鄂尔多斯盆地中生代晚期以来大地热流的变化及其对生态环境格局和演变的影响

鄂尔多斯盆地的西北部、东北部和南部三个区域现今大地热流平均值分别为56．3、67．3和65．3mW／m^2，对应的生态环境格局也有明显的差异。研究表明，大地热流每增加4～5mW／m^2可使年均地表温度升高约l℃，使最低月均地表温度升高2。C以上。鄂尔多斯盆地东北部的平均大地热流比西北部高出11mW／m^2，东北部年均地表温度可能比西北部高出2～3℃，其最低月均地表温度可能比西北部高出4～6℃。西北部的大地热流平均值已经低于维持地表生态系统延续所需大地热流的临界值(57mW／m^2)，其自然生态系统整体上已经处于脆弱境地；东北部和南部的大地热流均大于57mW／m^2，自然生态系统均尚较稳健。东北部的沙漠化可能是风沙侵入的结果，其生态应该是可以恢复的。整个西北部作为一个整体看，72万年以前大地热流就已衰减到临界值以下，区域生态系统渐趋脆弱，开始整体上向荒漠化演变。     

Studies on wind environment around high buildings in urban areas

High buildings or architectural complex in urban areas remarkably distort the urban surface wind fields. As the air flow approaches,local strong wind may appear around the buildings. The strong wind makes the pedestrians on sidewalks, entrances and terrace very uncomfortable and causes the pedestrian level wind environment problem. In this studies, hot-wire wind measurement, wind scouring in wind tunnel and numerical computation were carried out to evaluate the wind environment of tall buildings in the prevailing flow conditions in Beijing areas. The results obtained by three techniques were compared and mutually verified. The conclusions drawn from three approaches agree with each other. Also the advantages and limitations of each method were analyzed. It is suggested that the combination of different techniques may produce better assessment of wind environment around high buildings.     

Changes in the spatial scale of Beijing UHI and urban development

The seasonal and interannual variations of Beijing urban heat island (UHI) are investigated in this paper using the temperature data from 1960 to 2000 at 20 meteorological stations in the Beijing region, and then the relationship between the intensity and spatial scale of UHI and Beijing urbanization indices is analyzed and discussed. Main conclusions are the followings. First, Beijing UHI shows obvious seasonal variations, and it is strongest in winter, next in spring and autumn, and least in summer. The seasonal variation of the UHI mainly occurs in the urban area. The UHI intensity at the center of Beijing is more than 0.8℃ in winter, and only 0.5℃ in summer. Second, the intensity of Beijing HUI exhibits a clear interannual warming trend with its mean growth rate (MGR) being 0.3088℃/10 a. The MGR of HUI is largest in winter, next in spring and autumn, and least in summer, and the urban temperature increase makes a major contribution to the growth of HUI intensity. Third, since the Reform and Opening, the urbanization indices have grown several ten times or even one hundred times, the intensity of HUI has increased dramatically, and its spatial scale also expanded distinctively along with the expansion of urban architectural complexes. Fourth, the interannual variation of urbanization indices is very similar with that of HUI intensity, and their linear correlation coefficients are significant at a more than 0.001 confidence level.     

“探宝号”船可变阵列震源的实现及应用

2001年，广州海洋地质调查局对“探宝号”船原有震源更新升级为阵列可变的BOLT震源系统。随着更新改造工程的成功，该船已成为具备承担高分辨率、常规、低频深水油气地震勘探的多功能地震调查船。本文介绍了地震勘探震源的基本工作原理以及三种阵列的分布、波形、频谱等特性。     

基于门限回归的气温对光伏发电量的影响分析

光伏发电与气象要素密切相关,正确认识气象因子对于光伏发电量及其发电效率的影响是进行发电量预测和维持光伏电站稳定运行的重要基础。采用江苏省淮安市某小型光伏电站2018—2020年发电量数据、淮安市太阳辐射观测站数据及光伏电站附近气象站观测数据,分析气温、太阳总辐射等气象因子对光伏发电量的影响。相关性分析结果表明,光伏发电量与太阳总辐射呈极强的正相关,基本随太阳总辐射的变化而变化;与气温、降水分别呈弱的正相关和弱的负相关;与风速几乎无相关。然而,灰色关联度分析显示,光伏发电量还与气温呈现出较高的灰色关联度。进一步分析表明,光伏发电量随太阳总辐射的变化受到气温的明显调制,不同气温下光伏发电效率不同。门限回归分析显示,当气温达到一定阈值时光伏发电效率会出现下降,具体表现为：当气温达到12.1 ℃,光伏发电效率下降26.7%;当气温超过22.8 ℃,光伏发电效率下降43.7%。使用这两个温度阈值建立的TR（Threshold Regression）模型的准确率要比线性回归模型提高约10%。     

北极河流径流量变化及影响因子分析

利用最新的北极径流资料(R-arcticNET V3.0和Arctic RIMS),对进入北冰洋的4条主要河流的季节及年代际变化进行诊断分析。结果表明:入海径流在4-6月的大幅增加主要是由气温达到融点后积雪融化造成的,降水的作用次之。总的来说,欧亚区域在过去的70年里入海径流量是增加的,而北美区域在近30年里入海径流量是减小的,但注入北冰洋的径流总量是增大的。值得注意的是入海径流的年代际变化在不同季节增减趋势显著不同,夏季和秋季径流量减小,而其他两个季节径流量增大。进一步分析了影响入海径流变化的一些气候因子,结果表明:北大西洋涛动(北太平洋指数)与欧亚(北美)区域的冬、春季径流量存在正相关。春季气温与春季径流量呈正相关,而与夏季径流量呈负相关。降水与径流量基本上为同步正相关。春季积雪覆盖面积与春季径流量为负相关,而与夏季径流量为正相关,夏季积雪覆盖面积与夏季的径流量为正相关。     

南京市日最高气温对支气管和心血管类疾病就诊人数的影响

融合应用分布滞后非线性模型(Distributed Lag Mon-linear Model,DLNM)与广义相加模型(Generalized Additive Model,GAM),在控制新冠疫情影响、节假日效应、星期效应、长期趋势以及大气污染因子等因素基础上,探究了2018—2020年南京市日最高气温与当地支气管类、心血管类疾病就诊人数的暴露反应关系,包括滞后效应和累积效应。结果表明:对于支气管类疾病,冬季为高风险期,低温的即时效应和累积效应显著;中短期累积作用下,气温越低危险性越大;长期累积作用下,10 ℃左右的危险性最大;高温累积效应不显著,30 ℃左右滞后效应显著。对于心血管类疾病,低温的即时效应和累积效应显著,11~12 ℃左右影响的累积效应和持续性最强;高温的滞后效应显著,温度越高,滞后效应越明显;长期暴露于高温环境的患病风险会快速增加,日最高气温32 ℃左右的暴露累积风险最大。针对这两类疾病,当日最高气温在22~24 ℃范围内,属于人体最舒适温度。     

四川盆周山地暖季单站暴雨事件的精细特征

利用四川省2010—2019年2 165个气象站逐小时降水资料,分区统计了四川盆周山地暖季(5—9月)单站暴雨事件的精细特征。结果表明:(1)四川省单站暴雨事件频数在川西山地与川西南山地呈密集的带状分布。川西与川西南山地通常在降水开始不久就达到雨量最大值,而川东北山地的峰值时间集中在暴雨事件中段。(2)盆周山地的暴雨系统整体呈自南向北由前半夜向后半夜传播的特征。川西南山地和川东北山地的暴雨系统分别呈现较弱的自南向北和自西向东传播,而川西山地的暴雨系统则存在明显的自西向东的传播特征。(3)长历时暴雨事件的峰值出现时间略落后于短历时暴雨事件。暴雨持续时间在空间上存在显著的经向差异,大值区主要位于川西山地和川东北山地一带,暴雨雨量、频次和峰值基本不随持续时间变化,但川西南山地的暴雨峰值则随持续时间的加长而推迟。(4)在四川省大部区域,单站暴雨事件的降水量、频次和强度均表现出随海拔高度升高而减小的特征。在成都平原西南部、东部以及川东北山地,夜间暴雨事件持续时间越长,降水量和频次在较高海拔越易出现最大值。     

Homogenization of the Daily Land Surface Temperature over the Mainland of China from 1960 through 2017

Land surface temperature(LST) is one of the most important factors in the land-atmosphere interaction process. Raw measured LSTs may contain biases due to instrument replacement, changes in recording procedures, and other non-climatic factors. This study attempts to reduce the above biases in raw daily measurements and achieves a homogenized daily LST dataset over China using 2360 stations from 1960 through 2017. The high-quality land surface air temperature(LSAT)dataset is used to correct the LST warming biases especially evident during cold months in regions north of 40°N due to the replacement of observation instruments around 2004. Subsequently, the Multiple Analysis of Series for Homogenization(MASH) method is adopted to detect and then adjust the daily observed LST records. In total, 3.68 × 103 effective breakpoints in 1.65 × 106 monthly records(about 20%) are detected. A large number of these effective breakpoints are located over large parts of the Sichuan Basin and southern China. After the MASH procedure, LSTs at more than 80% of the breakpoints are adjusted within +/– 0.5°C, and of the remaining breakpoints, only 10% are adjusted over 1.5°C.Compared to the raw LST dataset over the whole domain, the homogenization significantly reduces the mean LST magnitude and its interannual variability as well as its linear trend at most stations. Finally, we perform preliminary analysis upon the homogenized LST and find that the annual mean LST averaged across China shows a significant warming trend [0.22°C(10 yr)–1]. The homogenized LST dataset can be further adapted for a variety of applications(e.g.,model evaluation and extreme event characterization).