Overview of the CMIP6 Historical Experiment Datasets with the Climate System Model CAS FGOALS-f3-L

The three-member historical simulations by the Chinese Academy of Sciences Flexible Global Ocean–Atmosphere–Land System model,version f3-L(CAS FGOALS-f3-L),which is contributing to phase 6 of the Coupled Model Intercomparison Project(CMIP6),are described in this study.The details of the CAS FGOALS-f3-L model,experiment settings and output datasets are briefly introduced.The datasets include monthly and daily outputs from the atmospheric,oceanic,land and sea-ice component models of CAS FGOALS-f3-L,and all these data have been published online in the Earth System Grid Federation(ESGF,https://esgf-node.llnl.gov/projects/cmip6/).The three ensembles are initialized from the 600th,650th and 700th model year of the preindustrial experiment(piControl)and forced by the same historical forcing provided by CMIP6 from 1850 to 2014.The performance of the coupled model is validated in comparison with some recent observed atmospheric and oceanic datasets.It is shown that CAS FGOALS-f3-L is able to reproduce the main features of the modern climate,including the climatology of air surface temperature and precipitation,the long-term changes in global mean surface air temperature,ocean heat content and sea surface steric height,and the horizontal and vertical distribution of temperature in the ocean and atmosphere.Meanwhile,like other state-of-the-art coupled GCMs,there are still some obvious biases in the historical simulations,which are also illustrated.This paper can help users to better understand the advantages and biases of the model and the datasets。

The CMIP6 Historical Simulation Datasets Produced by the Climate System Model CAMS-CSM

This paper describes the historical simulations produced by the Chinese Academy of Meteorological Sciences(CAMS)climate system model(CAMS-CSM),which are contributing to phase 6 of the Coupled Model Intercomparison Project(CMIP6).The model description,experiment design and model outputs are presented.Three members’historical experiments are conducted by CAMS-CSM,with two members starting from different initial conditions,and one excluding the stratospheric aerosol to identify the effect of volcanic eruptions.The outputs of the historical experiments are also validated using observational data.It is found that the model can reproduce the climatological mean states and seasonal cycle of the major climate system quantities,including the surface air temperature,precipitation,and the equatorial thermocline.The long-term trend of air temperature and precipitation is also reasonably captured by CAMS-CSM.There are still some biases in the model that need further improvement.This paper can help the users to better understand the performance and the datasets of CAMS-CSM.

Test Calibration of the Paleoclimatic Proxy Data with Chinese Historical Records

The calibration of paleoclimate proxies is one of the key problems in the study of paleoclimate at present. Historical documentary records of climate are suitable for calibration on dating and the climatic implication of the proxy data in a climatological sense. A test calibration on correcting the Delingha tree ring precipitation series using Chinese historical documentary records shows that among the 44 extreme dry cases in 1401 1950 AD, 42 cases （or 95.5%） are believable. Thus the long series of Delingha rings-denoted precipitation is highly reliable. Another test to validate the monsoon intensity proxy data based on the Zhanjiang Huguangyan sediments using historical records indicates that the years of Lake Maar Ti content series-designated winter monsoon intensities are entirely opposite to historical documents- depicted years of harsh winters in 800-900 AD. As a result, serious doubt is raised about the climatic implication of this paleo-monsoon proxy series.

On the Combination of “The Textual Research on Historical Documents” and “The Comparative Study of Historical Data” —— and a Discussion on “The Law of Quan-ma and Gui-mei” in Chinese Language Studies

In Chinese language studies, both “The Textual Research on Historical Documents” and “The Comparative Study of Historical Data” are traditional in methodology and they both deserve being treasured, passed on, and further developed. It will certainly do harm to the development of academic research if any of the two methods is given unreasonable priority. The author claims that the best or one of the best methodologies of the historical study of Chinese language is the combination of the two, hence a new interpretation of “The Double-proof Method”. Meanwhile, this essay is also an attempt to put forward “The Law of Quan-ma and Gui-mei” in Chinese language studies, in which the author believes that it is not advisable to either treat Gui-mei as Quan-ma or vice versa in linguistic research. It is crucial for us to respect always the language facts first, which is considered the very soul of linguistics.

Mapping a Paleodrainage System of the Keriya River Using Remote Sensing Data and Historical Materials

Keriya River, one of the ancient Four Green Corridors in the Tarim Basin, recording the changes of climate-environment and the ancient Silk Road of the region. According to the archaeological data, historical materials and paleoclimates information, its eeo-environment and climate have taken great changes since the 1.09 Ma B.P, especially during the recent 2,000 years, many famous ancient cities having been abandoned and the south route of the Silk Road has been moved southward. This study illustrates the capability of the remote sensing data （radar data, topographic data and optical images） and historical materials, in mapping the ancient drainage networks. A major paleodrainage system of Keriya River has linked the Kunlun Mountains to the Tienshan Mountains, possibly as far back as the early Pleistocene. The Keriya River will have important implications for not only the understanding of the paleoenvironments and paleoclimates of Tarim Basin from the early Pleistocene to the Holocene, but also the changes of the Silk Road.

Optimization of Portfolio of Stocks at ZSE through the Analysis of Historical Data

Decision-making of investors at the stock exchange can be based on the fundamental indicators of stocks, on the technical indicators, or can exist as a combination of these two methods. The paper gives emphasis to the domain of technical analysis. In the broader sense the technical analysis enables the dynamics of the expected future values of the shares estimation. This can be performed on the basis of the data on historical trends of the revenues, profits and other indicators from the balance sheet, but also on the basis of historical data on changes in the values of the shares. Companies generally belong to the different sectors that have different presumptions of development resulting from the global market trends, technology and other characteristic. Processing of historical data values of the outstanding shares of the Zagreb Stock Exchange （ZSE） is origination of this research. Investors are interested to know the estimation of future returns for the stocks as well as the size of the risk associated with the expected returns. Research task in this paper is finding the optimal portfolio at the ZSE based on the concept of dominant portfolio by Markowitz approach. The portfolio is created by solving non-linear programming problem using the common software tools. The results of obtained optimal portfolios contain relevant conclusions about the specifics of the shares as well as the characteristics of the industrial sectors but also provide a further knowledge about diverse sectors treatment at the stock exchange in a multi-year period.

Tourism Development Mode of Historical and Cultural Blocks from the Perspective of Urban Renewal Based on Online Review Data:A Case Study of Nanluoguxiang in Beijing

Under the background of urban renewal, this paper re-explores the tourism development modeof Nanluoguxiang historical and cultural block based on online review data, and puts forward correspondingdevelopment strategies. As a cultural label of a city, historical and cultural blocks should be updated first inorder to achieve sustainable development. By using multi-source big data review and qualitative researchmethods, the perception evaluation of tourists in Nanluoguxiang is obtained, and the shortcomings ofcurrent tourism development mode are analyzed. Furthermore, corresponding improvement strategies andsuggestions are put forward, in order to provide some effective ideas for the sustainable development ofhistorical and cultural blocks in the future.

Evaluation of the Historical Sampling Error for Global Models

Various ensemble-based schemes are employed in data assimilation because they can use the ensemble to estimate the flow-dependent background error covariance. The most common way to generate the real-time ensemble is to use an ensemble forecast; however, this is very time-consuming. The historical sampling approach is an alternative way to generate the ensemble,by picking some snapshots from historical forecast series.With this approach, many ensemble-based assimilation schemes can be used in a deterministic forecast environment. Furthermore, considering the time that it saves, the method has the potential for operational application.However, the historical sampling approach carries with it a special kind of sampling error because, in a historical forecast, the way to integrate the ensemble members is different from the way to integrate the initial conditions at the analysis time(i.e., forcing and lateral boundary condition differences, and ‘warm start' or ‘cold start' differences). This study analyzes the results of an experiment with the Global Regional Assimilation Prediction System-Global Forecast System(GRAPES-GFS), to evaluate how the different integration configurations influence the historical sampling error for global models. The results show that the sampling error is dominated by diurnal cycle patterns as a result of the radiance forcing difference.Although the RMSEs of the sampling error are small, in view of the correlation coefficients of the perturbed ensemble, the sampling error for some variables on some levels(e.g., low-level temperature and humidity, stratospheric temperature and geopotential height and humidity), is non-negligible. The results suggest some caution must be applied, and advice taken, when using the historical sampling approach.

Prediction of Commuter Vehicle Demand Torque Based on Historical Speed Information

The development of vehicle-to-everything and cloud computing has brought new opportunities and challenges to the automobile industry.In this paper,a commuter vehicle demand torque prediction method based on historical vehicle speed information is proposed,which uses machine learning to predict and analyze vehicle demand torque.Firstly,the big data of vehicle driving is collected,and the driving data is cleaned and features extracted based on road information.Then,the vehicle longitudinal driving dynamics model is established.Next,the vehicle simulation simulator is established based on the longitudinal driving dynamics model of the vehicle,and the driving torque of the vehicle is obtained.Finally,the travel is divided into several accelerationcruise-deceleration road pairs for analysis,and the vehicle demand torque is predicted by BP neural network and Gaussian process regression.

Gridding cropland data reconstruction over the agricultural region of China in 1820

Recent studies have demonstrated the importance of LUCC change with climate and ecosystem simulation, but the result could only be determined precisely if a high-resolution underlying land cover map is used. While the efforts based satellites have provided a good baseline for present land cover, what the next advancement in the research about LUCC change required is the development of reconstruction of historical LUCC change especially spatially-explicit historical dataset. Being different from other similar studies, this study is based on the analysis of historical land use patterns in the traditional cultivated region of China. Taking no account of the less important factors, altitude, slope and population patterns are selected as the major drivers of reclamation in ancient China, and used to design the HCGM （Historical Cropland Gridding Model, at a 60 km×60 km resolution）, which is an empirical model for allocating the historical cropland inventory data spatially to grid cells in each political unit. Then we use this model to reconstruct cropland distribution of the study area in 1820, and verify the result by prefectural cropland data of 1820, which is from the historical documents. The statistical analyzing result shows that the model can simulate the patterns of the cropland distribution in the historical period in the traditional cultivated region efficiently.

A Survey of Time Series Data Visualization Methods

In the era of big data,the general public is more likely to access big data,but they wouldn’t like to analyze the data.Therefore,the traditional data visualization with certain professionalism is not easy to be accepted by the general public living in the fast pace.Under this background,a new general visualization method for dynamic time series data emerges as the times require.Time series data visualization organizes abstract and hard-to-understand data into a form that is easily understood by the public.This method integrates data visualization into short videos,which is more in line with the way people get information in modern fast-paced lifestyles.The modular approach also facilitates public participation in production.This paper summarizes the dynamic visualization methods of time series data ranking,studies the relevant literature,shows its value and existing problems,and gives corresponding suggestions and future research prospects.

Revealing GE Interactions from Trial Data without Replications

Detecting genotype-by-environment (GE) interaction effects or yield stability is one of the most important components for crop trial data analysis, especially in historical crop trial data. However, it is statistically challenging to discover the GE interaction effects because many published data were just entry means under each environment rather than repeated field plot data. In this study, we propose a new methodology, which can be used to impute replicated trial data sets to reveal GE interactions from the original data. As a demonstration, we used a data set, which includes 28 potato genotypes and six environments with three replications to numerically evaluate the properties of this new imputation method. We compared the phenotypic means and predicted random effects from the imputed data with the results from the original data. The results from the imputed data were highly consistent with those from the original data set, indicating that imputed data from the method we proposed in this study can be used to reveal information including GE interaction effects harbored in the original data. Therefore, this study could pave a way to detect the GE interactions and other related information from historical crop trial reports when replications were not available.

Probabilistic Estimation of Hazard on Engineering Site Based on the Intensity of Historic Earthquakes and A Preliminary Comparison with Seismic Hazard Analysis

This paper introduces a new method to estimate the seismic hazard on engineering site.The method is mainly based on intensity data of historical earthquakes.The obvious feature of the method is to use some ideas of seismic hazard analysis and considering regional seismicity tendency.The authors depict the comprehensive method to estimate the related parameters and predict the seismic hazards for 14 sites as practical examples.Some problems are also discussed.Compared with seismic hazard analysis,this method has certain advantages,such as simpler computation,lower uncertainty and smaller sensitivity factor.Moreover total hazard P(I≥i)of a site can be examined with real historic data.The result given by the method in this paper can be more stable than that given by seismic hazard analysis nowadays.

Study of the methodologies in the researches on the legal history

The subject of the legal history belongs to the interdisciplinary of the law and the history. Because of the attribute of the interdisciplinary of the subject of the legal history, the reference of the experience in the development of the h/story is very important. The subject of the legal history must pay attention to the problems encountered in the process of the development of the history and the accumulated experience. The historical development since the last century displays the importance and necessity of the theory of the social science in the study of the history. The researcher of the legal history should focus on the comprehensive use of the theories and methods of the subject of the social sciences, and through the innovative use of the historical data and the use of the multidisciplinary interpretation methods, re-interpret the historical events and figures. With the aid of the comprehensive use of the methods of the multiple disciplines, further open the new situation of the study of the legal history.

知识图谱赋能下的历史人物数据平台构建实践——以宋庆龄文献数据中心平台建设为例

线上数据平台已成为历史人物文献史料研究的重要载体,其借助数字化、知识化充分保护文献、挖掘史料的内在价值,能为广大研究者和历史爱好者提供强有力的数据支撑和便捷的文献服务。本研究在梳理历史人物数据库和数字人文下知识图谱的相关研究基础之上,提出并分析了构建历史人物数据平台的两大关键问题:多源异构文献数据的结构化和多模态信息下的知识图谱构建,并通过数据分类统计、元数据结构化设计、Schema构建、知识抽取、实体融合5个环节解决了上述问题,实现了文献聚合、文献检索、文献可视化等功能,并以宋庆龄为研究对象进行实证研究,所设计的数据平台构建流程为图书馆智慧化领域研究提供了切实可行的方案实例。

笔谈:数字化为文明赋彩——文物和文化遗产数字技术应用现状与实践路径

数字技术在文化遗产领域的应用已从最初的信息储存和传输,发展到数据处理分析,进而进化到今天的自动化和智能化处理与展示,在文化遗产研究、记录、保护、利用等方面起到了至关重要的作用。当前,我国基本形成覆盖文物保护工作全链条的数字化解决方案,并不断创新核心技术与设备,形成通用技术与国际并驾齐驱、特色技术引领国际潮流的发展趋势。数字技术在考古遗址三维空间信息的获取、分析、模拟、研究和展示等全过程中发挥着重要作用,为古代遗址与自然环境之间的人地关系等研究开辟了新的途径。新一代测绘技术,可实现对建成遗产三维数字形式的记录与保存,在精度、纹理、展示分析、交互以及文物古建的数字修复等方面具有不可替代的价值。通过“空间历史大数据”途径,可以打破过往人文学科与空间操作之间的知识鸿沟与技术壁垒,促进文化遗产以体系化技术操作实现“公众化”,通过文化空间实践达成未来城乡高质量发展和历史人文知识存续之间的良性互动。数字化实践在非物质文化遗产保护中的应用范围在不断扩大,已然从保存、宣传扩展到传承、振兴的层面。从全球视野审视数字化这一新兴领域的发展历程和前沿动态,文化遗产数字化面临着建立更完善的数据资源等挑战。

南海及其附属岛礁海洋科学考察历史资料系统整编2.数据治理技术与应用

在南海及其附属岛礁海洋科学考察历史资料系统整编项目实施过程中,数据管理是一项重要工作。文章从数据管理者的角度,以数据为研究对象,以数据治理为研究核心,探讨数据的科学管理工作,构建一个简单的数据治理模型,包含安全体系、组织体系、标准体系、资源体系、共享体系、对接体系共6大体系,为项目数据以及南海海洋数据的数据治理工作提供保障。文章重点围绕数据安全体系、数据标准体系、数据资源体系做简要论述。

南海及其附属岛礁海洋科学考察历史资料系统整编3.数据共享服务及应用

在南海及其附属岛礁海洋科学考察历史资料系统整编项目实施过程中,数据共享是一项重要工作。文章主要介绍南海科考历史资料整编综合数据库暨“数字南海”平台的设计与建设。首先阐述“数字南海”的设计与开发重点,实现数据管理共享的流程集约化和资源利用高效化;其次以“航次一张图”和“岛礁一张图”模块介绍数据的交互分析应用及动态可视化应用。“数字南海”平台建设按照项目目标,统一规划部署、统一标准体系、统一数据平台、统一成果发布,数据服务贯穿项目实施的全生命周期,推动形成共商共建共享共赢的数据工作发展新格局。

自采集街景数据下历史街区空间品质量化研究

探究云南省香格里拉市独克宗古城历史文化街区空间品质现状,提出改善对策。基于自采集的11814张街景图片,量化评估古城空间品质,分析空间失序、绿视率、天空率等指标。发现空间环境较好的样本占8.98%,较差的占33.3%,绿视率低,建筑风貌不突出,路面铺装单一,停车混乱。对提升民族地区历史文化街区空间品质有较好的借鉴和指导作用,通过量化测度和微改造介入,可针对性优化绿化、停车和建筑风貌,提升古城空间品质。