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。     

Statistical analysis and forecasts of long-term sandbank evolution at Great Yarmouth, UK

A data-driven model has been developed to analyse the long-term evolution of a sandbank system and to make ensemble predictions in a period of 8 years. The method uses a combination of empirical orthogonal function (EOF) analysis, (to define spatial and temporal patterns of variability), jack-knife resampling, (to generate an ensemble of EOFs), a causal auto-regression technique, (to extrapolate the temporal eigenfunctions), and straightforward statistical analysis of the resulting ensemble of predictions to determine a ‘forecast’ and associated uncertainty. The methodology has been applied to a very demanding site which includes a curved shoreline and a group of mobile nearshore sandbanks. The site is on the eastern coast of the UK and includes the Great Yarmouth sandbanks and neighbouring shoreline. A sequence of 33 high quality historical survey charts reaching back to 1848 have been used to analyse the patterns and to predict morphological evolution of the sandbank system. The forecasts demonstrate an improved skill relative to an assumption of persistence, but suffer in locations where there are propagating features in the morphology that are not well-described by EOFs.     

Water level variations in the Neuse and Pamlico Estuaries,North Carolina due to local and remote forcing

Water level time series records from the Neuse and Pamlico River Estuaries were statistically compared to local and distant wind field data, water level records within the Pamlico Sound and also coastal ocean sites to determine the relative contribution of each time series to water levels in the Neuse and Pamlico Estuaries. The objectives of this study were to examine these time series data using various statistical methods (i.e. autoregressive, empirical orthogonal function analysis (EOF), exploratory data analysis (EDA)) to determine short- and long-time-scale variability, and to develop predictive statistical models that can be used to estimate past water level fluctuations in both the Neuse Estuary (NE) and Pamlico Estuary (PE). Short- and long-time-scale similarities were observed in all time series of estuarine, Pamlico Sound and subtidal coastal ocean water level and wind component data, due to events (nor'easters, fronts and tropical systems) and seasonality. Empirical orthogonal function analyses revealed a strong coastal ocean and wind field contribution to water level in the NE and PE. Approximately 95% of the variation was captured in the first two EOF components for water level data from the NE, sound and coastal ocean, and 70% for the PE, sound and coastal ocean. Spectral density plots revealed strong diurnal signals in both wind and water level data, and a strong cross correlation and coherency between the NE water level and the North/South wind component. There was good agreement between data and predictions using autoregressive statistical models for the NE (R² = 0.92) and PE (R² = 0.76). These methods also revealed significant autoregressive lags for the NE (days 1 and 3) and for the PE (days 1, 2 and 3). Significant departures from predictions are attributed to local meteorological and hydrological events. The autoregressive techniques showed significant predictive improvement over ordinary least squares methods. The results are considered within the context of providing long time-scale hindcast data for the two estuaries, and the importance of these data for multidisciplinary researchers and managers.     

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基于F-范数的不确定性平差模型的解算方法

为提高基于F-范数的不确定性平差模型的解算效率,给出直接迭代算法进行参数估计。该算法无需SVD,解算过程简单且易于编程计算,同时给出迭代不收敛时的SVD-解方程算法。二元线性拟合及沉降观测AR模型的算例结果表明,这2种算法正确可行,与SVD-迭代算法具有等价性。当迭代收敛时,宜使用直接迭代算法,收敛速度更快,解算效率更高;当迭代不收敛时,可釆用SVD-解方程算法。     

性类固醇激素及其受体在半滑舌鳎性腺分化发育过程中的表达与生理功能

首次用17β-雌二醇(E_2)及其受体(ERα)、睾酮受体(AR)的多克隆抗体在半滑舌鳎(Cynoglossus semilaevisG(u|¨)nther)性腺分化发育过程中进行免疫细胞化学定位研究。结果表明:在半滑舌鳎原始性腺中已有E_2、ERα和AR的分布和表达;卵原细胞、初级卵母细胞、精原细胞、初级精母细胞、次级精母细胞对E_2及ERα、AR抗体均呈现不同程度的阳性反应,在精细胞和精子中对E_2和ERα呈免疫阴性反应,而AR则一直保持较强表达,揭示了半滑舌鳎性腺中类固醇激素可能通过旁分泌调控机制刺激卵子和精子发育和成熟。性类固醇激素及其受体免疫阳性物定位在生殖细胞的胞质、胞膜和核膜等广泛部位并有表达,在性腺分化和不同发育时期的表达强度有所不同,表明其在性腺分化发育过程各阶段所起生理功能不同。这些结果为证明性类固醇激素及受体参与调节半滑舌鳎性腺分化发育提供了重要形态学新证据。