黄河中游多沙粗沙区水沙变化趋势及其主控因素的贡献率

随着气候变化和人类活动影响加剧,黄河中游多沙粗沙区的水沙变化剧烈,因此研究影响黄河中游多沙粗沙区径流量和输沙量的驱动因素对预测未来水沙变化具有重要意义。本文选取Mann-Kendall趋势检验法,Pettitt突变点检验法,位置、尺度、形状的广义可加模型以及累积量斜率变化率比较法对黄河中游多沙粗沙区15个水文站控制流域1956-2010年的年降水量、年径流量以及年输沙量变化特征及其贡献率进行分析,确定影响黄河中游多沙粗沙区径流量和输沙量变化的主要原因。结果表明：① Mann-Kendall趋势检验在5%的显著性水平下,表明降水量虽呈减少趋势但并不显著,径流量和输沙量则有显著的减少趋势;② Pettitt突变点检验得出所研究区域径流量和输沙量的突变年份在1972年、1985年以及1996年左右;③ GAMLSS模型分析结果同样表明降水的均值不随时间发生变化,但降水的方差有减小的趋势;④ 通过累积量斜率变化率比较法得出,人类活动对窟野河流域径流输沙的影响大于无定河流域。通过分析黄河中游多沙粗沙区径流量和输沙量变化的原因,可为黄河中游多沙粗沙区水资源合理分配提供一定的理论支持。     

Exploring the relationship between density and completeness of urban building data in OpenStreetMap for quality estimation

OpenStreetMap (OSM) is a free spatial data source based on crowd sourced data. Although the OSM data have a range of applications, such as generating 3D models, and routing and navigation, quality issues are still significant concerns when using the data. Several studies have undertaken quality assessments by comparing OSM data with reference data. However, reference data are not always available due to high costs or licensing restrictions, and very few studies have quantitatively estimated the quality of OSM data under conditions where the corresponding reference data are not available. This study proposed the use of a building density (or building coverage ratio) indicator as a proxy, and designed a series of experiments involving different study areas to quantitatively explore the relationship between building density and building completeness for OSM data in urban areas. The residuals (estimated building completeness and reference building completeness) were also analyzed. Two main results were found from the experiments. (1) There was an approximate linear relationship between building density and building completeness in the OSM data. More precisely, the building completeness of OSM data was approximately 3.4–4 times the building density of OSM data. (2) Approximately 70–80% of the absolute residuals were smaller than 10%, and 80–90% of them were smaller than 20%. This shows that, in most cases, estimated building completeness was close to the corresponding reference building completeness. Therefore, we concluded that the building density indicator is a potential proxy for the quantitative completeness estimation of OSM building data in urban areas. The limitations of using this indicator were also addressed.     

From highly polluted inland city of China to “Lanzhou Blue”: The air-pollution characteristics

Air quality was improved considerably and the so-called "Lanzhou Blue" appeared frequently in Lanzhou due to implementation of some strict emission-control measures in recent years. To better understand whether the concentration of each air pollutant had decreased significantly and then give some suggestions as to urban air-quality improvement in the near future, the variations of the Air Quality Index (AQI) and six criterion air pollutants (PM_2.5, PM₁₀, CO, SO₂, NO₂, and O₃) at five state-controlled monitoring sites of Lanzhou were studied from 2013 to 2016. The AQI, PM_2.5, PM₁₀, and SO₂ gradually decreased from 2013 to 2016, while CO and NO₂ concentrations had slightly increasing trends, especially in urban areas, due to the large number of motor vehicles, which had an annual growth rate of 30.87%. The variations of the air pollutants in the no-domestic-heating season were more significant than those in the domestic-heating season. The increase of ozone concentration for the domestic-heating season at a background station was the most significant among the five monitoring sites. The vehicle-exhaust and ozone pollution was increasingly severe with the rapid increase in the number of motor vehicles. The particulate-matter pollution became slight in the formerly highly polluted Lanzhou City. Some synergetic measures in urban and rural areas of Lanzhou should be taken by the local government in the near future to control fine particulate-matter (PM_2.5) and ozone pollution.     

Relationships between Genetic Diversity of Vascular Plant Species and Climate Factors

Genetic diversity is crucial for plants to respond to global climate change, and exploring relationships between genetic diversity and climatic factors may help predict how global climate change will shape the genetic diversity of plants in the future. So far, however, the extent and magnitude of the impact of climatic factors on the genetic diversity of plants has not been clarified. We collected data from 68 published papers on two widely used measures of genetic diversity of populations (average expected heterozygosity (He) and average observed heterozygosity (Ho)) and on localities of populations of 79 vascular plants, and extracted data on 19 climatic factors from WorldClim. We then explored the relationships between measures of genetic diversity and climatic factors using linear regressions. He of plant populations was significantly correlated with climatic factors in 58.7% (44) of the 75 species that used He as a measure of genetic diversity, and Ho was correlated with climatic factors in 65.1% (41) of the 63 species that used this genetic diversity measure. In general, Mean Temperature of Wettest Quarter, Precipitation Seasonality, Precipitation of Driest Quarter and Temperature Seasonality played a vital role in shaping He, and Ho was mostly correlated with Precipitation of Warmest Quarter, Mean Temperature of Wettest Quarter, Precipitation of Driest Quarter and Precipitation of Driest Month. Also, the proportion of the significant correlations between genetic diversity of populations and climatic factors was higher for woody than for herbaceous species, and different climatic factors played different roles in shaping genetic diversity of these two growth forms. Our results suggest that climate may play an important role in shaping genetic diversity of plant populations, that climatic change in the future may alter genetic diversity of plants, and that genetic diversity of different plant forms may respond to climatic change differently.     

基于组网观测的那曲土壤湿度不同时间尺度的变化特征

利用第三次青藏高原大气科学试验的土壤湿度观测数据,分析了那曲多空间尺度组网观测的28个站2、5、10、20和30 cm 5个不同深度土壤湿度的季节变化和日变化特征,并对比讨论了土壤湿度站点间的差异。分析表明,各层土壤湿度均存在显著的季节变化。冬春季节,20 cm以上土壤湿度随深度变浅而减小。夏秋季节土壤湿度随深度增加而减小,并分别在7月上、中旬和9月出现两个峰值。10月以后进入土壤湿度衰减期。土壤温度和土壤湿度存在协同变化关系。在一定的温度范围内,土壤发生冻结-融化过程,引起土壤湿度变化。在太阳辐射加热下,土壤表层水分蒸发,进而影响土壤温度。不同观测站间土壤湿度差异较大,夏秋季离散性大于冬春季。不同季节土壤湿度的日变化存在差异。春季10 cm以上土壤湿度日变化明显,08-10时（北京时）达到最低,19-20时达到最高。夏季土壤湿度日变化较为平缓。秋季2 cm深度土壤湿度日变化明显。线性拟合结果表明,1、4、10月土壤湿度和土壤温度为正相关关系。但是在夏季,土壤湿度与土壤温度为负相关。站点间土壤湿度变化的离散性表明,多测站才能全面体现青藏高原某区域的陆面状态。文中结果为青藏高原地区土壤湿度卫星参数验证和数值模式参数化提供了多角度的观测依据。      

青藏高原地表位涡密度强迫对2008年1月中国南方降水过程的影响Ⅰ:资料分析

位涡外部源汇是驱动大气环流的原动力。文中详细介绍了地表位涡制造和位涡密度强迫的联系,讨论了不同坐标系中位涡密度方程的特点及其在应用中应当注意的问题。还以2008年初南方低温雨雪冰冻灾害为例,探讨了青藏高原地表位涡密度强迫及东传对下游地区对流性天气发生的影响,拟由此揭示青藏高原位涡密度强迫激发中国东部激烈天气发生的一种新机制。伴随着青藏高原地表正位涡密度的东传,下游地区对流层中高层出现纬向正绝对涡度平流,气旋性环流增强,从而促使低空南风发展,为南方地区提供充沛的水汽条件。另外,南风的增强有利于低空经向负绝对涡度平流的加强,从而使南方地区高、低空形成绝对涡度平流随高度增大的大尺度环流背景,有利于上升运动的发展。上升运动的加强又促进低空南风气流的增强,使高、低空绝对涡度平流随高度增大的环流背景进一步增强,最终导致降水的产生。      

夏季黄河流域降水气候特征及其与大气环流的关系

本文基于1958—2015年夏季黄河流域55个观测站降水量和NCEP/NCAR再分析1高度场等资料,使用MannKendall突变检验、合成分析和Monte Carlo检验等气候统计方法,分析了黄河流域58年夏季降水量的气候变化特征,以及导致其变化的大气环流成因。58年期间,黄河流域夏季降水量总体呈减少趋势,尤其在河套北部有显著性减少趋势,其主要原因是欧亚中高纬度等压面升高、西风带减弱所致;1975年和1996年是黄河流域夏季降水的两个明显年代际气候变化转折点,在1958—1975年期间,黄河流域夏季降水量年际变化大,异常偏多和偏少年出现频次较高,期间欧亚中高纬度及其以南包括黄河流域地区高度场偏低,主要受高空低压系统和较强冷空气影响;在1976—1995年期间,黄河流域大部降水偏多,其主要环流成因为乌拉尔山阻塞高压发展、贝加尔湖到东北亚一带受负高度距平控制高空槽加深,同时,来自南方的暖湿气流输送增强;到1996—2015年最近20年间,乌拉尔山北部环流高度场偏低、里海至贝加尔湖再到东北亚一带高度场一致偏高,黄河流域一带西风带强度和冷空气势力均较弱,流域受高压影响导致大部区域降水偏少。不同时期黄河各流域段降水量与中高纬度阻塞高压以及与西北太平洋副热带高压的相关关系分析进一步说明了上述结论。     

北印度洋-南海季风区热带海洋极端波候变化特征

利用1979—2016年ERA-Interim有效波高（SWH）和海表风场数据,分析了南海-北印度洋极端海浪场分布和变化.结果表明：南海-北印度洋极端SWH分布和极端风速分布形态以及年际变化趋势高度一致,说明了涌浪为主的北印度洋和风浪为主的南海一样,极端SWH都由局地的极端风速控制;强极端SWH主要分布在阿拉伯海以及南海北部,阿拉伯海北部增长与该区域气旋强度增强有着密切关系,而南海的极端SWH主要受东北季风控制;东非沿岸极端SWH线性增长趋势则与索马里急流的年代际尺度上有逐渐增强的线性趋势有关.北印度洋及南海海域极端SWH距平场的EOF分析结果表明,南海极端SWH与北印度洋表现出反相变化的特征.北印度洋（南海海域）极端SWH多出现在西南季风（东北季风）期间,因为在西南季风（东北季风）期间,极端风速也相对增强.     

THE EFFECTS OF STATION NETWORK DENSITY ON STATISTICAL ANALYSES OF TROPICAL CYCLONE PRECIPITATION

In this paper, 1416 conventional ground-based meteorological observation stations on the mainland of China were subdivided into groups of differing spatial density. Data from each subgroup were then used to analyze variations in the tropical cyclone (TC) precipitation statistics derived from each subgroup across the mainland of China (excluding Taiwan, Hong Kong, and Macao), as well as in two regions (east China and south China) and three provinces (Guangdong, Hainan, and Jiangxi) between 1981 and 2010. The results showed that for the mainland of China, total precipitation, mean annual precipitation, mean daily precipitation, and its spatial distribution were the same regardless of the spatial density of the stations. However, some minor differences were evident with respect to precipitation extremes and their spatial distribution. Overall, there were no significant variations in the TC precipitation statistics calculated from different station density schemes for the mainland of China. The regional and provincial results showed no significant differences in mean daily precipitation, but this was not the case for the maximum daily precipitation and torrential rain frequency. The maximum daily precipitation calculated from the lower-density station data was slightly less than that based on the higher-density station schemes, and this effect should be taken into consideration when interpreting regional climate statistics. The impact of station density on TC precipitation characteristics was more obvious for Hainan than for Guangdong or Jiangxi provinces. In addition, the effects were greater for south China (including Guangxi Zhuang Autonomous region, Guangdong, and Hainan provinces) than east China (including Shandong, Jiangsu, Zhejiang, Shanghai, Fujian, Anhui, and Jiangxi provinces). Furthermore, the analysis proved that the statistical climatic characteristics began to change significantly when the station spacing was between 40 and 50 km, which are close to the mean spacing for all stations across the mainland of China. Moreover, TC areal precipitation parameters, including mean total areal precipitation and mean daily areal precipitation, also began to change significantly when the spacing was between 40 and 50 km, and were completely different when it was between 100 and 200 km.     

冬季北大西洋涛动与中国北方极端低温相关性的年代际变化

本文基于中国地面气温日值网格数据集（V2.0）,采用滑动相关和相关分析等方法,揭示了冬季北大西洋涛动（NAO）对中国北方极端低温影响的事实,进一步证实了东北后冬（1、2月）冷日（夜）与同期NAO相关性的年代际变化。研究发现:在20世纪80年代中期前,东北后冬冷日（夜）频发,与NAO的相关性较好,而在80年代中期后东北后冬冷日（夜）少发,与NAO的相关性减弱。其中,1月在1969~1988阶段,东北冷日（夜）与NAO的相关性最好,相关区域显著,相关系数可达-0.68（-0.66）,而在1989~2009阶段二者相关性最弱,相关区域不显著。进一步分析发现,在不同年代际背景下,NAO引起的大气环流异常是导致东北1月冷日（夜）与1月NAO相关性年代际变化的重要原因。相关性较好的年代,NAO引起的环流异常有利于冷涡等天气系统维持在贝加尔湖到东北一带,使东北地区气温偏低,冷日（夜）频发;相关性较弱的年代,不利于冷空气南下,使东北地区气温偏高,冷日（夜）少发。