西北太平洋九州-帕劳海脊北部KPR12岩芯40万年来有机碳来源、埋藏特征及其环境响应

西北太平洋海陆相互作用强烈,受黑潮和亚洲大陆风尘输入影响显著,是研究海洋沉积物中有机碳埋藏与陆源输入、海洋初级生产力和海洋环境演化关系的理想靶区。本研究基于采自九州-帕劳海脊北部的重力活塞647 cm长的KPR12岩芯,分析了总有机碳（TOC）、总氮（TN）、有机碳稳定碳同位素组成（δ¹³C_TOC）、蛋白石（Opal）以及粒度等指标,初步探讨了近40万年来轨道尺度沉积有机碳的来源、埋藏特征及其影响机制。岩芯的TOC含量平均值为0.214%,呈冰期较高、间冰期较低的旋回特征。岩芯沉积物粒度的不同端元反映了研究区风尘输入大致呈冰期较高的趋势。岩芯的δ¹³C_TOC（-25.24‰~-21.04‰,平均值为-22.59‰）显示有机质以海源为主（约62%）,海源有机碳含量趋势与TOC的变化一致。研究区不同时期陆源物质的输入受风尘输送和黑潮的综合控制,黑潮增强可能对该区间冰期陆源有机碳贡献的升高有一定影响。岩芯中TOC与Opal含量的相关性分析表明,海洋初级生产力可能不是控制该岩芯有机碳含量变化的主要原因。冰期-间冰期旋回中的深层水通风条件、黑潮和北太平洋中层水的发育以及陆源细颗粒物质输入可能共同影响着本区沉积有机碳的降解与埋藏保存。

     

末次冰盛期-全新世东海陆坡滑塌沉积的地质年代与沉积学证据

基于东海陆坡区OT12-01孔长度为5.35 m沉积物AMS 14C测年、高分辨率粒度分析和XRF岩芯元素扫描数据,识别出了末次冰盛期(LGM)至全新世期间发生的多次滑塌事件。研究发现,OT12-01孔全新世晚期沉积层缺失,LGM至全新世期间呈现AMS 14C年龄模式频繁倒转、沉积物粒度、元素比值垂向上多处突变或"错动"等特征,保存了LGM至全新世非连续的沉积记录。OT12-01孔沉积物主要来源于低海平面时期的长江/黄河物质,OT12-01孔是由中国大陆陆源物质在东海陆架经水动力分选,细颗粒被搬运至东海陆坡后,发生多次滑塌形成。LGM时期物源供给是OT12-01孔形成滑塌沉积的重要因素,末次冰消期海平面快速上升可能是高频滑塌沉积的触发原因,而低海平面时期甲烷水合物溢出、频繁的地震和火山喷发可能是海底滑坡作用发生的诱因。     

机载激光测深系统强度数据AGC补偿异常区域识别及改正

机载激光测深系统（Airborne Laser Bathymetry,ALB）因集成了具有独特水体穿透能力的绿波段（532 nm）而被广泛用于水深测量。除地形数据外,ALB还记录了地物目标的辐射特性（后向散射强度）,可用于条带配准、海底底质分类和几何建模。然而,由于自动增益控制（Automatic Gain Control,AGC）设计局限,增益值调整存在延缓,对于裸露岩石、水域等高返回、低返回目标较多的海岛海岸带区域,强度补偿异常问题格外突出。针对该问题本文设计了一种基于双向移动的局部加权强度改正方法,提出索引共享机制辅以地形信息实现有效强度数据精确提取;以扫描周期为依据进行扫描线分割,通过柯尔莫可洛夫−斯米洛夫检验进行强度补偿异常区识别;通过对邻近扫描线和邻域强度联合加权进行强度改正,保证强度细节的同时较好地消除与邻域强度偏差,独特的双向移动策略能有效削弱改正不足积累造成的强度改正精度下降问题。实验证明该方法能有效解决AGC补偿异常问题,相较于改正前,改正后的强度数据平均绝对百分比误差降低了约0.27,均方根误差下降了约693,异常区强度与邻域强度偏差控制在26 DN（Digital Number）以内,得到高质量强度图像。     

Measures of Parameter Uncertainty in Geostatistical Estimation and Geostatistical Optimal Design

Studies of site exploration, data assimilation, or geostatistical inversion measure parameter uncertainty in order to assess the optimality of a suggested scheme. This study reviews and discusses measures for parameter uncertainty in spatial estimation. Most measures originate from alphabetic criteria in optimal design and were transferred to geostatistical estimation. Further rather intuitive measures can be found in the geostatistical literature, and some new measures will be suggested in this study. It is shown how these measures relate to the optimality alphabet and to relative entropy. Issues of physical and statistical significance are addressed whenever they arise. Computational feasibility and efficient ways to evaluate the above measures are discussed in this paper, and an illustrative synthetic case study is provided. A major conclusion is that the mean estimation variance and the averaged conditional integral scale are a powerful duo for characterizing conditional parameter uncertainty, with direct correspondence to the well-understood optimality alphabet. This study is based on cokriging generalized to uncertain mean and trends because it is the most general representative of linear spatial estimation within the Bayesian framework. Generalization to kriging and quasi-linear schemes is straightforward. Options for application to non-Gaussian and non-linear problems are discussed.     

Recent evolution of Lake Arreo,northern Spain: influences of land use change and climate

We present a high-resolution, multiproxy reconstruction of the depositional history of Lake Arreo, northern Spain, for the last 60 years. We conducted sedimentological, geochemical and diatom analyses in short cores and made a detailed comparison with regional instrumental climate data (1952–2007), limnological monitoring of the lake (1992–2008) and recent land use changes that affect the lake catchment. Chronology is based on “floating” discontinuous varve counts and ¹³⁷Cs and ¹⁴C dates. Four periods were identified in the Lake Arreo recent history: (1) prior to 1963, varved facies intercalated with fine turbidite deposits, and diatom assemblages dominated by Cyclotella taxa indicate predominantly meromictic conditions, (2) from 1964 to 1978, permanent anoxia persisted in bottom waters, as shown by similar facies and diatom assemblages as before, though detrital layers were coarser, (3) from 1979 to 1994, sediment delivery to the lake increased and laminated, clastic facies were deposited, and (4) from 1995 to 2008, dominance of massive facies and an increase in Fragilaria tenera and Achnanthes minutissima reflect relatively lower lake levels, less frequent bottom anoxia with more frequent water column mixing, similar to modern conditions. The period 1952–1979 was a time of meromixis and varved facies deposition, and was characterized by higher rainfall and less intense agricultural pressure in the watershed. There were two short humid periods (1992–1993 and 1996–1998) when monitoring data show more anoxic weeks per year and relatively higher lake levels. Increased cultivation of small landholdings in 1963, and particularly after 1979, caused a large increase in sediment delivery to the lake. The inferred lake evolution is in agreement with monitoring data that suggest a transition from dominantly meromictic conditions prior to 1993–1994 to a predominantly monomictic pattern of circulation since then, particularly after 2000. The synergistic effects of intensive water extraction for irrigation and lower rainfall since 1979, and particularly since 1994, brought the long period of meromictic conditions in Lake Arreo to an end. Water balance and sediment delivery to the lake are dominant factors that control the limnological and mixing conditions in Lake Arreo and they must be considered in management and restoration plans.     

High-precision repeat-groundtrack orbit design and maintenance for Earth observation missions

The focus of this paper is the design and station keeping of repeat-groundtrack orbits for Sun-synchronous satellites. A method to compute the semimajor axis of the orbit is presented together with a station-keeping strategy to compensate for the perturbation due to the atmospheric drag. The results show that the nodal period converges gradually with the increase of the order used in the zonal perturbations up to \(J_{15}\). A differential correction algorithm is performed to obtain the nominal semimajor axis of the reference orbit from the inputs of the desired nodal period, eccentricity, inclination and argument of perigee. To keep the satellite in the proximity of the repeat-groundtrack condition, a practical orbit maintenance strategy is proposed in the presence of errors in the orbital measurements and control, as well as in the estimation of the semimajor axis decay rate. The performance of the maintenance strategy is assessed via the Monte Carlo simulation and the validation in a high fidelity model. Numerical simulations substantiate the validity of proposed mean-elements-based orbit maintenance strategy for repeat-groundtrack orbits.     

Formation Mechanism of Mud Bank Along the Southwest Coast of India

Mud bank formation during the southwest monsoon along the southwest coast of India remains an enigma to the researchers and coastal community in spite of several earlier studies. The present study attempts to unravel the mystery through a high-frequency, season-long time-series observation at Alappuzha, located at the southern part of the west coast of India, a region of frequent occurrence of mud bank. Using 7-month-long weekly time-series observation, we identified strong winds and high waves associated with onset of the southwest monsoon and subsequent three episodic atmospheric low-pressure events (LPEs).With the help of in situ time-series data, we show that the strong winds and high waves associated with southwest monsoon pre-conditions the near shore bottom sediment to bring it into suspension. The high amplitude waves associated with the southwest monsoon, while propagating from the deep water to shallow water region, interact with the bottom initiating bottom-sediment movement and its suspension due to wave refraction and shoaling. The sporadic occurrence of the atmospheric LPEs enhances the process of suspension of bottom sediment in the near shore region leading to the formation of fluid mud. Simulations with a cohesive sediment transport model yielded realistic estimates of sediment transport, in the presence of an onshore current, a pre-requisite for transporting the fluid mud toward the coast. The prevailing onshore upwelling current during the southwest monsoon provides the favorable pre-requisite conditions for transporting the fluid mud through depression channel network towards the coast. Once sufficient quantity and thickness of fluid mud is accumulated in the near shore region, it acts as a wave damper for subsequent high monsoon waves, as indicated by the time-series wave data, leading to the formation of tranquil mud bank region. Depression channel networks extending from the shelf to the coast off Alappuzha, Kochi, Ponnani, Beypore, and Ullal were found in the bathymetric charts, thus explaining why mud banks occur only at few locations in spite of the prevalence of similar monsoon conditions.     

High-efficiency calculation method for watershed rainfall-runoff routing using one-dimensional dynamic wave equations

Efficiency in solving the Saint-Venant equations for watershed rainfall-runoff routing is important in flood hydrology. This paper presents a high-efficiency numerical solution of one-dimensional dynamic wave equations (HEDWE) for watershed rainfall-runoff routing, in which the full momentum equation is written as a quadratic equation with only one unknown variable Q, water depth is derived from the continuity equation using the two-step predictor-corrector method, and the discrete scheme is the explicit upwind scheme. The results of numerical tests showed the HEDWE approach has several major advantages. 1) It is a stable numerical method, even for an initially dry area. 2) Its computational efficiency is higher than 4.76E+05 times/s. 3) It can be used for overland flow, river flow, and combinations thereof. The primary disadvantages of the HEDWE approach are its unsuitability for rapidly varying flow, such as dam-break floods.     

Identification of Gleissberg Cycles and a Rising Trend in a 315-Year-Long Series of Sunspot Numbers

We show in this short note that the method of singular spectrum analysis (SSA) is able to clearly extract a strong, clean, and clear component from the longest available sunspot (International Sunspot Number, ISN) time series (1700?–?2015) that cannot be an artifact of the method and that can be safely identified as the Gleissberg cycle. This is not a small component, as it accounts for 13% of the total variance of the total original signal. Almost three and a half clear Gleissberg cycles are identified in the sunspot number series. Four extended solar minima (XSM) are determined by SSA, the latest around 2000 (Cycle 23/24 minimum). Several authors have argued in favor of a double-peaked structure for the Gleissberg cycle, with one peak between 55 and 59 years and another between 88 and 97 years. We find no evidence of the former: solar activity contains an important component that has undergone clear oscillations of \(\approx90\) years over the past three centuries, with some small but systematic longer-term evolution of “instantaneous” period and amplitude. Half of the variance of solar activity on these time scales can be satisfactorily reproduced as the sum of a monotonous multi-secular increase, a \(\approx90\)-year Gleissberg cycle, and a double-peaked (\(\approx10.0\) and 11.0 years) Schwabe cycle (the sum amounts to 46% of the total variance of the signal). The Gleissberg-cycle component definitely needs to be addressed when attempting to build dynamo models of solar activity. The first SSA component offers evidence of an increasing long-term trend in sunspot numbers, which is compatible with the existence of the modern grand maximum.     

Automatic Determination of Stellar Atmospheric Parameters Using Neural Networks and Instance-Based Machine Learning

In this article we show how machine learning methods can beeffectively applied to the problem of automatically predictingstellar atmospheric parameters from spectral information, a veryimportant problem in stellar astronomy. We apply feedforwardneural networks, Kohonen's self-organizing maps andlocally-weighted regression to predict the stellar atmosphericparameters effective temperature, surface gravity and metallicityfrom spectral indices. Our experimental results show that thethree methods are capable of predicting the parameters with verygood accuracy. Locally weighted regression gives slightly betterresults than the other methods using the original dataset asinput, while self-organizing maps outperform the other methods when significant amounts of noise are added. We also implemented a heterogeneous ensemble of predictors, combining the results given by the three algorithms. This ensemble yields better results than any of the three algorithms alone, using both the original and the noisy data.