We have developed a new three-dimensional seismic velocity model of the central United States (CUSVM) that includes the New Madrid Seismic Zone (NMSZ) and covers parts of Arkansas, Mississippi, Alabama, Illinois, Missouri, Kentucky, and Tennessee. The model represents a compilation of decades of crustal research consisting of seismic, aeromagnetic, and gravity profiles; geologic mapping; geophysical and geological borehole logs; and inversions of the regional seismic properties. The density and P- and S-wave velocities are synthesized in a stand-alone spatial database that can be queried to generate the required input for numerical seismic-wave propagation simulations. The velocity model has been tested and calibrated by simulating ground motions of the 18 April 2008 Mw 5.4 Mt. Carmel, Illinois, earthquake and comparing the results with observed records within the model area (see associated publication).

This dataset contains monthly-averaged ocean velocity interpolated to a regular 0.5-degree grid from the ECCO Version 4 revision 4 (V4r4) ocean and sea-ice state estimate. Estimating the Circulation and Climate of the Ocean (ECCO) ocean and sea-ice state estimates are dynamically and kinematically-consistent reconstructions of the three-dimensional, time-evolving ocean, sea-ice, and surface atmospheric states. ECCO V4r4 is a free-running solution of the 1-degree global configuration of the MIT general circulation model (MITgcm) that has been fit to observations in a least-squares sense. Observational data constraints used in V4r4 include sea surface height (SSH) from satellite altimeters [ERS-1/2, TOPEX/Poseidon, GFO, ENVISAT, Jason-1,2,3, CryoSat-2, and SARAL/AltiKa]; sea surface temperature (SST) from satellite radiometers [AVHRR], sea surface salinity (SSS) from the Aquarius satellite radiometer/scatterometer, ocean bottom pressure (OBP) from the GRACE satellite gravimeter; sea ice concentration from satellite radiometers [SSM/I and SSMIS], and in-situ ocean temperature and salinity measured with conductivity-temperature-depth (CTD) sensors and expendable bathythermographs (XBTs) from several programs [e.g., WOCE, GO-SHIP, Argo, and others] and platforms [e.g.,research vessels, gliders, moorings, ice-tethered profilers, and instrumented pinnipeds]. V4r4 covers the period 1992-01-01T12:00:00 to 2018-01-01T00:00:00.

This data set, part of the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, contains seasonal (winter) ice sheet-wide velocity maps for Greenland. The maps are derived from Interferometric Synthetic Aperture Radar (InSAR) data obtained by the Canadian Space Agency's (CSA) RADARSAT-1, the Japan Aerospace Exploration Agency's (JAXA) Advanced Land Observation Satellite (ALOS), and the German Aerospace Center's (DLR) TerraSAR-X/TanDEM-X (TSX/TDX) satellites, as well as from the European Space Agency's (ESA) C-band Synthetic Aperture Radar data from Copernicus Sentinel-1A and -1B. See Greenland Ice Mapping Project (GIMP) for related data.

Weathered oil in the surf-zone after an oil spill may mix with suspended sediments to form sand and oil agglomerates (SOA). Sand and oil agglomerates may form in mats on the scale of tens of meters (m), and may break apart into pieces between 1 and 10 centimeters (cm) in diameter. These more mobile pieces are susceptible to alongshore and cross-shore transport, and lead to beach re-oiling on the time scale of months to years following a spill. The U.S. Geological Survey (USGS) conducted experiments March 10 - 13, 2014, to expand the available data on sand and oil agglomerate motion; test shear stress based incipient motion parameterizations in a controlled, laboratory setting; and directly observe SOA exhumation and burial processes. Artificial sand and oil agglomerates (aSOA) were created and deployed in a small-oscillatory flow tunnel in two sets of experiments, during which, video and velocity data were obtained. The first experiment, which was set up to help researchers investigate incipient motion, used with an immobile, rough bottom (referred to as false-floor) and the second–testing seafloor interactions–utilized with a coarse grain sand bottom (movable sand bed). Detailed information regarding the creation of the aSOA can be found in Dalyander et al. (2015). More information about the USGS laboratory experiment conducted in collaboration with the Naval Research Laboratory can be found in the associated Open File Report (OFR Number Unknown).

This data set, part of the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, provides annual maps of Antarctic ice velocity. The maps are assembled using SAR data from the Japanese Space Agency's (JAXA) ALOS PALSAR, the European Space Agency's (ESA) ENVISAT ASAR and Copernicus Sentinel-1, the Canadian Space Agency's (CSA) RADARSAT-1, RADARSAT-2, the German Aerospace Agency's (DLR) TerraSAR-X (TSX) and TanDEM –X (TDX), and the U.S. Geological Survey's (USGS) Landsat-8 optical imagery.. See Antarctic Ice Sheet Velocity and Mapping Data for related data.

Water velocities were measured at discrete cross-sections along an approximately 1-mile reach of the Kentucky Dam tailwater on September 12 and 17-18, 2020, using a 1200 kHz acoustic Doppler current profiler (ADCP). The data were geo-referenced with an integrated global navigation satellite system (GNSS) smart antenna with submeter accuracy. The ADCP and GNSS antenna were mounted on a marine survey vessel, and data were collected as the survey vessel traversed the tailwater along planned survey lines. There was typically one reciprocal pair (two passes) of data collected per line. There was a total of 53 survey lines equally spaced 100 feet apart and oriented approximately perpendicular to the primary flow direction. Data collection software integrated and stored the velocity and position data from the ADCP and GNSS antenna in real time. Data were processed using the Velocity Mapping Toolbox (Parsons and others, 2013) to derive temporally- and spatially-averaged water velocity val ...

This data set, part of the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, contains a multi-year ice-sheet-wide velocity mosaic for Greenland, derived from Interferometric Synthetic Aperture Radar (InSAR), Synthetic Aperture Radar (SAR), and Landsat 8 optical imagery data.

See Greenland Ice Mapping Project (GIMP) for related data.

View data of the frequency at which one unit of currency purchases domestically produced goods and services within a given time period.

These NetCDF files contain ADCP and ocean current velocity measurements from the TAO/TRITON array, averaged over different time periods indicated by the filename. The data, and much more, can be found here. This data is provided for reproducibility purposes, as it was used in:Halpern, D., Le, M. K., Smith, T. A., & Heimbach, P. (2023). Comparison of ADCP and ECCOv4r4 Currents in the Pacific Equatorial Undercurrent. Journal of Atmospheric and Oceanic Technology, 40(12), 1369-1381. https://doi.org/10.1175/JTECH-D-23-0013.1Users of this dataset should follow these acknowledgement guidelines, copied here:If you use these data in publications, please acknowledge the GTMBA Project Office of NOAA/PMEL. Also, we would appreciate receiving a preprint and/or reprint of publications utilizing the data for inclusion in the GTMBA bibliography. Relevant publications should be sent to:GTMBA Project OfficeNOAA/Pacific Marine Environmental Laboratory7600 Sand Point Way NESeattle, WA 98115

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

Invasive Asian carps established in the United States spawn in turbulent water of rivers and their eggs and early larvae develop while drifting in the current. The eggs are slightly denser than water and are held in suspension by water turbulence. The eggs are believed to perish if they settle before hatching. It is thus possible to use egg drift modeling to assess the capability of a river to support survival of Asian carp eggs. Data to populate such models include the physical properties of the assessed rivers, and information on egg size, density, and terminal fall velocity (sinking rates). Herein, we present the physical characteristics of the eggs as a function of post fertilization time. We recorded mean egg diameter and terminal fall velocity for eggs from each species during the first five hours of development, and at approximately 12 and 22 hours post fertilization. Eggs of all species reached their maximum size before 4 hours. Water-hardened Silver Carp Hypophathalmicthys molitrix and Grass Carp Ctenopharyngodon idella eggs were similarly sized in our trials, and Bighead Carp Hypophathalmichthys nobilis water-hardened eggs were the largest. After water hardening, Silver Carp eggs sank slowest and Bighead Carp eggs sank fastest. For a given species, smaller diameter eggs generally had faster terminal velocity and had higher specific gravity than larger eggs. These data were used to develop a regression growth model of eggs of three species of Asian carp, which includes time-dependent relations for density and diameter of eggs. Asian carp growth models used in conjunction with egg drifting models provide insights regarding the potential of a river to transport Asian carp eggs in suspension until hatching.

description: Velocity data are being provided in an Access database and Excel spreadsheets. The database summarizes the velocity data, site location and description, vegetative characteristics, and water quality parameters. The spreadsheet filters and averages the complete raw velocity data set per measurement. This data was collected at two minute intervals for 10 minutes. The file naming convention is as follows: (example) E07T31197.xls Column 1: E or W East or west from Taylor Slough Airboat Trail Column 2-3: Sequential numbers from the center of the transect Column 4-5: Sequential transect number Column 6-9: Month and Year data was collected; abstract: Velocity data are being provided in an Access database and Excel spreadsheets. The database summarizes the velocity data, site location and description, vegetative characteristics, and water quality parameters. The spreadsheet filters and averages the complete raw velocity data set per measurement. This data was collected at two minute intervals for 10 minutes. The file naming convention is as follows: (example) E07T31197.xls Column 1: E or W East or west from Taylor Slough Airboat Trail Column 2-3: Sequential numbers from the center of the transect Column 4-5: Sequential transect number Column 6-9: Month and Year data was collected

This data set, part of the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Program, provides the first comprehensive, high-resolution, digital mosaics of ice motion in Antarctica assembled from multiple satellite interferometric, synthetic-aperture radar systems. Data were largely acquired during the International Polar Years 2007 to 2009, as well as between 2013 and 2016. Additional data acquired between 1996 and 2016 were used as needed to maximize coverage. See Antarctic Ice Sheet Velocity and Mapping Data for related data.

This data release contains data collected during science flights using the drone-based QCam, which is a Doppler (velocity) radar designed to measure surface velocity and compute river discharge when channel bathymetry is known. Five science flights were conducted on the Arkansas River in Colorado and the data acquired are presented in comma separated values (CSV) files.

Projectile velocity data, from tests using the National Institute of Justice (NIJ) body armor standard (NIJ-0101.06) test threats, collected over a numbers of years at the NIST ballistics laboratory, that was used to assess the uncertainty associated with a chronograph/light screen system.

This dataset includes data from the Sound Velocity Profiler system onboard the UNOLS R/V Thompson ship during the Bering Sea Ecosystem Study-Bering Sea Integrated Ecosystem Research Program (BEST-BSIERP) 2010 TN250 (summer) cruise. BEST-BSIERP together are the Bering Sea project. The data files are collected into one tar file for the cruise.

Here are the training and testing data sets involved in the numerical experiments in the article that has been submitted to the journal “Journal of Geophysical Research: Solid Earth”, named “Joint Model and Data-Driven Simultaneous Inversion of Velocity and Density”: Marmousi model. Each dataset consists of two parts: a training dataset and a testing dataset. Both training and testing data sets contain three parts: seismic data, velocity model and density model.

Glacier ice flow velocity is an important variable to document the past and current status of the glacier worldwide. The aim of the ESA AlpGlacier project is to create innovative products for glaciers and their environments from remote sensing data for the European Alps mountain range. The data set proposed here includes maps of annual glacier surface flow velocities for the period 2015-2021, created from Sentinel-2 optical data with the work-flow presented in Mouginot et al., 2023. It can be used for the monitoring of glacier dynamics or for hazards detection associated to glaciers destabilization, as well as an input of models calibration and validation. These products are distributed in both netCDF and GeoTiff formats, georeferenced under the UTM-32N projection.

Accurate data and maps of sea floor geology are important first steps toward protecting fish habitat, delineating marine resources, and assessing environmental changes due to natural or human impacts. To address these concerns the U.S. Geological Survey, in cooperation with the Massachusetts Office of Coastal Zone Management (CZM), comprehensively mapped the Cape Cod Bay sea floor to characterize the surface and shallow subsurface geologic framework. Geophysical data collected include swath bathymetry, backscatter, and seismic reflection profile data. Ground-truth data, including sediment samples, underwater video, and bottom photographs were also collected. This effort is part of a long-term collaboration between the USGS and the Commonwealth of Massachusetts to map the State’s waters, support research on the Quaternary evolution of coastal Massachusetts, the influence of sea-level change and sediment supply on coastal evolution, and efforts to understand the type, distribution, and quality of subtidal marine habitats. This collaboration produces high-resolution geologic maps and Geographic Information System (GIS) data that serve the needs of research, management and the public. Data collected as part of this mapping cooperative continue to be released in a series of USGS Open-File Reports and Data Releases (https://www.usgs.gov/centers/whcmsc/science/geologic-mapping-massachusetts-seafloor). This data release provides the geophysical and geologic sampling data collected in Cape Cod Bay during USGS Field Activities 2019-002-FA and 2019-034-FA in 2019.

This is a composite 3D seismic velocity that was constructed from compiled information from several local studies regarding seismic velocities and structural information. This seismic velocity model is provided in NonLinLoc format (slow_len), which is readily usable in NonLinLoc software. Other model formats and versions of the model can be produced using the Python script provided with this data set. Details on how the model was created and prior velocity and structural information was used is provided in the accompanying documentation.