Theory and practice of urban spatial planning in big data era- Taking Hunan as an example

In recent years, the rapid development of information and communication technologies accelerates the arrival of the big data era. But it still needs to be explored further for what large data brought on the impact of urban planning and how to respond to the implementation and formation of urban planning to the end. We will research from two aspects of the practice study and formation of urban planning in Hunan to discuss based on brief review of research about urban space big data era.

Continuous land cover change monitoring in the remote sensing big data era

Since the late 20th century,global change issues have attracted lots of attention.As a key component of global changes,land cover and land use information has been increasingly important for improved understanding of global environmental changes and feedbacks between social and environmental systems（Verburg et al.,2015）.

Decadal trends in precipitable water vapor over the Indus River Basin using ERA5 reanalysis data

Precipitable Water Vapor(PWV)constitutes a pivotal parameter within the domains of atmospheric science,and remote sensing due to its profound influence on Earth’s climate dynamics and weather patterns.It exerts a significant impact on atmospheric stability absorption and emission of radiation,thus engendering alterations in the Earth’s radiative equilibrium.As such,precise quantification of PWV holds the potential to enhance weather prognostication and fortify preparedness against severe meteorological phenomena.This study aimed to elucidate the spatial and temporal changes in seasonal and annual PWV across the Indus River Basin and its sub-basins using ERA5 reanalysis datasets.The present study used ERA5 PWV(entire atmospheric column),air temperature at 2 m(t2m)and 500 hPa(T_500hPa),evapotranspiration,and total cloud cover data from 1960 to 2021.Theil Sen slope estimator and Mann-Kendall test were used for trend analysis.Correlation and multiple regression methods were used to understand the association of PWV with other factors.The findings have unveiled the highest increase in mean PWV during the monsoon(0.40 mm/decade),followed by premonsoon(0.37 mm/decade),post-monsoon(0.27 mm/decade),and winter(0.19 mm/decade)throughout the study period.Additionally,the mean PWV exhibited the most pronounced positive trend in the sub-basin Lower Indus(LI),followed by Panjnad(P),Kabul(K),and Upper Indus(UI)across all seasons,except winter.Annual PWV has also risen in the Indus basin and its sub-basins over the last six decades.PWV exhibits a consistent upward trend up to an elevation of 3500 m within the basin which is most pronounced during the monsoon season,followed by the pre-monsoon.The escalating PWV within the basin is reasonably ascribed to increasing air temperatures,augmented evapotranspiration,and heightened cloud cover.These findings hold potential utility for pertinent authorities engaged in water resource management and planning.

Data-driven Discovery: A New Era of Exploiting the Literature and Data

In the current data-intensive era, the traditional hands-on method of conducting scientific research by exploring related publications to generate a testable hypothesis is well on its way of becoming obsolete within just a year or two. Analyzing the literature and data to automatically generate a hypothesis might become the de facto approach to inform the core research efforts of those trying to master the exponentially rapid expansion of publications and datasets. Here, viewpoints are provided and discussed to help the understanding of challenges of data-driven discovery.

Applicability analysis of the sea surface pressure and wind speed of ERA5 reanalysis data in the Bohai Sea and the Northern Huanghai Seas

A preliminarily assessment of the applicability of the sea surface pressure and wind speed of ERA5 reanalysis data is carried out using the observation data at 10 m height observation data of 9 buoys in the Bohai Sea and the Northern Huanghai Sea.The results show that:the sea surface pressure and wind speed of ERA5 reanalysis data has high correlation coefficients with the observation data,the correlation between sea surface pressure and wind speed is different in different time scales.The correlation of monthly average is better than that of daily average and daily extreme value,and the correlation coefficient is the lowest in extreme weather.In generally,the deviation between statistical products of the ERA5 and the observed products is negative.It means that the high pressure is weaker than the observed data,and the low pressure is stronger than the observed data,and there is some systematic deviation between ERA5 reanalysis data and the observed data.The deviation varies with the different wind speed level,when the wind is high,the reanalysis wind speed is generally less than the measured.By analyzing the monthly average data,the reanalysis data reveal the seasonal variation of sea surface pressure in the study area,and the deviation from the observed data also show seasonal variation characteristics,the applicability in winter is better than in summer.The error of reanalysis data of sea surface pressure and wind speed is large under extreme weather conditions,especially the typhoon process,further evaluation and revision of the data are needed.

Broadband Mobile Data Service Era is Coming

For China’s telecom industry,2009 is destined to be an extraordinary year due to the approach of long-thirsted-for mobile 3G era,which will have significant impact on current work and lifestyles.2009 will also be a year full of opportunities and challenges because the coming 3G era will bring limitless business opportunities and impose more challenges on Chinese telecom operators.The reshuffling of Chinese telecom markets has been brought to an end.The new China Unicom,China Mobile and China Telecom all focus their strategies on broadband mobile data services in order to achieve the objective of a smooth transforming from voice services to data services.Technologically,various 3G technologies and their evolutions become great concerns of telecom operators;while in terms of services,the key for 3G systems is their data services.As a result,high speed broadband data services see an era of rapid development.

Exploitable wave energy assessment based on ERA-Interim reanalysis data—A case study in the East China Sea and the South China Sea

Wave energy resources assessment is a very important process before the exploitation and utilization of the wave energy. At present, the existing wave energy assessment is focused on theoretical wave energy conditions for interesting areas. While the evaluation for exploitable wave energy conditions is scarcely ever performed. Generally speaking, the wave energy are non-exploitable under a high sea state and a lower sea state which must be ignored when assessing wave energy. Aiming at this situation, a case study of the East China Sea and the South China Sea is performed. First, a division basis between the theoretical wave energy and the exploitable wave energy is studied. Next, based on recent 20 a ERA-Interim wave field data, some indexes including the spatial and temporal distribution of wave power density, a wave energy exploitable ratio, a wave energy level, a wave energy stability, a total wave energy density, the seasonal variation of the total wave energy and a high sea condition frequency are calculated. And then the theoretical wave energy and the exploitable wave energy are compared each other; the distributions of the exploitable wave energy are assessed and a regional division for exploitable wave energy resources is carried out; the influence of the high sea state is evaluated. The results show that considering collapsing force of the high sea state and the utilization efficiency for wave energy, it is determined that the energy by wave with a significant wave height being not less 1 m or not greater than 4 m is the exploitable wave energy. Compared with the theoretical wave energy, the average wave power density, energy level, total wave energy density and total wave energy of the exploitable wave energy decrease obviously and the stability enhances somewhat. Pronounced differences between the theoretical wave energy and the exploitable wave energy are present. In the East China Sea and the South China Sea, the areas of an abundant and stable exploitable wave energy are primarily located in the north-central part of the South China Sea, the Luzon Strait, east of Taiwan, China and north of Ryukyu Islands; annual average exploitable wave power density values in these areas are approximately 10-15 kW/m; the exploitable coefficient of variation （COV） and seasonal variation （SV） values in these areas are less than 1.2 and 1, respectively. Some coastal areas of the Beibu Gulf, the Changjiang Estuary, the Hangzhou Bay and the Zhujiang Estuary are the poor areas of the wave energy. The areas of the high wave energy exploitable ratio is primarily in nearshore waters. The influence of the high sea state for the wave energy in nearshore waters is less than that in offshore waters. In the areas of the abundant wave energy, the influence of the high sea state for the wave energy is prominent and the utilization of wave energy is relatively difficult. The developed evaluation method may give some references for an exploitable wave energy assessment and is valuable for practical applications.

Study on the Applicability of ERA5 Reanalysis Data at Lake Taihu

Lakes are an important component of the earth climate system. They play an important role in the study of basin weather forecasting, air quality forecasting, and regional climate research. The accuracy of driving variables is the basic premise to ensure the rationality of lake mode simulation. Based on the in-situ observations at Bifenggang site of the Lake Taihu Eddy flux Network from 2012 to 2017, this paper investigated temporal variations in temperature, relative humidity, wind speed, radiation components at different time scales (hourly, seasonal and interannual). ERA5 reanalysis data were compared with in-situ observation to quantify the error and evaluate the performance of reanalysis data. The results show that: 1) On the hourly scale, the ERA5 reanalysis data described air temperature, and downward long-wave radiation more accurately. 2) On the seasonal variation scale, the ERA5 reanalysis data described air temperature, and downward long-wave radiation more accurately. However, the descriptions of wind speed, relative humidity and downward short-wave have large deviations. 3) On the interannual scale, the ERA5 reanalysis data show a good performance for temperature, followed by downward longwave radiation, downward shortwave radiation and relative humidity.

Preliminary assessment of ERA5 wind data in Jiangsu sea area

ERA5 data and station observation data are both of great importance in studying the regional meteorological and environmental characteristics.The accuracy of ERA5 reanalysis wind field data was evaluated using observations at five offshore platforms in Jiangsu sea area in this study.Results revealed that ERA5 wind speed was generally in reasonable agreement with that observed at each station,and that the accuracy of ERA5 wind speed data was significant better than that of wind direction.The consistency of wind direction between ERA5 and each observation station was better in autumn and winter than that in spring and summer.With increasing wind speed,the mean absolute error and root mean squared error between the ERA5 and observed wind speed(direction)data increased(decreased)obviously.During periods of typhoon,ERA5 wind data were largely consistent with observational data in terms of increasing wind speed and changing wind direction;however,the ERA5 wind speeds were slightly low.The findings of this study could provide a basis for the application and further research of ERA5 wind data in Jiangsu offshore sea area.

The Path to Reshaping the Structure and Chain System of the Publishing Industry in the Era of Big Data

Today,we are living in the era of“big data”where massive amounts of data are used for quantitative decisions and communication management.With the continuous penetration of big data-based intelligent technology in all fields of human life,the enormous commercial value inherent in the data industry has become a crucial force that drives the aggregation of new industries.For the publishing industry,the introduction of big data and relevant intelligent technologies,such as data intelligence analysis and scenario services,into the structure and value system of the publishing industry,has become an effective path to expanding and reshaping the demand space of publishing products,content decisions,workflow chain,and marketing direction.In the integration and reconstruction of big data,cloud computing,artificial intelligence,and other related technologies,it is expected that a generalized publishing industry pattern dominated by virtual interaction will be formed in the future.

COMPARATIVE ANALYSIS OF VARIOUS DATA OF AIR-SEA TEMPERATURE DIFFERENCE AND ITS VARIATION ACROSS SOUTH CHINA SEA IN THE PAST 35 YEARS

Using the International Comprehensive Ocean-Atmosphere Data Set(ICOADS) and ERA-Interim data, spatial distributions of air-sea temperature difference(ASTD) in the South China Sea(SCS) for the past 35 years are compared,and variations of spatial and temporal distributions of ASTD in this region are addressed using empirical orthogonal function decomposition and wavelet analysis methods. The results indicate that both ICOADS and ERA-Interim data can reflect actual distribution characteristics of ASTD in the SCS, but values of ASTD from the ERA-Interim data are smaller than those of the ICOADS data in the same region. In addition, the ASTD characteristics from the ERA-Interim data are not obvious inshore. A seesaw-type, north-south distribution of ASTD is dominant in the SCS; i.e., a positive peak in the south is associated with a negative peak in the north in November, and a negative peak in the south is accompanied by a positive peak in the north during April and May. Interannual ASTD variations in summer or autumn are decreasing. There is a seesaw-type distribution of ASTD between Beibu Bay and most of the SCS in summer, and the center of large values is in the Nansha Islands area in autumn. The ASTD in the SCS has a strong quasi-3a oscillation period in all seasons, and a quasi-11 a period in winter and spring. The ASTD is positively correlated with the Nio3.4 index in summer and autumn but negatively correlated in spring and winter.

ERA-Interim和NCEP/NCAR再分析数据气温和气压值在天山山区适用性分析

利用在天山山区海拔超过1 500 m的气象站的逐日气温和气压数据与同期经过水平方向和垂直方向插值后ERA-Interim和NCEP/NCAR两套再分析数据进行回归分析,研究再分析数据在天山山区不同季节的适用性,并验证再分析数据偏差与气候区的一致性。结果表明:从整体上,ERA-Interim数据气压和气温的可信度优于NCEP/NCAR数据,但在局部存在差异。两套再分析数据的偏差与气候分区、高程和季节相关。中天山山区再分析数据气温偏差呈现暖偏差,而天山南坡呈现冷偏差。两套再分析数据的气温偏差在高山带呈现暖偏差,在中山带呈现冷偏差。春秋两季气温的偏差小于夏冬两季。气压的偏差在夏季低于其他三季。而偏差可能会导致以再分析数据为驱动的气候模式结果的偏差。

CFSR、ERA-Interim再分析降水数据在高寒山区径流模拟中的适用性

为能更好地在严重稀缺资料地区开展水文水资源相关方面的工作,以天山西部山区的喀什河流域为典型研究区,基于1990~2000年现有的实测水文气象站点资料、CFSR与ERA-Interim数据,通过对比流域内两再分析降水数据空间分布情况、水文站点处实测与两再分析数据的降水时间序列变化及两再分析降水数据经过一定处理后驱动VIC模型所得的径流过程与实测径流过程三个方面,并评价了各再分析降水数据在喀什河流域的适用性。结果表明,两再分析降水分布符合山区大于平原、东部多于西部的规律,符合实际地理分布特点。流域内ERA-Interim年降水范围较为合理,而CFSR年降水范围则不太符合现实情况;两再分析降水数据春夏秋三季降水分布较为一致,其中ERA-Interim降水在流域内的高值区随季节变化较为明显,CFSR降水可能由于数据集本身或分辨率较低的缘故导致变化不为明显。冬季降水可能由于所针对的对象并非高寒区及冬季固液态降水的转化关系未深究这两个因素而较为反常。此外,CFSR降水高估了ERAInterim弱降水区,低估了其强降水区;研究区内CFSR降水存在高估实际降水的现象,而ERA-Interim降水存在低估强降水的现象;ERA-Interim在两套水文参数下均具有较为良好的模拟效果,且ERA-Interim数据在喀什河流域具有更好的适用性。

东亚地区500 hPa位势高度场NCEP/NCAR再分析资料与ERA-40资料的比较

运用统计分析方法对3份500 hPa位势高度场资料,即NCEP/NCAR全球大气再分析月平均资料和欧洲中心ERA-40资料,国家气候中心的NMC资料(该资料的基础是站点观测资料的实测数据,并结合中央气象台的日常累积资料整编而成)进行比较,以讨论NCEP/NCAR再分析资料与ERA-40资料以及NMC资料的相关性,尤其在东亚地区的可靠性。3份资料综合分析得到如下结论:在东亚地区,特别是贝加尔湖以南至中国西北和中西部的大部分区域内(30°—50°N,80°—115°E),NCEP/NCAR资料和ERA-40资料各季的平均场、相关场均存在大范围的显著性差异区,差异最大的季节在夏季,时段为1958—1970年,而在冬季相关较好。同时NCEP/NCAR资料在20世纪60年代初出现异常低值,在60年代中期有突然的增长,而欧洲中心的ERA-40资料和国家气候中心的NMC资料均无此现象。针对以上问题,对北半球500 hPa资料的使用提出如下建议:在东亚地区应用NCEP/NCAR资料时,如果范围涉及贝加尔湖以南至中国西北和中西部地区(30°—50°N,80°—115°E),尽量应用20世纪70年代以后的资料,尤其在春、夏两季;而该区域内的ERA-40资料和NMC资料在这一时段内是基本一致,具有可信性。

比较NCEP/NCAR和ERA-40再分析资料与观测资料计算得到的感热资料的差异

利用1951-2000年我国西北干旱、半干旱区地温、气温和表面风场逐日4个时次（北京时间2、8、14和20时）的台站观测资料，以及NCEP／NCAR和ERA-40再分析资料，计算并比较了在我国西北地区春夏季感热输送的差异。分析结果表明：NCEP／NCAR和ERA-40的感热输送再分析资料都能显示出我国西北地区是欧亚大陆上的感热中心之一。从年代际时间尺度上，ERA-40再分析资料的感热资料更接近于实际台站观测资料计算得到的感热资料。

基于ERA-Interim再分析数据的南海波浪能资源评估

利用欧洲中期天气预报中心近37 a(1979年1月—2015年12月)ERA-interim高分辨率(0.125°×0.125°)波浪再分析数据,计算南海海域的波浪能流密度、有效波高、平均周期、有效波时等波浪能参数,分析南海海域的波浪能资源时空分布特征。研究表明:1)南海波浪能资源呈现明显的季节分布特征,冬季资源最丰富,秋季次之,夏季最贫乏;2)波浪能资源丰富区位于吕宋海峡—中南半岛东南海域一线,呈东北—西南走向,大值区为吕宋海峡附近海域,波浪能流密度高达16 kW/m;3)综合考虑能流密度、有效波时间、与大陆最近港口距离和岛礁面积,建议A(112.33°E,16.81°N)岛屿作为开发利用的首选。

中国西北地区大气边界层高度变化特征——基于探空资料与ERA-Interim再分析资料

利用中国西北地区2015年9月至2016年8月38个站点L波段探空观测、2016年7月加密探空观测和ERA-Interim边界层高度资料,对比分析了西北地区大气边界层高度变化特征。观测资料表明,在中国西北地区,08:00(北京时,下同)冬季边界层高度最高;20:00春季边界层高度最高,边界层高度从西部到东部有显著降低的趋势。ERA-Interim资料基本能表现出边界层高度的区域分布,但相对于探空观测得到的边界层高度,除夏季20:00外,ERA-Interim再分析资料边界层高度均偏低。全年平均而言,08:00(20:00)偏低160 m(170 m),其中在08:00(20:00),冬季(春季)偏低最显著。08:00边界层高度与低层稳定度、近地层温度和风速相关更加显著;20:00边界层高度与低层稳定度和相对湿度相关更加显著。2016年7月加密观测资料对比表明,ERA-Interim资料的对流(中性)边界层高度显著偏高;低层稳定度、相对湿度偏小,风速偏大可能是造成边界层高度偏高的原因;ERA-Interim资料的稳定边界层高度偏低,与低层稳定度和近地层温度偏低相关,但其影响因素相对更加复杂。

基于ERA-Interim高分辨率数据的中国东海南海波浪能评估

利用近20年ERA-Interim再分析资料提供的海浪场数据研究东海、南海近海和近岸（4个波能富集区）波浪能资源的分布状况。研究表明：波功率密度大值区位于南海中北部、吕宋海峡、琉球群岛附近、台湾和菲律宾东部海域，P。约为14～18kW／m，波能资源秋冬季大，春夏季小；波能丰富且稳定的区域位于东海、南海北部近岸海域、台湾东部海域；南海年总波能量高于东海，越接近外海，年总波能量越大。近岸波能富集区波功率指向性好，波功率方向集中，有利于获得最大吸能效率；极值波功率最大可达330kW／m，对总波能密度有突出贡献的波况大致相同，H2为0．5～4．0m，Te为4～9s，该波况范围的能量约占总能量的90．0％以上。所得结果可为波能电站的选址及波能装置的设计提供参考。

Research on the Application of Big Data and Artificial Intelligence Technology in Computer Network

With the continuous development of social economy,science and technology are also in continuous progress,relying on the Internet technology of big data era has come in an all-round way.On the basis of the development of cloud computing and Internet technology,artificial intelligence technology has emerged as the times require.It also has more advantages.Applying it to computer network technology can effectively improve the data processing efficiency and quality of computer network technology,and improve the convenience for people’s life and production.This paper studies and analyzes the practical application requirements of computer network,and discusses the application characteristics and timeliness of artificial intelligence technology.