System identification of instrumented bridge systems

Several recorded motions for seven bridge systems in California during recent earthquakes were analysed using parametric and non‐parametric system identification (SI) methods. The bridges were selected considering the availability of an adequate array of accelerometers and accounting for different structural systems, materials, geometry and soil types. The results of the application of SI methods included identification of modal frequencies and damping ratios. Excellent fits of the recorded motion in the time domain were obtained using parametric methods. The multi‐input/single‐output SI method was a suitable approach considering the instrumentation layout for these bridges. Use of the constructed linear filters for prediction purposes was also demonstrated for three bridge systems. Reasonable prediction results were obtained considering the various limitations of the procedure. Finally, the study was concluded by identifying the change of the modal frequencies and damping of a particular bridge system in time using recursive filters. Copyright © 2003 John Wiley & Sons, Ltd.     

建筑物沉降规律的综合时序分析

建筑物的沉降监测数据序列具有趋势变化和随机变化的特点，本文针对两种变化项的特点分别建立相应的数学模型，再将其组合起来建立综合数学模型，从总体上把握沉降数据序列的变化规律。实例计算分析表明，此方法具有较高的拟合精度和预测能力，具有一定的应用参考价值。     

IPCC AR6报告解读：未来的全球气候——基于情景的预估和近期信息

依据IPCC第六次评估报告（AR6）第一工作组报告第四章的内容,对未来全球气候的预估结果进行解读。报告对21世纪全球表面气温、降水、大尺度环流和变率模态、冰冻圈和海洋圈的可能变化进行了系统评估,并对2100年以后的气候变化做了合理估计。评估指出全球平均表面气温将在未来20年内达到或超过1.5℃,平均降水也将增加,但随季节和区域而异,同时变率将增大。大尺度环流和变率模态受内部变率影响较大。到21世纪末,北冰洋可能出现无冰期;全球海洋会继续酸化,平均海平面将持续上升,百年内上升幅度依赖不同排放情景,都在2100年后继续升高。在最新的评估中采用多种约束方法,减小了预估不确定性的范围。AR6对于低排放情景以及“小概率高增暖情节”的关注为应对气候变化提供了更多、更完整的信息。综合报告的评估结果指出,未来需要进一步减小区域,特别是季风区气候预估的不确定性,并从科学研究和模式发展两方面加强我国气候预估能力的建设。     

IPCC AR6报告解读：极端天气气候事件变化

与IPCC第五次评估报告（AR5）相比,在第六次评估报告（AR6）评估中,观测的极端天气气候事件变化证据,特别是归因于人为影响的证据加强。人类活动造成的气候变化已影响到全球每个区域的许多极端天气气候事件。随着未来全球变暖进一步加剧,预估极端热事件、强降水、农业生态干旱的强度和频次以及强台风（飓风）比例等将增加,越罕见的极端天气气候事件,其发生频率的增长百分比越大。这些结论再次凸显了应对气候变化和极端天气气候事件的必要性和紧迫性。     

Modelling coastal land use change by incorporating spatial autocorrelation into cellular automata models

This paper presents a spatial autoregressive (SAR) method-based cellular automata (termed SAR-CA) model to simulate coastal land use change, by incorporating spatial autocorrelation into transition rules. The model captures the spatial relationships between explained and explanatory variables and then integrates them into CA transition rules. A conventional CA model (LogCA) based on logistic regression (LR) was studied as a comparison. These two CA models were applied to simulate urban land use change of coastal regions in Ningbo of China from 2000 to 2015. Compared to the LR method, the SAR model yielded smaller accumulated residuals that showed a random distribution in fitting the CA transition rules. The better-fitting SAR model performed well in simulating urban land use change and scored an overall accuracy of 85.3%, improving on the LogCA model by 3.6%. Landscape metrics showed that the pattern generated by the SAR-CA model has less difference with the observed pattern.     

最近十多年来冰冻圈加速萎缩——IPCC第六次评估报告之冰冻圈变化解读

政府间气候变化专门委员会（IPCC）于2021年8月发布了第六次评估报告第一工作组报告《气候变化2021：自然科学基础》。该报告基于最新的观测和模拟研究,评估了冰冻圈变化的现状,并采用CMIP6模式对未来变化进行了预估。报告明确指出,近十多年来冰冻圈呈现加速萎缩状态：北极海冰面积显著减小、厚度减薄、冰量迅速减少;格陵兰冰盖、南极冰盖和全球山地冰川物质亏损加剧;多年冻土温度升高、活动层增厚,海底多年冻土范围减少;北半球积雪范围也在明显变小,但积雪量有较大空间差异。冰冻圈的快速萎缩加速海平面的上升。未来人类活动对冰冻圈萎缩的影响将愈加显著,从而导致北极海冰面积继续减少乃至消失,冰盖和冰川物质将持续亏损,多年冻土和积雪的范围继续缩减。报告也提出,目前冰冻圈研究仍存在观测资料稀缺、模型对各影响因素的敏感性参数和过程描述亟需提升、对吸光性杂质的变化机制认知不足等问题,从而影响了对冰冻圈变化预估的准确性,未来需要重点关注。     

Pricing Weather Derivatives Index based on Temperature: The Case of Bahir Dar,Ethiopia

In this paper we present a stochastic model for daily average temperature to calculate the temperature indices upon which temperature-based derivatives are written. We propose a seasonal mean and volatility model that describes the daily average temperature behavior using the mean-reverting Ornstein-Uhlenbeck process. We also use higher order continuous-time autoregressive process with lag 3 for modeling the time evolution of the temperatures after removing trend and seasonality. Our model is fitted to 11 years of data recorded, in the period 1 January 2005 to 31 December 2015, Bahir Dar, Ethiopia, obtained from Ethiopia National Meteorological Services Agency. The analytical approximation formulas are used to price heating degree days (HDD) and cooling degree days (CDD) futures. The suggested model is analytically tractable for derivation of explicit prices for CDD and HDD futures and option. The price of the CDD future is calculated, using analytical approximation formulas. Numerical examples are presented to indicate the accuracy of the method. The results show that our model performs better to predict CDD indices.     

基于全球分布的地震观测数据估计0S0模态的特征频率及品质因子

选取2011-03-11日本MW9.3地震后全球地震台站记录的约220 h波形数据,基于一定的判断准则,筛选出质量较高的448个垂向观测数据,采用频域AR方法对0S0模态的特征频率和品质因子进行估值,并以信噪比为权重进行加权平均,得到特征频率f=0.814 658 4±5.3×10-7,品质因子Q=5 586±12。该结果与已有研究成果相比精度更高,有助于约束现有地球介质密度和衰减模型,使其更接近真实地球。     

雄性半滑舌鳎雄激素受体基因的克隆与表达分析

利用RT-PCR方法从半滑舌鳎(Cynoglossus semilaevis)中克隆了雄激素受体(Androgen receptor,AR)基因cDNA的部分序列(434 bp),经BLAST比对与狼鲈(Dicentrarchus labrax)、花溪(Kryptolebias marmoratus)、三斑海猪鱼(Halichoeres trimaculatus)和三刺鱼(Gasterosteus aculeatus)的雄激素受体同源性分别为84%,82%,82%和81%.组织表达分析表明,AR基因在半滑舌鳎的性腺、肝、胃、脾、肾、头肾、肠、鳃、心、脑和肌肉这11种组织中均有表达,表达量有所差异.肾中表达量最丰富,鳃中最少.根据其他硬骨鱼类表达模式,推测半滑舌鳎可能只含有1种AR.     

基于AR（p）的卡尔曼滤波在GPS变形监测中的应用

由于AR（p）模型结构比较简单且计算比较方便,在变形分析中,目前常采用此模型建立变形模型。然而单纯的AR模型把模型参数作为定值,变形数据拟合误差及变形预测误差可能会比较大。介绍了将卡尔曼滤波引入AR模型,利用观测数据建立AR模型,即建立观测方程;以AR模型的参数为状态向量建立状态方程。从而形成动态系统的卡尔曼滤波函数模型,动态计算出AR模型的参数以便预测。此方法快速、实时,且占有较少内存,充分利用了AR模型和卡尔曼滤波二者的优点。