scholarly journals The Slichter mode of the Earth: Revisit with optimal stacking and autoregressive methods on full superconducting gravimeter data set

2015 ◽  
Vol 120 (10) ◽  
pp. 7261-7272 ◽  
Author(s):  
Hao Ding ◽  
Benjamin F. Chao
Keyword(s):  
Superconducting Gravimeter ◽  
Data Set ◽  
The Earth ◽  
Slichter Mode

scholarly journals An efficient technique for CT scan images classification of COVID-19

2020 ◽  
pp. 1-14
Author(s):  
Esraa Hassan ◽  
Noha A. Hikal ◽  
Samir Elmuogy
Keyword(s):  
Neural Network ◽  
Diagnostic Tool ◽  
Deep Neural Network ◽  
Data Augmentation ◽  
Performance Metrics ◽  
Classification Model ◽  
Data Set ◽  
Training Models ◽  
The Earth ◽  
Diagnostic Time

Nowadays, Coronavirus (COVID-19) considered one of the most critical pandemics in the earth. This is due its ability to spread rapidly between humans as well as animals. COVID_19 expected to outbreak around the world, around 70 % of the earth population might infected with COVID-19 in the incoming years. Therefore, an accurate and efficient diagnostic tool is highly required, which the main objective of our study. Manual classification was mainly used to detect different diseases, but it took too much time in addition to the probability of human errors. Automatic image classification reduces doctors diagnostic time, which could save human’s life. We propose an automatic classification architecture based on deep neural network called Worried Deep Neural Network (WDNN) model with transfer learning. Comparative analysis reveals that the proposed WDNN model outperforms by using three pre-training models: InceptionV3, ResNet50, and VGG19 in terms of various performance metrics. Due to the shortage of COVID-19 data set, data augmentation was used to increase the number of images in the positive class, then normalization used to make all images have the same size. Experimentation is done on COVID-19 dataset collected from different cases with total 2623 where (1573 training,524 validation,524 test). Our proposed model achieved 99,046, 98,684, 99,119, 98,90 In terms of Accuracy, precision, Recall, F-score, respectively. The results are compared with both the traditional machine learning methods and those using Convolutional Neural Networks (CNNs). The results demonstrate the ability of our classification model to use as an alternative of the current diagnostic tool.

scholarly journals Normalized nonzero-lag crosscorrelation elastic full-waveform inversion

Geophysics ◽  
2019 ◽  
Vol 84 (1) ◽  
pp. R1-R10 ◽  
Author(s):  
Zhendong Zhang ◽  
Tariq Alkhalifah ◽  
Zedong Wu ◽  
Yike Liu ◽  
Bin He ◽  
...  
Keyword(s):  
Field Data ◽  
Extreme Values ◽  
Time Lag ◽  
Waveform Inversion ◽  
Optimal Time ◽  
Full Waveform Inversion ◽  
Data Set ◽  
Velocity Models ◽  
Full Waveform ◽  
The Earth

Full-waveform inversion (FWI) is an attractive technique due to its ability to build high-resolution velocity models. Conventional amplitude-matching FWI approaches remain challenging because the simplified computational physics used does not fully represent all wave phenomena in the earth. Because the earth is attenuating, a sample-by-sample fitting of the amplitude may not be feasible in practice. We have developed a normalized nonzero-lag crosscorrelataion-based elastic FWI algorithm to maximize the similarity of the calculated and observed data. We use the first-order elastic-wave equation to simulate the propagation of seismic waves in the earth. Our proposed objective function emphasizes the matching of the phases of the events in the calculated and observed data, and thus, it is more immune to inaccuracies in the initial model and the difference between the true and modeled physics. The normalization term can compensate the energy loss in the far offsets because of geometric spreading and avoid a bias in estimation toward extreme values in the observed data. We develop a polynomial-type weighting function and evaluate an approach to determine the optimal time lag. We use a synthetic elastic Marmousi model and the BigSky field data set to verify the effectiveness of the proposed method. To suppress the short-wavelength artifacts in the estimated S-wave velocity and noise in the field data, we apply a Laplacian regularization and a total variation constraint on the synthetic and field data examples, respectively.

Monitoring the Ocean Heat Content and the Earth Energy imbalance from space altimetry and space gravimetry: the MOHeaCAN product

2021 ◽  
Author(s):  
Marti Florence ◽  
Ablain Michaël ◽  
Fraudeau Robin ◽  
Jugier Rémi ◽  
Meyssignac Benoît ◽  
...  
Keyword(s):  
Time Scales ◽  
Radiant Energy ◽  
Heat Content ◽  
Ocean Heat Content ◽  
Global Ocean ◽  
Argo Data ◽  
Data Set ◽  
Energy Imbalance ◽  
Temporal Sampling ◽  
The Earth

<p>The Earth Energy Imbalance (EEI) is a key indicator to understand climate change. However, measuring this indicator is challenging since it is a globally integrated variable whose variations are small, of the order of several tenth of W.m<sup>-2</sup>, compared to the amount of energy entering and leaving the climate system of ~340 W.m<sup>-2</sup>. Recent studies suggest that the EEI response to anthropogenic GHG and aerosols emissions is 0.5-1 W.m<sup>-2</sup>. It implies that an accuracy of <0.3 W.m<sup>-2</sup> at decadal time scales is necessary to evaluate the long term mean EEI associated with anthropogenic forcing. Ideally an accuracy of <0.1 W.m<sup>-2</sup> at decadal time scales is desirable if we want to monitor future changes in EEI.</p><p>In the frame of the MOHeaCAN project supported by ESA, the EEI indicator is deduced from the global change in Ocean Heat Content (OHC) which is a very good proxy of the EEI since the ocean stores 93% of the excess of heat  gained by the Earth in response to EEI. The OHC is estimated from space altimetry and gravimetry missions (GRACE). This “Altimetry-Gravimetry'' approach is promising because it provides consistent spatial and temporal sampling of the ocean, it samples nearly the entire global ocean, except for polar regions, and it provides estimates of the OHC over the ocean’s entire depth. Consequently, it complements the OHC estimation from the ARGO network. </p><p>The MOHeaCAN product contains monthly time series (between August 2002 and June 2017) of several variables, the main ones being the regional OHC (3°x3° spatial resolution grids), the global OHC and the EEI indicator. Uncertainties are provided for variables at global scale, by propagating errors from sea level measurements (altimetry) and ocean mass content (gravimetry). In order to calculate OHC at regional and global scales, a new estimate of the expansion efficiency of heat at global and regional scales have been performed based on the global ARGO network. </p><p>A scientific validation of the MOHeaCAN product has also been carried out performing thorough comparisons against independent estimates based on ARGO data and on the Clouds and the Earth’s Radiant energy System (CERES) measurements at the top of the atmosphere. The mean EEI derived from MOHeaCAN product is 0.84 W.m<sup>-2</sup> over the whole period within an uncertainty of ±0.12 W.m<sup>-2</sup> (68% confidence level - 0.20 W.m<sup>-2</sup> at the 90% CL). This figure is in agreement (within error bars at the 90% CL) with other EEI indicators based on ARGO data (e.g. OHC-OMI from CMEMS) although the best estimate is slightly higher. Differences from annual to inter-annual scales have also been observed with ARGO and CERES data. Investigations have been conducted to improve our understanding of the benefits and limitations of each data set to measure EEI at different time scales.</p><p><strong>The MOHeaCAN product from “altimetry-gravimetry” is now available</strong> and can be downloaded at https://doi.org/10.24400/527896/a01-2020.003. Feedback from interested users on this product are welcome.</p>

scholarly journals Heights of SuperDARN F region echoes estimated from the analysis of HF radio wave propagation

2007 ◽  
Vol 25 (9) ◽  
pp. 1987-1994 ◽  
Author(s):  
A. V. Koustov ◽  
D. André ◽  
E. Turunen ◽  
T. Raito ◽  
S. E. Milan
Keyword(s):  
Electron Density ◽  
Hf Radar ◽  
Field Of View ◽  
Data Set ◽  
Density Distributions ◽  
F Region ◽  
The Earth ◽  
Earth Magnetic Field ◽  
Field Lines ◽  
Radar Wave

Abstract. Tomographic estimates of the electron density altitudinal and latitudinal distribution within the Hankasalmi HF radar field of view are used to predict the expected heights of F region coherent echoes by ray tracing and finding ranges of radar wave orthogonality with the Earth magnetic field lines. The predicted ranges of echoes are compared with radar observations concurrent with the tomographic measurements. Only those events are considered for which the electron density distributions were smooth, the band of F region HF echoes existed at ranges 700–1500 km, and there was a reasonable match between the expected and measured slant ranges of echoes. For a data set comprising of 82 events, the typical height of echoes was found to be 275 km.

scholarly journals On the Chandler periodicity (Polar Motion, LOD and Climate)

2000 ◽  
Vol 178 ◽  
pp. 397-402
Author(s):  
F. Buffa ◽  
A. Poma
Keyword(s):  
Time Series ◽  
Polar Motion ◽  
Superconducting Gravimeter ◽  
Spin Axis ◽  
Rainfall Time Series ◽  
Observation Level ◽  
Motion Data ◽  
The Earth ◽  
Chandler Period ◽  
Free Nutation

AbstractThe 14-month Chandler period is associated with the free nutation of the Earth about its spin axis. The observed value of the Chandler period comes usually from the analysis of astronomical series of polar motion data as well as from superconducting gravimeter measurements. At the observation level a periodicity of about 420–440 days also was noticed in microseismic activities. Recently we found evidence of a signal with period similar to the Chandler one in the Sardinia rainfall time series.

scholarly journals MODEL INDEPENDENT CONSTRAINTS ON NON-ELECTRONIC FLAVORS IN THE SOLAR BORON NEUTRINO FLUX

2006 ◽  
Vol 21 (22) ◽  
pp. 1761-1768 ◽  
Author(s):  
S. DEV ◽  
SANJEEV KUMAR ◽  
SURENDER VERMA
Keyword(s):  
General Model ◽  
Sterile Neutrino ◽  
Neutrino Flux ◽  
Flux Measurement ◽  
Data Set ◽  
The Earth ◽  
Independent Analysis ◽  
Antineutrino Flux ◽  
Model Independent ◽  
Salt Phase

We perform the most general model-independent analysis of the latest 391-Day Salt Phase SNO Data Set incorporating the super-Kamiokande ES flux measurement and obtain bounds on the antineutrino and sterile neutrino flux in the solar 8 B neutrino flux reaching the detectors on the earth. The muon/tauon antineutrino flux is found to be disallowed at 1.4σ C.L. The sterile flux is found to be nonzero at about 1.26 standard deviations.

The Magnetics Information Consortium (MagIC) Data Repository: Successes and Continuing Challenges

2020 ◽  
Author(s):  
Nicholas Jarboe ◽  
Rupert Minnett ◽  
Catherine Constable ◽  
Anthony Koppers ◽  
Lisa Tauxe
Keyword(s):  
Earth Science ◽  
Journal Article ◽  
Research Capacity ◽  
Digital Data ◽  
Data Repository ◽  
Data Set ◽  
Data Repositories ◽  
The Earth ◽  
Ocean Sciences ◽  
Space Sciences

<p>MagIC (earthref.org/MagIC) is an organization dedicated to improving research capacity in the Earth and Ocean sciences by maintaining an open community digital data archive for rock and paleomagnetic data with portals that allow users access to archive, search, visualize, download, and combine these versioned datasets. We are a signatory of the Coalition for Publishing Data in the Earth and Space Sciences (COPDESS)'s Enabling FAIR Data Commitment Statement and an approved repository for the Nature set of journals. We have been in collaboration with EarthCube's GeoCodes data search portal, adding schema.org/JSON-LD headers to our data set landing pages and suggesting extensions to schema.org when needed. Collaboration with the European Plate Observing System (EPOS)'s Thematic Core Service Multi-scale laboratories (TCS MSL) is ongoing with MagIC sending its contributions' metadata to TCS MSL via DataCite records.</p><p>Improving and updating our data repository to meet the demands of the quickly changing landscape of data archival, retrieval, and interoperability is a challenging proposition. Most journals now require data to be archived in a "FAIR" repository, but the exact specifications of FAIR are still solidifying. Some journals vet and have their own list of accepted repositories while others rely on other organizations to investigate and certify repositories. As part of the COPDESS group at Earth Science Information Partners (ESIP), we have been and will continue to be part of the discussion on the needed and desired features for acceptable data repositories.</p><p>We are actively developing our software and systems to meet the needs of our scientific community. Some current issues we are confronting are: developing workflows with journals on how to publish the journal article and data in MagIC simultaneously, sustainability of data repository funding especially in light of the greater demands on them due to data policy changes at journals, and how to best share and expose metadata about our data holdings to organizations such as EPOS, EarthCube, and Google.</p>

scholarly journals A 2003 stratospheric aerosol extinction and PSC climatology from GOMOS measurements on Envisat

2005 ◽  
Vol 5 (1) ◽  
pp. 863-874
Author(s):  
F. Vanhellemont ◽  
D. Fussen ◽  
C. Bingen ◽  
E. Kyrölä ◽  
J. Tamminen ◽  
...  
Keyword(s):  
Ozone Depletion ◽  
Stratospheric Aerosol ◽  
Atmospheric Dynamics ◽  
The Other ◽  
Aerosol Extinction ◽  
Extinction Data ◽  
Data Set ◽  
The Earth ◽  
Antarctic Ozone ◽  
Stratospheric Clouds

Abstract. Stratospheric aerosols play an important role in a number of atmospheric issues such as midlatitude ozone depletion, atmospheric dynamics and the Earth radiative budget. Polar stratospheric clouds on the other hand are a crucial factor in the yearly Arctic 5 and Antarctic ozone depletion. It is therefore important to quantify the stratospheric aerosol/PSC abundance. In orbit since March 2002, the GOMOS instrument onboard the European Envisat satellite has provided a vast aerosol extinction data set. In this paper we present an aerosol/PSC climatology that was constructed from this data set, together with a discussion of the results.

scholarly journals The Catastrophe of the Niedów Dam—The Causes of the Dam’s Breach, Its Development, and Consequences

Water ◽  
2021 ◽  
Vol 13 (22) ◽  
pp. 3254
Author(s):  
Stanisław Kostecki ◽  
Robert Banasiak
Keyword(s):  
Extreme Rainfall ◽  
Iterative Solution ◽  
Numerical Approach ◽  
Flood Event ◽  
Dam Breach ◽  
Data Set ◽  
Local Conditions ◽  
The Earth ◽  
Rapid Release ◽  
Downstream Area

Due to extreme rainfall in 2010 in the Lusatian Neisse River catchment area (in Poland), a flood event with a return period of over 100 years occurred, leading to the failure of the Niedów dam. The earth-type dam constructed for cooling the Turów power plant was washed away, resulting in the rapid release of nearly 8.5 million m3 of water and the flooding of the downstream area with substantial material losses. Here we analyze the conditions and causes of the dam’s failure, with special attention given to the mechanism and dynamics of the compound breaching process, in which the dam’s upstream slope reinforcement played a specific and remarkable role. The paper also describes a numerical approach for simulating a combined flood event downstream from the dam with the use of a two-dimensional hydrodynamic model (MIKE21). Considering the specific local conditions, i.e., wide floodplain, meandering character of the main channel, embankment overtopping, and available data set, an iterative solution of the unsteady state problem is proposed. This approach enables realistic flood propagation estimates to be delivered, the dam breach outflow to be reconstructed, and several important answers concerning the consequences of the dam’s failure to be provided. Finally, the paper presents the reconstruction of the dam that is more resilient to extreme hydrological conditions under changing climate.

GRACE-FO accelerometer data: An alternative approach using Least Squares Spectral Analysis

2021 ◽  
Author(s):  
Myrto Tzamali ◽  
Spiros Pagiatakis
Keyword(s):  
Magnetic Field ◽  
Least Squares ◽  
Frequency Domain ◽  
Gravity Field ◽  
Thermal Sensitivity ◽  
Accelerometer Data ◽  
Data Set ◽  
The Earth ◽  
Gravity Field Models ◽  
The Magnetic Field

<p>Technological advances in satellite geodesy have been demanding more and more accurate gravity field models but also precise measurements of the movement of water along the Earth system. GRACE-FO (GFO) mission is dedicated to monitor the Earth with a purpose of estimating the gravity field and the hydrological cycles. For the extraction of monthly gravity field models the non-gravitational accelerations are essential. The performance of GFO accelerometers (ACC) is not the optimal.  The ACC measurements present immense spikes, spurious signals and bias jumps on all three axes affecting the validity of the measurements. The bias jumps are similar to those presented at GRACE measurements and they have been related to the satellites’ entrance to and exit from the Earth’s shadow. The dominant spikes, mainly appearing in the equatorial region, have been connected to the thermal sensitivity of the instrument or the orientation of the magnetic field lines. We propose an alternative dataset generated from Level 1A of GFO C with corresponding Gaussian weights and an optimal correction of the bias jumps, along with the estimation of linear and quadratic trends using the Least Squares methodology in the frequency domain and in all three axes. The method does not remove spikes, nor does it interpolate missing values. The new 1B dataset with estimated variances shows no spike effects in the frequency domain contrastingly to the existing ACT Level 1B data. Also, a preliminary analysis of the daily amplitudes of the orbital period and semi-period components of the ACT Level 1B data set spanning one year, reveals a strong periodic signal of ~ 153 days. This signal vanishes when the proposed weighted data set is used. This signal could be related to calibration deficiencies or a systematic error in the ACC data that requires further study. The same weighted filtering approach is proposed for the ACC measurements of Swarm C satellite, a LEO constellation that measures the magnetic field of the Earth. The ACC measurements of Swarm display low signal to noise ratio due to an increased thermal sensitivity of the instrument. A weighted Gaussian filter applied on the Swarm ACC measurements reduces the contribution of the dominant spikes in the frequency domain and displays the non-gravitational signals more clearly leading to a more extended use of Swarm non-gravitational accelerations measurements.</p>

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