scholarly journals Towards improved analysis of short mesoscale sea level signals from satellite altimetry

2021 ◽  
Author(s):  
Yves Quilfen ◽  
Jean-François Piolle ◽  
Bertrand Chapron
Keyword(s):  
Sea Level ◽  
Signal To Noise Ratio ◽  
Ocean Dynamics ◽  
Small Scale ◽  
Noise Filtering ◽  
Signal To Noise ◽  
Data Set ◽  
Noise Ratio ◽  
Filter Noise ◽  
Along Track

Abstract. Satellite altimeters routinely supply sea surface height (SSH) measurements, which are key observations for monitoring ocean dynamics. However, below a wavelength of about 70 km, along-track altimeter measurements are often characterized by a dramatic drop in signal-to-noise ratio, making it very challenging to fully exploit the available altimeter observations to precisely analyze small mesoscale variations in SSH. Although various approaches have been proposed and applied to identify and filter noise from measurements, no distinct methodology has emerged for systematic application in operational products. To best address this unresolved issue, the Copernicus Marine Environment Monitoring Service (CMEMS) actually provides simple band-pass filtered data to mitigate noise contamination of along-track SSH signals. More innovative and suitable noise filtering methods are thus left to users seeking to unveil small-scale altimeter signals. As demonstrated here, a fully data-driven approach is developed and applied successfully to provide robust estimates of noise-free Sea Level Anomaly (SLA) signals. The method combines Empirical Mode Decomposition (EMD), to help analyze non-stationary and non-linear processes, and an adaptive noise filtering technique inspired by Discrete Wavelet Transform (DWT) decompositions. It is found to best resolve the distribution of SLA variability in the 30–120 km mesoscale wavelength band. A practical uncertainty variable is attached to the denoised SLA estimates that accounts for errors related to the local signal-to-noise ratio, but also for uncertainties in the denoising process, which assumes that the SLA variability results in part from a stochastic process. For the available period, measurements from the Jason-3, Sentinel-3 and Saral/AltiKa missions are processed and analyzed, and their energy spectral and seasonal distributions characterized in the small mesoscale domain. In anticipation of the upcoming SWOT (Surface Water and Ocean Topography) mission data, the SASSA data set (Satellite Altimeter Short-scale Signals Analysis, Quilfen and Piolle, 2021) of denoised SLA measurements for three reference altimeter missions already yields valuable opportunities to evaluate global small mesoscale kinetic energy distributions.

scholarly journals High Radio Frequency Studies of Equatorial and Southern AGN

1996 ◽  
Vol 175 ◽  
pp. 99-100
Author(s):  
M. Tornikoski ◽  
E. Valtaoja
Keyword(s):  
Radio Frequency ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Data Set ◽  
Noise Ratio

The Swedish-ESO Submillimetre Telescope (SEST) has been used for the high radio frequency observations of our group's AGN monitoring projects since the end of 1987.Our SEST results from October 1987 until June 1994 will be published in A&AS (in press); the data will be available electronically. The data set consists of 155 sources with the signal-to-noise -ratio of at least one observation (at 90 or 230 GHz) ≥ 4.

scholarly journals Noise reduction with reflection supervirtual interferometry

Geophysics ◽  
2020 ◽  
Vol 85 (3) ◽  
pp. V249-V256
Author(s):  
Kai Lu ◽  
Zhaolun Liu ◽  
Sherif Hanafy ◽  
Gerard Schuster
Keyword(s):  
Noise Reduction ◽  
Field Data ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Data Set ◽  
Reflection Data ◽  
The Poor ◽  
The Earth ◽  
The Common ◽  
Noise Ratio

To image deeper portions of the earth, geophysicists must record reflection data with much greater source-receiver offsets. The problem with these data is that the signal-to-noise ratio (S/N) significantly diminishes with greater offset. In many cases, the poor S/N makes the far-offset reflections imperceptible on the shot records. To mitigate this problem, we have developed supervirtual reflection interferometry (SVI), which can be applied to far-offset reflections to significantly increase their S/N. The key idea is to select the common pair gathers where the phases of the correlated reflection arrivals differ from one another by no more than a quarter of a period so that the traces can be coherently stacked. The traces are correlated and summed together to create traces with virtual reflections, which in turn are convolved with one another and stacked to give the reflection traces with much stronger S/Ns. This is similar to refraction SVI except far-offset reflections are used instead of refractions. The theory is validated with synthetic tests where SVI is applied to far-offset reflection arrivals to significantly improve their S/N. Reflection SVI is also applied to a field data set where the reflections are too noisy to be clearly visible in the traces. After the implementation of reflection SVI, the normal moveout velocity can be accurately picked from the SVI-improved data, leading to a successful poststack migration for this data set.

scholarly journals A backward encoding approach to recover subcortical auditory activity

2019 ◽  
Author(s):  
Fabian Schmidt ◽  
Gianpaolo Demarchi ◽  
Florian Geyer ◽  
Nathan Weisz
Keyword(s):  
Signal To Noise Ratio ◽  
Auditory Pathway ◽  
Auditory Brainstem ◽  
Signal To Noise ◽  
Spatial Filters ◽  
Data Set ◽  
Stimulation Rate ◽  
Spatial Coverage ◽  
Brainstem Response ◽  
Noise Ratio

1.AbstractSeveral subcortical nuclei along the auditory pathway are involved in the processing of sounds. One of the most commonly used methods of measuring the activity of these nuclei is the auditory brainstem response (ABR). Due to its low signal-to-noise ratio, ABR’s have to be derived by averaging over thousands of artificial sounds such as clicks or tone bursts. This approach cannot be easily applied to natural listening situations (e.g. speech, music), which limits auditory cognitive neuroscientific studies to investigate mostly cortical processes.We propose that by training a backward encoding model to reconstruct evoked ABRs from high-density electrophysiological data, spatial filters can be tuned to auditory brainstem activity. Since these filters can be applied (i.e. generalized) to any other data set using the same spatial coverage, this could allow for the estimation of auditory brainstem activity from any continuous sensor level data. In this study, we established a proof-of-concept by using a backward encoding model generated using a click stimulation rate of 30 Hz to predict ABR activity recorded using EEG from an independent measurement using a stimulation rate of 9 Hz. We show that individually predicted and measured ABR’s are highly correlated (r ∼ 0.7). Importantly these predictions are stable even when applying the trained backward encoding model to a low number of trials, mimicking a situation with an unfavorable signal-to-noise ratio. Overall, this work lays the necessary foundation to use this approach in more interesting listening situations.

scholarly journals Analisa Perbandingan Adaptif Median Filter Dan Median Filter Dalam Reduksi Noise Salt & Pepper

2016 ◽  
Vol 2 (2) ◽  
pp. 157 ◽  
Author(s):  
Ivan Maulana ◽  
Pulung Nurtantio Andono
Keyword(s):  
Signal To Noise Ratio ◽  
Median Filter ◽  
Signal To Noise ◽  
Noise Ratio ◽  
Filter Noise ◽  
Audio Video

Suatu data atau informasi disajikan tidak hanya berupa data teks tetapi juga dapat berupa audio, video, dan gambar. Pada zaman sekarang informasi sangatlah penting dan diperlukan, begitu juga informasi yang terdapat pada citra. Citra (image) atau istilah lain untuk gambar merupakan salah satu komponen multimedia yang berperan penting sebagai bentuk informasi visual. Dibandingkan dengan data teks, citra memiliki banyak informasi. Namun terkadang citra juga dapat mengalami penurunan yaitu degradasi atau penurunan kualitas yang disebabkan oleh derau / noise, warna terlalu kontras, kabur, dan lain-lain. Ada beberapa jenis noise dalam pengolahan citra salah satunya yaitu Salt & Pepper noise. Noise Salt & Pepper berbentuk seperti bintik hitam dan putih pada citra. Untuk mengurangi noise ini dibutuhkan suatu metode, salah satunya yaitu median filter. Metode yang digunakan pada penelitian ini adalah median filter dan adaptif median filter. Perbedaan mendasar antara kedua metode ini yaitu pada besarnya windows pada adaptif median filter adalah variabel. Dari hasil penelitian, citra yang menggunakan metode adaptif median filter lebih baik daripada median filter. Dari perhitungan Peak Signal to Noise Ratio (PSNR) citra yang menggunakan adaptif median filter mendapatkan 29,2495 dB sedangkan median filter mendapatkan 23,8181 dB.Kata Kunci: Median filter, Adaptif Median filter, Noise salt & pepper, PSNR

scholarly journals The Effect of Signal-to-Noise Ratio on the Study of Sea Level Trends

2011 ◽  
Vol 24 (5) ◽  
pp. 1396-1408 ◽  
Author(s):  
B. D. Hamlington ◽  
R. R. Leben ◽  
R. S. Nerem ◽  
K.-Y. Kim
Keyword(s):  
Least Squares ◽  
Sea Level ◽  
Least Squares Method ◽  
Secular Trend ◽  
Signal To Noise Ratio ◽  
Empirical Orthogonal Functions ◽  
Signal To Noise ◽  
Orthogonal Functions ◽  
Geophysical Processes ◽  
Noise Ratio

Abstract Extracting secular sea level trends from the background ocean variability is limited by how well one can correct for the time-varying and oscillating signals in the record. Many geophysical processes contribute time-dependent signals to the data, making the sea level trend difficult to detect. In this paper, cyclostationary empirical orthogonal functions (CSEOFs) are used to quantify and improve the signal-to-noise ratio (SNR) between the secular trend and the background variability, obscuring this trend in the altimetric sea level record by identifying and removing signals that are physically interpretable. Over the 16-yr altimetric record the SNR arising from the traditional least squares method for estimating trends can be improved from 4.0% of the ocean having an SNR greater than one to 9.9% when using a more sophisticated statistical method based on CSEOFs. From a standpoint of signal detection, this implies that the secular trend in a greater portion of the ocean can be estimated with a higher degree of confidence. Furthermore, the CSEOF method improves the standard error on the least squares estimates of the secular trend in 97% of the ocean. The convergence of the SNR as the record length is increased is used to estimate the SNR of sea level trends in the near future as more measurements become available from near-global altimetric sampling.

scholarly journals Temporal Behavior of Solar P-Modes from Gong and Golf Experiments

1998 ◽  
Vol 185 ◽  
pp. 227-228
Author(s):  
V.G. Gavryusev ◽  
E.A. Gavryuseva
Keyword(s):  
Time Series ◽  
Signal To Noise Ratio ◽  
Temporal Behavior ◽  
The Sun ◽  
Solar Oscillations ◽  
Signal To Noise ◽  
Data Set ◽  
Noise Ratio

We used the measurements of solar oscillations taken by GONG and GOLF experiments. The first set of data are the integrated images obtained from the complex GONG observations taken from June 10 of 1995 to January 7 of 1997, 578 days in total, referenced below as ts0 time series. Radial, dipole and quadrupole modes are well visible in this time series. The second data set is the GOLF time series obtained on-board SOHO mission from April 11, 1996 to June 22, 1997. GOLF observes the “Sun as a star”. This time series is similar to ts0 of GONG but of a better quality (better signal-to-noise ratio; uniform, practically uninterrupted data). Both experiments are significantly overlapped in time. Because of this the direct comparison between them is possible, and the effects visible in both observations support each other.

scholarly journals VHF signal power suppression in stratiform and convective precipitation

2006 ◽  
Vol 24 (1) ◽  
pp. 23-35 ◽  
Author(s):  
A. J. McDonald ◽  
K. P. Monahan ◽  
D. A. Hooper ◽  
C. Gaffard
Keyword(s):  
Signal To Noise Ratio ◽  
Convective Precipitation ◽  
Small Scale ◽  
Signal Power ◽  
Signal To Noise ◽  
Bright Band ◽  
Signal Suppression ◽  
Stratiform Precipitation ◽  
Noise Ratio

Abstract. Previous studies have indicated that VHF clear-air radar return strengths are reduced during periods of precipitation. This study aims to examine whether the type of precipitation, stratiform and convective precipitation types are identified, has any impact on the relationships previously observed and to examine the possible mechanisms which produce this phenomenon. This study uses a combination of UHF and VHF wind-profiler data to define periods associated with stratiform and convective precipitation. This identification is achieved using an algorithm which examines the range squared corrected signal to noise ratio of the UHF returns for a bright band signature for stratiform precipitation. Regions associated with convective rainfall have been defined by identifying regions of enhanced range corrected signal to noise ratio that do not display a bright band structure and that are relatively uniform until a region above the melting layer. This study uses a total of 68 days, which incorporated significant periods of surface rainfall, between 31 August 2000 and 28 February 2002 inclusive from Aberystwyth (52.4° N, 4.1° W). Examination suggests that both precipitation types produce similar magnitude reductions in VHF signal power on average. However, the frequency of occurrence of statistically significant reductions in VHF signal power are very different. In the altitude range 2-4 km stratiform precipitation is related to VHF signal suppression approximately 50% of the time while in convective precipitation suppression is observed only 27% of the time. This statistical result suggests that evaporation, which occurs more often in stratiform precipitation, is important in reducing the small-scale irregularities in humidity and thereby the radio refractive index. A detailed case study presented also suggests that evaporation reducing small-scale irregularities in humidity may contribute to the observed VHF signal suppression.

The value of constrained conjugate-gradient least-squares migration in seismic inversion: Application to a fractured-basement play, Texas Panhandle

2017 ◽  
Vol 5 (3) ◽  
pp. SN13-SN23 ◽  
Author(s):  
Thang Ha ◽  
Kurt Marfurt
Keyword(s):  
Least Squares ◽  
Signal To Noise Ratio ◽  
Seismic Inversion ◽  
High Signal ◽  
Radon Transforms ◽  
Signal To Noise ◽  
Data Set ◽  
Texas Panhandle ◽  
Noise Ratio ◽  
Least Squares Migration

Seismic inversion has become almost routine in quantitative 3D seismic interpretation. To ensure the quality of the seismic inversion, the input seismic data need to have a high signal-to-noise ratio. With the current low oil price environment, seismic reprocessing is often preferred over reacquisition to improve data quality. Common filter pairs include forward and inverse [Formula: see text]-[Formula: see text] and Radon transforms. Forward and inverse migrations (i.e., migration and demigration) are a more recently introduced transform pair that, when used together in an iterative workflow, results in a least-squares migration algorithm. Least-squares migration compensates for surface variation in data density and, when combined with a filter applied to prestack migrated images, suppresses the operator and data aliasing. We apply a least-squares migration workflow to a fractured-basement data set from the Texas Panhandle to demonstrate the enhancement in signal-to-noise ratio, the reduction in acquisition footprint and migration artifacts, and the improvement in the P-impedance inversion result.

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