The diurnal and seasonal characteristics of urban heat island variation in Beijing city and surrounding areas and impact factors based on remote sensing satellite data

Based on the land surface temperature (LST), the land cover classification map,vegetation coverage, and surface evapotranspiration derived from EOS-MODIS satellite data, and by the use of GIS spatial analytic technique and multivariate statistical analysis method, the urban heat island (UHI) spatial distribution of the diurnal and seasonal variabilities and its driving forces are studied in Beijing city and surrounding areas in 2001. The relationships among UHI distribution and landcover categories, topographic factor, vegetation greenness, and surface evapotranspiration are analyzed. The results indicate that: (i) The significant UHI occur in Beijing city areas in the four seasons due to high heat capacity and multi-reflection of compression building, as well as with special topographic features of its three sides surrounded by mountains,especially in the summer. The UHI spatial distribution is corresponding with the urban geometry structure profile. The LST difference is approximately 4-6℃ between Beijing city and suburb areas, comparatively is 8- 10℃ between Beijing city area and outer suburb area in northwestern regions. (ii) The UHI distribution and intensity in daytime are different from nighttime in Beijing city area, the nighttime UHI is obvious. However, in the daytime, the significant UHI mainly appears in the summer, the autumn takes second place, and the UHI in the winter and the spring seem not obvious. The surface evapotranspiration in suburb areas is larger than that in urban areas in the summer, and high latent heat exchange is evident, which leads to LST difference between city area and suburb area. (iii) The reflection of surface landcover categories is sensitive to the UHI, the correlation between vegetation greenness and UHI shows obviously negative.The scatterplot shows that there is the negative correlation between NDVI and LST (R2 = 0.6481).The results demonstrate that the vegetation greenness is an important factor for reducing the UHI,and large-scale construction of greenbelts can considerably reduce the UHI effect.     

高压旋喷桩复合地基在高层住宅楼中的应用

以郑州市某高层住宅楼工程为例,介绍了高压旋喷桩复合地基的设计计算和施工方法,经静荷载试验和建筑物沉降观测,复合地基的承载力可以满足设计要求,说明高压旋喷桩复合地基可以成功地用于高层住宅楼的建筑中.     

北祁连山白山子花岗闪长岩成岩时代

寒山大型金矿是近年来在北祁连山西段发现的与侵人岩有关的构造蚀变岩型金矿。笔者首次利用锆石U-Pb方法测得白山子花岗闪长岩的形成年龄为370±25 Ma，属于华力西期。寒山金矿的成矿主要在213.95~339 Ma间。在多期热液叠加，多期成矿作用中，早期成矿的热液很可能是白山子花岗闪长岩（370±25 Ma) ,寒山辉长岩(347.1±6. 4 Ma）共同提供的。由于该区有较多的中酸性岩体存在，它们可能为金的主要来源，因而，确定这些侵入体的形成年龄，对于在该区寻找蚀变岩型金矿不仅有重要的理论意义，而且有重要的现实意义。     

GIS支持下的小城镇土地定级--以福建省天宝镇区为例

小城镇土地定级是小城镇土地管理的基础性工作,以福建省天宝镇区土地定级为例,就地理信息系统技术在城镇土地定级中的应用进行了探讨。着重论述了GIS环境下土地定级基础图件库和基础属性数据库的建立、评价单元的生成、单元分值和单元总分值的计算及成果图的生成等属性数据和空间数据的处理过程。     

基于多模态感知的水下目标检测应用构想

水下目标检测在海洋生物研究、考古探索、军事防御等多领域广泛应用,随着人工智能快速发展,水下目标检测也朝着无人化、智能化发展。深度学习采用神经网络挖掘信息特征,在速度和精度上均表现出优异的性能,成为了计算机视觉技术的主流算法,然而水下环境复杂,将其应用于水下图像目标检测仍存在较大的挑战。水下目标各模态信息互补,特征丰富,有利于目标检测识别,因此结合应用场景调研现有技术,然后设计基于深度学习的多模态水下目标检测系统,同时对比分析了现有关键技术的优缺点,最后对多模态目标检测系统未来发展进行总结与展望,具有重要意义。     

基于YOLO算法的海洋中尺度涡三维结构构建

海洋中尺度涡是一种常见的中尺度海洋现象,研究海洋中尺度涡的分布及运动特性对航运、气候、军事等具有重要作用,海洋中尺度涡的识别是海洋学和计算机科学领域的一个热门研究课题。运用深度学习的方法和框架,对中尺度涡的二维识别和三维结构构建展开研究分析。首先,获取全球海洋再分析数据并进行流线可视化,构建涡旋流线数据集;其次,利用YOLO v5s卷积神经网络对涡旋流线数据集进行训练,并对南海区域中尺度涡进行有效检测。实验结果表明,YOLO v5s训练后得到最优模型经过测试,平均检测精度均值达到了86.10%;最后,根据涡旋检测结果,对检测出的同时刻不同深度的涡旋判断是否属于同一涡旋,确定后进行该涡旋的三维结构构建。     

采用泵喷补偿技术的近底拖体水压场数值模拟研究

采用标准 k-ε 模型,结合 Fluent 软件,对采用泵喷补偿技术的拖体水下被拖行运动所产生的压力场变化进行了数值模拟实验。结果表明：采用泵喷补偿技术对拖体水压场的“马鞍形”分布特性影响较小, 但随着喷水速度的增加,拖体首端压力负值略有增加,而中段的负峰幅值显著增加,当喷水速度达到一定值后,拖体的压力特性曲线已经较为接近期望值,证明泵喷补偿技术具有一定的可行性。     

L波段海水介电模型构建与误差分析

基于实验室测量数据,构建了盐度和温度多项式形式的L波段海水介电模型,并采用最小二乘法和奇异值分解技术求解模型系数。将新模型与目前广泛使用的Klein-Swift(KS)模型、Meissner-Wentz(MW)模型以及George Washington University(GWU)模型进行比较。结果表明：新模型计算的海水介电常数与实验室测量数据的RMSE误差为0.09（实部）和0.25（虚部）,均优于KS、MW、GWU模型。     

波浪条件下小型回转体高速入水动力学特性研究

采用光滑粒子流体动力学（SPH）方法,建立了刚体入水六自由度响应模型,实现了波浪环境下小型回转体高速入水过程的数值模拟。对波浪环境下小型回转体高速入水过程中的运动姿态、冲击载荷进行讨论分析,结果表明：波浪条件下入水点相位不同,导致回转体实际入水角不同,实际入水角越大,入水冲击载荷越大,弹道越稳定;实际入水角越小,入水冲击载荷越小,弹道越易发生失稳。本研究表明,入水点相位对小型回转体弹道特性和冲击载荷产生影响,进而为波浪条件下跨介质武器低载稳定入水提供基础性技术支撑。     

Could CMIP6 climate models reproduce the early-2000s global warming slowdown?

The unexpected global warming slowdown during 1998–2013 challenges the existing scientific understanding of global temperature change mechanisms, and thus the simulation and prediction ability of state-of-the-art climate models since most models participating in phase 5 of the Coupled Model Intercomparison Project(CMIP5) cannot simulate it. Here, we examine whether the new-generation climate models in CMIP6 can reproduce the recent global warming slowdown, and further evaluate their capacities for simulating key-scale natural variabilities which are the most likely causes of the slowdown. The results show that although the CMIP6 models present some encouraging improvements when compared with CMIP5, most of them still fail to reproduce the warming slowdown. They considerably overestimate the warming rate observed in 1998–2013,exhibiting an obvious warming acceleration rather than the observed deceleration. This is probably associated with their deficiencies in simulating the distinct temperature change signals from the human-induced long-term warming trend and/or the three crucial natural variabilities at interannual, interdecadal, and multidecadal scales. In contrast, the 4 models that can successfully reproduce the slowdown show relatively high skills in simulating the long-term warming trend and the three keyscale natural variabilities. Our work may provide important insight for the simulation and prediction of near-term climate changes.