Long-term analysis of extreme wave characteristics based on the SWAN hindcasts over the Black Sea using two different wind fields

The long-term variations of wave characteristics in the Black Sea are evaluated by using a third-generation wave model (Simulating WAves Nearshore, SWAN), forced by the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim and National Centers for Environmental Prediction/Climate Forecast System Reanalysis (NCEP/CFSR) wind data, covering the period of 1979−2018. The model results were calibrated and validated with buoy measurements at seven stations along the Black Sea. The comparative study shows that the CFSR dataset predicted slightly greater significant wave heights than the ERA-Interim dataset. The greatest difference between two datasets in terms of wave characteristics was found in the northeastern part of the Black Sea. The long-term averages and the variations of long-term trends for wave characteristics show that southwestern part of the Black Sea was characterized by greater significant wave heights, longer mean wave periods and storm durations, and lower variability, while the northeastern part of the basin was characterized by lower significant wave heights, shorter mean wave periods and storm durations, and higher variability. The long-term trends indicate that the wave characteristics over the 40-year period are more likely to be exposed to higher variation on the eastern part of the Black Sea than the western part of the basin.     

21世纪初澜沧江流域夏季降水的突变及相应的大气环流异常特征

基于台站资料和三套格点化降水资料,分析了21世纪初澜沧江流域夏季降水的年代际变化特征,并着重研究了其在不同月份的特点以及可能带来的旱涝风险。分析结果发现:澜沧江流域夏季降水发生了显著的年代际变化,在2002年前后,澜沧江流域夏季降水量经历了由多到少的年代际突变,且该突变主要发生在流域的中、下游。同时,在夏季的不同月份,降水的年代际变化也具有不同的特点,主要表现为:初夏(6月)降水量明显减少,而盛夏(7月)降水略有增加,且7月降水呈现集中的趋势。夏季降水量在时间分布上的变化使得澜沧江流域中、下游湿季明显缩短,进而对流域旱涝灾害产生显著的影响,主要表现为:使流域6月干旱频率增加,初夏干旱风险加大,7月极端强降水的发生频率增加,盛夏洪涝风险加大。进一步对突变前、后的水平环流场进行对比分析发现:2002年以后,澜沧江流域6月对流层低层有偏北风异常,不利于西南季风的向北推进,对流层高层有辐合异常,不利于降水的发生。在孟加拉湾地区对流层低层有明显的偏东北风异常,高层有偏西风异常,表明孟加拉湾季风偏弱,不利于印度洋和孟加拉湾向流域的水汽输送,不利于降水的形成。在这样的高、低层异常环流系统的配合下,2002年以后6月降水量显著减少。     

京津冀典型工业城市沙河市大气污染特征及来源分析

近些年京津冀地区秋、冬季大气重污染事件频发,工业生产与居民燃煤是大气灰霾污染的重要原因。河北省沙河市是京津冀地区以玻璃制造和加工为主的典型工业城市,本研究选取该城市为研究对象,主要利用2017年1月至12月国控站点的大气环境监测和气象数据,采用扩散模型、潜在源分析等手段,分析了沙河市主要污染物的时空分布特征和污染来源。主要结论有:（1）沙河市首要污染物具有明显季节特征,春季、夏季、秋冬季分别以PM₁₀、O₃、PM_2.5污染为主,季节贡献率分别为43.3%、72.3%、61.5%。（2）受城市大气边界层和排放的共同影响,PM₁₀、PM_2.5、SO₂、NO₂和CO浓度均有剧烈的季节—日变化特征。（3）冬季东北风时PM_2.5、NO₂、SO₂均展现出高浓度和高相关性特征,表明站点可能受东北方向玻璃企业排放影响。同时,站点可能也受城中村散煤燃烧影响。（4）沙河市冬季PM_2.5浓度为143 μg m-3。冬季的一次重污染中硫氧化率SOR、氮氧化率NOR的最高值分别达0.67、0.39,气态污染物的二次转化剧烈,高湿度利于二次粒子的生成。重污染中C(NO₃-)/C(SO₄2-)均值为1.89,推测沙河市NO₂主要来自大型运输车辆和企业的共同排放。（5）本地源是沙河市PM_2.5的主要潜在源区,周边几个重工业城市也有一定贡献。因此本研究建议沙河市PM_2.5的治理除需加强本地污染源的削减和控制外,区域联防联控也十分重要。     

Non-stationary spatial covariance structure estimation in oversampled domains by cluster differences scaling with spatial constraints

In the analysis of spatiotemporal processes underlying environmental studies, the estimation of the non-stationary spatial covariance structure is a well known issue in which multidimensional scaling (MDS) provides an important methodological approach (Sampson and Guttorp in J Am Stat Assoc 87:108–119, 1992). It is also well known that approximating dispersion by a non-metric MDS procedure offers, in general, low precision when accurate differences in spatial dispersion are needed for interpolation purposes, specially if a low dimensional configuration is employed besides a high number of stations in oversampled domains. This paper presents a modification, consisting of including geographical spatial constraints, of Heiser and Groenen’s (Psychometrika 62:63–83, 1997) cluster differences scaling algorithm by which not the original stations but the cluster centres can be represented, while the stations and clusters retain their spatial relationships. A decomposition of the sum of squared dissimilarities into contributions from several sources of variation can be employed for an exploratory diagnosis of the model. Real data are analyzed and differences between several cluster-MDS strategies are discussed.     

Spatiotemporal patterns of carbon sequestration in a large shallow lake,Chaohu Lake: Evidence from multiple-core records

Lake sediment can sequestrate large amounts of carbon and this issue has become a research hotspot. However, most of research on carbon burial in lakes is based on a single (or a few) sediment core records and so may underestimate the variability of carbon burial features within a single lake. In this study, therefore, Chaohu Lake, a typical large shallow lake in the middle and lower reaches of the Yangtze River, was selected to conduct multiple, high resolution sediment core studies to elucidate that variability. Overall 18 sediment cores are analyzed according to paleolimnological proxies (including ²¹⁰Pb/¹³⁷Cs for 3 master cores); sediment accumulation rate, total organic carbon, grain size and loss of ignition is measured or estimated for most cores. The spatiotemporal variations of organic carbon burial rate (OCBR), carbon storage and their driving factors were examined. Results show: 1) There was a clear temporal difference in carbon burial during the past 150 years, with OCBR varying from 1.1 g C/m²/y to 25.6 g C/m²/y (mean 9.8 g C/m²/y). OCBR began to increase after around 1900, a rapid increase followed after 1950s and a downward trend after 1970s. Total carbon burial amount (OCBA) in the lake since the 1850s is 1.11 x 10¹⁰ g. 2) The average OCBR of six sediment cores in the northwest lake area is 13.4 g C/m²/y, significantly higher than that for sediment cores in other areas (9.6 g C/m²/y). 3) TOC, OCBR, OCBA in all 18 cores exhibited similar temporal patterns (i.e. marked increase since 1950s in most of the cores) but with significant differences in several lake locations. 4) During the last 150 years, carbon burial in Chaohu Lake appears to be greatly affected by changes in regional temperature and population size, according to their significant correlations. OCBR also has a significant correlation with the average lake level in the past 50 years, indicating human activity (notably dam building). This has imposed an important impact on OCBR in Chaohu Lake. This multi-sediment core study reveals the spatiotemporal characteristics of carbon burial in the lake and provides an important basis for increasing the accuracy of calculating carbon storage in large shallow lakes.     

大震前区域地震活动应变场的时空异常特征

本文基于自然正交函数展开方法, 以地震应变为变量, 计算1980年以来中国大陆7级以上大震前的地震应变, 提取出大震前区域地震活动应变场的时空异常。 结果表明大震前时间因子在平稳背景上会出现突跳上升或突跳下降异常变化。 一般情况下, 前4个应变场中至少有3个出现异常变化, 异常分布具有多分量特点, 出现的最早时间大约在震前3年, 少数出现在震前1~6个月。 对比应变场时间因子异常与研究区域每个网格单元(0.5°×0.5°)内的地震能量时间因子异常形态的相似性、 时间的一致性, 找出地震应变场空间异常位置。 结果表明, 多数大震前的空间异常分布在主震震中周围; 少数大震的空间异常远离主震震中。 产生这种现象的原因是大震前与主震不同距离的单元网格内发生中短期或者临震的震群、 显著地震等地震活动性异常。     

天津市短时暴雨雨型时空分异及其对城市内涝的影响

利用天津市1961—2018年分钟级降水数据,统计了天津地区短时暴雨过程,结合模糊识别法对暴雨过程进行分类,分析了暴雨雨型的时空分布特征,基于天津城市暴雨内涝数值模型,评估了不同雨型对内涝积水总量的影响.结果表明:近58 a天津地区短时暴雨雨型以单峰型(Ⅰ型、Ⅱ型和Ⅲ型)为主,其中各年代60 min暴雨雨型以Ⅰ型、Ⅲ型...     

近十年来南四湖水质时空变化特征研究

基于南四湖湖区2006～2016年的水质监测数据,选取COD_cr、TP、TN、和NH_3-N作为水质评价指标,对南四湖各湖区的污染情况及年际变化趋势进行对比分析,并利用综合水质标识指数法,对南四湖水质变化年际趋势进行综合评价。结果表明:2006～2016年间,各监控站点COD_cr、TP、TN和NH_3-N浓度的年平均值总体呈下降趋势,其中NH_3-N的浓度平均值下降率最大,为72%。2016年南阳湖、独山湖、昭阳湖、微山湖的综合水质指标分别为4.096、3.446、3.350、3.128,呈现出北高南低的空间分布特征。2006～2016年间南四湖的综合水质标识指数由4.620下降至3.350,整体提高了1～2个水质类别,水质得到一定改善。由此可见,加强湖泊区域实施"治"、"用"、"保"并举等流域综合治理措施对湖区的治污效果意义重大。     

论时空大数据的智能处理与服务

时空大数据智能处理与服务是以测绘、遥感和地理信息技术为中心的地球空间信息学的重要应用途径和发展契机。本文首先全面论述了时空大数据的兴起发展、主要特点和挖掘手段,进而介绍了时空大数据的自动匹配、变化检测、智能决策等智能处理技术,并在此基础上论述了由对地观测到对人观测的“3S”社会化应用,最后介绍了天基信息的实时智能服务(PNTRC)的现状、发展目标、关键技术及应用前景。诸多实践证明,在大数据和人工智能时代,面对海量的多源异构的时空大数据,抓好自动化、实时化、智能化、大众化和社会化,地球空间信息学的创新发展前景必将一片光明。