G. Fornari , F.C. de Meneses , R.R. Rosa , Esfhan A. Kherani , S. Domingos
{"title":"电离层参数波动测量的光谱指数估算方法","authors":"G. Fornari , F.C. de Meneses , R.R. Rosa , Esfhan A. Kherani , S. Domingos","doi":"10.1016/j.jastp.2024.106273","DOIUrl":null,"url":null,"abstract":"<div><p>Spectral analysis is a technique largely used to study scale size regime of ionospheric plasma irregularities based on <em>in situ</em> measurements, notwithstanding the visual representation of power spectral density (PSD) of a signal is often a source of ambiguity during fitting routines and identification of breakpoints. In this work, a method is proposed in order to mitigate the uncertainties inherent to this process. Here, the spectral behavior of time series fluctuations is alternatively investigated using Detrended Fluctuation Analysis (DFA). The DFA algorithm is a scaling analysis procedure widely applied to estimate the detection of long-range correlation without considering apparent short-range ones. Furthermore, the DFA technique is able to remove trends implicit to the signal and to be applied to non-stationary time series. Using <em>in situ</em> measurements of both ionospheric electron density and electric field fluctuations, it was able to analyze plasma bubbles with scales ranging from 1.66 km to 12.4 m. The results show that DFA and PSD routines provide quite similar spectra, but different spectral indices. On the other hand, the spectra revealed steep slopes wrapping the medium scales, a characteristic also detected in other studies. Besides that, the DFA is less noisy than Fourier spectra, which allows a more precise identification of spectral breakpoints.</p></div>","PeriodicalId":15096,"journal":{"name":"Journal of Atmospheric and Solar-Terrestrial Physics","volume":null,"pages":null},"PeriodicalIF":1.8000,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A methodology for estimating spectral indices to fluctuation measurements of ionospheric parameters\",\"authors\":\"G. Fornari , F.C. de Meneses , R.R. Rosa , Esfhan A. Kherani , S. Domingos\",\"doi\":\"10.1016/j.jastp.2024.106273\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Spectral analysis is a technique largely used to study scale size regime of ionospheric plasma irregularities based on <em>in situ</em> measurements, notwithstanding the visual representation of power spectral density (PSD) of a signal is often a source of ambiguity during fitting routines and identification of breakpoints. In this work, a method is proposed in order to mitigate the uncertainties inherent to this process. Here, the spectral behavior of time series fluctuations is alternatively investigated using Detrended Fluctuation Analysis (DFA). The DFA algorithm is a scaling analysis procedure widely applied to estimate the detection of long-range correlation without considering apparent short-range ones. Furthermore, the DFA technique is able to remove trends implicit to the signal and to be applied to non-stationary time series. Using <em>in situ</em> measurements of both ionospheric electron density and electric field fluctuations, it was able to analyze plasma bubbles with scales ranging from 1.66 km to 12.4 m. The results show that DFA and PSD routines provide quite similar spectra, but different spectral indices. On the other hand, the spectra revealed steep slopes wrapping the medium scales, a characteristic also detected in other studies. Besides that, the DFA is less noisy than Fourier spectra, which allows a more precise identification of spectral breakpoints.</p></div>\",\"PeriodicalId\":15096,\"journal\":{\"name\":\"Journal of Atmospheric and Solar-Terrestrial Physics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2024-06-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Atmospheric and Solar-Terrestrial Physics\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1364682624001019\",\"RegionNum\":4,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"GEOCHEMISTRY & GEOPHYSICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Atmospheric and Solar-Terrestrial Physics","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1364682624001019","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"GEOCHEMISTRY & GEOPHYSICS","Score":null,"Total":0}
A methodology for estimating spectral indices to fluctuation measurements of ionospheric parameters
Spectral analysis is a technique largely used to study scale size regime of ionospheric plasma irregularities based on in situ measurements, notwithstanding the visual representation of power spectral density (PSD) of a signal is often a source of ambiguity during fitting routines and identification of breakpoints. In this work, a method is proposed in order to mitigate the uncertainties inherent to this process. Here, the spectral behavior of time series fluctuations is alternatively investigated using Detrended Fluctuation Analysis (DFA). The DFA algorithm is a scaling analysis procedure widely applied to estimate the detection of long-range correlation without considering apparent short-range ones. Furthermore, the DFA technique is able to remove trends implicit to the signal and to be applied to non-stationary time series. Using in situ measurements of both ionospheric electron density and electric field fluctuations, it was able to analyze plasma bubbles with scales ranging from 1.66 km to 12.4 m. The results show that DFA and PSD routines provide quite similar spectra, but different spectral indices. On the other hand, the spectra revealed steep slopes wrapping the medium scales, a characteristic also detected in other studies. Besides that, the DFA is less noisy than Fourier spectra, which allows a more precise identification of spectral breakpoints.
期刊介绍:
The Journal of Atmospheric and Solar-Terrestrial Physics (JASTP) is an international journal concerned with the inter-disciplinary science of the Earth''s atmospheric and space environment, especially the highly varied and highly variable physical phenomena that occur in this natural laboratory and the processes that couple them.
The journal covers the physical processes operating in the troposphere, stratosphere, mesosphere, thermosphere, ionosphere, magnetosphere, the Sun, interplanetary medium, and heliosphere. Phenomena occurring in other "spheres", solar influences on climate, and supporting laboratory measurements are also considered. The journal deals especially with the coupling between the different regions.
Solar flares, coronal mass ejections, and other energetic events on the Sun create interesting and important perturbations in the near-Earth space environment. The physics of such "space weather" is central to the Journal of Atmospheric and Solar-Terrestrial Physics and the journal welcomes papers that lead in the direction of a predictive understanding of the coupled system. Regarding the upper atmosphere, the subjects of aeronomy, geomagnetism and geoelectricity, auroral phenomena, radio wave propagation, and plasma instabilities, are examples within the broad field of solar-terrestrial physics which emphasise the energy exchange between the solar wind, the magnetospheric and ionospheric plasmas, and the neutral gas. In the lower atmosphere, topics covered range from mesoscale to global scale dynamics, to atmospheric electricity, lightning and its effects, and to anthropogenic changes.