Large scale three-dimensional seepage analysis model test and numerical simulation research on undersea tunnel

During the construction process of Qingdao Jiaozhou Bay Undersea Tunnel, the faults and other unfavorable geological discontinuities were often encountered. To study the water inrush mechanism in the faults, both physical model test and numerical analysis were carried out. The results of crown displacement and hydraulic pressure of the monitoring sections in the physical model and numerical model were analyzed in this paper. It was found that the displacement and hydraulic pressure in the process of tunnel construction are often interacted as both cause and effect, and the lower of hydraulic pressure is often accompanied with the growth of its displacement. The changing of the excavation disturbed zone during the excavation in the undersea tunnel was also studied. The results show that the excavation disturbed zone in fault is larger than that in surrounding rock mass, and the excavation disturbance effects in the filling type fault are both transient and persistent. When the displacement and hydraulic pressure in the undersea tunnel change sharply during excavation, there are relatively slow and continuous change trend of the displacement and hydraulic pressure. For practical purposes, to prevent water inrush in the undersea tunnel, more attentions should also be paid to the undersea tunnel after excavation.     

Land-surface segmentation as a method to create strata for spatial sampling and its potential for digital soil mapping

Sampling efforts are constrained by limited availability of resources. Therefore, methods to reduce the number of samples, while still achieving reasonable accuracy are needed. Land-surface segmentation (LSS) has proven a powerful technique to partition digital elevation models (DEMs) and their derivatives into relatively homogeneous areas, which can be further employed as support in soil sampling. Though topography is one of the main soil forming factors, a robust assessment of the potential of this technique to digital soil mapping (DSM) is still missing. In this study, we aimed at evaluating the potential of LSS in stratifying a landscape into relatively homogeneous areas, which can be used as strata for guiding the selection of sampling points in DSM. The experiments were carried out in two study areas where soil samples were available. Land-surface derivatives were derived from DEMs and segmented with a tool based on the multiresolution segmentation algorithm, into objects considered as homogeneous soil-landscape divisions. Thus, one sample was randomly selected within each segment from the existing sample data, based on which predictions of soil classes/sub-orders and properties, i.e. soil texture and A-horizon thickness, were made. Results were compared with predictions based on simple random sampling (SRS) and conditioned Latin hypercube (cLHS). The segmentation-based sampling (SBS) scheme performed better than SRS and cLHS schemes in predicting the A-horizon thickness, soil texture fractions and soil classes, showing a high potential of LSS in stratifying a landscape for the purposes of DSM. The novelty of this study is in the way strata are constructed, rather than in the sampling design itself. Further research is needed to demonstrate the value of a SBS design for practical use. The analyses presented here further highlight the importance of considering locally adaptive techniques in optimization of sampling schemes and predictions of soil properties.     

A new assessment model for evacuation vulnerability in urban areas

In the high-speed urbanization process of China, the urban population has been increasing significantly, leading to a high-density aggregation of population. However, the sharp increase in population density has not produced commensurate improvements in the road networks. On the contrary, the population increase induced a serious evacuation vulnerability, which cities experience during various hazards and catastrophic events. Therefore, research on evacuation vulnerability is important to urban planning. To assess the evacuation vulnerability, the optimal and worst scenarios should be considered because all possible evacuation plans occur between these extremes. However, most previous evacuation vulnerability studies are based on the worst-case scenario, only providing an upper bound of a potential evacuation assessment. To provide a more comprehensive theoretical basis for decision-makers to understand the consequences caused by all possible evacuations, this paper proposes an optimal evacuation vulnerability assessment model that provides the lower bound on potential evacuation difficulties. The model is solved by a stepwise spreading algorithm based on Graph Theory. Subsequently, to evaluate the effectiveness of the model, the study adopts the model to assess the evacuation capability of different road network topologies. A comparison with previous research was performed. The model was demonstrated in an application to the South Luogu Alley of Beijing, China. The significance of this paper is that the combination of our model with previous research may provide a more complete theoretical basis for an evacuation vulnerability assessment.     

The Digital Belt and Road program in support of regional sustainability

The Belt and Road initiative has a significant focus on infrastructure, trade, and economic development across a vast region, and it also provides significant opportunities for sustainable development. The combined pressure of climate variability, intensified use of resources, and the fragility of ecosystems make it very challenging, however, to achieve future sustainability. To develop the path in a sustainable way, it is important to have a comprehensive understanding of these issues across nations and evaluate them in a scientific and well-informed approach. In this context, the Digital Belt and Road (DBAR) program was initiated as an international venture to share expertise, knowledge, technologies, and data to demonstrate the role of Earth observation science and technology and big Earth data applications to support large-scale development. In this paper, we identify pressing challenges, present the research priorities and foci of the DBAR program, and propose solutions where big Earth data can make significant contributions. This paper calls for further joint actions and collaboration to build a digital silk road in support of sustainable development at national, regional and global levels.     

模式内部变率引起的1.5℃和2℃升温阈值出现时间模拟的不确定性研究

模式内部变率是模拟结果不确定性的重要来源,然而它对于1.5℃和2℃升温阈值出现时间不确定性的影响尚不清楚。因此,基于耦合模式比较计划第五阶段(CMIP5)的多模式数据研究了模式内部变率对1.5℃和2℃升温阈值出现时间不确定性的影响以及对未来排放情景的敏感性。结果表明,模式内部变率对升温阈值出现时间模拟的影响与外强迫的影响相当,单个模式内部不同成员达到全球平均1.5℃或2℃增温的年份相差2~12年;其影响具有明显的空间差异,影响极大值出现在欧亚大陆以北洋面、白令海峡周围区域、北美东北部及其与格陵兰岛之间的海域、南半球高纬地区等;低排放情景下模式内部变率的影响大于高排放情景。     

基于数值预报模式的乡镇温度预报方法研究

利用2015年8月至2017年7月长兴岛站和交流岛站日最高气温、日最低气温实况资料,对ECMWF细网格2 m温度预报值和日本FSFE02(24 h地面形势场预报)、FSFE03(36 h地面形势场预报)进行了检验。结果表明:根据历史回归统计检验,ECMWF细网格模式24 h的2 m最高气温、最低气温预报效果显著,通过了0. 05信度显著性检验。对各月做相关分析,相关性均较好。利用前一日ECMWF细网格2 m温度预报值与长兴岛站实况差值,根据统计的ECMWF细网格2 m温度预报订正值,做出长兴岛站未来24 h的气温预报。交流岛站温度预报是在长兴岛站温度预报的基础上订正做出,经统计分析,交流岛站和长兴岛站的气温差值与地面形势场和风场有较好的对应关系,根据不同类型的地面形势场和风场订正值,做出交流岛站的温度预报。应用Matlab计算机语言的开发功能,提取ECMWF细网格2 m温度预报的最高、最低气温值,并录入当日长兴岛站和交流岛站最高、最低气温实况值,自动预报各站未来24 h最高气温、最低气温。创建可视化预报工作界面,实现乡镇温度预报自动化。     

基于WACCM+DART的临近空间SABER和MLS臭氧观测同化试验研究

本研究在WACCM+DART（Whole Atmosphere Community Climate Model,Data Assimilation Research Test-Bed）临近空间资料同化预报系统中加入SABER（Sounding of the Atmosphere using Broadband Emission Radiometry）和MLS（Microwave Limb Sounder）臭氧观测同化接口,并以2016年2月一次平流层爆发性增温（SSW）过程为模拟个例进行了SABER和MLS臭氧观测同化试验,得出以下结论:同化SABER和MLS臭氧体积浓度观测得出的WACCM+DART臭氧分析场能够较真实反映SSW期间北极上空平流层臭氧廓线随时间的演变特征,且与ERA5（Fifth Generation of ECMWF Reanalyses）再分析资料描述的臭氧变化特征具有很好的一致性;基于SABER和MLS臭氧观测的WACCM臭氧6 h预报检验表明同化臭氧观测对臭氧分析和预报误差的改善效果主要体现在南半球高纬平流层和北半球中高纬平流层中上层-中间层底部;基于ERA5再分析资料的WACCM+DART分析场检验表明同化SABER和MLS臭氧体积浓度资料可在提高北半球高纬地区上平流层-中间层底部臭氧场分析质量的同时减小该地区上平流层-中间层底部温度场和中间层底部纬向风场的分析误差;基于MLS臭氧资料的臭氧中期预报检验表明相对控制试验同化SABER和MLS臭氧体积浓度资料能更好改善0~5 d下平流层和中间层底部臭氧的预报效果。     

Latitudinal and Scan-dependent Biases of Microwave Humidity Sounder Measurements and Their Dependences on Cloud Ice Water Path

The relationship between differences in microwave humidity sounder(MHS)–channel biases which represent measured brightness temperatures and model-simulated brightness temperatures, and cloud ice water path(IWP) as well as the influence of the cloud liquid water path(LWP) on the relationship is examined. Seven years(2011–17) of NOAA-18 MHS-derived measured brightness temperatures and IWP/LWP data generated by the NOAA Comprehensive Large Array-data Stewardship System Microwave Surface and Precipitation Products System are used. The Community Radiative Transfer Model, version2.2.4, is used to simulate model-simulated brightness temperatures using European Center for Medium-Range Weather Forecasts reanalysis data as background fields. Scan-angle deviations of the MHS window channel biases range from-1.7 K to1.0 K. The relationships between channels 2, 4, and 5 biases and scan angle are symmetrical about the nadir. The latitudedependent deviations of MHS window channel biases are positive and range from 0–7 K. For MHS non-window channels,the latitudinal deviations between measured brightness temperatures and model-simulated brightness temperatures are larger when the detection height is higher. No systematic warm or cold deviations are found in the global spatial distribution of difference between measured brightness temperatures and model-simulated brightness temperatures over oceans after removing scan-angle and latitudinal deviations. The corrected biases of five different MHS channels decrease differently with respect to the increase in IWP. This decrease is stronger when LWP values are higher.     

GRAPES全球集合预报系统模式扰动随机动能补偿方案初步探究

为了体现次网格尺度能量升尺度转换过程中存在的不确定性, 文中将随机动能补偿(Stochastic Kinetic Energy Backscatter, SKEB)方案应用于GRAPES(Global/Regional Assimilation and Prediction System)全球集合预报系统(GRAPES-GEPS), 以更好地表征模式误差并且增大集合离散度。使用的SKEB方案基于具有一定时、空相关特征的随机型以及由数值扩散导致的局地动能耗散率来构造随机流函数强迫。并根据流函数与水平风速旋转分量的关系, 将SKEB方案中的流函数强迫转化为适用于GRAPES全球模式的水平风速扰动。结果表明, SKEB方案的使用一方面能够提高GRAPES对大气动能谱的模拟能力; 另一方面能够改善GRAPES-GEPS的集合离散度与集合平均误差的关系, 增加了集合离散度, 并在一定程度上减小了集合平均误差, 尤其是在热带地区这种改进更为显著。而且该方案使得热带地区连续分级概率评分(CRPS评分)显著减小。就降水预报而言, 从Brier评分与相对作用特征面积(AROC, Area under the Relative Operating Characteristics)的结果来看, SKEB方案有助于改善中国地区小雨[0.1 mm, 10 mm)、中雨[10 mm, 25 mm)与大雨[25 mm, 50 mm)量级降水的概率预报技巧, 而对暴雨[50 mm, ∞)量级降水预报技巧影响很小(24 h降水量)。总体上, 模式扰动随机动能补偿方案提高了GRAPES-GEPS的概率预报技巧。      

基于ENVI-met的福州大学校区冬季热环境模拟与热舒适度变化分析

选取福州大学校园教学区为研究区域,基于典型冬季日背景,运用三维非静力微气候模型ENVI-met,分析模拟校园热环境的差异变化及其热舒适度响应。结合实地勘测,对模型进行校准和验证。结果表明：ENVI-met模型能较好地表征室外热环境,准确预测温度和相对湿度的日变化趋势。混凝土路面、灰色地砖路面行人高度的日平均气温分别比草地高出0.1 ℃和0.3 ℃,逐时最大温差分别为0.68 ℃和0.65 ℃。建筑物阴影和树阴可降低行人高度的气温1.1—1.9 ℃;同一组团在有无遮阴的条件下,平均辐射温度（T_mrt）相差最大可达30 ℃;树木附近和建筑物组团内部生理等效温度（PET）值较小,比硬质路面低2—3个等级。无植被方案下,高温低湿区范围有所扩张,在垂直方向上的增温效应可伸展至10.5 m;风速最大增幅可达1.23 m·s^-1,平均辐射温度较高区域的面积增加了69.25%;热舒适区和热不适区面积分别增加了19.78%和2.03%。