Probability estimation based on grey system theory for simulation evaluation

In the evaluation of some simulation systems, only small samples data are gotten due to the limited conditions. In allusion to the evaluation problem of small sample data, an interval estimation approach with the improved grey confidence degree is proposed.On the basis of the definition of grey distance, three kinds of definition of the grey weight for every sample element in grey estimated value are put forward, and then the improved grey confidence degree is designed. In accordance with the new concept, the grey interval estimation for small sample data is deduced. Furthermore,the bootstrap method is applied for more accurate grey confidence interval. Through resampling of the bootstrap, numerous small samples with the corresponding confidence intervals can be obtained. Then the final confidence interval is calculated from the union of these grey confidence intervals. In the end, the simulation system evaluation using the proposed method is conducted. The simulation results show that the reasonable confidence interval is acquired, which demonstrates the feasibility and effectiveness of the proposed method.

Evaluation of the Arctic Sea-Ice Simulation on SODA3 Datasets

This study evaluates the Arctic sea-ice simulation of the SODA3 dataset driven by different atmospheric forcing fields and explores the errors of the Arctic sea-ice simulation caused by the forcing field.We find that the SODA3 data driven by different forcing fields represent a significant systematical error in the simulation of Arctic sea-ice concentration,showing a low concentration of thick ice and a high concentration of thin ice.In terms of sea-ice extent,the SODA3 data from different versions well characterize the interannual variability and declining trend in the observed data,but they overestimate the overall Arctic sea-ice extent,which is related to excessive simulation of ice in the sea-ice margin.Compared to observations,all the chosen SODA3 reanalysis versions driven by different atmospheric forcing generally tend to underestimate the Arctic sea-ice thickness,especially for thick ice in the multi-year sea-ice regions.Inaccurate simulations of Arctic sea-ice transport may partly explain the error in SODA3 sea-ice thickness in multi-year sea-ice areas.The results of different SDOA3 versions differ greatly in the Beaufort Sea,the Fram Strait,and the Central Arctic Sea.The difference in sea-ice thickness among different SODA3 versions is primarily due to the thermodynamic contribution,which may come from the diversity of atmospheric forcing fields.Our work provides a reference for using SODA3 data to study Arctic sea ice.

THE SIMULATION EVALUATION SYSTEM FOR WEAPON OPERATIONAL EFFECTIVENESS BASED ON KNOWLEDGE MANAGEMENT

The objective of the simulation evaluation system for weapon operational effectiveness based on knowledge management is to solve the problem that the evaluation activities need the participation of many experts in different fields.Three kinds of expert knowledge models used in evaluation activities and the general framework of the evaluation system were proposed.The storage models of evaluation knowledge,simulation experiment database and evaluation project database were designed.The evaluation system has been applied in many evaluation activities and the results show that it can improve the efficiency of simulation evaluation for weapon operational effectiveness and reduce the cost for employing experts.

The Warm Arctic-Cold Eurasia Pattern and Its Key Region in Winter in CMIP6 Model Simulations

An enhanced Warm Arctic-Cold Eurasia(WACE)pattern has been a notable feature in recent winters of the Northern Hemisphere.However,divergent results between model and observational studies of the WACE still remain.This study evaluates the performance of 39 climate models participating in the Coupled Model Intercomparison Project Phase 6(CMIP6)in simulating the WACE pattern in winter of 1980-2014 and explores the key factors causing the differences in the simulation capability among the models.The results show that the multimodel ensemble(MME)can better simulate the spatial distribution of the WACE pattern than most single models.Models that can/cannot simulate both the climatology and the standard deviation of the Eurasian winter surface air temperature well,especially the latter,usually can/cannot simulate the WACE pattern well.This mainly results from the different abilities of the models to simulate the range and intensity of the warm anomaly in the Barents Sea-Kara seas(BKS)region.Further analysis shows that a good performance of the models in the BKS area is usually related to their ability to simulate location and persistence of Ural blocking(UB),which can transport heat to the BKS region,causing the warm Arctic,and strengthen the westerly trough downstream,cooling central Eurasia.Therefore,simulation of UB is key and significantly affects the model’s performance in simulating the WACE.

A Review on Aspects of Climate Simulation Assessment

This paper reviews some aspects of evaluation of climate simulation, including the ITCZ, the surface air temperature （SAT）, and the monsoon. A brief introduction of some recently proposed approaches in weather forecast verification is followed by a discussion on their possible application to evaluation of climate simulation. The authors suggest five strategies to extend the forecast verification methods to climate simulation evaluation regardless significant differences between the forecasts and climate simulations. It is argued that resolution, convection scheme, stratocumulus cloud cover, among other processes in the atmospheric general circulation model （AGCM） and the ocean-atmosphere feedback are the potential causes for the double ITCZ problem in coupled models and AGCM simulations, based on the system- and component-level evaluations as well as the downscaling strategies in some recent research. Evaluations of simulated SAT and monsoons suggest that both coupled models and AGCMs show good performance in representing the SAT evolution and its variability over the past century in terms of correlation and wavelet analysis but poor at reproducing rainfall, and in addition, the AGCM alone is not suitable for monsoon regions due to the lack of air-sea interactions.

Evaluation of Arctic Sea-ice Cover and Thickness Simulated by MITgcm

A regional Arctic Ocean configuration of the Massachusetts Institute of Technology General Circulation Model(MITgcm)is applied to simulate the Arctic sea ice from 1991 to 2012.The simulations are evaluated by comparing them with observations from different sources.The results show that MITgcm can reproduce the interannual and seasonal variability of the sea-ice extent,but underestimates the trend in sea-ice extent,especially in September.The ice concentration and thickness distributions are comparable to those from the observations,with most deviations within the observational uncertainties and less than 0.5 m,respectively.The simulated sea-ice extents are better correlated with observations in September,with a correlation coefficient of 0.95,than in March,with a correlation coefficient of 0.83.However,the distributions of sea-ice concentration are better simulated in March,with higher pattern correlation coefficients(0.98)than in September.When the model underestimates the atmospheric influence on the sea-ice evolution in March,deviations in the sea-ice concentration arise at the ice edges and are higher than those in September.In contrast,when the model underestimates the oceanic boundaries’influence on the September sea-ice evolution,disagreements in the distribution of the sea-ice concentration and its trend are found over most marginal seas in the Arctic Ocean.The uncertainties of the model,whereby it fails to incorporate the atmospheric information in March and oceanic information in September,contribute to varying model errors with the seasons.

An experimental analysis of situation awareness for cockpit display interface evaluation based on flight simulation

Aircraft cockpit display interface （CDI） is one of the most important human-machine interfaces for information perceiving. During the process of aircraft design, situation awareness （SA） is frequently considered to improve the design, as the CDI must provide enough SA for the pilot to maintain the flight safety. In order to study the SA in the pilot-aircraft system, a cockpit flight simulation environment is built up, which includes a virtual instrument panel, a flight visual display and the corresponding control system. Based on the simulation environment, a human-in-the-loop experiment is designed to measure the SA by the situation awareness global assessment technique （SAGAT）. Through the experiment, the SA degrees and heart rate （HR） data of the subjects are obtained, and the SA levels under different CDI designs are analyzed. The results show that analyzing the SA can serve as an objective way to evaluate the design of CDI, which could be proved from the consistent HR data. With this method, evaluations of the CDI design are performed in the experimental flight simulation environment, and optimizations could be guided through the analysis.

Evaluation of the applicability of climate forecast system reanalysis weather data for hydrologic simulation： A case study in the Bahe River Basin of the Qinling Mountains, China

In recent years, global reanalysis weather data has been widely used in hydrological modeling around the world, but the results of simulations vary greatly. To consider the applicability of Climate Forecast System Reanalysis（CFSR） data in the hydrologic simulation of watersheds, the Bahe River Basin was used as a case study. Two types of weather data（conventional weather data and CFSR weather data） were considered to establish a Soil and Water Assessment Tool（SWAT） model, which was used to simulate runoff from 2001 to 2012 in the basin at annual and monthly scales. The effect of both datasets on the simulation was assessed using regression analysis, Nash-Sutcliffe Efficiency（NSE）, and Percent Bias（PBIAS）. A CFSR weather data correction method was proposed. The main results were as follows.（1） The CFSR climate data was applicable for hydrologic simulation in the Bahe River Basin（R^2 of the simulated results above 0.50, NSE above 0.33, and ｜PBIAS｜ below 14.8. Although the quality of the CFSR weather data is not perfect, it achieved a satisfactory hydrological simulation after rainfall data correction.（2） The simulated streamflow using the CFSR data was higher than the observed streamflow, which was likely because the estimation of daily rainfall data by CFSR weather data resulted in more rainy days and stronger rainfall intensity than was actually observed. Therefore, the data simulated a higher base flow and flood peak discharge in terms of the water balance, except for some individual years.（3） The relation between the CFSR rainfall data（x） and the observed rainfall data（y） could berepresented by a power exponent equation： y=1.4789x0.8875（R2=0.98,P〈0.001）. There was a slight variation between the fitted equations for each station. The equation provides a theoretical basis for the correction of CFSR rainfall data.

Numerical Simulation for FWM Power Evaluation in Optical Fiber Transmission Systems

In order to realize reliable and fast simulation of FWM power evaluation, USSD (Uniform Step-Size Distribution) method is modified and its corresponding simulation results of FWM efficiency and computational time are presented.

Modeling and analytic optimization of dynamic comfort for wheelchair robots undergoing random roads

To make a rapid comfort assessment and a reasonable dynamic parameters choice of wheelchair robots,this paper proposes a dynamic comfort coefficientκand analytically optimizes the cushion damping.Firstly,a traveling vibration model of the occupantwheelchair system for wheelchair robots running on random roads was created.Secondly,the analytic formula of the occupant RMS(root mean square)acceleration was deduced.Moreover,the dynamic coefficientκwas proposed and its influence laws were revealed.Finally,the cushion system optimal damping ratio was calculated based onκ.The results show that theκvalue is only determined by the parameters of the occupant-wheelchair system.The smaller theκvalue is,the better the dynamic comfort is for wheelchair robots running on random roads.By minimizingκ,the occupant-wheelchair system can achieve a statistically optimal dynamic comfort effect.