Atmospheric and Oceanic Optics最新文献_第10页

Aerosol Sounding of the Troposphere and Stratosphere by Lidar and Aerological Technologies 利用激光雷达和航空技术探测对流层和平流层的气溶胶

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Atmospheric and Oceanic Optics Pub Date : 2024-09-05 DOI: 10.1134/S1024856024700428

N. V. Balugin, V. N. Marichev, V. A. Yushkov, B. A. Fomin, D. A. Bochkovskiy

{"title":"Aerosol Sounding of the Troposphere and Stratosphere by Lidar and Aerological Technologies","authors":"N. V. Balugin, V. N. Marichev, V. A. Yushkov, B. A. Fomin, D. A. Bochkovskiy","doi":"10.1134/S1024856024700428","DOIUrl":"10.1134/S1024856024700428","url":null,"abstract":"Weather conditions are a natural limitation of the use of remote lidar sensing methods of the atmosphere, while the direct method based on an aerological aerosol backscattersonde has no such limitations, and these methods are close in physical principles of measurement. The creation of an all-weather stratospheric aerosol monitoring system can be based on the combination of direct and remote observation methods; however, their consistency should be experimentally confirmed. The results of a lidar-aerological experiment on atmospheric sounding at altitudes of 7–50 and 0–30 km using a ground-based lidar and an aerosol backscattersonde (AZOR), respectively, are presented. The experiment was conducted in Tomsk on March 15–16, 2023. Vertical profiles of backscattering coefficients of radiation from sources with close wavelengths were measured: ground-based 532 nm (in lidar) and balloon-based 528 nm (in AZOR). The obtained consistency of lidar and balloon measurements indicates the possibility of using AZOR as a mobile tool to complement lidar measurements in the case of clouds. The combination of direct and remote sensing of the atmosphere with the aim of improving the quality of measurements in studies of the aerosol composition of the atmosphere is discussed. The possibility of extending two wave (355 and 532 nm) lidar observations by direct measurements of AZOR with an additional set of wavelengths (470, 528, 850, and 940 nm) is shown.","PeriodicalId":46751,"journal":{"name":"Atmospheric and Oceanic Optics","volume":"37 3","pages":"338 - 342"},"PeriodicalIF":0.9,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142180678","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

Dynamics of Microphysical Parameters of Pyrolysis Smoke Based on the Results of Inversion of Aerosol Scattering and Extinction Coefficients in the Big Aerosol Chamber of IAO SB RAS 基于 IAO SB RAS 大气溶胶室中气溶胶散射和消光系数反演结果的热解烟雾微物理参数动态变化

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Atmospheric and Oceanic Optics Pub Date : 2024-09-05 DOI: 10.1134/S1024856024700416

V. V. Veretennikov, V. N. Uzhegov, V. P. Shmargunov

{"title":"Dynamics of Microphysical Parameters of Pyrolysis Smoke Based on the Results of Inversion of Aerosol Scattering and Extinction Coefficients in the Big Aerosol Chamber of IAO SB RAS","authors":"V. V. Veretennikov, V. N. Uzhegov, V. P. Shmargunov","doi":"10.1134/S1024856024700416","DOIUrl":"10.1134/S1024856024700416","url":null,"abstract":"The temporal variability of microphysical parameters of pyrolysis smoke, retrieved by inverting the characteristics of aerosol scattering and extinction, has been studied. The polarization scattering phase functions and spectral extinction coefficients were measured for 65 hours in smoke aerosols produced from thermal decomposition of pine wood during low-temperature pyrolysis in the Big Aerosol Chamber (BAC) of Institute of Atmospheric Optics, Siberian Branch, Russian Academy of Sciences. The microstructure parameters (volume concentration and mean radius of particles with division into fine and coarse fractions) and the complex refractive index of pyrolysis smoke are retrieved following the developed algorithm for inverting optical measurements. The real part of the refractive index is found to be in the vicinity of n = 1.55, and the imaginary part is in the range 0.007 < κ < 0.009; the mean radius of fine particles varies in the narrow range 0.137–0.146 μm. During smoke aging, the particle ensemble-mean radius monotonically increased from 0.19 to 0.6 μm mainly due to a relative increase in the content of coarse aerosol. Results of this work are important for estimation of the radiative forcing of aerosol and improvement of climate models and algorithms of remote optical sounding.","PeriodicalId":46751,"journal":{"name":"Atmospheric and Oceanic Optics","volume":"37 3","pages":"327 - 337"},"PeriodicalIF":0.9,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142180680","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}

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LED Fourier Spectroscopy of H216O in the 14 800–15 500 cm–1 Spectral Region 14 800-15 500 cm-1 光谱区 H216O 的 LED 傅立叶光谱分析

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Atmospheric and Oceanic Optics Pub Date : 2024-09-05 DOI: 10.1134/S1024856024700556

I. A. Vasilenko, L. N. Sinitza, V. I. Serdukov

引用次数: 0

Estimation of Signal-to-Noise Ratio from Pulsed Coherent Doppler Lidar Measurements under Nonstationary Noise 非稳态噪声下脉冲相干多普勒激光雷达测量的信噪比估计

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Atmospheric and Oceanic Optics Pub Date : 2024-09-05 DOI: 10.1134/S1024856024700581

I. N. Smalikho, V. A. Banakh, A. M. Sherstobitov

引用次数: 0

Optical and Geometrical Characteristics of High-Level Clouds from the 2009–2023 Data on Laser Polarization Sensing in Tomsk 从 2009-2023 年托木斯克激光偏振传感数据看高层云的光学和几何特征

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Atmospheric and Oceanic Optics Pub Date : 2024-09-05 DOI: 10.1134/S1024856024700441

I. D. Bryukhanov, O. I. Kuchinskaia, E. V. Ni, M. S. Penzin, I. V. Zhivotenyuk, A. A. Doroshkevich, N. S. Kirillov, A. P. Stykon, V. V. Bryukhanova, I. V. Samokhvalov

{"title":"Optical and Geometrical Characteristics of High-Level Clouds from the 2009–2023 Data on Laser Polarization Sensing in Tomsk","authors":"I. D. Bryukhanov, O. I. Kuchinskaia, E. V. Ni, M. S. Penzin, I. V. Zhivotenyuk, A. A. Doroshkevich, N. S. Kirillov, A. P. Stykon, V. V. Bryukhanova, I. V. Samokhvalov","doi":"10.1134/S1024856024700441","DOIUrl":"10.1134/S1024856024700441","url":null,"abstract":"To improve the accuracy of weather and climate forecasts, a deeper understanding of atmospheric processes and phenomena, which are determined, among other things, by high-level clouds (HLCs), is required. The experimental results on polarization laser sensing of high-level clouds are presented. The data of systematic (from December 2009 to present) lidar measurements performed with the high-altitude matrix polarization lidar developed at the Tomsk State University are combined. Optical (backscattering phase matrix, optical depth, and scattering ratio) and geometric (lower and upper boundary altitudes and vertical thickness) characteristics of clouds are determined from the lidar measurements. The dataset is supplemented with corresponding vertical profiles of meteorological quantities (temperature, relative and specific humidity, and wind direction and speed) obtained from radiosonde observations and ERA5 reanalysis. The frequency of lidar detection of HLCs and those of them which are characterized by the preferential horizontal orientation of nonspherical ice particles is estimated. The results were combined into a database and used to create a software product based on neural networks to retrieve the dependences between the atmospheric meteorological parameters and HLC optical characteristics. The database can be used for various training options in solving problems of atmospheric optics including independent ones.","PeriodicalId":46751,"journal":{"name":"Atmospheric and Oceanic Optics","volume":"37 3","pages":"343 - 351"},"PeriodicalIF":0.9,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142180679","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

Cloud Cover Detection Using a Neural Network Based on MSU-GS Instrument Data of Arktika-M No. 1 Satellite 基于 Arktika-M 1 号卫星 MSU-GS 仪器数据的神经网络云层探测

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Atmospheric and Oceanic Optics Pub Date : 2024-09-05 DOI: 10.1134/S102485602470043X

V. D. Bloshchinskiy, L. S. Kramareva, Yu. A. Shamilova

引用次数: 0

Statistical Estimates of the Vapor Content and Atmospheric Optical Thickness from Reanalysis and Radiosounding Data as Applied to Millimeter Telescopes 应用于毫米波望远镜的再分析和辐射探测数据对水汽含量和大气光学厚度的统计估算

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Atmospheric and Oceanic Optics Pub Date : 2024-09-05 DOI: 10.1134/S1024856024700532

A. Yu. Shikhovtsev, P. G. Kovadlo

引用次数: 0

Trajectory Analysis of Variations in Ozone-Active Components inside the Stratospheric Arctic Vortex Using M2-SCREAM Reanalysis Data 利用 M2-SCREAM 再分析数据对北极平流层涡旋内部臭氧活性成分变化的轨迹分析

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Atmospheric and Oceanic Optics Pub Date : 2024-09-05 DOI: 10.1134/S1024856024700490

A. N. Lukyanov, V. A. Yushkov, A. S. Vyazankin

引用次数: 0

Cloud Recognition in Hyperspectral Satellite Images Using an Explainable Machine Learning Model 利用可解释的机器学习模型识别高光谱卫星图像中的云层

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Atmospheric and Oceanic Optics Pub Date : 2024-09-05 DOI: 10.1134/S1024856024700507

A. S. Minkin, O. V. Nikolaeva

{"title":"Cloud Recognition in Hyperspectral Satellite Images Using an Explainable Machine Learning Model","authors":"A. S. Minkin, O. V. Nikolaeva","doi":"10.1134/S1024856024700507","DOIUrl":"10.1134/S1024856024700507","url":null,"abstract":"Problem of developing algorithm based upon neutral networks and machine learning to find clouds on hyperspectral images are under consideration. It is required that the network is not a “black box,” but allows an analysis of the reasons for decision making and classification results. Presented hybrid model includes decision tree trained to overcast recognition (model 1) on pre-selected features of an image in combination with convolutional neural network (model 2). Model 2 uses the result of model 1 and brightness in a selected band of an image. Model 1 finds cloud cores, and model 2 finds cloud edges. Results of testing the hybrid model on data of HYPERION sensor are presented. Data obtained over three surface types (ocean, plant, and urban region) are considered. Overall accuracy, as well as commission and omission errors are assessed. It is shown that the hybrid model can find 85% cloud pixels, only if the neural network is trained on an image where the contrast attains a maximum in the same spectral band. The results of this work can be applied to solve the general problem of analyzing and processing multispectral satellite images and further in environmental science and monitoring of changes in vegetation, ocean and glaciers.","PeriodicalId":46751,"journal":{"name":"Atmospheric and Oceanic Optics","volume":"37 3","pages":"400 - 408"},"PeriodicalIF":0.9,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142180776","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}

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The Superresonance: The Discovery That Was Not Done More Than One Hundred Years Ago 超共振一百多年前未完成的发现

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Atmospheric and Oceanic Optics Pub Date : 2024-09-05 DOI: 10.1134/S1024856024700544

I. V. Minin, O. V. Minin

引用次数: 0