Comparison of ERA40 and NCEP/DOE near-surface data sets with other ISLSCP-II data sets

2006 ◽  
Vol 111 (D22) ◽  
Author(s):  
Alan K. Betts ◽  
Mei Zhao ◽  
P. A. Dirmeyer ◽  
A. C. M. Beljaars
Keyword(s):  
Data Sets ◽  
Near Surface ◽  
Surface Data

Shear and compressive wave data acquisition using multicomponent vibrating source and landstreamer

2021 ◽  
Author(s):  
Andre Pugin ◽  
Barbara Dietiker ◽  
Kevin Brewer ◽  
Timothy Cartwright
Keyword(s):  
Leading Edge ◽  
Data Sets ◽  
Compressive Wave ◽  
Near Surface ◽  
Source Type ◽  
Receiver Array ◽  
Surface Data ◽  
Source Orientation ◽  
Refracted Waves ◽  
Wave Modes

<p>In the vicinity of Ottawa, Ontario, Canada, we have recorded many multicomponent seismic data sets using an in-house multicom­ponent vibrator source named Microvibe and a landstreamer receiver array with 48 3-C 28-Hz geophones at 0.75-m intervals. The receiver spread length was 35.25 m, and the near-offset was 1.50 m. We used one, two or three source and three receiver orientations — vertical (V), inline-horizontal (H1), and transverse-horizontal (H2). We identified several reflection wave modes in the field records — PP, PS, SP, and SS, in addition to refracted waves, and Rayleigh-mode and Love-mode surface waves. We computed the semblance spectra of the selected shot records and ascertained the wave modes based on the semblance peaks. We then performed CMP stacking of each of the 9-C data sets using the PP and SS stacking velocities to compute PP and SS reflection profiles.</p><p>Despite the fact that any source type can generate any combination of wave modes — PP, PS, SP, and SS, partitioning of the source energy depends on the source orientation and VP/VS ratio. Our examples demonstrate that the most prominent PP reflection energy is recorded by the VV source-receiver orientation, whereas the most prominent SS reflection energy is recorded by the H2H2 source-receiver orientation with possibility to obtain decent shear wave near surface data in all other vibrating and receiving directions.</p><p>Pugin, Andre and Yilmaz, Öz, 2019. Optimum source-receiver orientations to capture PP, PS, SP, and SS reflected wave modes. The Leading Edge, vol. 38/1, p. 45-52. https://doi.org/10.1190/tle38010045.1</p>

scholarly journals The influence of surface gravity waves on the injection of turbulence in the upper ocean

2014 ◽  
Vol 21 (3) ◽  
pp. 713-733 ◽  
Author(s):  
M. Bakhoday Paskyabi ◽  
I. Fer
Keyword(s):  
Gravity Waves ◽  
Surface Gravity ◽  
Data Sets ◽  
Langmuir Circulation ◽  
Data Set ◽  
Near Surface ◽  
Wave Forcing ◽  
Surface Gravity Waves ◽  
Surface Data ◽  
Closure Scheme

Abstract. Observations were made in the near-surface layer, at about 8 m depth in 132 m deep water off the coast of Ålesund in Norway, for a duration of 2.5 months in late 2011. The measurement period covers the passage of two low pressure systems with substantial wind and wave forcing. The time series of the dissipation rate of turbulent kinetic energy, ε, and the estimates of surface gravity waves are analysed. Dissipation rates varied by 5 orders of magnitude and reached 10-5–10-4 W kg−1 in conditions when wind speed exceeded 15 m s−1 and the significant wave height was of the order of 10 m. The data set suggests substantial injection of turbulence from breaking surface gravity waves and Langmuir turbulence. To support and interpret the observations, numerical calculations are conducted using a second-order turbulence closure scheme based on the Mellor–Yamada level 2.5 scheme, modified to incorporate the near-surface processes such as Langmuir circulation and wave breaking. The results from a run forced by observed wind and wave fields compare favourably with the observations. Comparisons with other near-surface data sets available from the literature lend confidence on our dissipation measurements and the wave-forced simulations.

Seismic diffraction separation in the near-surface: Detection of high contrast voids in unconsolidated soils

Geophysics ◽  
2021 ◽  
pp. 1-72
Author(s):  
Parsa Bakhtiari Rad ◽  
Craig J. Hickey
Keyword(s):  
Soft Soil ◽  
Processing Parameters ◽  
Imaging Method ◽  
Data Sets ◽  
High Contrast ◽  
Near Surface ◽  
Time Migration ◽  
Diffraction Imaging ◽  
Dip Angle ◽  
Scattering Time

Seismic diffractions carry the signature of near-surface high-contrast anomalies and need to be extracted from the data to complement the reflection processing and other geophysical techniques. Since diffractions are often masked by reflections, surface waves and noise, a careful diffraction separation is required as a first step for diffraction imaging. A multiparameter time-imaging method is employed to separate near-surface diffractions. The implemented scheme makes use of the wavefront attributes that are reliable fully data-derived processing parameters. To mitigate the effect of strong noise and wavefield interference in near-surface data, the proposed workflow incorporates two wavefront-based parameters, dip angle and coherence, as additional constraints. The output of the diffraction separation is a time trace-based stacked section that provides the basis for further analysis and applications such as time migration. To evaluate the performance of the proposed wavefront-based workflow, it is applied to two challenging field data sets that were collected over small culverts in very near-surface soft soil environments. The results of the proposed constrained workflow and the existing unconstrained approach are presented and compared. The proposed workflow demonstrates superiority over the existing method by attenuating more reflection and noise, leading to improved diffraction separation. The abundance of unmasked diffractions reveal that the very near-surface is highly scattering. Time migration is carried out to enhance the anomaly detection by focusing of the isolated diffractions. Although strong diffractivity is observed at the approximate location of the targets, there are other diffracting zones observed in the final sections that might bring uncertainties for interpretation.

Data Sets

2013 ◽  
Author(s):  
James B. Elsner ◽  
Thomas H. Jagger
Keyword(s):  
Model Building ◽  
Careful Analysis ◽  
Logical Structure ◽  
Fortran Program ◽  
Data Sets ◽  
Data Set ◽  
Near Surface ◽  
Wind Speeds ◽  
The North ◽  
The One

Hurricane data originate from careful analysis of past storms by operational meteorologists. The data include estimates of the hurricane position and intensity at 6-hourly intervals. Information related to landfall time, local wind speeds, damages, and deaths, as well as cyclone size, are included. The data are archived by season. Some effort is needed to make the data useful for hurricane climate studies. In this chapter, we describe the data sets used throughout this book. We show you a work flow that includes importing, interpolating, smoothing, and adding attributes. We also show you how to create subsets of the data. Code in this chapter is more complicated and it can take longer to run. You can skip this material on first reading and continue with model building in Chapter 7. You can return here when you have an updated version of the data that includes the most recent years. Most statistical models in this book use the best-track data. Here we describe these data and provide original source material. We also explain how to smooth and interpolate them. Interpolations are needed for regional hurricane analyses. The best-track data set contains the 6-hourly center locations and intensities of all known tropical cyclones across the North Atlantic basin, including the Gulf of Mexico and Caribbean Sea. The data set is called HURDAT for HURricane DATa. It is maintained by the U.S. National Oceanic and Atmospheric Administration (NOAA) at the National Hurricane Center (NHC). Center locations are given in geographic coordinates (in tenths of degrees) and the intensities, representing the one-minute near-surface (∼10 m) wind speeds, are given in knots (1 kt = .5144 m s−1) and the minimum central pressures are given in millibars (1 mb = 1 hPa). The data are provided in 6-hourly intervals starting at 00 UTC (Universal Time Coordinate). The version of HURDAT file used here contains cyclones over the period 1851 through 2010 inclusive. Information on the history and origin of these data is found in Jarvinen et al (1984). The file has a logical structure that makes it easy to read with a FORTRAN program. Each cyclone contains a header record, a series of data records, and a trailer record.

Application of the Logarithmic Phase-Only Inversion to the Near-Surface Data

2018 ◽  
Author(s):  
Y. Choi ◽  
B. Sun ◽  
T. Alkhalifah ◽  
F. Alonaizi ◽  
M. AlMalki
Keyword(s):  
Logarithmic Phase ◽  
Near Surface ◽  
Surface Data

scholarly journals Rapid clay precipitation in explosion-induced fractures

Geology ◽  
2019 ◽  
Vol 47 (12) ◽  
pp. 1176-1180 ◽  
Author(s):  
Erika Swanson ◽  
Aviva Sussman ◽  
Jennifer Wilson
Keyword(s):  
Fold Increase ◽  
Data Sets ◽  
Nuclear Waste Storage ◽  
Near Surface ◽  
Underground Nuclear Explosions ◽  
Nuclear Explosions ◽  
Waste Storage ◽  
Fracture Opening ◽  
Chemical Explosions ◽  
Induced Fractures

Abstract Fractures within the earth control rock strength and fluid flow, but their dynamic nature is not well understood. As part of a series of underground chemical explosions in granite in Nevada, we collected and analyzed microfracture density data sets prior to, and following, individual explosions. Our work shows an ∼4-fold increase in both open and filled microfractures following the explosions. Based on the timing of core retrieval, filling of some new fractures occurs in as little as 6 wk after fracture opening under shallow (<100 m) crustal conditions. These results suggest that near-surface fractures may fill quite rapidly, potentially changing permeability on time scales relevant to oil, gas, and geothermal energy production; carbon sequestration; seismic cycles; and radionuclide migration from nuclear waste storage and underground nuclear explosions.

Interpretation of 3-D effects in long‐offset transient electromagnetic (LOTEM) soundings in the Münsterland area/Germany

Geophysics ◽  
1992 ◽  
Vol 57 (9) ◽  
pp. 1127-1137 ◽  
Author(s):  
Andreas Hördt ◽  
Vladimir L. Druskin ◽  
Leonid A. Knizhnerman ◽  
Kurt‐Martin Strack
Keyword(s):  
Integral Equation ◽  
Thin Sheet ◽  
Three Dimensional ◽  
Equation Modeling ◽  
Data Sets ◽  
Sign Reversal ◽  
Near Surface ◽  
Transient Electromagnetic ◽  
Long Offset ◽  
Geological Situation

The interpretation of long‐offset transient electromagnetic (LOTEM) data is usually based on layered earth models. Effects of lateral conductivity variations are commonly explained qualitatively, because three‐dimensional (3-D) numerical modeling is not readily available for complex geology. One of the first quantitative 3-D interpretations of LOTEM data is carried out using measurements from the Münsterland basin in northern Germany. In this survey area, four data sets show effects of lateral variations including a sign reversal in the measured voltage curve at one site. This sign reversal is a clear indicator of two‐dimensional (2-D) or 3-D conductivity structure, and can be caused by current channeling in a near‐surface conductive body. Our interpretation strategy involves three different 3-D forward modeling programs. A thin‐sheet integral equation modeling routine used with inversion gives a first guess about the location and strike of the anomaly. A volume integral equation program allows models that may be considered possible geological explanations for the conductivity anomaly. A new finite‐difference algorithm permits modeling of much more complex conductivity structures for simulating a realistic geological situation. The final model has the zone of anomalous conductivity aligned below a creek system at the surface. Since the creeks flow along weak zones in this area, the interpretation seems geologically reasonable. The interpreted model also yields a good fit to the data.

3-D imaging of subsurface magnetic permeability/susceptibility with portable frequency domain electromagnetic sensors for near surface exploration

2019 ◽  
Vol 219 (3) ◽  
pp. 1773-1785 ◽  
Author(s):  
Julien Guillemoteau ◽  
François-Xavier Simon ◽  
Guillaume Hulin ◽  
Bertrand Dousteyssier ◽  
Marion Dacko ◽  
...  
Keyword(s):  
Magnetic Permeability ◽  
Field Data ◽  
Large Data ◽  
Archaeological Site ◽  
Phase Response ◽  
Magnetic Method ◽  
Data Sets ◽  
Near Surface ◽  
Inversion Procedure ◽  
Multichannel Deconvolution

SUMMARY The in-phase response collected by portable loop–loop electromagnetic induction (EMI) sensors operating at low and moderate induction numbers (≤1) is typically used for sensing the magnetic permeability (or susceptibility) of the subsurface. This is due to the fact that the in-phase response contains a small induction fraction and a preponderant induced magnetization fraction. The magnetization fraction follows the magneto-static equations similarly to the magnetic method but with an active magnetic source. The use of an active source offers the possibility to collect data with several loop–loop configurations, which illuminate the subsurface with different sensitivity patterns. Such multiconfiguration soundings thereby allows the imaging of subsurface magnetic permeability/susceptibility variations through an inversion procedure. This method is not affected by the remnant magnetization and theoretically overcomes the classical depth ambiguity generally encountered with passive geomagnetic data. To invert multiconfiguration in-phase data sets, we propose a novel methodology based on a full-grid 3-D multichannel deconvolution (MCD) procedure. This method allows us to invert large data sets (e.g. consisting of more than a hundred thousand of data points) for a dense voxel-based 3-D model of magnetic susceptibility subject to smoothness constraints. In this study, we first present and discuss synthetic examples of our imaging procedure, which aim at simulating realistic conditions. Finally, we demonstrate the applicability of our method to field data collected across an archaeological site in Auvergne (France) to image the foundations of a Gallo-Roman villa built with basalt rock material. Our synthetic and field data examples demonstrate the potential of the proposed inversion procedure offering new and complementary ways to interpret data sets collected with modern EMI instruments.

scholarly journals Fennec dust forecast intercomparison over the Sahara in June 2011

2016 ◽  
Vol 16 (11) ◽  
pp. 6977-6995 ◽  
Author(s):  
Jean-Pierre Chaboureau ◽  
Cyrille Flamant ◽  
Thibaut Dauhut ◽  
Cécile Kocha ◽  
Jean-Philippe Lafore ◽  
...  
Keyword(s):  
High Resolution ◽  
Surface Wind ◽  
Dust Emission ◽  
Airborne Lidar ◽  
Data Sets ◽  
Density Currents ◽  
Data Set ◽  
Near Surface ◽  
Western Sahara ◽  
Deep Well

Abstract. In the framework of the Fennec international programme, a field campaign was conducted in June 2011 over the western Sahara. It led to the first observational data set ever obtained that documents the dynamics, thermodynamics and composition of the Saharan atmospheric boundary layer (SABL) under the influence of the heat low. In support to the aircraft operation, four dust forecasts were run daily at low and high resolutions with convection-parameterizing and convection-permitting models, respectively. The unique airborne and ground-based data sets allowed the first ever intercomparison of dust forecasts over the western Sahara. At monthly scale, large aerosol optical depths (AODs) were forecast over the Sahara, a feature observed by satellite retrievals but with different magnitudes. The AOD intensity was correctly predicted by the high-resolution models, while it was underestimated by the low-resolution models. This was partly because of the generation of strong near-surface wind associated with thunderstorm-related density currents that could only be reproduced by models representing convection explicitly. Such models yield emissions mainly in the afternoon that dominate the total emission over the western fringes of the Adrar des Iforas and the Aïr Mountains in the high-resolution forecasts. Over the western Sahara, where the harmattan contributes up to 80 % of dust emission, all the models were successful in forecasting the deep well-mixed SABL. Some of them, however, missed the large near-surface dust concentration generated by density currents and low-level winds. This feature, observed repeatedly by the airborne lidar, was partly forecast by one high-resolution model only.

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