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High-precision modeling of tide-induced 3-D magnetic field and analysis of geomagnetic satellite orbit requirements

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Science China Earth Sciences 2024年第1期67卷 165-178页

作者： Zhengyong REN Cong YANG Hongbo YAO Xu TANG Jingtian TANG Keke ZHANG key laboratory of Metallogenic Prediction of Nonferrous Metals and Geological environment Monitoring Ministry of Education Central South UniversityChangsha 410083China Hunan key laboratory of Nonferrous Resources and Geological Hazards Exploration Changsha 410083China School of Geosciences and Info-Physics Central South UniversityChangsha 410083China state key laboratory of Lunar and Planetary Sciences Macao University of Science and TechnologyMacao 999078China

Ground-based magnetic observatories and geomagnetic satellites can observe the induced magnetic field generated by the motion of seawater containing sodium and chlorine ions.Calculating the three-dimensional(3-D)spatial distribution of tide-induced magnetic fields(TIMF)is crucial for inverting the electrical conductivity structure of the oceanic lithosphere.It also serves as an essential basis for designing optimal geomagnetic observatories and satellite orbits.However,existing methods for simulating TIMF suffer from limitations in inaccurately modeling realistic coastlines,heterogeneous land and sea surface properties,and complex deep Earth structures,thereby the interpretational level of TIMF data is reduced.To overcome this issue,we developed a tetrahedral-based finite element method for simulating TIMF,which can efficiently approximate realistic coastlines,heterogeneous land and sea surface properties,and complex deep Earth structures.Firstly,we derived the boundary value problem for the seawater motion-induced electromagnetic field,which was solved using the vector finite element method based on tetrahedral elements.Secondly,using the latest ocean depth and seafloor sediment layer models,we constructed a 3-D conductivity model of the Earth,which includes realistic coastlines,heterogeneous land and sea conductivity distributions.We then computed the TIMF using the M_(2)tidal source as an example and validated our method by comparing it with results obtained from spherical harmonic finite element and integral equation methods.Finally,utilizing the computed high-precision M_(2),N_(2),and O1 TIMF signals,we marked global observatories capable of observing strong M_(2),N_(2),and O1 TIMF signals and predicted alternative stations suitable for tide signal observations.Additionally,we calculated TIMF at heights of 450 and 200 km for the Macao Science satellite 1 and its subsequent satellites.The results indicate that the amplitude of the tidal-induced magnetic field at 200 km is approximately twice that at 450 km.Th

关键词： ocean motional induction Electromagnetic induction ocean tides Geomagnetic satellite Macao Science satellite 1

Numerical simulations of Atlantic meridional overturning circulation(AMOC)from OMIP experiments and its sensitivity to surface forcing

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Journal of oceanology and Limnology 2024年第2期42卷 454-467页

作者： Xiaowei WANG Yongqiang YU state key laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid dynamics(LASG) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China University of Chinese Academy of Sciences Beijing 100049China

Atlantic meridional overturning circulation(AMOC)plays an important role in transporting heat meridionally in the Earth’s climate system and is also a key metrical tool to verify oceanic general circulation models.Two OMIP(ocean Model Intercomparison Project phase 1 and 2)simulations with LICOM3(version 3 of the LASG/IAP Climate System ocean Model)developed at the state key laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid dynamics(LASG),Institute of Atmospheric Physics(IAP),are compared in this study.Both simulations well reproduce the fundamental characteristics of the AMOC,but the OMIP1 simulation shows a significantly stronger AMOC than the OMIP2 simulation.Because the LICOM3 configurations are identical between these two experiments,any differences between them must be attributed to the surface forcing data.Further analysis suggests that sea surface salinity(SSS)differences should be mainly responsible for the enhanced AMOC in the OMIP1 simulation,but sea surface temperature(SST)also play an unignorable role in modulating AMOC.In the North Atlantic,where deep convection occurs,the SSS in OMIP1 is more saline than that in OMIP1.We find that in the major region of deep convection,the change of SSS has more significant effect on density than the change of SST.As a result,the SSS was more saline than that in OMIP2,leading to stronger deep convection and subsequently intensify the AMOC.We conduct a series of numerical experiments with LICOM3,and the results confirmed that the changes in SSS have more significant effect on the strength of AMOC than the changes in SST.

关键词： oceanic general circulation model(OGCM) Atlantic meridional overturning(AMOC) surface forcing deep convection

Crowdsourcing RTK:a new GNSS positioning framework for building spatial high-resolution atmospheric maps based on massive vehicle GNSS data

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satellite Navigation 2024年第1期5卷 91-108页

作者： Hongjin Xu Xingyu Chen Jikun Ou Yunbin Yuan state key laboratory of Geodesy and Earth’s dynamics Innovation Academy for Precision Measurement Science and Technology(APM)Chinese Academy of Sciences(CAS)Wuhan430071China College of Earth and Planetary Sciences University of Chinese Academy of SciencesBeijingChina

High-quality spatial atmospheric delay correction information is essential for achieving fast integer ambiguity resolution(AR)in precise positioning.However,traditional real-time precise positioning frameworks(i.e.,NRTK and PPP-RTK)depend on spatial low-resolution atmospheric delay correction through the expensive and sparsely distributed CORS network.This results in limited public appeal.With the mass production of autonomous driving vehicles,more cost-effective and widespread data sources can be explored to create spatial high-resolution atmospheric maps.In this study,we propose a new GNSS positioning framework that relies on dual base stations,massive vehicle GNSS data,and crowdsourced atmospheric delay correction maps(CAM).The map is easily produced and updated by vehicles equipped with GNSS receivers in a crowd-sourced way.Specifically,the map consists of between-station single-differenced ionospheric and tropospheric delays.We introduce the whole framework of CAM initialization for individual vehicles,on-cloud CAM maintenance,and CAM-augmented user-end positioning.The map data are collected and preprocessed in vehicles.Then,the crowdsourced data are uploaded to a cloud server.The massive data from multiple vehicles are merged in the cloud to update the CAM in time.Finally,the CAM will augment the user positioning performance.This framework forms a beneficial cycle where the CAM’s spatial resolution and the user positioning performance mutually improve each other.We validate the performance of the proposed framework in real-world experiments and the applied potency at different spatial scales.We highlight that this framework is a reliable and practical positioning solution that meets the requirements of ubiquitous high-precision positioning.

关键词： New GNSS positioning framework Spatial high-resolution atmospheric delay correction Crowdsourced atmospheric delay correction maps Crowdsourced ionosphere Crowdsourced troposphere Ubiquitous

A modified stochastic model for LS+AR hybrid method and its application in polar motion short-term prediction

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Geodesy and Geodynamics 2024年第1期15卷 100-105页

作者： Fei Ye Yunbin Yuan state key laboratory of Geodesy and Earth's dynamics Innovation Academy for Precision Measurement Science and TechnologyChinese Academy of SciencesWuhan 430077China BeiDou High-precision satellite Navigation and Location Service Hunan Engineering Research Center Hunan Institute of Geomatics Sciences and TechnologyChangsha 410007China Hunan Continuously Operating Reference Stations(HNCORS)Data Center Hunan Institute of Geomatics Sciences and TechnologyChangsha 410007China

Short-term(up to 30 days)predictions of Earth Rotation Parameters(ERPs)such as Polar Motion(PM:PMX and PMY)play an essential role in real-time applications related to high-precision reference frame conversion.Currently,least squares(LS)+auto-regressive(AR)hybrid method is one of the main techniques of PM prediction.Besides,the weighted LS+AR hybrid method performs well for PM short-term prediction.However,the corresponding covariance information of LS fitting residuals deserves further exploration in the AR model.In this study,we have derived a modified stochastic model for the LS+AR hybrid method,namely the weighted LS+weighted AR hybrid method.By using the PM data products of IERS EOP 14 C04,the numerical results indicate that for PM short-term forecasting,the proposed weighted LS+weighted AR hybrid method shows an advantage over both the LS+AR hybrid method and the weighted LS+AR hybrid method.Compared to the mean absolute errors(MAEs)of PMX/PMY sho rt-term prediction of the LS+AR hybrid method and the weighted LS+AR hybrid method,the weighted LS+weighted AR hybrid method shows average improvements of 6.61%/12.08%and 0.24%/11.65%,respectively.Besides,for the slopes of the linear regression lines fitted to the errors of each method,the growth of the prediction error of the proposed method is slower than that of the other two methods.

关键词： Stochastic model LS+AR Short-term prediction The earth rotation parameter(ERP) Observation model

Runout prediction of potential landslides based on the multi-source data collaboration analysis on historical cases

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China Geology 2024年第2期7卷 264-276页

作者： Jun Sun Yu Zhuang Ai-guo Xing Guizhou Geology and Mineral Engineering Construction Co. LtdGuiyang 550000China state key laboratory of ocean Engineering Shanghai Jiao Tong UniversityShanghai 200240China

Long runout landslides involve a massive amount of energy and can be extremely hazardous owing to their long movement distance,high mobility and strong destructive power.Numerical methods have been widely used to predict the landslide runout but a fundamental problem remained is how to determine the reliable numerical parameters.This study proposes a framework to predict the runout of potential landslides through multi-source data collaboration and numerical analysis of historical landslide events.Specifically,for the historical landslide cases,the landslide-induced seismic signal,geophysical surveys,and possible in-situ drone/phone videos(multi-source data collaboration)can validate the numerical results in terms of landslide dynamics and deposit features and help calibrate the numerical(rheological)parameters.Subsequently,the calibrated numerical parameters can be used to numerically predict the runout of potential landslides in the region with a similar geological setting to the recorded events.Application of the runout prediction approach to the 2020 Jiashanying landslide in Guizhou,China gives reasonable results in comparison to the field observations.The numerical parameters are determined from the multi-source data collaboration analysis of a historical case in the region(2019 Shuicheng landslide).The proposed framework for landslide runout prediction can be of great utility for landslide risk assessment and disaster reduction in mountainous regions worldwide.

关键词： Landslide runout prediction Drone survey Multi-source data collaboration DAN3D numerical modeling Jianshanying landslide Guizhou Province Geological hazards survey engineering

A Neural-network-based Alternative Scheme to Include Nonhydrostatic Processes in an Atmospheric Dynamical Core

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Advances in Atmospheric Sciences 2024年第6期41卷 1083-1099,I0002,I0003页

作者： Yang XIA Bin WANG Lijuan LI Li LIU Jianghao LI Li DONG Shiming XU Yiyuan LI Wenwen XIA Wenyu HUANG Juanjuan LIU Yong WANG Hongbo LIU Ye PU Yujun HE Kun XIA Ministry of Education key laboratory for Earth System Modeling and Department of Earth System ScienceTsinghua UniversityBeijing 100084China state key laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Innovation Group 311020008 Southern Marine Science and Engineering Guangdong LaboratoryZhuhai 519000China Shanghai Ecological Forecasting and Remote Sensing Center Shanghai 200030China key laboratory of Earth System Modeling and Prediction China Meteorological AdministrationBeijing 100081China College of ocean Sciences University of Chinese Academy of SciencesBeijing 100049China

Here,a nonhydrostatic alternative scheme(NAS)is proposed for the grey zone where the nonhydrostatic impact on the atmosphere is evident but not large enough to justify the necessity to include an implicit nonhydrostatic solver in an atmospheric dynamical core.The NAS is designed to replace this solver,which can be incorporated into any hydrostatic models so that existing well-developed hydrostatic models can effectively serve for a longer time.Recent advances in machine learning(ML)provide a potential tool for capturing the main complicated nonlinear-nonhydrostatic relationship.In this study,an ML approach called a neural network(NN)was adopted to select leading input features and develop the NAS.The NNs were trained and evaluated with 12-day simulation results of dry baroclinic-wave tests by the Weather Research and Forecasting(WRF)model.The forward time difference of the nonhydrostatic tendency was used as the target variable,and the five selected features were the nonhydrostatic tendency at the last time step,and four hydrostatic variables at the current step including geopotential height,pressure in two different forms,and potential temperature,respectively.Finally,a practical NAS was developed with these features and trained layer by layer at a 20-km horizontal resolution,which can accurately reproduce the temporal variation and vertical distribution of the nonhydrostatic tendency.Corrected by the NN-based NAS,the improved hydrostatic solver at different horizontal resolutions can run stably for at least one month and effectively reduce most of the nonhydrostatic errors in terms of system bias,anomaly root-mean-square error,and the error of the wave spatial pattern,which proves the feasibility and superiority of this scheme.

关键词： neural network nonhydrostatic alternative scheme atmospheric model dynamical core

Debris flow runout behaviors considering the influences of densely populated buildings

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Journal of Mountain Science 2024年第8期 2696-2712页

作者： ZHANG Shuai FANG Zhe DAI Cong WANG Shuairong PENG Jingyu ZHOU Yiling SHEN Ping MOE key laboratory of Soft Soils and Geoenvironmental Engineering Zhejiang University state key laboratory of Internet of Things for Smart City and Department of ocean Science and Technology University of Macau

Debris flows pose serious risks to communities in mountainous areas, often resulting in large losses of human life and property. The impeding presence of urban buildings often affects the runout behavior and deposition of debris flows. But the impact of different building densities and sizes on debris flow dynamics has yet to be quantified to guide urban planning in debris flow risk zones. This study focused on a debris flow that occurred in Zhouqu County, Gansu Province, China on August 7th, 2010, which was catastrophic and destroyed many buildings. The FLO-2D software was used to simulate this debris flow in two scenarios, i.e. the presence and the absence of buildings, to obtain debris-flow intensity parameters. The developed model was then used to further analyze the influence of large buildings and narrow channels within the urban environment. The simulation results show that considering the presence of buildings in the simulation is essential for accurate assessment of debris flow intensity and deposition distribution. The layout of buildings in the upstream urban area, such as large buildings or parallel buildings which form narrow channels, can affect the flow velocity and depth of debris flow heading towards downstream buildings. To mitigate damage to downstream buildings, the relative spacing(d/a) between upstream and downstream buildings should not exceed a value of two and should ideally be even lower. These findings provide valuable insights for improving the resistance of mountainous cities to urban debris flows.

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Ascending phase of solar cycle 25 tilts the current El Nino-Southern oscillation transition

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Atmospheric and oceanic Science Letters 2024年第1期17卷 34-38页

作者： Wenjuan Huo Ziniu Xiao Liang Zhao Fei Liu GEOMAR Helmholtz Centre for ocean Research KielGermany state key laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina School of Atmospheric Sciences Sun Yat-Sen UniversityKey Laboratory of Tropical Atmosphere–Ocean SystemMinistry of Educationand Southern Marine Science and Engineering Guangdong LaboratoryZhuhaiChina

关键词：厄尔尼诺-南方涛动太阳活动热带太平洋位相转变预测三重拉尼娜现象

Spatiotemporal variations in glacier area and surface velocity of the northern Antarctic Peninsula during 2018-2022

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Advances in Climate Change Research 2024年第2期15卷 297-311页

作者： Yu-Long KANG Shi-Chang KANG Wan-Qin GUO Tao CHE Zong-Li JIANG Zhen-Feng WANG Qiang-Qiang XU Cheng-De YANG state key laboratory of Cryospheric Science Northwest Institute of Eco-Environment and ResourcesChinese Academy of SciencesLanzhou 730000China University of Chinese Academy of Sciences Beijing 100083China key laboratory of Remote Sensing of Gansu Province Northwest Institute of Eco-Environment and ResourcesChinese Academy of SciencesLanzhou 730000China School of Earth Sciences and Spatial Information Engineering Hunan University of Science and TechnologyXiangtan 411201China

Ice sheet serves as a crucial indicator for assessing climate change.Mass loss in recent remote sensing-based studies indicated that the Antarctic Peninsula has rapid rates of glacier retreat and speed up of surface velocity.However,observations of seasonal variability of ice speed are limited,and glacier-area changes require multi-temporal monitoring.This study investigated the changes in area and surface velocities of∼375 glaciers on the northern Antarctic Peninsula(NAP)utilizing satellite images acquired by the Sentinel 1&2 satellites during 2018-2022.The results indicate that the glacier area reduced by approximately 166.1±44.2 km^(2)(-0.2%±0.1%per year)during the study period,with an acceleration after 2020(-0.4%±0.3%per year),and the most dramatic reduction happened on the eastern NAP.The maximum annual ice speeds on the NAP generally exceeded 3500 m per year,while the ice speeds in 2021 were the highest(exceeded 4210 m per year).The ice speed variability in austral autumn was higher than in other seasons,meanwhile the summer ice speeds showed an increasing trend.The glacier G012158E47018N,McNeile Glacier,glacier G299637E64094S and Drygalski Glacier showed the most remarkable ice speed variations represented by high daily velocities and strong fluctuations on their termini.Our results demonstrated that the variations in glacier area and seasonal ice speed on the NAP were responsive to the ice-ocean-atmosphere processes.Therefore,seasonal velocity and area variations should be considered when conducting accurate mass balance calculations,model validations and change mechanism analyses under climate warming scenarios.

关键词： Glacier area Seasonal ice speed Sentinel 1&2 Northern Antarctic Peninsula Ice-ocean-atmosphere processes