice simulation biases.Therefore,both the thermodynamic module of the sea ice component and the model grid of the ocean component need to be further improved.

Training and Implementation of Subjective Questions Scoring System Based on the Baidu Qianfan Model Platform

Leveraging the Baidu Qianfan model platform,this paper designs and implements a highly efficient and accurate scoring system for subjective questions,focusing primarily on questions in the field of computer network technology.The system enhances the foundational model by utilizing Qianfan’s training tools and integrating advanced techniques,such as supervised fine-tuning.In the data preparation phase,a comprehensive collection of subjective data related to computer network technology is gathered,cleaned,and labeled.During model training and evaluation,optimal hyperparameters and tuning strategies are applied,resulting in a model capable of scoring with high accuracy.Evaluation results demonstrate that the proposed model performs well across multiple dimensions-content,expression,and development scores-yielding results comparable to those of manual scoring.

Wave Hindcast for the Neighbouring Seas of Korea Based on Loosely Coupled Wave-Tide-Surge Model

A hindcast simulation of 75 typhoons and winter monsoons which affected the coastal areas of Korean Peninsula is performed by use of a third generation ocean wave prediction model, WAM-cycle 4 model, loosely coupled with a com-bined tide and surge model. Typhoon wind fields are derived from the planetary marine boundary layer model for effective neutral winds embedding the vortical storm wind from the parameterized Rankin vortex type model in the limited areas of the overall modeled region. The hindcasted results illustrate that significant wave heights (SWH) considering the wave-tide-surge coupled process are significantly different from the results via the decoupled case especially in the region of the estuaries of the Changjiang Estuary, The Hangzhou Bay, and the southwestern tip of Korean Peninsula. This extensive model simulation is the first attempt to investigate the strong wave-tide-surge interaction for the shallow depth area along the coasts of the Yellow Sea and the East China Sea Continental shelf.

Reliability modelling based on dependent two-stage virtual age processes

This paper proposes reliability and maintenance models for systems suffering random shocks arriving according to a non-homogeneous Poisson process.The system degradation process include two stages:from the installation of a new system to an initial point of a defect(normal stage),and then from that point to failure(defective stage),following the delay time concept.By employing the virtual age method,the impact of external shocks on the system degradation process is characterized by random virtual age increment in the two stages,resulting in the corresponding two-stage virtual age process.When operating in the defective state,the system becomes more susceptible to fatigue and suffers from a greater aging rate.Replacement is carried out either on failure or on the detection of a defective state at periodic or opportunistic inspections.This paper evaluates system reliability performance and investigates the optimal opportunistic maintenance policy.A case study on a cooling system is given to verify the obtained results.

A weakly coupled data assimilation system of a coupled physical–biological model for the northeastern South China Sea

A weakly coupled data assimilation system was established for a coupled physical–biological model for the northeastern South China Sea（NSCS）. The physical model used was the Regional Ocean Modeling System; the biological component was a seven-compartment nitrogen–phytoplankton–zooplankton–detritus ecosystem model; and the data assimilation method was Ensemble Optical Interpolation. To test the performance of the weakly coupled data assimilation system, two numerical experiments（i.e. control and assimilation runs） based on a process-oriented idealized case were conducted, and climatological SST was assimilated in the assimilation run. Only physical variables were adjusted in the weakly coupled data assimilation. The results showed that both the assimilated SST and other unassimilated physical variables had reasonable process responses. Due to the warmer SST observation, the water temperature（salinity） in the assimilation run increased（decreased） in coastal upwelling regions. Both the alongshore and bottom cross-shore currents were reduced, jointly demonstrating the weakening of the upwelling system. Meanwhile, ecosystem variables were also affected to some extent by the SST assimilation through the coupled model. For example, larger phytoplankton（chlorophyll） productivity was found in the upwelling region within the shallow layer due to the warmer waters in the assimilation run. Hence, the application of this data assimilation system could reasonably modify both physical and biological variables for the NSCS by SST assimilation.

Application, Evaluation, and Process Analysis of the US EPA’s 2002 Multiple-Pollutant Air Quality Modeling Platform

A multiple-pollutant version of CMAQ v4.6 (i.e., CMAQ-MP) has been applied by the US EPA over continental US in 2002 to demonstrate the model’s capability in reproducing the long-term trends of ambient criteria and hazardous air pollutants (CAPs and HAPs, respectively) in support of regulatory analysis for air quality management. In this study, a comprehensive model performance evaluation for the full year of 2002 is performed for the first time for CMAQ-MP using the surface networks and satellite measurements. CMAQ-MP shows a comparable and improved performance for most CAPs species as compared to an older version of CMAQ that did not treat HAPs and used older versions of national emission inventories. CMAQ-MP generally gives better performance for CAPs than for HAPs. Max 8-h ozone (O3) mixing ratios are well reproduced in the O3season. The seasonal-mean performance is fairly good for fine particulate matter (PM2.5), sulfate (SO42-), and mercury (Hg) wet deposition and worse for other CAPs and HAPs species. The reasons for the model biases may be attributed to uncertainties in emissions for some species (e.g., ammonia (NH3), elemental carbon (EC), primary organic aerosol (POA), HAPs), gas/aerosol chemistry treatments (e.g., secondary or- ganic aerosol formation, meteorology (e.g., overestimate in summer precipitation), measurements (e.g., NO3-), and the use of a coarse grid resolution. CMAQ cannot well reproduce spatial and seasonal variations of column variables except for nitrogen dioxide (NO2) and the ratio of column mass of HCHO/NO2. Possible reasons include inaccurate seasonal allocation or underestimation of emissions, inaccurate BCONs at higher altitudes, lack of model treatments such as mineral dust or plume-in-grid process, and limitations and errors in satellite data retrievals. The process analysis results show that in addition to transport, gas chemistry or aerosol/emissions play the most important roles for O3 or PM2.5, respectively. For most HAPs, emissions are important sources and cloud processes are a major sink. Simulated P H2 H O2/P HNO3 and HCHO/NO2 indicate VOC-limited chemistry in major urban areas throughout the year and in other non-urban areas in winter, but NOx-limited chemistry in most areas in summer.

Applying Analytical Hierarchy Process to a WiMAX Performance Evaluation Model

Evaluating performance of individual features of WiMAX technology is a topic of widespread discussion. Currently, there is no quantitative way of measuring WiMAX technology so that wireless operators can meet their design objectives. This paper outlines a set of design criteria for WiMAX and provides a decision-making aid that ranks the importance of criteria using Analytic Hierarchy Process （AHP）. This ranking should sufficiently reflect market expectations of the relative importance of various design criteria. A model integrating AHP priorities with enhanced Data Envelopment Analysis （DEA） is the basis for formulating a technological value in simple, comparable format. A case study is provided to show how this technological value is used to evaluate a three year network deployment plan. In the future, this model could be extended to WiMAX equipment suppliers for the purpose of validating performance targets of individual criteria, and enhancing supplier roadmaps for future network development.

Evaluation model for freeway incident management system

In order to evaluate the general situation and find special problems of the freeway incident management system, an evaluation model is proposed. First, the expert appraisal approach is used to select the primary evaluation index. As a result, 81 indices and the hierarchical structures of the index such as the object layer, the sub-object layer, the criterion layer and the index layer are determined. Then, based on the fuzzy characteristics of each index layer, the analytical hierarchy process（AHP）and the fuzzy comprehensive evaluation are applied to generate the weight and the satisfaction of the index and the criterion layers. When analyzing the relationship between the sub-object layer and the object layer, it is easy to find that the number of sub-objects is too large and sub-objects are significantly redundant. The partial least square （PLS） is proposed to solve the problems. Finally, an application example, whose result has already been accepted and employed as the indication of a new project in improving incident management, is introduced and the result verifies the feasibility and efficiency of the model.

A Fast Version of LASG/IAP Climate System Model and Its 1000-year Control Integration

A fast version of the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics （LASG）/Institute of Atmospheric Physics （IAP） climate system model is briefly documented. The fast coupled model employs a low resolution version of the atmospheric component Grid Atmospheric Model of IAP/LASG （GAMIL）, with the other parts of the model, namely an oceanic component LASG/IAP Climate Ocean Model （LICOM）, land component Common Land Model （CLM）, and sea ice component from National Center for Atmospheric Research Community Climate System Model （NCAR CCSM2）, as the same as in the standard version of LASG/IAP Flexible Global Ocean Atmosphere Land System model （FGOALS_g）. The parameterizations of physical and dynamical processes of the atmospheric component in the fast version are identical to the standard version, although some parameter values are different. However, by virtue of reduced horizontal resolution and increased time-step of the most time-consuming atmospheric component, it runs faster by a factor of 3 and can serve as a useful tool for longterm and large-ensemble integrations. A 1000-year control simulation of the present-day climate has been completed without flux adjustments. The final 600 years of this simulation has virtually no trends in global mean sea surface temperatures and is recommended for internal variability studies. Several aspects of the control simulation＇s mean climate and variability are evaluated against the observational or reanalysis data. The strengths and weaknesses of the control simulation are evaluated. The mean atmospheric circulation is well simulated, except in high latitudes. The Asian-Australian monsoonal meridional cell shows realistic features, however, an artificial rainfall center is located to the eastern periphery of the Tibetan Plateau persists throughout the year. The mean bias of SST resembles that of the standard version, appearing as a ＂double ITCZ＂ （Inter-Tropical Convergence Zone） associated with a westward extension of the equatorial eastern Pacific cold tongue. The sea ice extent is acceptable but has a higher concentration. The strength of Atlantic meridional overturning is 27.5 Sv. Evidence from the 600-year simulation suggests a modulation of internal variability on ENSO frequency, since both regular and irregular oscillations of ENSO are found during the different time periods of the long-term simulation.

Representation of the Arctic Oscillation in the CMIP5 Models

The temporal variability and spatial pattern of the Arctic Oscillation(AO)simulated in the historical experiment of26 coupled climate models participating in the Coupled Model Intercomparison Project Phase 5(CMIP5)are evaluated.Spectral analysis of the monthly AO index indicates that 23 out of the 26 CMIP5 models exhibit no statistically significant spectral peak in the historical experiment,as seen in the observations.These models are able to reproduce the AO pattern in the sea level pressure anomaly field during boreal winter,but the intensity of the AO pattern tends to be overestimated in all the models.The zonal-mean zonal wind anomalies associated with the AO is dominated by a meridional dipole in the mid-high latitudes of the Northern Hemisphere during boreal winter,which is well reproduced by only a few models.Most models show significant biases in both strength and location of the dipole compared to the observation.In considering the temporal variability as well as spatial structures in both horizontal and vertical directions,the MPI-ESM-P model reproduces an AO pattern that resembles the observation the best.