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This study analyzes sea level changes (SLCs) in China seas and their adjacent ocean (CSO) using data from the TOPEX/Poseidon and Jason-1/2/3 satellite altimetry missions from 1993 to 2022. A 30-year time series of sea level anomalies (SLAs) is established, with trends, spatial distribution, and periodicities analyzed through least squares linear fitting, Kriging interpolation, and wavelet analysis. The average yearly sea level rise in the CSO is 3.87 mm, with specific rates of 4.15 mm/yr in the Bohai Sea, 3.96 mm/yr in the Yellow Sea, 3.54 mm/yr in the East China Sea, and 4.09 mm/yr in the South China Sea. This study examines the spatiotemporal variations in SLAs and identifies an annual primary cycle, along with a new periodicity of 11 years. Utilizing 30 years of satellite observation data, particularly the newer Jason-3 satellite data, this reanalysis reveals new findings related to cycles. Overall, the research updates previous studies and provides valuable insights for further investigations into China's marine environment. [ABSTRACT FROM AUTHOR]

We study the periodogram operator of a sequence of functional data. Using recent advances in Gaussian approximation theory, we derive the asymptotic distribution of the maximum norm over all fundamental frequencies. We consider the case where the noise variables are independent and then generalize our results to functional linear processes. Our theory can be used for detecting periodic signals in functional time series when the length of the period is unknown. We demonstrate the proposed methodology in a simulation study as well as on real data. for this article are available online. [ABSTRACT FROM AUTHOR]

Neutron monitor counting rates show periodicities in the ≈ 1.6 – 2.2-year range. These periodicities have been associated with a solar origin affecting the cosmic ray propagation conditions through the heliosphere. Our hypothesis is that the periodicities in the ≈ 1.6 – 2.2-years range correspond to a single periodicity that changes its duration over time. López-Comazzi and Blanco (Astrophys. J.927(2), 155, 2022) found that the duration of the ≈ 1.6 – 2.2-year period (τ ) is linearly related to the average sunspot number (S S N a ) in each solar cycle. The relationship shows that shorter ≈ 1.6 – 2.2-year periods occur during stronger cycles when S S N a is higher. Therefore, the duration of this period varies from one solar cycle to another. This study focuses on this relation. For obtaining this relation, the values of the duration of the ≈ 1.6 – 2.2-year period in global neutron monitor counting rates (a virtual station determined by averaging of the different neutron monitor counting rates along the world) along the Solar Cycles 20 – 24 have been used. We extend the sample by adding the duration of the ≈ 1.6 – 2.2-year period in Huancayo neutron monitor counting rates along Solar Cycle 19 to this linear relationship. Once the linear relationship is extended, τ for the current Solar Cycle 25 is computed giving ≈ 2.24 years. Drawing on this more accurate relationship given by S S N a = (− 120 ± 10) τ + (320 ± 20) , we computed τ for the cycles previous to the existence of neutron monitors (Solar Cycles 7 – 18). These ≈ 1.6 – 2.2-year periodicities in neutron monitor counting rates could be produce by variations in the solar magnetic field due to an internal mechanism of the solar dynamo called Rossby waves. Concretely, the harmonic of fast Rossby waves with m = 1 and n = 8 fit with the detected ≈ 1.6 – 2.2-year periodicity. In addition, the variation of the solar magnetic-field strength from weaker to stronger solar cycles could explain the different periods detected in each cycle. Based on the detected periodicities using the dispersion relation for fast Rossby waves, a solar tachocline magnetic-field strength of ≈ 7 – 25 kG has been estimated. [ABSTRACT FROM AUTHOR]

Generated synthetic time series aim to be both realistic by mirroring the characteristics of real-world time series and useful by including characteristics that are useful for subsequent applications, such as forecasting and missing value imputation. To generate such realistic and useful time series, we require generation methods capable of controlling the non-stationarity and periodicities of the generated time series. However, existing approaches do not consider such explicit control. Therefore, in the present paper, we present a novel approach to control non-stationarity and periodicities with calendar and statistical information when generating time series. We first define the requirements for methods to generate time series with non-stationarity and periodicities, which we show are not fulfilled by existing generation methods. Second, we formally describe the novel approach for controlling non-stationarity and periodicities in generated time series. Thirdly, we introduce an exemplary implementation of this approach using a conditional Invertible Neural Network (cINN). We evaluate this cINN empirically in experiments with real-world data sets and compare it to state-of-the-art time series generation methods. Our experiments show that the evaluated cINN can generate time series with controlled periodicities and non-stationarity, and it also generally outperforms the selected benchmarks. [ABSTRACT FROM AUTHOR]

Ability to quantify variations in magnetic field topology and density within Jupiter's magnetosphere is an important step in understanding the overall structure and dynamics. The Juno spacecraft has provided a rich data set in the dawnside magnetosphere. The recent Grid Agnostic MHD for Extended Research Applications (GAMERA) global simulation study by Zhang et al. (2021, https://doi.org/10.1126/sciadv.abd1204) showed a highly structured plasmadisc with closed magnetic field lines mapped between the outer dawn‐tail flank and the high‐latitude polar region. To test these model predictions, we examined Juno's magnetic field data and electron/energetic particle data to categorize portions of orbits 1–15 into one of three regions based on plasma confinement: the flux pileup region, the intermediate region, and the plasmadisc region. For each region we examined periodicities from magnetic field fluctuations and particle density fluctuations on the 1–10 hr time scale. Periodicities on this time scale could relate to internal (e.g., plasmadisc structure) or external processes (e.g., Kelvin‐Helmholtz vortices). Similar analysis was performed on the GAMERA simulation with the data split into two regions, an outer (150 > R > 60) region and an inner (R < 60) region. Finally, using published density moments from Huscher et al. (2021, https://doi.org/10.1029/2021JA029446), we compared the relative density variations of the Juno moments and the GAMERA simulation to further understand the overall structure and dynamics of the plasmadisc. The agreement between data and simulation supports the existence of such a highly structured plasmadisc. Plain Language Summary: A very complex and poorly understood problem of Jupiter is the structure and dynamics of the planet's space environment (i.e., "magnetosphere"), due to its sheer size and unique internal ionized gas (i.e., plasma) sourced from the moon, Io. Thanks to the Juno mission, we are able to analyze data from previously unexplored regions around the planet. It has been demonstrated using Voyager data that ionized gas from Io formed a plasma disc‐like structure around the planet in the equatorial plane, becoming less confined in the outer regions. Computer simulations showed a similar structure. In order to investigate this structure, we utilized magnetic field data and particle data from the Juno spacecraft. This data was analyzed to understand the occurrence of regular fluctuations in the magnetic field and gas density, and to understand spatial domains where regular fluctuations occur. Similar analysis was done on magnetic field and density data from simulations for comparison. We found relations between the Juno data and simulation data that suggest a much more variable and structured plasma disc as well as a region in the dawn/tail flank that is magnetically connected to the high latitude polar region. Key Points: Three‐regions with different plasma confinement characteristics have been identified in Jupiter's dawn to postmidnight magnetosphereComparison of Juno data and Grid Agnostic MHD for Extended Research Applications simulations suggest a very structured plasmadiscPeriodicities in 1–4 hr range could be related to plasmadisc structure [ABSTRACT FROM AUTHOR]

Count time series are widely encountered in practice. As with continuous valued data, many count series have seasonal properties. This article uses a recent advance in stationary count time series to develop a general seasonal count time series modeling paradigm. The model constructed here permits any marginal distribution for the series and the most flexible autocorrelations possible, including those with negative dependence. Likelihood methods of inference are explored. The article first develops the modeling methods, which entail a discrete transformation of a Gaussian process having seasonal dynamics. Properties of this model class are then established and particle filtering likelihood methods of parameter estimation are developed. A simulation study demonstrating the efficacy of the methods is presented and an application to the number of rainy days in successive weeks in Seattle, Washington is given. [ABSTRACT FROM AUTHOR]

Volcanoes have been found to display periodicities or cyclic trends in a wide range of phenomena. These include the eruptive activity itself, but also in the time series of geophysical and geochemical monitoring data such as volcanic degassing. Here, we test the existence of periodicities of volcanic degassing at 32 volcanoes using the time series of sulfur dioxide (SO2) emission rates from data of the Network of Volcanic and Atmospheric Change (NOVAC). We use the Lomb‐Scargle periodogram to analyze the SO2 data which allows efficient computation of a Fourier‐like power spectrum from unevenly sampled data. We were able to calculate False‐Alarm Probabilities in 28 of the 32 volcanoes, and we identified significant periodicities in the SO2 emission rates in 17 of the 28 volcanoes. However, we find that most of these periodicities are also present in the plume speeds used to determine SO2 emission rates. Periodicities at about 30–70, ∼120, and ∼180 days were identified at volcanoes located between 16°N and 16°S and are related to intraseasonality and interseasonality in global trade winds and not volcanic in origin. Periodicities between 30 and 70 days in both plume speed and SO2 emission rates are associated to the Madden‐Julian Oscillation that is responsible for intraseasonal variability in the tropical atmosphere. Our study highlights the importance of using local wind data for deriving realistic SO2 emissions and the identification of short‐term periodicity in volcanic behavior. Plain Language Summary: Volcanoes may show cycling patterns in their eruption patterns but also in the geophysical and geochemical data used to monitor them. When these patterns occur at fixed‐time intervals, volcanic behavior may be described as periodic. Periodic patterns in volcanic phenomena may reveal the existence of a fundamental process which regulates the inner workings of the volcano and ultimately aid forecasts of eruptive activity. We analyzed the sulfur dioxide degassing patterns of 32 volcanoes from a global database and we reveal significant periodic patterns in 17 of them. However, we also find similar periodic patterns the wind speed of the volcanic plume. We propose that periodic patterns in the degassing rates do not represent physical‐chemical processes inside the volcano but result from atmospheric dynamics. Key Points: Majority of periodicities identified in the emission rate of SO2 are related global trade winds and not volcanic in originWe identified periodicities between 30 and 70 days that are associated to the Madden‐Julian OscillationWe find no statistically significant periodicities related to the long‐term influence of Earth tides on volcanic degassing of SO2 [ABSTRACT FROM AUTHOR]

Volcanoes have been found to display periodicities or cyclic trends in a wide range of phenomena. These include the eruptive activity itself, but also in the time series of geophysical and geochemical monitoring data such as volcanic degassing. Here, we test the existence of periodicities of volcanic degassing at 32 volcanoes using the time series of sulfur dioxide (SO2) emission rates from data of the Network of Volcanic and Atmospheric Change (NOVAC). We use the Lomb‐Scargle periodogram to analyze the SO2 data which allows efficient computation of a Fourier‐like power spectrum from unevenly sampled data. We were able to calculate False‐Alarm Probabilities in 28 of the 32 volcanoes, and we identified significant periodicities in the SO2 emission rates in 17 of the 28 volcanoes. However, we find that most of these periodicities are also present in the plume speeds used to determine SO2 emission rates. Periodicities at about 30–70, ∼120, and ∼180 days were identified at volcanoes located between 16°N and 16°S and are related to intraseasonality and interseasonality in global trade winds and not volcanic in origin. Periodicities between 30 and 70 days in both plume speed and SO2 emission rates are associated to the Madden‐Julian Oscillation that is responsible for intraseasonal variability in the tropical atmosphere. Our study highlights the importance of using local wind data for deriving realistic SO2 emissions and the identification of short‐term periodicity in volcanic behavior. Plain Language Summary: Volcanoes may show cycling patterns in their eruption patterns but also in the geophysical and geochemical data used to monitor them. When these patterns occur at fixed‐time intervals, volcanic behavior may be described as periodic. Periodic patterns in volcanic phenomena may reveal the existence of a fundamental process which regulates the inner workings of the volcano and ultimately aid forecasts of eruptive activity. We analyzed the sulfur dioxide degassing patterns of 32 volcanoes from a global database and we reveal significant periodic patterns in 17 of them. However, we also find similar periodic patterns the wind speed of the volcanic plume. We propose that periodic patterns in the degassing rates do not represent physical‐chemical processes inside the volcano but result from atmospheric dynamics. Key Points: Majority of periodicities identified in the emission rate of SO2 are related global trade winds and not volcanic in originWe identified periodicities between 30 and 70 days that are associated to the Madden‐Julian OscillationWe find no statistically significant periodicities related to the long‐term influence of Earth tides on volcanic degassing of SO2 [ABSTRACT FROM AUTHOR]

The analysis of the meteorological indices provides valuable information about the evolution of climate during past and may predict its reflection in the future. Analysis of trends in meteorological variables is challenging as they are of non-stationary nature and may include both stochastic and noise components. The aim of this research is to integrate the signal processing technique Discrete Wavelet Transform (DWT) with different versions of Mann-Kendall (MK) trend tests for investigating the dominant climate systems characterizing the long-term time-series of the two most important meteorological parameters: mean air temperature (oC) and total rainfall (mm) for the different stations lying in the upper Indus River basin of Pakistan. The observed time series were categorized into monthly, seasonal, seasonally-based, and annual time series for investigating trends. The analysis showed that winters have experienced significant warming over the study area except for stations Nowshera and Parachinar while summers are experiencing decreasing temperature trends. Rainfall trends were dominated by positive trends. The results from the DWT and MK tests (at 5% significance level) on the different data types revealed that for higher-resolution data (monthly); the high-frequency intra-annual periodicities affecting air-temperature trends were dominated by 8-monthly fluctuations, and for the lower-resolution seasonal and annual data the interannual periodicities ranged from 2-4 years. For total rainfall data: 2-8 monthly; 2-4 yearly; and 2-8 yearly periodic modes were found dominant and characterizing the monthly, seasonally-based, and annual trends, respectively. It was found that DWT effectively extracted the two-dimensional time-amplitude-frequency information from the time series that was hidden in the observed raw data i.e. the time-frequency information manifested in the shape of time periodicities of intra-annual to inter-annual events. [ABSTRACT FROM AUTHOR]

Deconstructing a time index into time granularities can assist in exploration and automated analysis of large temporal datasets. This article describes classes of time deconstructions using linear and cyclic time granularities. Linear granularities respect the linear progression of time such as hours, days, weeks and months. Cyclic granularities can be circular such as hour-of-the-day, quasi-circular such as day-of-the-month, and aperiodic such as public holidays. The hierarchical structure of granularities creates a nested ordering: hour-of-the-day and second-of-the-minute are single-order-up. Hour-of-the-week is multiple-order-up, because it passes over day-of-the-week. Methods are provided for creating all possible granularities for a time index. A recommendation algorithm provides an indication whether a pair of granularities can be meaningfully examined together (a "harmony"), or when they cannot (a "clash"). Time granularities can be used to create data visualizations to explore for periodicities, associations and anomalies. The granularities form categorical variables (ordered or unordered) which induce groupings of the observations. Assuming a numeric response variable, the resulting graphics are then displays of distributions compared across combinations of categorical variables. The methods implemented in the open source R package gravitas are consistent with a tidy workflow, with probability distributions examined using the range of graphics available in ggplot2. Supplementary files for this article are available online. [ABSTRACT FROM AUTHOR]

A method for surface analysis of cold rolled sheets is proposed in this paper. The approach is based on a low-cost specially built camera system followed by spectral analysis of the data captured from metal surfaces. The focus is on the changes in the surface topography caused by cold rolling with emphasis towards periodicities in the processed surface. Angular profile of the spectrum is calculated and used to display periodicities in surface topography and show their direction. The results obtained by using the proposed system were compared with results obtained from the optical profilometer MicroProf FRT. The experiments show that cold rolling creates marks on the surface of the material, which represent periodicities that can be effectively detected by the proposed method and camera system. Even though the camera system is not able to measure precise surface roughness, it is able to detect periodicities and the results of spectral analysis are comparable with the results from the optical profilometer.

• IR radiation data between of 2014–2020 used to search for short-term periodicities. • Cosmic ray data, F 10.7, Dst index, and solar wind speed data were also used. • Common peaks were found in the spectra of the selected variables. • These peaks include 227 days, 154–157 days, 25–27 days, and 21 days. • Results indicate that the solar activity affect the IR radiation. In this study downward longwave (LW) atmospheric radiation data for the period of 2014–2020 were used to search for short-term periodicities using fast Fourier transform (FFT). Several local peaks in the power spectrum density were found and established. The time series exhibits a series of significant peaks (exceeding the 95% confidence limit), such as at 273 days, 227 days, 200 days, 178 days, 157 days, 110 days, 120 days, 87 days, 73 days, 53–56 days, 35–30 days, 25–27 days, 21 days, 13 days, and 9–10 days. Moreover, cosmic ray data from KACST muon detector and the Oulu neutron monitor, as well as the data for the solar radio flux at 10.7 cm (F10.7 cm), Dst index, and solar wind speed for the same period as the LW data, were used to look for common cyclic variations and periodicities matching those found in the LW radiation. This was done to investigate the possible effect of the solar activity parameters on LW radiation. Several common periodicities were observed in the spectra of all the variables considered, such as 227 days, 154–157 days, 25–27 days, and 21 days. Some of the periodicities found in the LW radiation spectrum can be attributed to the modulation of the cosmic ray intensity by solar activity. Others are attributed to the disturbances in the interplanetary magnetic field. Based on the spectral results, we suggest that the solar signals may directly or indirectly affect the variations of the downward longwave radiation, which in turn may affect climate change. [ABSTRACT FROM AUTHOR]

• Uniform DWS method was proposed to evaluate significance of hydrologic variability. • Spatial variability of hydrologic process can be quantified by the method proposed. • Variabilities in shorter hydrologic data at small timescales have more uncertainty. • Significance of runoff variability increased from down- to up-stream in the study area. Detecting the signals of hydrologic variability, including both periodicities and trends, at multi-timescales with evaluation of their statistical significance is one of the primary goals in hydrology studies, but it is also a challenging task. While the discrete wavelet spectrum (DWS) has been widely used to meet this purpose, it has limitations in practical applications, especially with the difficulty in detecting the spatial heterogeneity in hydrologic variability. In this study, a uniform DWS method is developed by determining the spectral values of the reference DWS, which are used as a uniform criterion for significance evaluation to identify hydrologic signals and compare their spatial heterogeneity. Application of the uniform DWS method to three annual runoff (and the corresponding precipitation) time series in the Yarlung Tsangpo River basin indicates that the significance of the runoff variability increases from down- to up-streams. It is shown that the uncertainty becomes large when the variability at small timescales is considered in short hydrologic time series. It is also demonstrated that hydrologic variability at long timescales usually tends to have a non-monotonic trend and that a monotonic trend would misrepresent the true underlying behavior. The uniform DWS method proposed here, by identifying the periodicities, non-monotonic and monotonic trend with significance evaluation, has the potential for a much wider use in hydrologic and climate sciences. [ABSTRACT FROM AUTHOR]

A comparative statistical analysis of the spatiotemporal variability of atmospheric precipitation characteristics (mean and extreme values) in Western Siberia was performed based on data acquired from meteorological stations, global precipitation datasets such as the project of Asian Precipitation—Highly-Resolved Observational Data Integration Towards Evaluation (APHRODITE) and from Global Precipitation Climatology Centre (GPCC), and reanalysis archives, including from National Centers of Environmental Prediction (NCEP-DOE) and the European Center for Medium Range Weather Forecasts (ERA5) for the period 1979–2018. The best agreement of the values from the observational data was observed with the values from GPCC. This archive also represented the periodicities in the time series of observational data from meteorological stations, especially in the short-period part of the spectrum. Underestimated values were revealed for the APHRODITE archive, while overestimated ones were found for the NCEP reanalysis data. In comparison with GPCC, the ERA5 dataset reproduced the general variability but with a smaller amplitude (the correlation coefficient was up to 0.9). In general, the median estimates of the precipitation amount derived from the meteorological stations’ data, as well from the reanalysis data, were in better agreement with each other rather than their extreme values. However, their temporal variability can be effectively described by other datasets.

Epileptic seizure detection and prediction by using noninvasive measurements such as scalp EEG signals or invasive, intracranial recordings, has been at the heart of epilepsy studies for at least three decades. To this end, the most common approach has been to consider short‐length recordings (several seconds to a few minutes) around a seizure, aiming to identify significant changes that occur before or during seizures. An inherent assumption in this approach is the presence of a relatively constant EEG activity in the interictal period, which is interrupted by seizure occurrence. Here, we examine this assumption by using long‐duration scalp EEG data (21–94 hr) in nine patients with epilepsy, based on which we construct functional brain networks. Our results reveal that these networks vary over time in a periodic fashion, exhibiting multiple peaks at periods ranging between 1 and 24 hr. The effects of seizure onset on the functional brain network properties were found to be considerably smaller in magnitude compared to the changes due to these inherent periodic cycles. Importantly, the properties of the identified network periodic components (instantaneous phase) were found to be strongly correlated to seizure onset, especially for the periodicities around 3 and 5 hr. These correlations were found to be largely absent between EEG signal periodicities and seizure onset, suggesting that higher specificity may be achieved by using network‐based metrics. In turn, this implies that more robust seizure detection and prediction can be achieved if longer term underlying functional brain network periodic variations are taken into account. [ABSTRACT FROM AUTHOR]

Neutron monitor counting rates and solar wind velocity, interplanetary magnetic field, sunspot number and total solar irradiance measurements from 2013 to 2018 corresponding to the end of solar maximum and the decreasing phase of the Solar Cycle 24 have been used. The main objective is to check whether the periodicities observed in the cosmic rays are affected by the magnetic rigidity or the height at which the neutron monitors are placed. A Global Neutron Monitor (GNM) has been defined as representative of the neutron monitor global network. This GNM is constructed by averaging the counting rates of a set of selected neutron monitors. The selection process is based on the combination of three new data quality criteria, which are applied to neutron monitors in the Neutron Monitor Data Base giving a final pool of 22 selected neutron monitors. Morlet wavelet analysis is applied to the GNM and the selected solar activity parameters to find the common periodicities. Short-term periodicities of 13.5, 27, 48, 92, 132 and 298 days have been observed in cosmic ray intensity. A clear inverse relationship between rigidity and spectral power has been obtained for the 13.5-, 48-, 92-, 132-day periods. A not so clear but still observed direct relationship between the height of the neutron monitors and the spectral power for the 48-, 92-, 132-day periods has been also found. The periodicity of 92 days is the one which shows the highest dependence with rigidity cutoff and height. As far as we know, this is the first time that these dependencies are reported. We think that these observations could be explained by assuming some cosmic ray intensity energy dependence in such periodicities and a competitive effect between rigidity and height. [ABSTRACT FROM AUTHOR]

The results of recent replication studies suggest that false positive findings are a big problem in empirical finance. We contribute to this debate by reviewing a sample of articles dealing with the short-term directional forecasting of the prices of stocks, commodities, and currencies. Screening all relevant articles published in 2016 by one of the 96 journals covered by the Social Sciences Citation Index in the category "Business, Finance," we select only those studies that use easily accessible data of daily or higher frequency. We examine each study in detail, from the selection of the dataset to the interpretation of the results. We also include empirical analyses to illustrate the shortcomings of certain approaches. There are three main findings from our review. First, the number of selected papers is very low, which is surprising even when the strict selection criteria are taken into account. Second, there are hardly any relevant studies that use high-frequency data--despite the hype about financial big data and machine learning. Third, the economic significance of the findings--for example, their usefulness for trading purposes--is questionable. In general, apparently good forecasting performance does not translate into profitability once realistic transaction costs and the effect of data snooping are taken into account. Other typical problems include unsuitable benchmarks, short evaluation periods, and nonoperational trading strategies. [ABSTRACT FROM AUTHOR]

It is well-established that both volume conduction and the choice of recording reference (montage) affect the correlation measures obtained from scalp EEG, both in the time and frequency domains. As a result, a number of correlation measures have been proposed aiming to reduce these effects. In our previous work, we have showed that scalp-EEG based functional brain networks in patients with epilepsy exhibit clear periodic patterns at different time scales and that these patterns are strongly correlated to seizure onset, particularly at shorter time scales (around 3 and 5 h), which has important clinical implications. In the present work, we use the same long-duration clinical scalp EEG data (multiple days) to investigate the extent to which the aforementioned results are affected by the choice of reference choice and correlation measure, by considering several widely used montages as well as correlation metrics that are differentially sensitive to the effects of volume conduction. Specifically, we compare two standard and commonly used linear correlation measures, cross-correlation in the time domain, and coherence in the frequency domain, with measures that account for zero-lag correlations: corrected cross-correlation, imaginary coherence, phase lag index, and weighted phase lag index. We show that the graphs constructed with corrected cross-correlation and WPLI are more stable across different choices of reference. Also, we demonstrate that all the examined correlation measures revealed similar periodic patterns in the obtained graph measures when the bipolar and common reference (Cz) montage were used. This includes circadian-related periodicities (e.g., a clear increase in connectivity during sleep periods as compared to awake periods), as well as periodicities at shorter time scales (around 3 and 5 h). On the other hand, these results were affected to a large degree when the average reference montage was used in combination with standard cross-correlation, coherence, imaginary coherence, and PLI, which is likely due to the low number of electrodes and inadequate electrode coverage of the scalp. Finally, we demonstrate that the correlation between seizure onset and the brain network periodicities is preserved when corrected cross-correlation and WPLI were used for all the examined montages. This suggests that, even in the standard clinical setting of EEG recording in epilepsy where only a limited number of scalp EEG measurements are available, graph-theoretic quantification of periodic patterns using appropriate montage, and correlation measures corrected for volume conduction provides useful insights into seizure onset.

In the northeastern (NE) Arabian Sea, the fluctuation in terrestrial and freshwater runoff directly depends on southwest monsoon (SWM) precipitation as well as the meltwater flux provided by Indus River. Therefore, analysis of multi-proxy spectral signatures was carried out to trace the high-resolution SWM periodicities and their influence on the productivity, regional sea level fluctuations and depositional processes in the NE Arabian Sea. The time series data of stable isotopes of oxygen (δ 18O G.ruber), carbon (δ 13C G.ruber and δ 13C org) and nitrogen (δ 15N), Total Organic Carbon (TOC), planktic-benthic foraminiferal ratio (P/B ratio) and >63 μm coarse fraction (CF) were used from two coastal sedimentary cores located offshore Saurashtra, NE Arabian Sea (Core SK-240/485 having 88 m water depth; Core GC/SK-240/496 having 174 m water depth). The REDFIT based spectral analysis recorded significant periodicities (>90% significance) in δ 18O time series centered at ∼1609, ∼667, ∼525, ∼296, ∼290 and ∼256 years. Further, the significant periodicities recorded in carbon isotopes time series (δ 13C G.ruber and δ 13C org) centered at ∼681, ∼512, ∼471, ∼452, ∼438, ∼360, ∼292, ∼275, ∼269, ∼245 and ∼209 years. The significant periodicities in TOC include ∼471 and ∼322 years whereas δ 15N time series recorded significant periodicity centered at ∼360 years. The significant periodicities in P/B ratio time series centered at ∼512, ∼388, ∼304, ∼250, ∼235, ∼217, ∼152, ∼139 and ∼135 years while CF recorded ∼268, ∼216, ∼209, ∼198, ∼188, ∼173 and ∼140 years significant periodicities. The observed periodicities in the multi-proxy record consist of similar cycles (within the radiocarbon dating error) which also match with previously reported solar insolation influenced SWM and other global and regional cycles. Further, the stationarity of the data has been verified using wavelet analysis and shows similar periodicities as observed in REDFIT analysis. Thereafter, the depositional behaviour was studied using correlation analysis of the common periods of δ 18O time series of both the cores. The result suggests that the depositional behaviour was different for both the core sites during the early Holocene and became similar during the middle Holocene. The correlation analysis of Total Solar Index (TSI) with δ 18O time series reveals a significant correlation with the core SK-240/485 whereas an insignificant correlation with the core GC/SK-240/496. These observations suggest that the solar insolation has been a leading factor responsible for the SWM trends during the Holocene which may have further influenced the productivity, regional sea level fluctuations and depositional conditions in the NE Arabian Sea. However, these trends are better preserved in shallow marine sediments as compared to the deeper marine sediments. Image 1 • Comprehensive multi-proxy spectral analysis using marine sediment cores from offshore Saurashtra, NE Arabian Sea. • Significant periodicities in the SWM variations and its influence on the NE Arabian Sea paleoceonography • Decipher the possible amplifying mechanism of relation between solar insolation and SWM variability. [ABSTRACT FROM AUTHOR]

Highlights • The coefficient of variations and the Allan Factor revealed time-clustering. • The interevent times are persistent. • The magnitudes are weakly persistent or random. • The daily counts of the aftershock-depleted seismicity reveal quasi-monthly and bi-weekly periodicities. • Quasi-annual and quasi-semestral periodicities strengthen the link with Earth's tides. Abstract We studied the whole and aftershock-depleted shallow (depth ≤ 30 km) Taiwanese seismicity from 1990 to 2017 by using several independent methods. The coefficient of variations and the Allan Factor have revealed that time-clustering characterizes not only the time distribution of the whole seismic catalogue, but also that of the aftershock-depleted one, although this displays time-clustering at larger timescales. In particular the Allan Factor shows that at small timescales the seismic process of the whole as well as the aftershock-depleted one can be well described by a Poisson process. The detrended fluctuation analysis clearly evidence persistence in the interevent times and weak persistence or randomness in the magnitudes. The singular spectrum analysis of the daily counts in the aftershock-depleted catalogue reveals the existence of quasi-monthly and bi-weekly periodicities. Furthermore, quasi-annual and quasi-semestral periodicities have been identified that strengthen the link between seismic activity in Taiwan and Earth's tides. [ABSTRACT FROM AUTHOR]

Abstract In this study, radiosonde observations from seven sites in Saudi Arabia for the period 1985 to 2016 were utilized to investigate the interannual, monthly, and seasonal variations and trends of precipitable water vapour (PWV). The magnitudes of these trends have been characterized and tested using the Mann-Kendall (MK) rank statistics at different significance levels. A significant decrease in the annual mean PWV by about 7% is found for the entire period. A seasonal cycle of PWV with a maximum during summer time and a minimum during winter has been found and can be mostly attributed to the variations of air temperature. On a monthly basis, the PWV values revealed a decreasing trend with the rate of decrease ranging between 0.47 and 2.6 mm per 32 years. There was a decrease in PWV in all the seasons, but it was only significant for the spring season, when it was the highest (1.79 mm per 32 years). Power spectra analyses using the Fourier Transform (FT) technique were carried out for the period 1985–2016 to investigate the periodicities in the PWV time series. Several long, mid, and short-term periodicities were recognized. Short-term periodicities such as one year, six months, three months, and four months were found. On the other hand, long and mid term periodicities such as 10.8–11 years, 1.7 years, and 1.3 years were detected. The obtained periodicities are similar to those reported by several investigators and found in solar, interplanetary, and cosmic ray parameters. The spectral results suggest that the obtained PWV periodicities in Arabian Peninsula are, possibly, related to the solar activities, as well as, the effect of terrestrial meteorological phenomena. Highlights • Variations and trends of precipitable water vapour (PWV) were investigated using radiosonde observations from seven sites in Saudi Arabia. • The magnitudes of these trends were characterized using the Mann-Kendall (MK) rank statistics at different significance levels. • A significant decrease in the annual mean PWV over Saudi Arabia by about 7% is found. • Several long- and short-term periodicities were recognized. • Some of these periodicities were associated with an extra-terrestrial origin (such as solar activity and cosmic ray). [ABSTRACT FROM AUTHOR]

It is well-established that both volume conduction and the choice of recording reference (montage) affect the correlation measures obtained from scalp EEG, both in the time and frequency domains. As a result, a number of correlation measures have been proposed aiming to reduce these effects. In our previous work, we have showed that scalp-EEG based functional brain networks in patients with epilepsy exhibit clear periodic patterns at different time scales and that these patterns are strongly correlated to seizure onset, particularly at shorter time scales (around 3 and 5 h), which has important clinical implications. In the present work, we use the same long-duration clinical scalp EEG data (multiple days) to investigate the extent to which the aforementioned results are affected by the choice of reference choice and correlation measure, by considering several widely used montages as well as correlation metrics that are differentially sensitive to the effects of volume conduction. Specifically, we compare two standard and commonly used linear correlation measures, cross-correlation in the time domain, and coherence in the frequency domain, with measures that account for zero-lag correlations: corrected cross-correlation, imaginary coherence, phase lag index, and weighted phase lag index. We show that the graphs constructed with corrected cross-correlation and WPLI are more stable across different choices of reference. Also, we demonstrate that all the examined correlation measures revealed similar periodic patterns in the obtained graph measures when the bipolar and common reference (Cz) montage were used. This includes circadian-related periodicities (e.g., a clear increase in connectivity during sleep periods as compared to awake periods), as well as periodicities at shorter time scales (around 3 and 5 h). On the other hand, these results were affected to a large degree when the average reference montage was used in combination with standard cross-correlation, coherence, imaginary coherence, and PLI, which is likely due to the low number of electrodes and inadequate electrode coverage of the scalp. Finally, we demonstrate that the correlation between seizure onset and the brain network periodicities is preserved when corrected cross-correlation and WPLI were used for all the examined montages. This suggests that, even in the standard clinical setting of EEG recording in epilepsy where only a limited number of scalp EEG measurements are available, graph-theoretic quantification of periodic patterns using appropriate montage, and correlation measures corrected for volume conduction provides useful insights into seizure onset. [ABSTRACT FROM AUTHOR]

Jupiter's auroral X‐rays are rather mysterious, with an unknown driver, and several previous reports of individual cases of quasi‐periodic emission. In this work we revisit heritage X‐ray data sets from the 1990s to 2015 and apply robust significance testing of emerging quasi‐periodicities, seeking to understand the robustness and regularity of previously reported quasi‐periodic emissions. Our analysis incorporates the use of the Rayleigh test as an alternative to Lomb‐Scargle analysis or Fast Fourier Transforms, where Rayleigh is particularly suited to a time‐tagged data set of sparse counts such as is common for jovian X‐ray data. Furthermore, the analysis techniques that we present (including Rayleigh testing and Monte Carlo simulation) can be applied to any time‐tagged data set. The code to conduct such analysis is released as supplementary information to accompany this paper. The five most significant (p value <0.01) quasi‐periods from Jupiter's northern auroral region have periods ranging from ~8.0 to 45.96 min, and the two most significant (p value <0.01) quasi‐periods from the south have periods of ~14.1 and ~34.9 min. The selection of a restrictive hot spot source region seems to be critical for detecting quasi‐periodic emission, suggesting that the site of pulsations may be spatially localized. Periods vary from one Jupiter rotation to the next in one long observation, and the north and south are shown to pulse independently in another conjugate observation. These results have important implications for understanding the driver of jovian X‐ray emission. Key Points: Timing analysis of Chandra observations of Jupiter's X‐ray auroras from 1999 to 2015Statistically significant quasi‐periodicities in jovian auroral X‐rays are relatively rare and periods variable, even on successive planetary rotationsWe use Rayleigh testing and Monte Carlo simulation to search for statistically significant quasi‐periods in sparse, time‐tagged data [ABSTRACT FROM AUTHOR]

Abstract In this paper we introduce the notion of an optimal cover. Let M denote the maximum number of positions in w covered by any repeating substring of w. Then a longest (shortest) optimal cover u is a longest (shortest) repeating substring of w that covers M positions. The advantage of this notion is that it is not only applicable to all strings, but also that it does not share the deficiencies of the existing definitions of covers. We show that both the longest and the shortest optimal covers for a given string w of length n can be computed easily and efficiently in O (n log ⁡ n) time and O (n) space. We further show that the data structures used to compute optimal covers also compute the α -partial covers introduced in [10]. [ABSTRACT FROM AUTHOR]

Abstract: Saturn's planetary period oscillations (PPOs) are ubiquitous throughout its magnetosphere. We investigate the PPO's azimuthal magnetic field amplitude interior to the field‐aligned currents, during the closest approaches of Cassini's ring‐grazing orbits (October 2016 to April 2017), with periapses at ~2.5 RS. The amplitudes of the northern and southern PPO systems are shown to vary as a function of latitude. The amplitude ratio between the two PPO systems shows that the northern system is dominant by a factor of ~1.3 in the equatorial plane, and it is dominant to ~ −15° latitude in the southern hemisphere. The dayside amplitudes are approximately half of the 2008 nightside amplitudes, which agree with previous local time‐related amplitude observations. Overall, there is clear evidence that the PPOs are present on field lines that map to the outer edge of Saturn's rings, closer to Saturn than previously confirmed. [ABSTRACT FROM AUTHOR]

Abstract: We investigate the azimuthal magnetic field signatures associated with high‐latitude field‐aligned currents observed during Cassini's F‐ring orbits (October 2016–April 2017). The overall ionospheric meridional current profiles in the northern and southern hemispheres, that is, the regions poleward and equatorward of the field‐aligned currents, differ most from the 2008 observations. We discuss these differences in terms of the seasonal change between data sets and local time (LT) differences, as the 2008 data cover the nightside while the F‐ring data cover the post‐dawn and dusk sectors in the northern and southern hemispheres, respectively. The F‐ring field‐aligned currents typically have a similar four current sheet structure to those in 2008. We investigate the properties of the current sheets and show that the field‐aligned currents in a hemisphere are modulated by that hemisphere's “planetary period oscillation” (PPO) systems. We separate the PPO‐independent and PPO‐related currents in both hemispheres using their opposite symmetry. The average PPO‐independent currents peak at ~1.5 MA/rad just equatorward of the open closed field line boundary, similar to the 2008 observations. However, the PPO‐related currents in both hemispheres are reduced by ~50% to ~0.4 MA/rad. This may be evidence of reduced PPO amplitudes, similar to the previously observed weaker equatorial oscillations at similar dayside LTs. We do not detect the PPO current systems' interhemispheric component, likely a result of the weaker PPO‐related currents and their closure within the magnetosphere. We also do not detect previously proposed lower latitude discrete field‐aligned currents that act to “turn off” the PPOs. [ABSTRACT FROM AUTHOR]

In the present paper we have analyzed the solar irradiance data from the Earth Radiation Budget Satellite (ERBS) during the time period from October 15, 1984 to October 15, 2003 to detect the corresponding periods, if any with relevant scores (confidence). Power spectrum of the denoised signal has been obtained using FFT in order to search for its periodicities. Present calculation reveals strong periods around 9.08-9.35, 13.53-14.03, 27.50-28.17, 30.26, 35.99-36.37, 51.14-51.52, 68.27-68.60, 101.15, 124.85, 150.63-153.98, 659.90, 729.37, 1259.82, 3464.50 and 4619.33 days. We also got some weak periods around 46.19, 72.55, 82.49, 137.21-139.98, 395.94, 407.59 and 1979.71 days.

In this paper we consider substrings of an unrooted edge-labeled tree, which are defined as the composite labels of simple paths. We study how the number of distinct repetitive substrings depends on their exponent $$\alpha $$ . An $$\alpha $$ -power is defined as a string U with an (integral, not necessarily shortest) period $$|U|/\alpha $$ . For example, squares are 2-powers and cubes are 3-powers. We investigate the asymptotic growth of the maximal number $$\textsf {powers}_{\alpha }(n)$$ of distinct $$\alpha $$ -powers occurring as substrings of a tree with n nodes. The maximum number of such powers behaves much unlike in strings. In a previous work (CPM 2012. LNCS, vol 7354. Springer, Berlin, pp 27-40, 2012. It was proved that the number of different squares in a tree is $$\textsf {powers}_2(n) = \varTheta (n^{4/3})$$ . We extend this result and analyze powers of arbitrary rational exponent $$\alpha \ge 1$$ . We identify two phase-transition thresholds: This is a full version of a paper presented at CPM 2015. LNCS, vol 9133. Springer, Berlin, pp 284-294, 2015. Compared to the earlier version, we improve our main technical contribution, i.e., the upper bound on the number of cubes in a tree, from $$\mathcal {O}(n \log n)$$ to $$\mathcal {O}(n)$$ . This lets us obtain a tight asymptotic characterization of the $$\textsf {powers}$$ function. [ABSTRACT FROM AUTHOR]

The dynamics of the beryllium-7 specific activity in surface air over 1987–2011 is analyzed using wavelet transform (WT) analysis and time-dependent detrended moving average (tdDMA) method. WT analysis gives four periodicities in the beryllium-7 specific activity: one month, three months, one year, and three years. These intervals are further used in tdDMA to calculate local autocorrelation exponents for precipitation, tropopause height and teleconnection indices. Our results show that these parameters share common periods with the beryllium-7 surface concentration. tdDMA method indicates that on the characteristic intervals of one year and shorter, the beryllium-7 specific activity is strongly autocorrelated. On the three-year interval, the beryllium-7 specific activity shows periods of anticorrelation, implying slow changes in its dynamics that become evident only over a prolonged period of time. A comparison of the Hurst exponents of all the variables on the one- and three-year intervals suggest some similarities in their dynamics. Overall, a good agreement in the behavior of the teleconnection indices and specific activity of beryllium-7 in surface air is noted. [ABSTRACT FROM AUTHOR]

Some selected hydrochemical parameters of Diyala river including electricalconductivity (EC), 132 14Ca+2 ,Mg+2 ,SO- ,Cl - ,HCO- , total soluble solids (T.S.S.),discharge (Q) and total hardness(TH) were analyzed for their periodicities using monthlymeasurements for the period 1993-1997, to quantify and qualify surface water andinvestigate the periodicity behavior of these parameters. Results showed significantautocorrelation for all the studied series and therefore they were subjected to the Spectral(Fourier) analysis to investigate the main periodicities that contribute to the totalvariance of the observed data. Most of the selected parameters have strong (lessfrequent) semi-annual and biannual cycle, as well as seasonal cycle for, Cl, Mg, Ca, SO4,HCO3 ,TSS , and EC. These results reveal the variation of the factors affecting the riverwater quality including hydrological and meteorological conditions as well as the impactof human activities through the river catchments river.

To assess long-term trends and periodicities in geomagnetic storms, the discrete wavelet transform, using the Daubechies function, was applied. Among a variety of techniques, which are available for analyzing variability, wavelet analysis has emerged in the last decade as a useful statistical tool for this purpose. The number of geomagnetic storms from 1957 to 2004 was used for the present analysis. The wavelet analysis has been applied to storms with different intensities. For identify geomagnetic storms, the equatorial index, Dst, has been used. The long-term trend during the analyzed period is not a uniform, with minimum around the years 1965 and 2000, and a maximum around 1990. Different periodicities have been detected. Their behavior is not regular along the analyzed period, they have different intensity values. Possible causes for the observed variability are discussed.

In January 2007, King Abdulaziz University, Jeddah (21.5o N; 39.2o E; 14.8 GV), Saudi Arabia, installed a single channel muon detector for monitoring and studying the variations of the cosmic ray (CR) muons. Brief description of the developed detector will be presented. A few results obtained by the detector so far will be given and discussed. These include the impact of the atmospheric pressure and temperature, the daily variations, the responses of the detector to transit and long term of the solar disturbances. Performances of the detector were compared with the King Abdulaziz city for science and technology (KACST) muon detector installed in Riyadh Saudi Arabia and with the Oulu neutron monitor at Oulu and showed comparable results. • Cosmic ray muon detector was installed at Jeddah (cut off rigidity R c = 14.8GV) Saudi Arabia. • One of the main goal of this detector is to investigate CR correlations with solar activity and atmospheric phenomena. • The detector performance was tested and showed comparable results to other detectors. • Measurments from the detector were presented and compared with other detectors. • Short periodicities of the CR recorded by the detector were and found to be in good agreement with those reported by different researchers. [ABSTRACT FROM AUTHOR]

Cosmic rays (CR) play an important role in space weather-related studies. Their temporal variability, both of a quasi-periodic character as well as an irregular one, has been studied from ground-based direct measurements, as well as from cosmogenic nuclides, over a long time. We attempt to describe the current knowledge of selected quasi-periodicities in CR flux in the energy range above the atmospheric threshold, from direct measurements. The power spectrum density (PSD) of the CR time series as measured by neutron monitors (NMs) and by muon detectors has a rather complicated character. Along with the shape (slope) of the PSD, knowledge of the contribution of quasi-periodic variations (q-per) to the CR signal is of importance for the modulation, as well as for checking the links of CR to space weather, and/or to space climate effects. The rotation of the Earth and solar rotation cause two types of mechanisms behind the certain q-per observed in secondary CR on the Earth's surface. Solar activity and solar magnetic field cyclicities contribute to the q-per signals in CR if studied over a longer time. The complexity of the spatial structure of the interplanetary magnetic field (IMF) and its evolution within the heliosphere, in addition to the changes in the geomagnetic field, cause variability in contributions of the q-per in CR. Wavelet spectra are useful tools for checking the fine structure of q-per and their temporal behaviour. Over a long time NMs and muon telescopes provide information about q-per in CR. [ABSTRACT FROM AUTHOR]

Cycle spinning (CS) and a'trous algorithms are different implementations of the undecimated wavelet transform (UWT). Both algorithms can be used for UWT and even though the resulting wavelet coefficients are different, they keep a correspondence. This paper describes an analysis of the CS algorithm performed in the z-transform domain, showing the similarities and differences with the a'trous implementation. CS generates more wavelet coefficients than a'trous, but the number of significative and different coefficients is the same in both cases because of the occurrence of a periodic repetition in CS coefficients. Mathematical expressions for the relationship between CS and a'trous coefficients and for CS coefficient periodicities are provided in the z-transform domain. In some wavelet denoising applications, periodicities (present in the coefficients of the CS procedure) can also be found in the performance measure of the processed signals. In particular, in ultrasonic CS denoising applications, periodicities have been appreciated in the signal-to-noise ratio (SNR) of the ultrasonic denoised signals. These periodicities can be used to optimize the number of CS coefficients for an efficient implementation. Two examples showing the periodicities in the SNR are included. A selection of several reduced sets of CS wavelet coefficients has been utilized in the examples, and the SNRs resulting after denoising are analyzed. [ABSTRACT FROM AUTHOR]

10,000-year-long varved sediment records from lakes Nautajärvi and Korttajärvi, Finland provide evidence of climate and environment oscillations at multi-decadal to millennial timescales. We used two independent methods to extract periodic features from these time series of clastic laminae and assess their statistical reliability. Analyses revealed that seasonal sediment fluxes correspond to environmental changes with statistically significant periodicities of 1500–1800, 1000, 600–800, nearly 300, nearly 200, 150–170, nearly 90 and 47 years, showing variable coherency with different climate forcing factors and other palaeoproxy records in the Northern Hemisphere. Results indicate that the Holocene winter climate in continental Scandinavia was forced by a combination of several factors, at least by solar variability and the North Atlantic ocean–atmosphere circulation-patterns, with varying influences through time. [ABSTRACT FROM AUTHOR]

Investigating the roles and functions of DNA within genomes is becoming a primary focus of genomic research. Thus, the research works are moving towards cooperation between different scientific disciplines which aims at facilitating the interpretation of genetic information. In order to characterize the DNA of living organisms, signal processing tools appear to be very suitable for such study. However, a DNA sequence must be converted into a numerical sequence before processing; which defines the concept of DNA coding. In line with this, we propose a new one dimensional model based on the chaos game representation theory called Frequency Chaos Game Signal: FCGS. Then, we perform a Smoothed Fourier Transform to enhance hidden periodicities in the C.elegans DNA sequences. Through this study, we demonstrate the performance of our coding approach in highlighting characteristic periodicities. Indeed, several periodicities are shown to be involved in the 1D spectra and the 2D spectrograms of FCGSs. To investigate further about the contribution of our method in the enhancement of characteristic spectral attributes, a comparison with a range of binary indicators is established. [ABSTRACT FROM PUBLISHER]