G353.9−2.0, a new Galactic supernova remnant identified from the NRAO Very Large Array Sky Survey

G353.9−2.0 is a likely Galactic supernova remnant (SNR) identified from a visual inspection of the National Radio Astronomy Observations (NRAO) Very Large Array (VLA) Sky Survey (NVSS) observations in the Galactic plane. It shows a shell structure, about 13 arcmin in diameter, with a central extended source. VLA observations of G353.9−2.0 at 1.4 GHz, with a resolution of ≈40 arcsec, and a significantly better sensitivity than the NVSS observations, are presented here, together with observations at 327 MHz and observations of the central source at 8.4 GHz. These new observations and existing results from the literature are discussed. G353.9−2.0 is confirmed as a SNR, and the central source as a likely extragalactic double source.     

基于JavaScript的WebGIS地图发布原理与应用

本文介绍了一种新的WEBGIS实现模式和技术,利用JavaScript库提供给客户端浏览器地图应用接口,详细描述了地图库的核心算法;同时介绍了JavaScript地图库在湖北省电子政务空间基础地理信息系统中的实际应用。     

全球升温1.5℃和2.0℃情景下淮河上游干流径流量研究

基于ISI-MIP（The Inter-Sectoral Impact Model Inter-comparison Project）推荐使用的5个全球气候模式数据(HadGEM2-ES,GFDL-ESM2M,MIROC-ESM-CHEM,Nor-ESM1-M,IPSL-CM5ALR),驱动SWIM（Soil and Water Integrated Model）水文模型,研究全球升温1.5℃和2.0℃情景下淮河上游干流径流量变化,得出结论：(1)淮河上游干流径流量年际变化在2种升温情景下均呈先减小后增加趋势。全球升温1.5℃时年径流量较基准期(1986—2005年)增长9.5%,而升温2.0℃情景下涨幅更明显,高达17%。(2) 4个季节径流量在2种升温情景下较基准期均有增长,其中春季涨幅最明显,达24.4%,夏、秋、冬季涨幅分别为7.1%、16.1%、13.5%。全球升温2.0℃时淮河上游干流径流量在4个季节较基准期增长率均大于全球升温1.5℃时。(3)不同气候模式输出日径流量最大值相差较大而平均值相差较小。未来2种升温情景日径流量超过王家坝闸设计流量的日次较基准期均有增加,尤其升温2.0℃情景较基准期增多22次,较升温1.5℃情景多5.8次,表明未来升温2.0℃情景下淮河上游出现极端径流事件的可能性进一步增大。     

The Assessment of Global Surface Temperature Change from 1850s:The C-LSAT2.0 Ensemble and the CMST-Interim Datasets

Based on C-LSAT2.0,using high-and low-frequency components reconstruction methods,combined with observation constraint masking,a reconstructed C-LSAT2.0 with 756 ensemble members from the 1850s to 2018 has been developed.These ensemble versions have been merged with the ERSSTv5 ensemble dataset,and an upgraded version of the CMSTInterim dataset with 5°×5°resolution has been developed.The CMST-Interim dataset has significantly improved the coverage rate of global surface temperature data.After reconstruction,the data coverage before 1950 increased from 78%?81%of the original CMST to 81%?89%.The total coverage after 1955 reached about 93%,including more than 98%in the Northern Hemisphere and 81%?89%in the Southern Hemisphere.Through the reconstruction ensemble experiments with different parameters,a good basis is provided for more systematic uncertainty assessment of C-LSAT2.0 and CMSTInterim.In comparison with the original CMST,the global mean surface temperatures are estimated to be cooler in the second half of 19th century and warmer during the 21st century,which shows that the global warming trend is further amplified.The global warming trends are updated from 0.085±0.004℃(10 yr)^–1and 0.128±0.006℃(10 yr)^–1to 0.089±0.004℃(10 yr)^–1and 0.137±0.007℃(10 yr)^–1,respectively,since the start and the second half of 20th century.     

基于网格数据的内蒙古决策气象服务技术研究与实现

智能网格气象产品包括智能网格预报和cldasV2.0实况分析产品,将智能网格气象产品应用于决策气象服务,可提高内蒙古决策气象服务精细化水平。利用智能网格产品建立内蒙古地区决策气象服务敏感性分析启动阈值,采用动态数据库sql语句对智能网格格点预报数据和格点实况数据进行检测,当检测达到阈值后,自动启动制作决策气象服务材料。基于WebGis的Openlayers技术实现智能网格格点气象要素数据可视化动态展示和图形下载,根据需求设计自治区、盟市、旗县三级不同层级色斑图和格点图下载及预报图和实况图的自动生成；采用Postgres分布式集群数据库快速统计方法实现cldas2.0实况数据统计、计算和查询。     

基于BCC_CSM模式的山西省盛夏降水降尺度预测

降尺度方法是目前弥补气候系统模式预测结果不足的重要手段,为获得具有较高预测技巧的山西盛夏降水客观化预测产品,本文选取1990—2017年6月起报的BCC_CSM气候系统模式输出盛夏结果和同期NCEP/NCAR再分析资料同时与山西盛夏降水异常典型模态具有统计显著的因子,利用逐步回归方法建立了山西盛夏降水降尺度模型。进一步研究发现,降尺度模型的预测能力与BCC_CSM对影响山西盛夏降水关键区海温的预测技巧密切相关。检验回报与观测的时间和空间距平相关系数(TCC和ACC)、回报与观测的距平符号一致率(PC)以及趋势异常综合评分(PS),表明降尺度模型对山西盛夏降水的预测技巧较BCC_CSM输出有明显改进,BCC_CSM模拟降水TCC在山西全区没有通过95%信度检验,降尺度模型回报TCC在山西大部分地区通过95%信度检验,中南部通过99%信度检验;相应的ACC由-0.02提高到0.35,PC由53.3%提高到66.8%,PS由65.6%提高到78.9%。2018年盛夏业务试运行,ACC为0.42,PS为70.8%。     

中国不同排放情景下人为气溶胶的气候效应

本文利用区域气候模式RIEMS2.0(Regional Integrated Environmental Model System)和2006年以及2020年三种排放情景下的排放资料,研究了2006年气候背景下的人为气溶胶的浓度分布特征及辐射效应,估算了未来不同排放情景下人为气溶胶的主要成分硫酸盐、硝酸盐、黑碳、有机碳(含二次有机碳)的综合气候效应.结果表明:(1)2006年中国地区人为气溶胶浓度硫酸盐>有机碳>硝酸盐>黑碳,其区域柱浓度平均值分别为6.0、4.0、1.3和0.3 mg/m².(2)2006年硫酸盐、硝酸盐、有机碳和黑碳的平均辐射强迫分别为-1.32、-0.60、-0.40和0.28 W/m².硫酸盐、硝酸盐和有机碳的负辐射强迫超过黑碳的正辐射强迫,人为气溶胶总辐射强迫为-1.96 W/m².(3)人为气溶胶的辐射效应及引起的地面气温变化对排放源非常敏感,未来采取不同排放政策导致的人为气溶胶的含量及辐射效应有较大差异.在未来排放增加的情景下,各区域的气溶胶浓度、辐射强迫、气温下降幅度和降水减少幅度也相应加大.     

Re-creating Wilderness 2.0: Or getting back to work in a virtual nature

Camping on Twitter, trekking in Google Street View, mountaineering on Snapchat. Wilderness is dead. Long live Wilderness 2.0. In this paper, the term “Wilderness 2.0” refers to the articulation of new media technologies, including mobile digital devices, web 2.0 and locative media, with the practice of wilderness recreation. In this new era of virtual nature, outdoor recreation occurs as much in the statusphere and blogosphere as it does in the biosphere. While much public and academic debate about Wilderness 2.0 has focused on the extent to which new media technologies connect people to, or disconnect them from, nature, this paper argues that wilderness is not a static and essential reality that can simply be connected to or disconnected from, but a social construct that is continually re-created in different cultural contexts. In this sense, Wilderness 2.0 reflects the re-creation of a new ontology of wilderness as DigiPlace: an augmented reality that blurs the lines between the “actual” and the “virtual.” Moreover, Wilderness 2.0 does not simply refer to the creation of a new ontology of wilderness, but the incorporation of outdoor recreation into the political economy of the web 2.0. In the context of Wilderness 2.0, outdoor recreation is increasingly exploited as a form of virtual labour. Thus, despite being associated with a discourse of “sharing” and “connecting to nature,” Wilderness 2.0 is, above all else, a nature that capital can see.     

Crowdsourcing geospatial data

In this paper we review recent developments of crowdsourcing geospatial data. While traditional mapping is nearly exclusively coordinated and often also carried out by large organisations, crowdsourcing geospatial data refers to generating a map using informal social networks and web 2.0 technology. Key differences are the fact that users lacking formal training in map making create the geospatial data themselves rather than relying on professional services; that potentially very large user groups collaborate voluntarily and often without financial compensation with the result that at a very low monetary cost open datasets become available and that mapping and change detection occur in real time. This situation is similar to that found in the Open Source software environment.We shortly explain the basic technology needed for crowdsourcing geospatial data, discuss the underlying concepts including quality issues and give some examples for this novel way of generating geospatial data. We also point at applications where alternatives do not exist such as life traffic information systems. Finally we explore the future of crowdsourcing geospatial data and give some concluding remarks.     

基于Web 2.0的边与节点同时增长网络模型

模拟了Web 2.0网络的发展过程并研究其拓扑结构,分析某门户网站实际博客数据的度分布、节点度时间变化,发现与先前的无标度网络模型有所差别. 根据真实网络的生长特点,提出了边与节点同时增长的网络模型,包括随机连接及近邻互联的网络构造规则. 仿真研究表明,模拟的网络更接近实际,在没有优先连接过程时,模型能得到幂率的度分布; 并且网络有更大的聚类系数以及正的度相关性.