scholarly journals Soliton-Like Waves in the Vicinity of the Southern Kuril Islands

2021 ◽  
Vol 28 (1) ◽  
Author(s):  
V. A. Squire ◽  
Peter D. Kovalev ◽  
D. P. Kovalev ◽  
◽  
◽  
...  
Keyword(s):  
Time Series ◽  
Wave Packet ◽  
Model Simulation ◽  
Wave Packets ◽  
Tidal Flow ◽  
Pressure Sensors ◽  
Kuril Islands ◽  
Observation Data ◽  
Average Period ◽  
De Vries

urpose. This paper focuses on modulated solitons detected in time series of observational data on sea level oscillations in the Sea of Okhotsk, verifying the presence of nonstationary processes within a quantitative framework of methods. Methods and Results. The paper reports an analysis of wave observation data collected using ARW-type, bottom-mounted pressure sensors in the area of the Capes Castricum, Van-der-Lind and Lovtsova in the southern Kuril Islands. The time series obtained were bandpass filtered using hardware with a passband of 20 minutes to 2.5 hours. Residual time series show the presence of wave packets generated at the beginning of the K1 (diurnal) tide, which consistently appear as a group consisting of 5–7 packets. It is shown that the synchronicity between each wave packet and the K1 wave initiation is associated with the cyclic separation of the tidal flow of the K1 oscillation at the elevation in the Urup Strait located between the islands, along with a concomitant spawning of vortices. It is speculated that the vortices generate the detected wave packets, which are each found to encase a cluster of waves with an average period of about 1.6 hours that are attributed to either edge waves or shelf seiches or a combination of both. A numerical model simulation of the detected wave packets was performed using the Korteweg – de Vries equation, confirming that the envelope of the observed wave packets is close to the modeled one and behaves like a soliton. Conclusions. It is shown that synchronous initiation of a wave packet and a K1 wave is associated with the cyclic separation of the tidal flow of the K1 oscillations at a subsurface elevation in the Urup Strait located between the islands, with a concomitant spawning of vortices. The vortices are assumed to generate the detected wave packets. Each packet contains a cluster of waves with an average period of about 1.6 hours, which is conditioned by the period of the edge wave or shelf seiche. Spectral analysis performed for the 4.5-day-long time series with and without the groups of solitons, showed that the wave energy increases in the 0.5–5.5 hour period range when solitons occur. Application of a simple amplitude-based criterion permitted the authors to identify the waves detected in the wave packets as anomalous. Transformation of the time series into normalized time and normalized amplitude coordinates show that all the examples of anomalous wave packets could be modeled using the Korteweg – de Vries time equation

scholarly journals Soliton-Like Waves in the Vicinity of the Southern Kuril Islands

2021 ◽  
Vol 37 (1) ◽  
Author(s):  
V. A. Squire ◽  
Peter D. Kovalev ◽  
D. P. Kovalev ◽  
◽  
◽  
...  
Keyword(s):  
Time Series ◽  
Quantitative Methods ◽  
Model Simulation ◽  
Tidal Flow ◽  
Pressure Sensors ◽  
Kuril Islands ◽  
Observation Data ◽  
Average Period ◽  
Edge Waves ◽  
De Vries

Purpose. The paper is aimed at studying the modulated solitons detected in the time series of the observational data on the sea level oscillations and at verifying presence of nonstationary processes within the framework of the quantitative methods. Methods and Results. The paper represents analysis of the wave observation data collected using ARW-type, bottom-mounted pressure sensors in the area of the capes Castricum, Van-der-Lind and Lovtsova in the southern Kuril Islands. The time series obtained were bandpass filtered using hardware with a passband of 20 minutes – 2.5 hours. Residual time series show presence of the wavepackets generated at the beginning of the K1 (diurnal) tide, which consistently appear as a group consisting of 5–7 packets. It is shown that the synchronicity of wavepacket and the K1 wave initiation is associated with the cyclic separation of the tidal flow of the K1 oscillation at the elevation in the Urup Strait located between the islands, along with a concomitant spawning of vortices. It is speculated that the vortices generate the detected wavepackets, each of which are found to encase a cluster of waves of average period about 1.6 hours that are attributed to edge waves or shelf seiches. A numerical model simulation of the detected wavepackets was performed using the Korteweg-de Vries equation, which confirms that the envelope of the observed wavepackets is close to the modeled one and behaves like a soliton. Conclusions. It is shown that synchronous initiation of a wavepacket and a K1 wave is associated with the cyclic separation of the tidal flow of the K1 oscillations from the elevation in the Urup Strait located between the islands with a oncomitant spawning of vortices. The vortices are assumed to generate the detected wavepackets. Each of them contains a cluster of waves, the average period of which is about 1.6 hours that is conditioned by the edge waves’ or shelf seiches’ period. Spectral analysis performed for the 4.5-day-long time series at presence and absence of the groups of solitons, showed that when solitons occur, the wave energy increased in the 0.5–5.5 hr period range. Application of a simple amplitude-based criterion permitted to identify the waves detected in the wavepackets as the anomalous ones. Transformation of the time series into the normalized time and the normalized amplitude coordinates showed that all the examples of anomalous wavepackets could be modeled using the Korteweg-de Vries time equation.

scholarly journals Sea Ice Concentration Products over Polar Regions with Chinese FY3C/MWRI Data

2021 ◽  
Vol 13 (11) ◽  
pp. 2174
Author(s):  
Lijian Shi ◽  
Sen Liu ◽  
Yingni Shi ◽  
Xue Ao ◽  
Bin Zou ◽  
...  
Keyword(s):  
Time Series ◽  
Sea Ice ◽  
Ocean Circulation ◽  
The Arctic ◽  
Retrieval Algorithm ◽  
Atmospheric Effects ◽  
Observation Data ◽  
Long Time Series ◽  
Ice Concentration ◽  
Long Time

Polar sea ice affects atmospheric and ocean circulation and plays an important role in global climate change. Long time series sea ice concentrations (SIC) are an important parameter for climate research. This study presents an SIC retrieval algorithm based on brightness temperature (Tb) data from the FY3C Microwave Radiation Imager (MWRI) over the polar region. With the Tb data of Special Sensor Microwave Imager/Sounder (SSMIS) as a reference, monthly calibration models were established based on time–space matching and linear regression. After calibration, the correlation between the Tb of F17/SSMIS and FY3C/MWRI at different channels was improved. Then, SIC products over the Arctic and Antarctic in 2016–2019 were retrieved with the NASA team (NT) method. Atmospheric effects were reduced using two weather filters and a sea ice mask. A minimum ice concentration array used in the procedure reduced the land-to-ocean spillover effect. Compared with the SIC product of National Snow and Ice Data Center (NSIDC), the average relative difference of sea ice extent of the Arctic and Antarctic was found to be acceptable, with values of −0.27 ± 1.85 and 0.53 ± 1.50, respectively. To decrease the SIC error with fixed tie points (FTPs), the SIC was retrieved by the NT method with dynamic tie points (DTPs) based on the original Tb of FY3C/MWRI. The different SIC products were evaluated with ship observation data, synthetic aperture radar (SAR) sea ice cover products, and the Round Robin Data Package (RRDP). In comparison with the ship observation data, the SIC bias of FY3C with DTP is 4% and is much better than that of FY3C with FTP (9%). Evaluation results with SAR SIC data and closed ice data from RRDP show a similar trend between FY3C SIC with FTPs and FY3C SIC with DTPs. Using DTPs to present the Tb seasonal change of different types of sea ice improved the SIC accuracy, especially for the sea ice melting season. This study lays a foundation for the release of long time series operational SIC products with Chinese FY3 series satellites.

The Spectrum Segmentation Algorithm of Multimode Vibration Signal Based on Spectral Clustering

2011 ◽  
Vol 121-126 ◽  
pp. 2372-2376
Author(s):  
Dan Dan Wang ◽  
Yu Zhou ◽  
Qing Wei Ye ◽  
Xiao Dong Wang
Keyword(s):  
Wave Packet ◽  
Frequency Domain ◽  
Spectral Clustering ◽  
Clustering Algorithm ◽  
Wave Packets ◽  
Vibration Signal ◽  
Segmentation Algorithm ◽  
Frequency Curve ◽  
Macroscopic Observation ◽  
Spectral Clustering Algorithm

The mode peaks in frequency domain of vibration signal are strongly interfered by strong noise, causing the inaccuracy mode parameters. According to this situation, this paper comes up with the thought of mode-peak segmentation based on the spectral clustering algorithm. First, according to the concept of wave packet, the amplitude-frequency of vibration signal is divided into wave packets. Taking each wave packet as a sample of clustering algorithm, the spectral clustering algorithm is used to classify these wave packets. The amplitude-frequency curve of a mode peak becomes a big wave packet in macroscopic. The experiment to simulation signals indicates that this spectral clustering algorithm could accord with the macroscopic observation of mode segmentation effectively, and has outstanding performance especially in strong noise.

scholarly journals Spin-Orbit Entanglement in Time Evolution of Radial Wave Packets in Hydrogenic Systems

2004 ◽  
Vol 11 (04) ◽  
pp. 401-409
Author(s):  
Marcin Turek ◽  
Piotr Rozmej
Keyword(s):  
Wave Packet ◽  
Time Evolution ◽  
Time Scale ◽  
Degrees Of Freedom ◽  
Wave Packets ◽  
Characteristic Time Scale ◽  
Radial Wave ◽  
Mean Values ◽  
Breathing Motion ◽  
Wave Packet Revival

Time evolution of radial wave packets built from the eigenstates of Dirac equation for a hydrogenic system is considered. Radial wave packets are constructed from the states of different n quantum numbers and the same lowest angular momentum. In general they exhibit a kind of breathing motion with dispersion and (partial) revivals. Calculations show that for some particular preparations of the wave packet one can observe interesting effects in spin motion, coming from inherent entanglement of spin and orbital degrees of freedom. These effects manifest themselves through some oscillations in the mean values of spin operators and through changes of spatial probability density carried by upper and lower components of the wave function. It is also shown that the characteristic time scale of predicted effects (called T ls ) is much smaller for radial wave packets than in other cases, reaching values comparable to (or even less than) the time scale for the wave packet revival.

Local Finite-Amplitude Wave Activity as a Diagnostic for Rossby Wave Packets

2018 ◽  
Vol 146 (12) ◽  
pp. 4099-4114 ◽  
Author(s):  
Paolo Ghinassi ◽  
Georgios Fragkoulidis ◽  
Volkmar Wirth
Keyword(s):  
Rossby Wave ◽  
Model Simulation ◽  
Wave Packets ◽  
Meridional Wind ◽  
Finite Amplitude ◽  
Wave Activity ◽  
Amplitude Wave ◽  
High Impact Weather ◽  
Finite Amplitude Wave Activity ◽  
Isentropic Coordinates

AbstractUpper-tropospheric Rossby wave packets (RWPs) are important dynamical features, because they are often associated with weather systems and sometimes act as precursors to high-impact weather. The present work introduces a novel diagnostic to identify RWPs and to quantify their amplitude. It is based on the local finite-amplitude wave activity (LWA) of Huang and Nakamura, which is generalized to the primitive equations in isentropic coordinates. The new diagnostic is applied to a specific episode containing large-amplitude RWPs and compared with a more traditional diagnostic based on the envelope of the meridional wind. In this case, LWA provides a more coherent picture of the RWPs and their zonal propagation. This difference in performance is demonstrated more explicitly in the framework of an idealized barotropic model simulation, where LWA is able to follow an RWP into its fully nonlinear stage, including cutoff formation and wave breaking, while the envelope diagnostic yields reduced amplitudes in such situations.

scholarly journals New possibilities of the PCA-Seq method in the analysis of time series (on the example of solar activity)

2021 ◽  
Vol 2099 (1) ◽  
pp. 012034
Author(s):  
V M Efimov ◽  
K V Efimov ◽  
D A Polunin ◽  
V Y Kovaleva
Keyword(s):  
Time Series ◽  
Solar Activity ◽  
Maunder Minimum ◽  
High Solar Activity ◽  
External Influence ◽  
Average Period ◽  
Time Axis ◽  
Constant Amplitude ◽  
The Impact ◽  
Analysis Of Time Series

Abstract When analyzing a 1D time series, it is traditional to represent it as the sum of the trend, cyclical components and noise. The trend is seen as an external influence. However, the impact can be not only additive, but also multiplicative. In this case, not only the level changes, but also the amplitude of the cyclic components. In the PCA-Seq method, a generalization of SSA, it is possible to pre-standardize fragments of a time series to solve this problem. The algorithm is applied to the Anderson series – a sign alternating version of the well-known Wolf series, reflecting the 22-year Hale cycle. The existence of this cycle is not disputed at high solar activity, but there are doubts about the constancy of its period at this time, as well as its existence during the epoch of low solar activity. The processing of the series by the PCA-Seq method revealed clear oscillations fluctuations of almost constant amplitude with an average period of 21.9 years, and it was found that the correlation of these oscillations with the time axis for 300 years does not differ significantly from zero. This confirms the hypothesis of the existence of 22-year oscillations in solar activity even at its minima, like the Maunder minimum.

scholarly journals ACCELERATION OF PARTICLES BY THE FIELDS OF WAVE PACKETS

2019 ◽  
pp. 43-46
Author(s):  
V.А. Buts ◽  
V.V. Kuzmin ◽  
A.P. Tolstoluzhsky
Keyword(s):  
Wave Packet ◽  
Wave Packets ◽  
Dynamic Chaos ◽  
Acceleration Of Particles ◽  
Nonlinear Resonances ◽  
Dynamics Of Particles

The dynamics of particles in the field of a wave packet excited in a plasma is considered. The conditions are found under which such dynamics is regular, and when it becomes chaotic. It was found that the well-known (phenomenological) criterion for the emergence of dynamic chaos − the criterion for overlapping Chirikov nonlinear resonances − requires careful use.

scholarly journals Estimating uncertainties in hydraulicallymodelled rating curves for discharge time series assessment

2018 ◽  
Vol 40 ◽  
pp. 06013
Author(s):  
Valentin Mansanarez ◽  
Ida K. Westerberg ◽  
Steve W. Lyon ◽  
Norris Lam
Keyword(s):  
Time Series ◽  
Hydraulic Model ◽  
Observation Data ◽  
Rating Curve ◽  
Hydraulic Modelling ◽  
Discharge Time ◽  
High Flows ◽  
Rating Curves ◽  
Hydrometric Station ◽  
The Impact

Establishing a reliable stage-discharge (SD) rating curve for calculating discharge at a hydrological gauging station normally takes years of data collection. Estimation of high flows is particularly difficult as they occur rarely and are often difficult to gauge in practice. At a minimum, hydraulicallymodelled rating curves could be derived with as few as two concurrent SD and water-surface slope measurements at different flow conditions. This means that a reliable rating curve can, potentially, be developed much faster via hydraulic modelling than using a traditional rating curve approach based on numerous stage-discharge gaugings. In this study, we use an uncertainty framework based on Bayesian inference and hydraulic modelling for developing SD rating curves and estimating their uncertainties. The framework incorporates information from both the hydraulic configuration (bed slope, roughness, vegetation) using hydraulic modelling and the information available in the SD observation data (gaugings). Discharge time series are estimated by propagating stage records through the posterior rating curve results. Here we apply this novel framework to a Swedish hydrometric station, accounting for uncertainties in the gaugings and the parameters of the hydraulic model. The aim of this study was to assess the impact of using only three gaugings for calibrating the hydraulic model on resultant uncertainty estimations within our framework. The results were compared to prior knowledge, discharge measurements and official discharge estimations and showed the potential of hydraulically-modelled rating curves for assessing uncertainty at high and medium flows, while uncertainty at low flows remained high. Uncertainty results estimated using only three gaugings for the studied site were smaller than ±15% for medium and high flows and reduced the prior uncertainty by a factor of ten on average and were estimated with only 3 gaugings.

Rescue of groundwater level time series: how to identify and treat errors

2021 ◽  
Author(s):  
Jānis Bikše ◽  
Inga Retike ◽  
Andis Kalvāns ◽  
Aija Dēliņa ◽  
Alise Babre ◽  
...  
Keyword(s):  
Time Series ◽  
Groundwater Level ◽  
Monitoring Network ◽  
Observation Data ◽  
Automatic Data ◽  
Mean Values ◽  
Temporal Prediction ◽  
National Monitoring ◽  
Groundwater Drought

<p>Groundwater level time series are the basis for various groundwater-related studies. The most valuable are long term, gapless and evenly spatially distributed datasets. However, most historical datasets have been acquired during a long-term period by various operators and database maintainers, using different data collection methods (manual measurements or automatic data loggers) and usually contain gaps and errors, that can originate both from measurement process and data processing. The easiest way is to eliminate the time series with obvious errors from further analysis, but then most of the valuable dataset may be lost, decreasing spatial and time coverage. Some gaps can be easily replaced by traditional methods (e.g. by mean values), but filling longer observation gaps (missing months, years) is complicated and often leads to false results. Thus, an effort should be made to retain as much as possible actual observation data.</p><p>In this study we present (1) most typical data errors found in long-term groundwater level monitoring datasets, (2) provide techniques to visually identify such errors and finally, (3) propose best ways of how to treat such errors. The approach also includes confidence levels for identification and decision-making process. The aim of the study was to pre-treat groundwater level time series obtained from the national monitoring network in Latvia for further use in groundwater drought modelling studies.</p><p>This research is funded by the Latvian Council of Science, project “Spatial and temporal prediction of groundwater drought with mixed models for multilayer sedimentary basin under climate change”, project No. lzp-2019/1-0165.</p>

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