Many natural and man-made phenomena cause ionospheric responses that can be captured in total electron content data obtained from Global Navigation Satellite System observations. However, the increasing volume of the data poses challenges for its analysis. This study provides an algorithm for detecting covolcanic ionospheric disturbances in total electron content time series based on machine learning. Using the Sarychev Peak eruption (June 11-16, 2009) as an example, we identified and labeled the observational data, proposed data features, and generated datasets. The design and number of features were chosen considering the computational efficiency of the algorithm and its potential applicability in monitoring systems. A machine learning model based on a gradient boosting technique was trained and achieved a Matthews correlation coefficient of 0.86 on the test dataset, indicating the high quality. The proposed algorithm detects 96 % of the disturbances in the datasets with a minimal number of false positives (48 out of 200 test files), exhibiting a significant improvement compared with the conventional STA\LTA algorithm, which detected only 11 % of the disturbances. The validation of the algorithm on data corresponding to the Calbuco (2015) and Hunga Tonga-Hunga Ha'apai (2022) volcanoes eruptions showed 94 % and 81 % of the disturbances detected, respectively. (c) 2024 COSPAR. Published by Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

The strongest earthquakes with magnitudes Mw 8–9 generate coseismic displacements of the Earth’s crust, covering entire regions of the world. These displacements can be recorded using observations provided by the independent geodetic GNSS networks. The data of these networks are processed using different algorithms and methods for analyzing satellite observations, methods for calculating the coseismic shift, and different implementations of the coordinate system. These factors lead to "inconsistency" of the combined displacement fields and the appearance of additional errors in the results of coseismic effects modeling. The paper proposes a method for combining the fields of coseismic displacements of the Earth's crust, obtained in the far-field zone from the source according to data from heterogeneous GNSS networks. The results of applying the proposed method are demonstrated by the example of combining the fields of coseismic displacements in China, South Korea and the south of the Far East of the Russian Federation, initiated by the catastrophic Tohoku earthquake on March 11, 2011, Mw 9.1, as well as the calculation and analysis of the unified field of coseismic deformations of the region under study.

The explosive eruption of the Hunga Tonga-Hunga Haapai volcano occured on January 15, 2022 at 04:02 UTC led to generation of covolcanic ionospheric disturbances that spread over long distances. Using GNSS data obtained at permanent stations of the IGS network and sites located on the territory of Primorsky Krai, the search and analysis of ionospheric disturbances over the territory of Primorsky Krai and adjacent areas was performed. The velocity of the covolcanic ionospheric disturbances recorded over the Primorsky Krai reached about 340 m/s, and the average amplitude was equal to 1.0 TECU. The results obtained from GNSS-data were also compared with the results of observation data obtained by a laser strainmeters (oriented in the directions "north – south" and "east – west") and a laser nanobarograph located at the Schultz Cape (the south of Primorsky Krai). As a comparison result, time delays between the moments of fixation of disturbances in the troposphere and ionosphere were found. The delay between the first peaks of disturbances was equal to ~50 min.

The mechanisms of preparation and occurrence of the strongest deep-focus earthquakes with MW≥8, as well as their surface manifestations, remain insufficiently studied because of the lack of the relevant data. There are but three seismic events of this kind which have so far been instrumentally recorded. This paper describes the identification and analysis of the changes in the characteristics of modern crustal movement of the 2013, MW 8.3 Sea of Okhotsk deep-focus earthquake based on the data from long-term continuous geodetic-class GNSS stations in the Sea of Okhotsk region on the Kamchatka Peninsula, the Sakhalin Island, and the coast of the Sea of Okhotsk and the Sea of Japan. There has been found temporal stability of variations in the average annual geodetic site velocities. The coordinates of GNSS-stations do not show non-linear changes typical of strong shallow earthquakes in the initial post-seismic period. The Maxwell rheology for modeling of viscoelastic relaxation of the asthenosphere/upper mantle as a result of seismic impact allows for a first approximation to qualitatively and quantitatively reproduce the displacement patterns of GNSS-sites of the Kamchatka Peninsula observed in the initial postseismic period (2–3 years after the mainshock). After that, the model estimates of postseismic movements of the peninsula become systematically lower than the observed. The values calculated for the OKHT station motion on the western coast of the Sea of Okhotsk are in good agreement with those recorded for postseismic displacements over the entire measurement interval. The observed directions of the Sakhalin Island postseismic movements systematically deviate to the northeast from the model directions and are oriented almost orthogonally to the Kuril-Kamchatka Trench. Besides the viscoelastic relaxation process, another possible reason for this issue could be an enhanced viscous friction in the bottom of the subducting Pacific plate, leading to the intense deformation of the Sakhalin Island and the western coast of Kamchatka.

Работа посвящена оценке возможности применения искусственных нейронных сетей для поиска ковулканических ионосферных возмущений во временных рядах полного электронного содержания, полученных по данным ГНСС-наблюдений.На примере извержения влк

We investigated lithospheric and ionospheric disturbances caused by the 3 September 2017 underground nuclear test (UNT) in North Korea based on data from networks of seismic stations and GPS/GLONASS receivers. We analyzed frequency composition of longitudinal and surface waves detected at more than 40 seismic stations. Low frequencies (similar to 0.45 +/- 0.21 Hz) were found to prevail in the spec-trum of longitudinal waves. For both types of waves, frequencies decreased with distance according to the power law. Analysis revealed two trends in the spatial distribution of peak frequencies. First, high and mid-frequencies (0.14-0.50 Hz) are typical for the continental landmass regions, and low frequencies of surface waves (0.13 Hz and below) are more common for the regions adjacent to fringe seas. Second, uneven frequency variations of seismic waves for different azimuths relative to the UNT epicenter (frequencies subside rapidly in the east, southeast, and southwest directions from the epicenter; towards the continental landmass inner parts, frequency variation is much slower). Records of longitudinal waves made at different distances from the epicenter allowed estimating the size of the focal area. Analysis of data from GPS/GLONASS receiving stations near the Korean Peninsula revealed ionospheric disturbances that were most likely caused by UNT. The ionospheric disturbances started to be detected -8 min after UNT and were observed for about 5 hrs. During the first 1.5-2 hrs after UNT, travelling ionospheric disturbances (TID) were recorded; they propagated from the epicenter at similar to 600, 250 and 133 m/s. These TIDs had periods of 1-10.5 min and could be associated with acoustic waves induced in the Earth's atmosphere by the underground nuclear test. After TID passage over the UNT site, there was a long-lived (more than 3.5 hrs) region of non-travelling perturbations of ionospheric plasma with the velocity about 7 m/s. This velocity describes not so much the disturbance travel, but the time when the "receiver - satellite" line of sight (LOS) crosses the disturbance. This region can possibly occur due to the formation of standing waves in the atmosphere, development of plasma instabilities or penetration into the ionosphere of an anomalous electric field generated by radioactive substances leaked out onto the surface. (c) 2023 COSPAR. Published by Elsevier B.V. All rights reserved.

О некоторых аспектах применения ГНСС-технологий в метеорологии и экологии1 Дальневосточный федеральный университет, г.Владивосток, Российская Федерация 2 Институт прикладной математики ДВО РАН, г

SUMMARY The objective of this study was to examine co- and post-seismic deformation following the 2011 Mw9.0 Tohoku–Oki earthquake and its impact on Northeast Asia. Large-scale, long-term post-seismic deformation caused by the earthquake was extracted according to the continuous Global Navigation Satellite Systems (GNSS) observation data for Japan, South Korea, Northeast China and the Far East Russia. The present research adopted a 2-D viscoelastic model to simulate the observed large-scale seismic deformation, considering the subducting slab in the western Pacific. The duration of the after-slip in the northwest of the main rupture area was found to be greater than that in the south of the main rupture area (approximately 6 yr). The steady-state viscosity coefficient of the continental mantle was found to be 8 × 1018 Pa·s. Post-seismic deformation in Northeast Asia was primarily caused by viscoelastic relaxation of the mantle, and observations on the west side of the Tan-Lu fault were smaller than simulation, revealing the heterogeneity in viscosity structures in NE China.

Современные проблемы ДЗЗ из космоса, 20(

The article analyzes the integral atmospheric water content by data of continuous GPS/GLONASS observations over 2017–2019 at 13 observation points of the GNSS network in the territory of the Primorski Krai. The procedure of IWV evaluation is based on the decomposition of the total zenith tropospheric delay of satellite signal into the hydrostatic and humidity components. The GNSS-estimates of IWV were verified using radiosonde data from two weather stations of the Primorski Department of Hydrometeorological Service. The correlation between the results of GNSS and radiosonde observations was 0.93–0.99. The obtained IWV estimates were compared with Global Forecast System data. The comparison involved 16 nodes of the model grid nearest to each sensor. It was shown that the correlation of GNSS estimates of IWV with GFS data at the moment of forecast is, on the average, >0.90; starting from the forecast advance time of 48 h, the coefficient of correlation decreases to 0.60. The coefficient of correlation with GFS is 0.85–0.97 in the warm season and ≤0.60 in the cold season. The analysis of the spatial distribution of the correlation coefficient showed that the measured IWV values are linearly related with the PWEA model values, which refer to the grid nodes that show lesser elevation difference with the GNSS point. The results of the study suggest the conclusion that the expenses for the acquisition and processing of GNSS data are minimal and the operation of grid points does not depend on weather conditions. This makes the results of GNSS sounding promising for use in regional atmospheric models.

На основе анализа данных нескольких сетей станций приёма сигналов глобальных навигационных спутниковых систем (ГНСС) GPS, ГЛОНАСС проведены исследования ионосферных возмущений, инициированных северокорейским подземным ядерным испытанием (взрывом) 3 сентября 2017 г.Возмущения в ионосфере наблюдались на большом количестве лучей «приёмник ГНСС -спутник ГНСС».Форма возмущений, порождённых подземным ядерным испытанием, заметно отличалась от формы ионосферных аномалий, наблюдаемых после землетрясений.Ионосферные возмущения начали регистрироваться через ~8 мин после взрыва и наблюдались в течение более 5 ч после него.Показано, что в пределах 1,5 ч после взрыва регистрировались преимущественно перемещающиеся ионосферные возмущения (ПИВ) с периодами от 1,0 до 9,5 мин, распространявшиеся от эпицентра со средними скоростями порядка 580, 250 и 130 м/с.Эти ПИВ могут быть отнесены к акустическим волнам, вызванным в атмосфере подземным ядерным испытанием.Примерно через 60 мин после взрыва над эпицентром начала формироваться долгоживущая (наблюдалась более 3,5 ч) область малоподвижных возмущений ионосферной плазмы, скорость которых составляла ~8 м/с.Природа и механизмы формирования данной области требуют дальнейшего исследования и моделирования.

Apart from algebraic correlations, we need to take into account physical correlations in observations due to inestimable systematic errors. This is especially important in the case of GPS measurements. Different investigators have obtained values of correlation coefficients of up to 0.85 for identical satellite configuration due to physical correlations. The attempt has been to introduce these correlations or some correlation functions into post-processing of GPS measurements in order to improve the results. As illustrated in our report however, it may be very problematic in practice and could lead to extraordinarily absurd results. One such unexpected effect may be artificial increase of the weight P of the results. When weight

Global Navigation Satellite Systems have been extensively used to investigate the ionosphere response to various natural and man-made phenomena for the last three decades. However, ionospheric reaction to volcano eruptions is still insufficiently studied and understood. In this work we analyzed the ionospheric response to the 11–16 June 2009 VEI class 4 Sarychev Peak volcano eruption by using surrounding Russian and Japanese GPS networks. Prominent covolcanictotal electron content (TEC)ionospheric disturbances (CVIDs) with amplitudes and periods ranged between 0.03–0.15 TECU and 2.5–4.5 min were discovered for the three eruptive events occurred at 18:51 UT, 14 June; at 01:15 and 09:18 UT, 15 June 2009. The estimates of apparent CVIDs velocities vary within 700–1000 m/s in the far-field zone (300–900 km to the southwest from the volcano) and 1300–1800 m/s in close proximity toSarychev Peak. The characteristics of the observed TEC variations allow us to attribute them to acoustic mode. The south-southwestward direction is preferred for CVIDs propagation. We concluded that the ionospheric response to a volcano eruption is mainly determined by a ratio between explosion strength and background ionization level. Some evidence of secondary (F2-layer) CVIDs’ source eccentric location were obtained.

In this work, using the classical technique for determining of the integral water vapor content in the Earth's troposphere (Integrated Water Vapor -IWV) we studied the IWV variations in the continentocean transition zone from GNSS observations at two points located in the continental and coastal parts of Primorsky Krai (Far East of Russia).Using the measurements at the nearest stations of the global GNSS-network IGS and radiosonde data the high accuracy and reliability of the estimates of atmospheric moisture content have been confirmed.At the measurement points, IWV variations for the period from 2015 to 2019 were studied, empirical approximation models of annual variations in IWV were constructed, the obtained estimates were compared with the data of the global model GFS and Reanalysis ERA5.The diurnal changes in the concentration of water vapor in the atmosphere, as well as its change during the passage of typhoons, accompanied by massive precipitation, were studied.It was found that more than 60 % of massive precipitation (>20 mm) falls within 3-9 hours at the IWV decline after a sharp increase in the integral moisture content recorded by GNSS methods.The high accuracy and frequency of IVW determination (up to 1 Hz), together with the high efficiency of obtaining information about the IWV change from GNSS observations, open up broad prospects for the application of GNSS meteorology in the forecasting practice of hydrometeorological services in the Russian Federation.

о ПРИМеНеНИИ МеТоДоВ ГЛоБаЛЬНЫХ НаВИГаЦИоННЫХ СПУТНИКоВЫХ СИСТеМ ДЛЯ ЦеЛеЙ РаННеГо ПРеДУПРеЖДеНИЯ о ЦУНаМИ В

Обсуждается проблема современной геодинамики Дальневосточного региона на основе мониторинга разномасштабных деформаций и сейсмичности в области сочленения Евразийской, Североамериканской, Тихоокеанской, Амурской и Охотской литосферных плит с применением современных методов космической геодезии и широкополосной сейсмологии. Дан краткий обзор этапов развития Единой сети геодинамических наблюдений ДВО РАН, основных результатов сейсмологических и GPS/ГЛОНАСС-наблюдений, полученных в рамках целевой комплексной программы научных исследований ДВО РАН «Современная геодинамика, активные геоструктуры и природные опасности Дальнего Востока России (2009–2013 гг.)» и проектов ДВО РАН 2014, 2018, 2019 гг., а также достигнутых позиций ДВО РАН в области геодинамики. The problem of the recent geodynamics of the Far East region is discussed based on monitoring of different-scale deformations and seismicity in the articulation of Eurasian, North American, Pacific, Amurian and Okhotsk lithospheric plates using modern methods of space geodesy and broadband seismology. We present a brief overview of the development stages of the Unified Network of Geodynamic Observations of the Far Eastern Branch of the Russian Academy of Sciences, the main results of seismological and GPS/GLONASS observations obtained within the framework of the Targeted Comprehensive Research Program of the Far Eastern Branch of the Russian Academy of Sciences for 2009–2013 «Recent geodynamics, active geological structures and natural hazards of the Far East of Russia», Projects of the Far Eastern Branch of the Russian Academy of Sciences (2014, 2018, 2019) and the achievements of FEB RAS in the field of geodynamics.

基于中国东北和俄罗斯远东东南部2012-2017年的GPS观测数据,利用包含年周期、半年周期、线性项和阶跃项的函数模型拟合GPS站坐标时间序列,得到ITRF2014下的速度场,并进一步转换到欧亚参考框架下得到相对欧亚板块的速度场.基于多尺度球面小波方法解算应变率场,并分析了其空间分布特征,同时研究了各GPS站对2011年日本东北Mw9.0大地震的震后松弛响应特征和背景形变场特征.结果 表明:①若不扣除日本东北大地震的松弛效应,相对欧亚板块中国东北主体上表现为东南方向运动,在依兰伊通断裂和嫩江断裂带之间,地壳表现为逆时针旋转,其他区域向东南方向运动,方向一致性较好,在敦化—密山断裂东侧速度大小明显增加.敦化—密山断裂和依兰—伊通断裂两侧拉张量分别为3.96±0.04mm/a和0.71±0.05 mm/a,两条断裂的剪切运动不明显.总体上,面应变率显示出NW SE向的拉张和NE SW向的挤压,面应变率显示出依兰—伊通断裂南端、嫩江断裂带北端和俄罗斯远东东南部呈挤压状态.在依兰—伊通断裂、敦化—密山断裂南侧以及俄罗斯远东东南部最大剪应变率相对较大.②各GPS测站对2011年日本东北Mw9.0大地震震后松弛的响应整体上表现为东南向运动,松弛形变量随震中距增加而减小.松弛效应的面应变率总体上表现为NW SE向的拉张和NE-SW向的挤压,面应变率显示出依兰—伊通、敦化—密山断裂南端、嫩江断裂带北端以及俄罗斯远东地区具有挤压特征,其他地区表现为拉张特征.中国与俄罗斯远东边界南端存在一个明显的最大剪应变率高值区.③扣除日本东北Mw9.0大地震引起的松弛变形后,总体上面应变率仍然表现为NW SE向的拉张和NE-SW向的挤压,面应变率最大值仍然位于依兰—伊通断裂和敦化—密山断裂南端、第二松花江断裂带以及俄罗斯远东和中国边界最南段.在依兰—伊通断裂、敦化—密山断裂南端,中国与俄罗斯远东边界南端的最大剪应变率高值区仍然存在,表明这些地区应变积累较快,并且一直在持续.

Mathematical modeling of various natural and man-made processes is based on the Earth's surface displacement data, to obtain which the Global Positioning Systems GPS and GLONASS are widely used.The "instant" vertical surface displacements occurred at short time intervals (from seconds to minutes) are the subject of special interest.Based on the experiment using the moving GNSS antenna, the paper investigates the problem of detection ability, accuracy and reliability of determination of small "instant" displacements ranging from 6.4 to 32 mm by the high-precision and most frequently used software packages BERNESE, GAMIT/GLOBK and GIPSY-OASIS and standard geodynamic GNSS data processing techniques.It is shown that all antenna shifts associated with the investigated displacement range could be confidently resolved from the results of daily static GPS/GLONASS data processing performed by the BERNESE and GAMIT/GLOBK packages.The GIPSY-OASIS software is not recommended for the determination of subcentimeter level displacements due to high dispersion and relatively low precision of the obtained coordinate solutions.Joint processing of GPS and GLONASS signals slightly improves the precision determination of displacements.The formal rootmean-square errors of the Earth's surface displacements calculated based on coordinate errors resulting from the GNSS data processing are not realistic in some cases and need further rescaling.

Using global positioning system (GPS) observations of northeastern China and the southeast of the Russian Far East over the period 2012–2017, we derived an ITRF2014-referenced velocity field by fitting GPS time series with a functional model incorporating yearly and semiannual signals, linear trends, and offsets. We subsequently rotated the velocity field into a Eurasia-fixed velocity field and analyzed its spatial characteristics. Taking an improved multiscale spherical wavelet algorithm, we computed strain rate tensors and analyzed their spatial distribution at multiple scales. The derived Eurasia-referenced velocity field shows that northeastern China generally moved southeastward. Extensional deformation was identified at the Yilan–Yitong Fault (YYF) and the Dunhua–Mishan Fault (DMF), with negligible strike–slip rates. The principal strain rates were characterized by NE–SW compression and NW–SE extension. The dilation rates show compressional deformation in the southern segment of the YYF, northern end of the Nenjiang Fault (NJF), and southeast of the Russian Far East. We also investigated the impact of the 2011 Tohoku Mw 9.0 earthquake on the crustal deformation of northeastern China, generated by its post-seismic viscoelastic relaxation. The velocities generated by the post-seismic viscoelastic relaxation of the giant earthquake are generally orientated southeast, with magnitudes inversely proportional with the epicentral distances. The principal strain rates caused by the viscoelastic relaxation were also characterized by NW–SE stretching and NE–SW compression. The dilation rates show that compressional deformation appeared in the southern segment of the DMF and the YYF and southeast of the Russian Far East. Significant maximum shear rates were identified around the southern borderland between northeastern China and the southeast of the Russian Far East. Finally, we compared the multiple strain rates and the seismicity of northeastern China after the 2011 Tohoku earthquake. Our finding shows that the ML ≥ 4.0 earthquakes were mostly concentrated around the zones of high areal strain rates and shear rates at scales of 4 and 5, in particular, at the DMF and YYF fault zones.