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The Structure of Field-Aligned Current Systems as Inferred From the Multiscale Minimum Variance Analysis 从多尺度最小方差分析推断的场配向电流系统结构
IF 2.9 3区 地球科学 Q2 ASTRONOMY & ASTROPHYSICS Pub Date : 2024-10-24 DOI: 10.1029/2024EA003708
Costel Bunescu

Auroral field-aligned currents (FACs) have an intrinsic complexity caused by the superposition of contributions from a broad spectrum of scales and diversity of locations. The complex FAC systems are investigated by using the multiscale minimum variance analysis. This technique provides a scale based decomposition of the FAC systems by identifying the constituting FAC elements as well as their structure. At the basis, the analysis exploits the scale dependence of the eigenvalues of the magnetic field variance matrix. The scale decomposition along the transversal (latitudinal) direction results from the scale derivative of the maximum eigenvalue. The complementary information from the scale derivative of the minimum eigenvalue helps to infer the full structure of each FAC element by providing estimates of the FAC length (longitudinal) scale. The scale derivative of minimum and maximum eigenvalues are used to identify FAC signatures associated to different types of aurora (e.g., highly extended, finite arcs, gradient regions) as well as to characterize the influence of the crossing location with respect to the FAC structures (e.g., near edge crossings). The multiscale analysis is applied to simulated FACs and to spacecraft observations made by the Swarm mission. The use with real world data illustrates the power of this analysis, whose full benefits for magnetosphere-ionosphere coupling investigations are yet to be explored.

极光场配向流(FACs)具有内在的复杂性,这是由来自各种尺度和各种地点的贡献叠加造成的。利用多尺度最小方差分析对复杂的极光场配向流系统进行了研究。该技术通过识别构成 FAC 的元素及其结构,对 FAC 系统进行基于尺度的分解。在此基础上,分析利用了磁场方差矩阵特征值的尺度依赖性。沿横向(纬向)的尺度分解来自最大特征值的尺度导数。最小特征值的尺度导数提供了补充信息,有助于通过对 FAC 长度(纵向)尺度的估计来推断每个 FAC 元素的完整结构。最小和最大特征值的尺度导数可用于识别与不同类型极光相关的 FAC 特征(如高度延伸、有限弧形、梯度区域),以及描述交叉位置对 FAC 结构的影响(如边缘交叉附近)。多尺度分析应用于模拟 FAC 和 Swarm 任务的航天器观测。实际数据的使用说明了这种分析的威力,其对磁层-电离层耦合研究的全部益处还有待探索。
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引用次数: 0
Enhancing Weather Forecast Accuracy Through the Integration of WRF and BP Neural Networks: A Novel Approach 通过整合 WRF 和 BP 神经网络提高天气预报精度:一种新方法
IF 2.9 3区 地球科学 Q2 ASTRONOMY & ASTROPHYSICS Pub Date : 2024-10-23 DOI: 10.1029/2024EA003613
Zeyang Liu, Jing Zhang, Yadong Yang, Yaping Wang, Wangjun Luo, Xiancun Zhou

In the past century, scholars from both domestic and international communities have delved into the study of numerical weather prediction models to promptly understand meteorological factors and mitigate the impacts of extreme weather events on humanity. Effective and precise prediction models enable the forecasting of meteorological conditions in the upcoming days, empowering individuals to implement proactive measures to minimize the adverse effects of extreme weather (Liang et al., 2021). The WRF (Weather Research and Forecasting) modeling system is commonly used for forecasting meteorological elements. However, uncertainties terribly hamper the correctness of the forecasting results. To this end, the present study was conducted to build a secondary model on the basis of the WRF forecast model. The WRF-BPNN model was proposed for verification after constructing the network, the temperature vertical profile and the mixing ratio vertical profile were predicted, and the results on the validation set were tested. The results showed that the WRF-BPNN model could effectively predict the temperature profile and mixing ratio profile, presenting better performance than the traditional WRF model.

在过去的一个世纪里,国内外学者都在深入研究数值天气预报模式,以便及时了解气象因素,减轻极端天气事件对人类的影响。有效而精确的预测模型能够预报未来几天的气象条件,使人们有能力采取积极措施,将极端天气的不利影响降至最低(Liang 等,2021 年)。WRF(天气研究与预报)建模系统通常用于预报气象要素。然而,不确定性极大地影响了预报结果的正确性。为此,本研究在 WRF 预报模型的基础上建立了一个二级模型。在构建网络后,提出了 WRF-BPNN 模型进行验证,预测了温度垂直剖面和混合比垂直剖面,并对验证集上的结果进行了检验。结果表明,WRF-BPNN 模型能够有效预测温度剖面和混合比剖面,其性能优于传统的 WRF 模型。
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引用次数: 0
Worldwide Rocket Launch Emissions 2019: An Inventory for Use in Global Models 2019 年全球火箭发射排放:用于全球模型的清单
IF 2.9 3区 地球科学 Q2 ASTRONOMY & ASTROPHYSICS Pub Date : 2024-10-23 DOI: 10.1029/2024EA003668
Tyler F. M. Brown, Michele T. Bannister, Laura E. Revell, Timofei Sukhodolov, Eugene Rozanov

The rate of rocket launches is accelerating, driven by the rapid global development of the space industry. Rocket launches emit gases and particulates into the stratosphere, where they impact the ozone layer via radiative and chemical processes. We create a three-dimensional per-vehicle inventory of stratospheric emissions, accounting for flight profiles and all major fuel types in active use (solid, kerosene, cryogenic and hypergolic). In 2019, stratospheric (15–50 km) rocket launch emissions were 5.82 Gg CO2 ${mathrm{C}mathrm{O}}_{2}$, 6.38 Gg H2 ${mathrm{H}}_{2}$O, 0.28 Gg black carbon, 0.22 Gg nitrogen oxides, 0.50 Gg reactive chlorine and 0.91 Gg particulate alumina. The geographic locations of launch sites are preserved in the inventory, which covers all active launch sites in 2019. We also report the emissions data from contemporary vehicles that were not launched in 2019, so that users have freedom to construct their own launch activity scenarios. A subset of the inventory—stratospheric emissions for successful launches in 2019—is freely available and formatted for direct use in global chemistry-climate or Earth system models.

在全球航天工业快速发展的推动下,火箭发射的速度正在加快。火箭发射会向平流层排放气体和微粒,通过辐射和化学过程对臭氧层产生影响。我们创建了平流层排放量的三维每车清单,其中考虑到了飞行剖面和所有正在使用的主要燃料类型(固体燃料、煤油、低温燃料和高热能燃料)。2019年,平流层(15-50千米)火箭发射的排放量为5.82千兆克C O 2 ${mathrm{C}mathrm{O}}_{2}$ 、6.38千兆克H 2 ${mathrm{H}}_{2}$ O、0.28千兆克黑碳、0.22千兆克氮氧化物、0.50千兆克活性氯和0.91千兆克颗粒氧化铝。清单中保留了发射场的地理位置,涵盖了 2019 年所有活跃的发射场。我们还报告了 2019 年未发射的当代运载火箭的排放数据,以便用户自由构建自己的发射活动场景。清单中的一个子集--2019 年成功发射的平流层排放量--可免费获取,其格式可直接用于全球化学-气候或地球系统模型。
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引用次数: 0
Near Real-Time Earthquake Monitoring in Texas Using the Highly Precise Deep Learning Phase Picker 利用高精度深度学习相位选择器对得克萨斯州的地震进行近实时监测
IF 2.9 3区 地球科学 Q2 ASTRONOMY & ASTROPHYSICS Pub Date : 2024-10-21 DOI: 10.1029/2024EA003890
Yangkang Chen, Alexandros Savvaidis, Daniel Siervo, Dino Huang, Omar M. Saad

Artificial intelligence (AI) seismology has witnessed enormous success in a variety of fields, especially in earthquake detection and P and S-wave arrival picking. It has become widely accepted that DL techniques greatly help routine seismic monitoring by enabling more accurate picking than traditional pickers like STA/LTA. However, a completely automatic AI-driven earthquake monitoring framework has not been reported due to the concerns of potential false positives using DL pickers. Here, we propose a novel AI-facilitated near real-time monitoring framework using a recently developed deep learning (DL) picker (EQCCT) that has been deployed in the Texas seismological network (TexNet). For the West Texas area, TexNet's seismic monitoring relies on the EQCCT picker to report earthquake events. For earthquakes with a magnitude above two, the picks are further validated by analysts to output the final TexNet catalog. Due to the fast-increasing seismicity caused by continuing oil&gas production in West Texas, this AI-facilitated framework significantly relieves the workload of TexNet analysts. We show the mean absolute error (MAE) of automatic magnitude estimation for the magnitude-above-two earthquakes is smaller than 0.15 in West Texas and MAEs of hypocenter locations within 2.6 km in both distance and depth estimates. This research provides more evidence that DL pickers can play a fundamental role in daily earthquake monitoring.

人工智能(AI)地震学在多个领域取得了巨大成功,尤其是在地震探测以及 P 波和 S 波到达选取方面。人们普遍认为,与 STA/LTA 等传统采集器相比,DL 技术能实现更精确的采集,从而大大有助于常规地震监测。然而,由于担心使用 DL 挑选器可能会产生误报,完全由人工智能驱动的全自动地震监测框架尚未见报道。在此,我们提出了一个新颖的人工智能辅助近实时监测框架,该框架使用了最近开发的深度学习(DL)选取器(EQCCT),并已部署在德克萨斯州地震学网络(TexNet)中。在德克萨斯州西部地区,TexNet 的地震监测依靠 EQCCT 采集器报告地震事件。对于震级在 2 级以上的地震,分析人员会对选取的地震事件进行进一步验证,以输出最终的 TexNet 目录。由于德克萨斯州西部持续的石油和天然气生产导致地震活动迅速增加,这一人工智能辅助框架大大减轻了 TexNet 分析人员的工作量。我们的研究表明,在德克萨斯州西部,震级大于 2 级地震的自动震级估计平均绝对误差 (MAE) 小于 0.15,在距离和深度估计方面,震中位置的平均绝对误差在 2.6 千米以内。这项研究提供了更多证据,证明 DL 采样器可在日常地震监测中发挥重要作用。
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引用次数: 0
Land and Atmospheric Drivers of the 2023 Flood in India 2023 年印度洪灾的陆地和大气驱动因素
IF 2.9 3区 地球科学 Q2 ASTRONOMY & ASTROPHYSICS Pub Date : 2024-10-20 DOI: 10.1029/2024EA003750
Anuj Prakash Kushwaha, Hiren Solanki, Urmin Vegad, Shanti Shwarup Mahto, Vimal Mishra

Floods in India are recurring natural disasters resulting from extreme precipitation during the summer monsoon season (June–September). The recent flood in North India in July 2023 caused substantial damage to lives, agriculture, and infrastructure. However, what led to the 2023 North India flood and the role of atmospheric and land drivers still need to be examined. Using in situ observations, satellite data, and ERA5 reanalysis combined with hydrological and hydrodynamical modeling, we examine the role of land and atmospheric drivers in flood occurrence and its impacts. Extreme precipitation in a large region during 7–10 July 2023 created favorable conditions for the flood in the hilly terrains and plains of north India. More than 300 mm of precipitation fell in just 4 days, which was eight times higher than the long-term average (2001–2022). Anomalously high moisture transport over northern India was recorded on 7 July 2023, making atmospheric conditions favorable for intense landfall. Increased column water vapor and specific humidity at different pressure levels confirmed the continuous moisture presence before the extreme rainfall that caused floods in northern India from 7 to 12 July 2023. Atmospheric and land (high antecedent soil moisture) conditions contributed to a more than 200% rise in streamflow at several gauge stations. Satellite-based flood extent shows a considerable flood inundation that caused damage in the Sutlej and Yamuna River basins. Our findings highlight the crucial role of the favorable land and atmospheric conditions that caused floods and flash floods in north India in July 2023.

印度的洪水是夏季季风季节(6 月至 9 月)极端降水造成的经常性自然灾害。最近于 2023 年 7 月发生在北印度的洪水给生命、农业和基础设施造成了巨大损失。然而,导致 2023 年北印度洪灾的原因以及大气和陆地驱动因素的作用仍有待研究。利用现场观测、卫星数据、ERA5 再分析以及水文和流体力学建模,我们研究了陆地和大气驱动因素在洪水发生及其影响中的作用。2023 年 7 月 7-10 日期间,印度北部丘陵地带和平原大面积的极端降水为洪水的发生创造了有利条件。短短 4 天降水量超过 300 毫米,是长期平均值(2001-2022 年)的 8 倍。2023 年 7 月 7 日,印度北部录得异常高的水汽输送,为强烈登陆创造了有利的大气条件。在 2023 年 7 月 7 日至 12 日造成印度北部洪灾的极端降雨之前,不同气压水平上增加的柱状水汽和比湿度证实了水汽的持续存在。大气和陆地(高先兆土壤湿度)条件导致多个测量站的溪流流量增加了 200% 以上。基于卫星的洪水范围显示,洪水淹没范围相当大,给苏特莱杰河和亚穆纳河流域造成了破坏。我们的研究结果凸显了有利的土地和大气条件在 2023 年 7 月造成印度北部洪水和山洪暴发的关键作用。
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引用次数: 0
Intermediate Wave Scale Rocky Bottom Variability for the Nearshore Along California 加利福尼亚近岸的中波尺度岩底可变性
IF 2.9 3区 地球科学 Q2 ASTRONOMY & ASTROPHYSICS Pub Date : 2024-10-19 DOI: 10.1029/2023EA003475
Jamie MacMahan, Ed Thornton, Stef Dressel, Mike Cook
<div> <section> <p>Approximately 75% of the world's and California's shores are rocky. Rocky shores are of biological interest owing to their diverse and productive species assemblages, where waves and currents play a critical role in larval dispersal and recruitment. Surface variability for nearshore <span></span><math> <semantics> <mrow> <mo>(</mo> <mrow> <mn>5</mn> <mo>⪅</mo> <mi>d</mi> <mi>e</mi> <mi>p</mi> <mi>t</mi> <mi>h</mi> <mo>⪅</mo> <mn>60</mn> <mspace></mspace> <mi>m</mi> </mrow> <mo>)</mo> </mrow> <annotation> $(5lessapprox mathrm{d}mathrm{e}mathrm{p}mathrm{t}mathrm{h}lessapprox 60hspace*{.5em}mathrm{m})$</annotation> </semantics></math> rocky bottoms at intermediate wave scale <span></span><math> <semantics> <mrow> <mfenced> <mrow> <mn>1</mn> <mo>/</mo> <mn>750</mn> <mo><</mo> <mi>k</mi> <mo><</mo> <mn>1</mn> <mo>/</mo> <mn>4</mn> <mspace></mspace> <msup> <mi>m</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </mfenced> </mrow> <annotation> $left(1/750< k< 1/4hspace*{.5em}{mathrm{m}}^{-1}right)$</annotation> </semantics></math> is described for the first time using existing high-resolution bathymetric surveys extending the length of California. The vertical variability of rocky shores is three times larger than measured coral reefs at the reef scale of <span></span><math> <semantics> <mrow> <mn>1</mn> <mo>/</mo> <mn>64</mn> <mo><</mo>
全世界和加利福尼亚州约有 75% 的海岸是岩石海岸。岩石海岸因其多样且富饶的物种组合而备受生物界关注,其中波浪和海流对幼虫的扩散和繁殖起着至关重要的作用。Surface variability for nearshore ( 5 ⪅ d e p t h ⪅ 60 m ) $(5lessapprox mathrm{d}mathrm{e}mathrm{p}mathrm{t}mathrm{h}lessapprox 60hspace*{.5em}mathrm{m})$ rocky bottoms at intermediate wave scale 1 / 750 < k < 1 / 4 m − 1 $left(1/750< k< 1/4hspace*{.5em}{mathrm{m}}^{-1}right)$ is described for the first time using existing high-resolution bathymetric surveys extending the length of California.在 1 / 64 < k < 1 / 4 m - 1 $1/64 < k < 1/4hspace*{.5em}{mathrm{m}}^{-1}$ 的珊瑚礁尺度下,岩石海岸的垂直变化比测量的珊瑚礁大三倍。经过归一化处理的集合平均波数高程谱具有自相似性,至少有两个负幂律斜率区域,1.3 表示粗糙的底部,2.75 的高波数表示较平滑的凹陷。岩质海底的集合统计量似乎是各向同性的,因为它们的跨岸和沿岸方差以及波数斜率谱在统计上是相等的。各向同性的原因是波浪随时间的侵蚀只发生在近岸海洋区域。为沿岩石海岸的波浪和海流驱动的水动力模型开发了海底边界条件 G‾z ′ ${overline{G}}_{{z}^{prime }}$ 的傅立叶谱表示法。相对于重建剖面和表面的观测光谱数据,该模型的误差小于 2%。
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引用次数: 0
Faint Space Target Information Extraction Based on Small Aperture Telescope in Complex Background 复杂背景下基于小孔径望远镜的微小空间目标信息提取
IF 2.9 3区 地球科学 Q2 ASTRONOMY & ASTROPHYSICS Pub Date : 2024-10-18 DOI: 10.1029/2023EA003404
Ping Jiang, Yaoqin Xie, Sijia Wu, Tangsheng Wang, Yalan Li

There are many problems in space debris monitoring with ground-based telescopes, such as too many stars in the same field of view, uneven background and optical distortion in the optical system. We propose a two-stage weak debris detection algorithm. In the first stage, wavelet transform is used to extract different components of three frames of images, and the median of corresponding components of the images is taken respectively to eliminate the influence of stars. In the second stage, an improved version of the faint space target extraction based on principal component analysis. The algorithm uses a smooth-detection idea to extract target information. Based on a 150 mm aperture telescope, we improved the existing method of faint space debris extraction based on principal component analysis by introducing the smooth-detection idea, and transformed the target detection problem into the separation problem of sparse matrix and low-rank matrix. We applied a certain preprocessing consisting of wavelet-based star removal and median pre-filtering to keep as little noise and other contaminants as possible. After experimental measurements by observers, the algorithm demonstrated advanced detection capabilities on multiple indicators.

使用地面望远镜进行空间碎片监测存在许多问题,如同一视场中的恒星过多、背景不均匀以及光学系统的光学失真等。我们提出了一种两阶段弱碎片检测算法。在第一阶段,利用小波变换提取三帧图像的不同分量,并分别取图像对应分量的中值来消除恒星的影响。第二阶段是基于主成分分析的微弱空间目标提取改进版。该算法采用平滑检测思想提取目标信息。基于 150 毫米口径望远镜,我们对现有的基于主成分分析的微弱空间碎片提取方法进行了改进,引入了平滑检测思想,将目标检测问题转化为稀疏矩阵和低秩矩阵的分离问题。我们采用了一定的预处理方法,包括基于小波的除星和中值预滤波,以尽可能减少噪声和其他污染物。经过观测者的实验测量,该算法在多个指标上都表现出了先进的探测能力。
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引用次数: 0
Ensemble Based Estimation of Wet Refractivity Indices Using a Functional Model Approach 使用函数模型法进行基于集合的湿折射率指数估算
IF 2.9 3区 地球科学 Q2 ASTRONOMY & ASTROPHYSICS Pub Date : 2024-10-15 DOI: 10.1029/2023EA003453
Masoud Dehvari, Saeed Farzaneh, Ehsan Forootan

The estimation of the wet refractivity indices is crucial for applications like weather predictions or improving the accuracy of real-time positioning techniques. Traditionally, solving the inverse tomography problem to estimate these atmospheric parameters has been challenging due to its ill-posed nature and high computational demands, necessitating additional constraints. To overcome these challenges, the data assimilation method is proposed here to integrate Global Navigation Satellite System (GNSS) observations into a background model. In this study, the Ensemble Kalman Filter (EnKF) was served as the assimilation core to reduce the computational load and to enable the epoch-wise estimation of wet refractivity indices. The Global Pressure and Temperature 3 (GPT3w) model was utilized as the background, and wet refractivity indices at each epoch were transformed into B-spline coefficients, representing state vector parameters. Subsequently, GNSS derived zenith wet delay (ZWD) values were integrated into the model using the EnKF method. The study's region encompassed the western parts of Europe and incorporated approximately 893 GNSS stations. Evaluation spanned from 1 January 2017 to 31 December 2017. The estimated wet refractivity indices from the proposed method were compared with observations from 16 existing radiosonde stations, radio occultation data, and ZWD values from the 47 selected GNSS test stations. Additionally, calculated ZWD values, resulting from the integration of wet refractivity indices, were compared to the ZWD values from 47 test stations in the study region. The numerical results demonstrated that the proposed method achieved a root mean square error value of approximately 2.6 ppm, which was nearly 49% and 18% lower than that of the considered empirical and numerical atmospheric models, respectively.

湿折射率指数的估算对于天气预报或提高实时定位技术精度等应用至关重要。传统上,解决反层析问题以估算这些大气参数具有挑战性,这是因为它的不确定性和高计算要求需要额外的约束条件。为了克服这些挑战,本文提出了数据同化方法,将全球导航卫星系统(GNSS)观测数据整合到背景模型中。在这项研究中,将集合卡尔曼滤波器(EnKF)作为同化核心,以减少计算负荷,并实现湿折射率指数的历时估算。利用全球气压和温度 3(GPT3w)模型作为背景,将每个历元的湿折射率指数转换为 B 样条系数,代表状态矢量参数。随后,利用 EnKF 方法将全球导航卫星系统得出的天顶湿延迟(ZWD)值整合到模型中。研究区域包括欧洲西部,约有 893 个全球导航卫星系统台站。评估时间跨度为 2017 年 1 月 1 日至 2017 年 12 月 31 日。将拟议方法估算出的湿折射率指数与 16 个现有无线电探空仪观测站的观测数据、无线电掩星数据以及 47 个选定全球导航卫星系统测试站的 ZWD 值进行了比较。此外,还将湿折射率指数积分计算得出的 ZWD 值与研究区域 47 个测试站的 ZWD 值进行了比较。数值结果表明,拟议方法的均方根误差值约为 2.6 ppm,比所考虑的经验模型和数值大气模型的均方根误差值分别低近 49% 和 18%。
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引用次数: 0
Improvements to EXSIM in Ground Motion Simulation for Earthquakes Explained by Double-Corner-Frequency Source Model EXSIM 在双角频源模型解释地震的地动模拟中的改进
IF 2.9 3区 地球科学 Q2 ASTRONOMY & ASTROPHYSICS Pub Date : 2024-10-13 DOI: 10.1029/2024EA003797
Wanjun Ma, Zhinan Xie, Lei Fu, Zhendong Shan, Jianqi Lu, Lihua Tang, Xubin Zhang

The stochastic EXtended finite-fault ground-motion SIMulation algorithm (EXSIM) has been widely applied in simulating and predicting broadband strong ground-motion. However, an increasingly number of researchers have found that EXSIM may overestimate ground-motions at low frequencies for some large-magnitude earthquakes and/or thrust earthquakes, for which the far-field source model has been explained by a double-corner-frequency model. Despite controversy, the double-corner-frequency model is now being accepted as one of the main categories of the far-field source model. This study demonstrated the limited applicability of EXSIM to earthquakes explained by the double-corner-frequency source model, by presenting the equivalence between motions generated by EXSIM and those generated by EXSIM's point-source version, SMSIM, which adopts the ω-square single-corner-frequency model. Furthermore, two improvements to EXSIM have been proposed: (a) the incorporation of the asperity-distributed stress-drop compound faults model and (b) the hybrid application of EXSIM with the proposed model. The effects of the two improvements have been verified by comparing EXSIM-generating motions with recorded ground-motions for the 2013 Mw 6.7 Lushan thrust earthquake. Significantly, consistent simulation accuracy has been achieved across high- and low-frequency bands as well as in far- and near-fields. The consistent accuracy of the improved EXSIM in simulating high- and low-frequency ground motions enables its direct and independent application to broadband ground motion simulations. Moreover, the first validation of this consistent accuracy in both near- and far-field scenarios further enhances its application in earthquake engineering practices.

随机扩展有限断层地动模拟算法(EXSIM)已被广泛应用于模拟和预测宽带强地动。然而,越来越多的研究人员发现,对于一些大震级地震和/或推力地震,EXSIM 可能会高估低频地动。尽管存在争议,但双角频率模型目前已被接受为远场震源模型的主要类别之一。本研究通过展示 EXSIM 生成的地震运动与 EXSIM 的点源版本 SMSIM(采用 ω 方形单角频率模型)生成的地震运动之间的等效性,证明 EXSIM 对双角频率源模型解释的地震的适用性有限。此外,还对 EXSIM 提出了两点改进建议:(a) 加入表面分布应力下降复合断层模型;(b) 将 EXSIM 与提出的模型混合应用。通过比较 EXSIM 生成的地震运动和 2013 年 6.7 级芦山推力地震的地面运动记录,验证了这两项改进的效果。值得注意的是,高、低频段以及远、近场都实现了一致的模拟精度。改进后的 EXSIM 在模拟高频和低频地动时具有一致的精度,这使其能够直接、独立地应用于宽带地动模拟。此外,EXSIM 在近场和远场情况下的一致精度首次得到验证,进一步加强了其在地震工程实践中的应用。
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引用次数: 0
Investigating Subsurface Properties of the Shallow Lunar Crust Using Seismic Interferometry on Synthetic and Recorded Data 利用合成数据和记录数据的地震干涉测量法研究月球浅壳的次表层特性
IF 2.9 3区 地球科学 Q2 ASTRONOMY & ASTROPHYSICS Pub Date : 2024-10-11 DOI: 10.1029/2024EA003742
S. Keil, H. Igel, M. Schimmel, F. Lindner, F. Bernauer

In the past few years, the remarkable progress of commercially operated spacecrafts, the success with reusable rocket engines, as well as the international competition to explore space, has led to a substantial acceleration of activities in the design and preparation of ambitious future lunar missions. In the search for ice and/or cavities imaging the shallow subsurface structure is of vital importance. Hereby, previous studies have shown that seismic interferometry is a promising method to investigate the subsurface properties from passive lunar data. In this study, we want to evaluate the potential of this method further by examining the required duration of seismic measurements and the influence of scattering on the Green's function retrieval. Therefore, we applied seismic interferometry to both measured Apollo 17 data and synthetic data. Our findings indicate that, under optimal conditions, a few hours of data are sufficient when using the method of time-scaled phase-weighted stack (ts-PWS). However, this strongly depends on the inter-station distance, the orientation toward the principal noise sources, and the timing of the measurement during the lunar cycle. Additionally, we were able to reproduce the measured data using numerical simulations in 2D. The synthetic results show that scattering effects clearly influence the Green's function extraction, especially for larger station distances.

在过去的几年里,商业运营的航天器取得了显著的进步,可重复使用的火箭发动机取得了成功,探索太空的国际竞争也促使设计和准备未来雄心勃勃的月球任务的活动大大加快。在寻找冰和/或空洞的过程中,地表下浅层结构的成像至关重要。因此,以往的研究表明,地震干涉测量法是利用被动月球数据研究地表下特性的一种很有前途的方法。在本研究中,我们希望通过研究地震测量所需的持续时间以及散射对格林函数检索的影响,进一步评估这种方法的潜力。因此,我们将地震干涉测量法应用于阿波罗 17 号的测量数据和合成数据。我们的研究结果表明,在最佳条件下,使用时间尺度相位加权叠加(ts-PWS)方法,几个小时的数据就足够了。然而,这在很大程度上取决于站间距离、主要噪声源的方向以及月球周期中的测量时间。此外,我们还利用二维数值模拟重现了测量数据。合成结果表明,散射效应明显影响了格林函数的提取,尤其是在测站距离较大的情况下。
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Earth and Space Science
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