Atmospheric and Oceanic Optics最新文献_第4页

Sixteen-day Atmospheric Planetary Wave in Variations in the Earth’s Magnetic Field According to Data from European Observatories 根据欧洲天文台的数据，地球磁场变化中的16天大气行星波

IF 0.7

Atmospheric and Oceanic Optics Pub Date : 2026-07-08 DOI: 10.1134/S1024856026700193

S. A. Riabova

{"title":"Sixteen-day Atmospheric Planetary Wave in Variations in the Earth’s Magnetic Field According to Data from European Observatories","authors":"S. A. Riabova","doi":"10.1134/S1024856026700193","DOIUrl":"10.1134/S1024856026700193","url":null,"abstract":"When studying the dynamics of the Earth’s atmosphere, it is of interest to examine the frequencies of geomagnetic field variations in the range of periods of a 16-day atmospheric planetary wave (from 14.5 to 18 days). This work analyzes the spectra of Earth’s magnetic field variations recorded between 2000 and 2023 at three European midlatitude magnetic observatories: the Belsk Observatory (Eastern Europe), the Furstenfeldbruck Observatory (Central Europe), and the Dourbes Observatory (Western Europe). Using the Lomb–Scargle periodogram method, harmonics associated with the modulation effects of long-period variations and tidal effects were identified in the spectrum in the range from 14.5 to 18 days. The analysis shows that the frequencies of geomagnetic variations are independent of the longitude of observations (the observatories are located at approximately the same latitude). Spectral harmonics caused by the modulation with a semiannual variation in the second harmonic of the sunspot cycle and a declination tidal were identified. For a tidal wave with a period of about two weeks, harmonics caused by the modulation effects of the 11-year solar cycle (Schwabe cycle), the fourth harmonic of the 22-year solar cycle, and annual and semiannual variations were identified. Harmonics with periods corresponding to the above modulation effects on a 16-day planetary wave are distinguished in the spectra. The spectral analysis results confirm the influence of processes observed in the neutral lower atmosphere on the dynamics of the upper atmosphere. The results can be used to develop atmospheric dynamics models.","PeriodicalId":46751,"journal":{"name":"Atmospheric and Oceanic Optics","volume":"39 3","pages":"391 - 396"},"PeriodicalIF":0.7,"publicationDate":"2026-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148394880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

WRF Model Estimation of Precipitable Water Vapor over the Sayan Solar Observatory and Khulugaysha Peak 萨彦太阳观测台和呼鲁盖沙峰可降水量的WRF模式估算

IF 0.7

Atmospheric and Oceanic Optics Pub Date : 2026-07-08 DOI: 10.1134/S1024856026700144

M. Yu. Shikhovtsev, A. Yu. Shikhovtsev, A. A. Lezhenin, V. S. Gradov, V. B. Khaikin, K. E. Kirichenko, P. G. Kovadlo

引用次数: 0

Enhancement of the Efficiency of Generating Radiation at Shifted Wavelengths by Transforming a Single-mode Femtosecond Laser Beam into Multimode One 通过将单模飞秒激光束转换成多模飞秒激光束来提高在移位波长产生辐射的效率

IF 0.7

Atmospheric and Oceanic Optics Pub Date : 2026-07-08 DOI: 10.1134/S102485602670003X

D. V. Apeksimov, P. A. Babushkin, Yu. E. Geints, A. M. Kabanov, V. K. Oshlakov, E. E. Khoroshaeva

{"title":"Enhancement of the Efficiency of Generating Radiation at Shifted Wavelengths by Transforming a Single-mode Femtosecond Laser Beam into Multimode One","authors":"D. V. Apeksimov, P. A. Babushkin, Yu. E. Geints, A. M. Kabanov, V. K. Oshlakov, E. E. Khoroshaeva","doi":"10.1134/S102485602670003X","DOIUrl":"10.1134/S102485602670003X","url":null,"abstract":"Remote laser excitation of fluorescence in spectral lines and bands useful for environmental diagnostics and generation of non-optical electromagnetic radiation, such as terahertz, are topical applied problems. Enhancement of the efficiency of laser energy conversion is an important issue for the above problems. Based on complex experimental studies of filamentation of high-power (up to 150 GW) femtosecond Ti:Sapphire laser beam propagating in air along a 100-m path, we have shown that forced chaotic modulation (power stochastization) of a radiation beam, which initiates inhomogeneities in the transverse energy structure of laser radiation, splits an original beam into many high-intensity subbeams (channels) stable over long distances. Creation of a localized air layer with a randomly inhomogeneous refractive index (artificial turbulent layer) at the beginning of a radiation propagation path increases the number of these channels and makes their characteristic intensity high enough for two-photon absorption in a volume of colored water aerosol microparticles created at the end of the path, which almost doubles lidar-recorded fluorescence signal from the particles. In addition, this artificial turbulent layer multiply enhances the efficiency of low-frequency (THz) electromagnetic radiation generation from laser filamentation domain. The results can be used for remote diagnostics of atmospheric aerosol and the generation of THz electromagnetic radiation.","PeriodicalId":46751,"journal":{"name":"Atmospheric and Oceanic Optics","volume":"39 3","pages":"256 - 261"},"PeriodicalIF":0.7,"publicationDate":"2026-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148394950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Approximation of Planetary Waves from Combined Satellite and Ground-Based Observations Using an Adaptive Metaheuristic Algorithm 利用自适应元启发式算法从卫星和地面观测组合中逼近行星波

IF 0.7

Atmospheric and Oceanic Optics Pub Date : 2026-07-08 DOI: 10.1134/S1024856026700181

V. I. Sivtseva, A. V. Savvin, V. V. Grigoriev, I. I. Koltovskoi

{"title":"Approximation of Planetary Waves from Combined Satellite and Ground-Based Observations Using an Adaptive Metaheuristic Algorithm","authors":"V. I. Sivtseva, A. V. Savvin, V. V. Grigoriev, I. I. Koltovskoi","doi":"10.1134/S1024856026700181","DOIUrl":"10.1134/S1024856026700181","url":null,"abstract":"The study of large-scale atmospheric processes, such as planetary waves is essential for understanding the coupling between the lower and upper atmosphere. However, accurate simulation of these waves is complicated by heterogeneity and sparsity of observational data (both satellite and ground-based), as well as high dimensionality of the parameter space when describing wave structures. We suggest an approach to approximation of planetary waves with the use of the Two Strategy adaptive Artificial Bee Colony (TSaABC) algorithm based on heterogeneous satellite and ground-based data. The TSaABC algorithm enables optimizing the parameters of a nonlinear spatiotemporal model of air temperature measured with MLS instrument onboard Aura satellite and at three ground-based stations, which monitor hydroxyl OH(3, 1) emission band. The temperature data are approximated by the sum of planetary wave harmonics, selected from a dictionary of harmonics, with unknown parameters, including amplitudes and wavenumbers. By solving the inverse problem of minimizing the data divergence and the L1 norm of harmonic amplitudes, the method achieves approximation accuracy and sparsity in a large dictionary of harmonics. To minimize the L1 norm, a hard thresholding strategy was developed within the TSaABC algorithm, which enables reducing the dimension of the solution search, thus increasing computational efficiency. The results show the potential of the algorithm for assimilating heterogeneous data and improving models of atmospheric processes.","PeriodicalId":46751,"journal":{"name":"Atmospheric and Oceanic Optics","volume":"39 3","pages":"385 - 390"},"PeriodicalIF":0.7,"publicationDate":"2026-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148394967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Correlation of the Outer Scales of Temperature and Wind Turbulence with Temperature and Wind Speed Stratification in the Surface Air Layer 温度和风湍流的外尺度与地面空气层温度和风速分层的关系

IF 0.7

Atmospheric and Oceanic Optics Pub Date : 2026-07-08 DOI: 10.1134/S102485602670020X

V. A. Gladkikh, A. P. Kamardin, I. V. Nevzorova, S. L. Odintsov, V. A. Fedorov

引用次数: 0

Estimation of the Importance of Spatial and Spectral Features in Cloud Segmentation in Satellite Images 空间和光谱特征在卫星图像云分割中的重要性估计

IF 0.7

Atmospheric and Oceanic Optics Pub Date : 2026-07-08 DOI: 10.1134/S1024856026700077

A. S. Minkin

{"title":"Estimation of the Importance of Spatial and Spectral Features in Cloud Segmentation in Satellite Images","authors":"A. S. Minkin","doi":"10.1134/S1024856026700077","DOIUrl":"10.1134/S1024856026700077","url":null,"abstract":"The work solves the problem of cloud segmentation in hyperspectral satellite imagery with the use of an interpretable neural network classifier for partial cloudiness. For effective solution, spectral bands and derived features are preliminary selected using decision trees, trained with labeled satellite HYPERION images, and then used for building a convolutional neural network based on modified Unet architecture. Modifications to the original Unet architecture enable simplifying the network structure, avoiding overfitting, assessing the importance of spatial and spectral features, analyzing classification results, and explaining decision-making processes. Feature selection and evaluation of their importance are critical stages in developing adequate machine learning and deep learning models combined with the analysis of their generalization ability. The suggested feature selection method is based on iterative training of decision trees to identify significant features in terms of classification accuracy. The operation of the convolutional neural network is interpreted and the importance of spatial and spectral features is assessed based on the computation of Shapley vectors. The importance of input features, caused by their distribution across spectral bands and the relative positions of pixels in an image, for the detection of solid and thin clouds in hyperspectral satellite images is analyzed. The neural network is tested with HYPERION images made over three surface types (ocean, vegetation, and urbanized territory); its accuracy, commission and omission errors are estimated. The model enables semantic segmentation of images with thin clouds with accuracy over 95% in selected spectral bands and features. The presented neural network model is designed for working with small datasets, enables applying augmentation, and can be used to assess the importance of selected spectral bands and spatial features.","PeriodicalId":46751,"journal":{"name":"Atmospheric and Oceanic Optics","volume":"39 3","pages":"286 - 295"},"PeriodicalIF":0.7,"publicationDate":"2026-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148394980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Temporal Variability of Nonlinear Wave Processes during Different Sudden Stratospheric Warming Types 不同平流层突然变暖类型中非线性波过程的时间变率

IF 0.7

Atmospheric and Oceanic Optics Pub Date : 2026-07-08 DOI: 10.1134/S1024856026700107

K. A. Didenko, A. V. Koval, T. S. Ermakova

{"title":"Temporal Variability of Nonlinear Wave Processes during Different Sudden Stratospheric Warming Types","authors":"K. A. Didenko, A. V. Koval, T. S. Ermakova","doi":"10.1134/S1024856026700107","DOIUrl":"10.1134/S1024856026700107","url":null,"abstract":"In winter, planetary-scale atmospheric waves play the main role in the formation of atmosphere conditions, and a polar vortex forms in the stratosphere. Sudden stratospheric warming (SSW) is a striking example of the interannual variability of the stratospheric polar vortex caused by stationary planetary waves. SSW significantly affects the entire middle atmosphere, ionosphere, weather conditions in the troposphere, and occurrence of extreme weather events. Based on MERRA-2 reanalysis data, this work analyzes the internal dynamics of a major SSW accompanied by stratospheric polar vortex (SPV) displacement and splitting. Nonlinear interactions of planetary waves with each other and with the mean flow are explicitly calculated with the aim of identifying similar trends in origination of different SSW types. It is shown that the occurrence of a SSW with SPV splitting is not always be accompanied by variations in the activity of stationary planetary wave with zonal wavenumber 2 (SPW2), but is determined by the maximal interactions of SPW2 with the mean flow. For SSW with SPV displacement, wave–wave interactions during the generation of secondary stationary planetary wave with zonal wavenumber 1 (SPW1) are shown to be maximal 1–2 weeks before a SSW, and during the generation of secondary SPW2, 5–10 days before a SSW with SPV displacement. The results are important for identifying SSW predictors.","PeriodicalId":46751,"journal":{"name":"Atmospheric and Oceanic Optics","volume":"39 3","pages":"314 - 322"},"PeriodicalIF":0.7,"publicationDate":"2026-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1134/S1024856026700107.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148394941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Automated Method of Estimating the State of the Ionosphere Based on Ionosonde Data in the Aurora Interactive System 基于极光交互系统中电离层数据的电离层状态自动估计方法

IF 0.7

Atmospheric and Oceanic Optics Pub Date : 2026-07-08 DOI: 10.1134/S1024856026700168

O. V. Mandrikova, Yu. A. Polozov

{"title":"An Automated Method of Estimating the State of the Ionosphere Based on Ionosonde Data in the Aurora Interactive System","authors":"O. V. Mandrikova, Yu. A. Polozov","doi":"10.1134/S1024856026700168","DOIUrl":"10.1134/S1024856026700168","url":null,"abstract":"Monitoring and analysis of the dynamics of ionospheric parameters allow one to detect disturbances that negatively impact technical systems. Problems of the timely detection of ionospheric disturbances are associated with a high degree of uncertainty in our prior knowledge about the dynamics of ionospheric processes during disturbed periods and the influence of interference and uneven observation network in certain areas. These issues necessitate the development of data recording and analysis methods that guarantee high accuracy and efficiency. The paper presents a new automated method for estimating the state of the ionosphere using ground-based vertical radiosonde data. This method is based on combining elements of statistical decision theory and threshold estimation with the wavelet transform. Numerical solutions constructed using this method are used in the Aurora interactive system (https://lsaoperanalysis.ikir.ru/lsaoperanalysis.html), which was developed at the Institute of Cosmophysical Research and Radio Wave Propagation, Far East Branch, Russian Academy of Sciences. The results of the implemented algorithms provide data on the state of the ionosphere over Kamchatka (calm or perturbed) and the parameters of ionospheric inhomogeneities in the case of a perturbed state. The algorithms are adaptive and do not require preliminary training. Data from the Paratunka (Russia, Kamchatka Krai) and Wakkanai (Japan) stations were used to evaluate the method. The behavior of the ionosphere during periods of strong geomagnetic storms in 2023–2024 was studied. The study confirmed the method efficiency in analyzing ionospheric data and detecting inhomogeneities. Prior to the analyzed events, signs of an anomalous increase in electron density in the ionosphere were identified, which is of significant practical importance. The suggested method can be used in ionospheric data analysis techniques for monitoring and forecasting space weather conditions with the aim of timely detecting ionospheric disturbances.","PeriodicalId":46751,"journal":{"name":"Atmospheric and Oceanic Optics","volume":"39 3","pages":"371 - 377"},"PeriodicalIF":0.7,"publicationDate":"2026-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148394942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Thermal Radiation Transfer Through the Rain Atmosphere in Successive Scattering Orders 在连续散射阶中通过雨大气的热辐射传输

IF 0.7

Atmospheric and Oceanic Optics Pub Date : 2026-07-08 DOI: 10.1134/S1024856026700120

Y. V. Kopcov, Y. A. Ilyushin, B. G. Kutuza

引用次数: 0

Anomaly Recognition in Neutron Monitor Observations Using Wavelet Decompositions and Rules of Statistical Decision Theory 基于小波分解和统计决策规则的中子监测观测异常识别

IF 0.7

Atmospheric and Oceanic Optics Pub Date : 2026-07-08 DOI: 10.1134/S1024856026700156

O. V. Mandrikova, B. S. Mandrikova

{"title":"Anomaly Recognition in Neutron Monitor Observations Using Wavelet Decompositions and Rules of Statistical Decision Theory","authors":"O. V. Mandrikova, B. S. Mandrikova","doi":"10.1134/S1024856026700156","DOIUrl":"10.1134/S1024856026700156","url":null,"abstract":"Disturbances in the near-Earth environment are accompanied by disruptions in ground-based and satellite technological systems, including catastrophic failures. Therefore, the problem of developing methods for real-time analysis and monitoring of the natural environment with an acceptable accuracy becomes particularly pressing. This paper presents a new automated method for detecting and estimating anomalies in neutron monitor (NM) observations. This method is based on the synthesis of wavelet decompositions with the rules of statistical decision theory; it enables the detection of anomalies in NM observations and estimation of their intensity. Discrete wavelet decompositions with adaptive threshold functions are used to detect anomalies. Parameters of the threshold functions are automatically estimated (as the data enter the processing system) using rules of statistical decision theory. Applying these rules yields a solution with an error not exceeding an a priori specified value. The intensity of anomalies in NM observations is then calculated by summing the amplitudes of wavelet coefficients exceeding the estimated thresholds. The paper studies periods of strong and extreme geomagnetic storms in 2024–2025. Correlations between values of the Dst index and the intensity of anomalies in NM observations are analyzed. The results show a significant increase in the correlation during geomagnetic storms. The Dst index reached its maximums relative to the intensity maximums with a delay of several hours, which demonstrates the importance of neutron monitor observations and their consideration when solving space weather problems. The results of the work can be used in space weather forecasting for the early detection of sporadic variations in the cosmic ray flux.","PeriodicalId":46751,"journal":{"name":"Atmospheric and Oceanic Optics","volume":"39 3","pages":"362 - 370"},"PeriodicalIF":0.7,"publicationDate":"2026-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148394973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0