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245 results for “geophysical”
SWOT Level 2 Nadir Altimeter Geophysical Data Record with Waveforms - GDR Version D
The SWOT Level 2 Nadir Altimeter Geophysical Data Record (GDR) with Waveforms dataset produced by the Surface Water and Ocean Topography (SWOT) mission provides sea surface height, significant wave height and wind speed measurements from the Poseidon-3C nadir altimeter, a Jason-class dual frequency (Ku/C) altimeter. SWOT is a joint mission between NASA and CNES that launched on December 16, 2022. It aims to measure ocean surface topography with unprecedented resolution and accuracy, as well as map inland water bodies globally. The GDR dataset consists of discrete measurements for each half orbit along the ground track with sampling resolutions of approximately 6-km and 300-m at 1Hz and 20Hz, respectively. The data were processed using restituted auxiliary data and the Precise Orbit Ephemeris (POE). The data are available with latency of < 90 days and distributed in netCDF-4 file format.<br>This collection is a sub-collection of its parent: https://podaac.jpl.nasa.gov/dataset/SWOT_L2_NALT_GDR_D
GEOS-3 ALTIMETER GEOPHYSICAL DATA RECORD 1975-1978
These data consist of Geos-3 altimeter measurements produced by NOAA/NODC/Laboratory for Satellite Altimetry. The dataset contains 5,006,956 altimetric sea surface heights and supporting information such as sea state, wind speed, Schwiderski ocean tide height, and Cartwright solid-tide height. Corrections for altimeter bias, wet and dry troposheric delays, and electromagnetic bias are not included. The corrections in this dataset (tides and even orbit height) are old and not very accurate. This dataset should only be used by those with an expertise in altimetry. Measurements are compressed to a rate of 1 per second using a trim mean filter. Data values are written in binary format.
Aqua AIRS Level 2 JoSFRA Retrieval Standard: Atmosphere cloud and surface geophysical state per footprint V2 at GES DISC
The Joint Single Footprint Retrieval Algorithm (JoSFRA) Level-2 geophysical parameters include estimates of atmospheric temperature and water vapor profiles, cloud properties, and surface temperature. These are retrieved from infrared spectra observed by the Atmospheric Infrared Sounder (AIRS) instrument on the Aqua satellite. AIRS is a grating spectrometer aboard Aqua, the second Earth Observing System (EOS) polar-orbiting platform. AIRS is co-boresited with the Advanced Microwave Sounding Unit (AMSU) also on Aqua. Horizontal resolutions are 50 km for AMSU and 13.5 km for AIRS. The JoSFRA algorithm uses an optimal-estimation scheme and retrieves geophysical quantities from AIRS thermal infrared spectra at their native horizontal resolution. Cloud observations from MODIS are used in the forward model without recourse to a cloud-cleared state. JOSFRA retrievals provide improved spatial resolution (13.5 km vs 50 km for cloud-cleared retrievals) and information content quantification, making them well-suited for process studies. JoSFRA retrievals are particularly useful in cases where high resolution (finer than 45 km) is needed or is beneficial, such as regions of strong horizontal gradients in water vapor. Use of JoSFRA retrievals is recommended under medium to low cloud cover. AIRS observations provide near-global coverage twice daily (around 1:30 am and pm local time) since August 30, 2002. An AIRS granule includes 6 minutes of data, 90 AIRS (30 AMSU) footprints across the orbit track by 135 AIRS (45 AMSU) footprints along track. Each day includes 240 granules, with an orbit repeat cycle of approximately 16 days. For the initial release of Version 2 JoSFRA, a limited test data set is provided. Future releases will expand the dataset. The initial dataset includes full global coverage data for two 5-day periods: January 13-17, 2011 and July 13-17, 2011, the Marine ARM GPCI Investigation of Clouds (MAGIC) (Lewis and Teixeira, EOS, 2015) test campaign in the Pacific Ocean with all 6-minute granules that overlap the box bounded by 20-35 degrees North latitude and 120-160 West longitude, June 1, 2012 – September 30, 2013, select granules from the years 2002-2007 where correlative data were available. The locations include Dept. of Energy (DOE) Atmospheric Radiation Measurement (ARM) sites at the North Slope of Alaska (NSA), Southern Great Plains (SGP), and Tropical Western Pacific (TWP), as well as scientific field campaigns.
Sounder SIPS: Suomi NPP ATMS Level 2 RAMSES II: Atmosphere, cloud and surface geophysical state V1 (SNDRSNML2RMS) at GES DISC
This SNDRSNM2RMS level 2 product is generated by the RAMSES (Retrieval Algorithm for Microwave Sounders in Earth Science) II algorithm. Different from the CLIMCAPS (Community Long-term Infrared Microwave Coupled Product System) algorithm, the RAMSES II algorithm is a microwave only retrieval algorithm. While the CLIMCAPS uses measurements from both Cross-track Infrared Sounder (CrIS) and Advanced Technology Microwave Sounder (ATMS) instruments, also known as CrIMSS (Cross-track Infrared and Microwave Sounding Suite), the RAMSES II only uses observations from ATMS. The ATMS instrument used for this product is a cross-track scanner with 22 channels in spectral bands from 23 GHz through 183 GHz on board the Suomi National Polar-orbiting Partnership (SNPP) platform. The RAMSES II algorithm doesn't have a cloud clearing process and produces all weather retrieval. A level 2 granule has been set as 6 minutes of data. There are 240 granules per day, with an orbit repeat cycle of approximately 16 day.For the initial release of version 1 RAMSES II, a test data set of 8 months is provided. This includes the months of January, April, July and October of the years 2013 and 2015. The dataset is designed to allow research and comparisons over a full seasonal cycle and comparisons of different phases of the ENSO cycle
Sounder SIPS: JPSS-1 ATMS Level 2 RAMSES2 Standard: Atmosphere, precipitation and surface geophysical state V3 (SNDRJ1ML2RMS) at GES DISC
This level 2 product is generated by the RAMSES (Retrieval Algorithm for Microwave Sounders in Earth Science II algorithm.The RAMSES II algorithm is a microwave only retrieval algorithm using observations from the NOAA-20 (National Oceanic and Atmospheric Administration) also know as Joint Polar Satellite System (JPSS-1) Advanced Technology Microwave Sounder (ATMS) instrument. The ATMS instrument used for this product is a cross-track scanner with 22 channels in spectral bands from 23 GHz through 183 GHz. The RAMSES II Level-2 retrieval products contain a variety of geophysical parameters retrieved from ATMS measurements, including profiles of temperature, water in all phases as well as surface properties for six minutes of instrument observation at a time. The RAMSES II algorithm doesn't have a cloud clearing process and produces all weather retrievalA level 2 granule has been set as 6 minutes of data. There are 240 granules per day, with an orbit repeat cycle of approximately 16 day.
MLS/Aura Level 2 Diagnostics, Geophysical Parameter Grid V005 (ML2DGG) at GES DISC
ML2DGG is the EOS Aura Microwave Limb Sounder (MLS) product containing geophysical diagnostic quantities pertaining directly to the standard geophysical data products, generally on a similar (or identical) grid, and at different spectral ranges. The data version is 5.0. Data coverage is from August 8, 2004 to current. Spatial coverage is near-global (-82 degrees to +82 degrees latitude), with each profile spaced 1.5 degrees or ~165 km along the orbit track (roughly 15 orbits per day). Vertical resolution varies between species and typically ranges from 3 - 6 km. Users of the ML2DGG data product should read the EOS MLS Level 2 Version 5 Quality Document for more information.The data are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5), which is based on the version 5 Hierarchical Data Format, or HDF-5. Each file contain swaths objects for each diagnostics measurement. Each swath has a set of data and geolocation fields, swath attributes, and metadata.
Sounder SIPS: AQUA AIRS IR + MW Level 2 CLIMCAPS: Atmosphere, cloud and surface geophysical state V2 (SNDRAQIML2CCPRET) at GES DISC
WARNING: To users of the derived product “co_mmr_midtrop” (carbon monoxide mass mixing ratio to dry air [kg/kg] at ~500 hPa). This variable has a significant bias due to a conversion error: the molecular weight of carbon dioxide (CO2, 44.01 g/mol) was used instead of carbon monoxide (CO, 28.01 g/mol). To correct, simply multiply “co_mmr_midtrop” by 28.01/44.01. Alternatively, derive a profile of mass mixing ratio from scratch using the retrieved column density values (“mol_lay/co_mol_lay”) in the Level 2 files. For further questions or concerns please contact the Sounder SIPS at: sounder.sips@jpl.nasa.govThe CLIMCAPS (Community Long-term Infrared Microwave Coupled Product System) algorithm is used to analyze data from the AIRS (Atmospheric Infrared Sounder) and AMSU (Advanced Microwave Sounding Unit). The AIRS instrument is a grating spectrometer (R = 1200) aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. The AIRS in combination with the AMSU constitutes an innovative atmospheric sounding group of infrared and microwave sensors. The AIRS Standard Retrieval Product consists of retrieved estimates of cloud and surface properties, plus profiles of retrieved temperature, water vapor, ozone, carbon monoxide and methane. The temperature profile vertical resolution is 100 levels total between 1100 mb and 0.1 mb, while moisture profile is reported at atmospheric layers between 1100 mb and 300 mb. The horizontal resolution is 50 km. The CLIMCAPS algorithm uses an Optimal Estimation methodology and uses an a-priori first guess to start the process. A CLIMCAPS sounding is comprised of a set of parameters that characterizes the full atmospheric state and includes a variety of geophysical parameters derived from the CrIMSS data. These include surface temperature and infrared emissivity; full atmosphere profiles of temperature, water vapor and ozone; infrared effective cloud top characteristics; carbon monoxide, methane, carbon dioxide, sulfur dioxide, nitrous oxide, and nitric acid.An AIRS granule has been set as 6 minutes of data, 30 footprints cross track by 45 lines along track for each of the approximate 2378 channels. There are 240 granules per day, with an orbit repeat cycle of approximately 16 day.
NSCAT Level 2 Ocean Wind Vector Geophysical Data Record
The NASA Scatterometer (NSCAT) Level 2 ocean wind vectors in 50 km wind vector cell (WVC) swaths contain daily data from ascending and descending passes. Wind vectors are accurate to within 2 m/s (vector speed) and 20 degrees (vector direction). Wind vectors are not considered valid in rain contaminated regions; rain flags and precipitation information are not provided. Data is flagged where measurements are either missing, ambiguous, or contaminated by land/sea ice. Winds are calculated using the NSCAT-2 model function. This is the most up-to-date version, which designates the final phase of calibration, validation and science data processing, which was completed in November of 1998, on behalf of the JPL NSCAT Project; wind vectors are processed using the NSCAT-2 geophysical model function.
Sentinel-6A MF Jason-CS L2 Advanced Microwave Radiometer (AMR-C) NRT Geophysical Parameters
Provides L2 near real time (NRT; 3-hour latency) geophysical information from the Advanced Microwave Radiometer on the Sentinel-6A Michael Freilich spacecraft including surface type, wind speed, water vapor, brightness temperature, sigma0, wet troposphere, and associated quality flags. The data are interpolated to intervals that correspond to altimetry measurements from the Poseidon-4 SAR to supply the geophysical and environmental corrections for altimetry. The S6A NRT product is analogous to the Jason-3 OGDR product.
Sounder SIPS: Suomi NPP ATMS Level 2 RAMSES2 Standard: Atmosphere, precipitation and surface geophysical state, V3 (SNDRSNML2RMS ) at GES DISC
This level 2 product is generated by the RAMSES (Retrieval Algorithm for Microwave Sounders in Earth Science) II algorithm.The RAMSES II algorithm is a microwave only retrieval algorithm using observations from the Suomi-National Polar-orbiting Partnership (NPP) Advanced Technology Microwave Sounder (ATMS) instrument. The ATMS instrument used for this product is a cross-track scanner with 22 channels in spectral bands from 23 GHz through 183 GHz. The RAMSES II Level-2 retrieval products contain a variety of geophysical parameters retrieved from ATMS measurements, including profiles of temperature, water in all phases as well as surface properties for six minutes of instrument observation at a time. The RAMSES II algorithm doesn't have a cloud clearing process and produces all weather retrievalA level 2 granule has been set as 6 minutes of data. There are 240 granules per day, with an orbit repeat cycle of approximately 16 day.
Sounder SIPS: Suomi NPP CrIMSS Level 2 CHART Normal Spectral Resolution: Atmosphere, cloud and surface geophysical state V1
The objective of this limited edition data collection is to examine products generated by the Climate Heritage AIRS Retrieval Technique (CHART) algorithm to analyze Cross-track Infrared Sounder/Advanced Technology Microwave Sounder (CrIS/ATMS) instruments, also known as CrIMSS (Cross-track Infrared and Microwave Sounding Suite). The CrIS/ATMS instruments used for this product are on board the Suomi National Polar-orbiting Partnership (SNPP) platform and use the Normal Spectral Resolution (NSR) data. The CrIS instrument is a Fourier transform spectrometer with a total of 1305 NSR infrared sounding channels covering the longwave (655-1095 cm-1), midwave (1210-1750 cm-1), and shortwave (2155-2550 cm-1) spectral regions. The ATMS instrument is a cross-track scanner with 22 channels in spectral bands from 23 GHz through 183 GHz. The CHART algorithm is uses the basic cloud clearing and retrieval methodologies used including the definition and derivation of Jacobians, the channel noise covariance matrix, and the use of constraints including the background term, are essentially identical to those of AIRS Version-6.6 and previous AIRS Science Team retrieval algorithms. As with the Version-6.6 AIRS system, the CHART algorithm uses a Neural Network system as an initial guess. The sounding retrieval methodology characterizes the full atmospheric state and the retrievals contains a variety of geophysical parameters derived from the CrIMSS data. These include surface temperature and infrared emissivity; full atmosphere profiles of temperature, water vapor and ozone; infrared effective cloud top characteristics; outgoing longwave radiation (OLR); and an infrared-based precipitation estimate.The CHART system was designed to serve as a seamless follow on to the Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit (AIRS/AMSU) instrument processing system. For comparison, the AIRS/AMSU data collection AIRX2SUP contains similar meteorological information to this CHART data collection and the CLIMCAPS (Community Long-term Infrared Microwave Coupled Product System) data collection SNDRSNIML2CCPRETN contains CRIMSS data processed with an analogous algorithm. A level 2 granule has been set as 6 minutes of data, 30 footprints cross track by 45 lines along track. There are 240 granules per day, with an orbit repeat cycle of approximately 16 day.
Sounder SIPS: Suomi NPP CrIMSS Level 2 CLIMCAPS Normal Spectral Resolution: Atmosphere cloud and surface geophysical state V2 (SNDRSNIML2CCPRETN) at GES DISC
WARNING: To users of the derived product “co_mmr_midtrop” (carbon monoxide mass mixing ratio to dry air [kg/kg] at ~500 hPa). This variable has a significant bias due to a conversion error: the molecular weight of carbon dioxide (CO2, 44.01 g/mol) was used instead of carbon monoxide (CO, 28.01 g/mol). To correct, simply multiply “co_mmr_midtrop” by 28.01/44.01. Alternatively, derive a profile of mass mixing ratio from scratch using the retrieved column density values (“mol_lay/co_mol_lay”) in the Level 2 files. For further questions or concerns please contact the Sounder SIPS at: sounder.sips@jpl.nasa.govThe CLIMCAPS (Community Long-term Infrared Microwave Coupled Product System) algorithm is used to analyze data from the Cross-track Infrared Sounder/Advanced Technology Microwave Sounder (CrIS/ATMS) instruments, also known as CrIMSS (Cross-track Infrared and Microwave Sounding Suite). The CrIS/ATMS instruments used for this product are on board the Suomi National Polar-orbiting Partnership (SNPP) platform and use the Normal Spectral Resolution (NSR) data. The CrIS instrument is a Fourier transform spectrometer with a total of 1305 NSR infrared sounding channels covering the longwave (655-1095 cm-1), midwave (1210-1750 cm-1), and shortwave (2155-2550 cm-1) spectral regions. The ATMS instrument is a cross-track scanner with 22 channels in spectral bands from 23 GHz through 183 GHz. The CLIMCAPS algorithm uses an Optimal Estimation methodology and uses an a-priori first guess to start the process. A CLIMCAPS sounding is comprised of a set of parameters that characterizes the full atmospheric state and includes a variety of geophysical parameters derived from the CrIMSS data. These include surface temperature and infrared emissivity; full atmosphere profiles of temperature, water vapor and ozone; infrared effective cloud top characteristics; carbon monoxide, methane, carbon dioxide, sulfur dioxide, nitrous oxide, and nitric acid. The CLIMCAPS algorithm uses data from the second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) as a first-guess for the atmospheric state. Because MERRA-2 products typically have a latency from 3 to 7 weeks, so too do the CLIMCAPS products. A level 2 granule has been set as 6 minutes of data, 30 footprints cross track by 45 lines along track. There are 240 granules per day, with an orbit repeat cycle of approximately 16 day.
SWOT Level 2 Nadir Altimeter Operational Geophysical Data Record with Waveforms
The SWOT Level 2 Nadir Altimeter Operational Geophysical Data Record (OGDR) with Waveforms Version 1.0 dataset produced by the Surface Water and Ocean Topography (SWOT) mission provides sea surface height, significant wave height and wind speed measurements from the Poseidon-3C nadir altimeter, a Jason-class dual frequency (Ku/C) altimeter. SWOT is a joint mission between NASA and CNES that launched on December 16, 2022. It aims to measure ocean surface topography with unprecedented resolution and accuracy, as well as map inland water bodies globally.The OGDR dataset consists of discrete measurements along the nadir track with sampling resolutions of approximately 6-km and 300-m at 1Hz and 20Hz, respectively. The data were processed using the onboard DORIS orbit ephemeris, with predicted values for certain auxiliary data and no GIM ionosphere model values. The OGDR data are distributed as one file per data downlink in netCDF-4 file format with a nominal latency of < 7 hours.<br>This collection is the parent collection to the following sub-collections: <br>https://podaac.jpl.nasa.gov/dataset/SWOT_L2_NALT_OGDR_SSHA_2.0 <br>https://podaac.jpl.nasa.gov/dataset/SWOT_L2_NALT_OGDR_GDR_2.0 <br>
The Lithospheric Structure of the Saharan Metacraton from 3D Integrated Geophysical-Petrological Modelling
<p>We provide the final lithospheric model of Saharan Metacraton resulting from our work presented in the manuscript. It is part of the archive file “Model_data_2020-02-06”</p>
Geophysical data from: "Seismic Signatures Reveal Persistence of Soil Compaction"
<p>The geophysical data presented herein was collected in the Soil Structure Observatory (see, Keller et. al. 2017) and were used to create Figures 3, 4, 5, and 6 for the manuscript titled: "Seismic Signatures Reveal Persistence of Soil Compaction". The data set includes:<br> <br> Time-lapse seismic data collected for different time periods at the full-compacted ley (CL), non-compacted ley (NL) and full-compacted bare soil (CB):</p> <p>CL.zip</p> <p>NL.zip</p> <p>CB.zip</p> <p>The time-lapse data files are in a seg2 format. Information regarding the acquisition time and date, sampling frequency and geometry of the seismic array can be found in the file headers.</p> <p><br> Time-domain reflectometry data (TDR) from 2019 collected at various depths at the soil treatments mentioned above:</p> <p>2019_BlockC_TDR.csv</p> <p>Meteorological data from 2019 collected at the SSO:</p> <p>2019_Meteo.csv</p> <p>The corrected first-break and zero-crossing picks along with the mean value and standard deviation of estimated seismic velocities for CL, NL and CB.</p> <p>picked_times-seismic_velocities.ods</p> <p>Volumetric water content at 10 cm depth inferred from TDR data using Topp's equation.</p> <p>water_content10cm.ods</p> <p> </p> <p>Keller, T., Colombi, T., Ruiz, S., Manalili, M. P., Rek, J., Stadelmann, V., ... & Schymanski, S. (2017). Long-Term Soil Structure Observatory for Monitoring Post-Compaction Evolution of Soil Structure. <em>Vadose Zone Journal</em>, <em>16</em>(4).</p> <p> </p>
Data in support "Turbidity hysteresis in an estuary and tidal river following an extreme discharge event", manuscript submitted to Geophysical Research Letters,
<p>Data set in support of manuscript "Turbidity hysteresis in an estuary and tidal river following an extreme discharge event" submitted to Geophysical Research Letters. Submitted March 2020, revised and resubmitted April 2020. Matlab script (makeFigs_hysteresis_upload.m) is used to generate the figures from the manuscript. Data files (*.mat) correspond with each figure (*.png). For questions or additional information please contact D. Ralston. </p>
Dataset of geophysical logs
<p>Data set of Geophysical Research Letter paper "Thermal properties of the Chinese Continental Scientific Drilling Project-SK-2 from geophysical logs: Implications for the crustal thermal structure of Songliao Basin, NE China".</p>
Geophysical datasets used in the paper: Looking for subsurface features: the role of geophysical research in the revitalisation of the palace and park complex in Rzuchów, Poland
<p>Datasets are related to the paper entitled: <strong>Looking for subsurface features: the role of geophysical research in the revitalisation of the palace and park complex in Rzuchów, Poland</strong></p><p>This paper discusses the significance of geophysical research in the context of historical renewal, emphasising its contributions to risk assessment, sustainable redevelopment, and non-uniqueness in geophysical interpretation. The studies were conducted in the surroundings of the Palace of Rzuchów, and they were aimed at locating the modern infrastructure, historical objects, and other environmental elements that either can threaten the renewal process or add value to the historical heritage. We used four geophysical methods to study the palace surroundings: frequency domain electromagnetics, electrical resistivity tomography, proton magnetometry and seismic. Results indicated that the electrical methods are the most predisposed.</p>
Gussage St Michael 10 Geophysics On Lidar Dsm
Gussage St Michael 10 Neolithic long barrow. Magnetometer survey results on Lidar DSM. Contains public sector information licensed under the Open Government Licence v3.0 Source: Objaverse 1.0 / Sketchfab
Understanding the fate of H2S injected in basalts by means of time-domain induced polarization geophysical logging.
<p>Data for paper published at JGR-Solid Earth</p> <p>Input data (five zipped folders): TDIP fullwaveform data, resistivity, temperature, fluid conductivity (.xlsx and .txt formats)</p> <p>Matlab_scripts.zip: scripts for reading, processing, analyzing, plotting, saving data (.m format). It also includes data saved as .mat at the intermediary steps of the processing.</p> <p>Output_data.zip: Processed data used in the plots stored in .xlsx files</p> <p>Readme.pdf : file that explains the different scripts</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.