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110 results for “altimeter”
JasonAlongTrack: A reformatted version of the Integrated Multi-Mission Ocean Altimeter Data for Climate Research Version 5.1
<p>JasonAlongTrack contains geo-registered along-track sea surface height anomalies with respect to the DTU15 mean sea surface at 1-second intervals from Jason-class altimeters, reformatted for convenience into a 3D array with dimensions of along-track direction by geographically sorted track number by cycle.</p><p>This is a reformatted version of Beckley et al.'s <i>Integrated Multi-Mission Ocean Altimeter Data for Climate Research complete time series Version 5.1</i> dataset, available from <a href="https://podaac.jpl.nasa.gov/dataset/MERGED_TP_J1_OSTM_OST_ALL_V51">https://podaac.jpl.nasa.gov/dataset/MERGED_TP_J1_OSTM_OST_ALL_V51</a>. </p><p>The changes are as follows. Altimeter passes are sorted according to their initial longitude, then split into descending and ascending potions with all descending tracks preceding all ascending tracks. Descending tracks are then flipped so that latitude increases in the alongtrack direction for all tracks. This leads to a 3373 x 254 matrix of observational locations, with the first dimension being the along-track location and the second dimension being the track index. Sea surface height anomaly, time, and flag values are then placed into their correct locations within this matrix, such that these three variables are all of size 3373 x 254 x K where K is the number of cycles, currently 1087. A very good approximation to the time at each of the 3373 x 254 x K observation points is constructed with a length K array of cycles times together with a 3373 x 254 array of time offsets. A median-based editing criterion in introduced to identify a small number of suspect data points. These are set to a value of NaN in sla, but their positions and values are recorded in rejected_index and rejected_values, respectively. The DTU15 mean dynamic topography (mdt) is included, in addition to the mean sea surface field already provided, interpolated onto the track locations using bicubic interpolation. Finally, an estimate of the small-scale noise level, sigma, is produced using a wavelet transform filter.</p>
SDUST2020MGCR: a global marine gravity change rate model determined from multi-satellite altimeter data
<p>SDUST2020MGCR.nc is the global marine gravity change rate model covering 70°S~70°N and 0°~360°E on 5′×5′ grids. The dataset contains geospatial information (latitude, longitude), SDUST2020MGCR and an attachment data (GIA MGCR).</p>
Compositional maps of the lunar polar regions derived from the Kaguya Spectral Profiler and the Lunar Orbiter Laser Altimeter data
<p>Compositional maps of the lunar polar regions derived from the Kaguya Spectral Profiler and the Lunar Orbiter Laser Altimeter data as described in Lemelin et al. (2022). </p> <p>This folder includes different GeoTIFF files described and shown in Lemelin et al. (2022). The files are projected in Polar Stereographic Projection, at a spatial resolution of 1000 m/pixel. A version of each of the following file is given for the north and south polar region (50-90 N/S).</p> <p>- Gridded and interpolated Spectral Profiler reflectance mosaics scaled to the LOLA dataset at 1064 nm<br> - Data counts used in the gridded and interpolated Spectral Profiler reflectance mosaics scaled to the LOLA dataset at 1064 nm<br> - Spectral Profiler FeO mosaics <br> - Spectral Profiler OMAT mosaics <br> - Spectral Profiler plagioclase mosaics <br> - Spectral Profiler olivine mosaics <br> - Spectral Profiler low-calcium pyroxene mosaics<br> - Spectral Profiler high-calcium pyroxene mosaics <br> - Nanophase iron mosaics <br> - Correlation coefficient mosaics</p>
SDUST2024MSS_AO: a mean sea surface model of the Arctic Ocean based on CryoSat-2 SAR altimeter data
<p>This model is a mean sea surface model for ice-covered regions, using CryoSat-2 satellite SAR mode altimeter data from July 2010 to December 2023. The heights are referenced to the WGS-84 ellipsoid, and the grid size is 5 km × 5 km.</p>
Inputs (forcing, observations and config file) for the experiments included in "Spatio-temporal snow data assimilation with the ICESat-2 laser altimeter".
<p>Inputs or the experiments included in the manuscript <a href="https://doi.org/10.5194/egusphere-2024-1404">Spatio-temporal snow data assimilation with the ICESat-2 laser altimeter</a>. </p> <p>Three experiment's inputs (forcing, observations and config file) for the Multiple Snow data Assimilation system (<a href="https://doi.org/10.5281/zenodo.11147258">MuSA</a>, v2.1) for the experimental catchment of Izas in the Spanish Pyrenees. All the experiments use ERA5 data downscaled to 20 m spatial resolution with the statistical downscaling tool <a href="https://doi.org/10.21105/joss.05059">TopoPySCALE</a>. The experiments assimilate different variables. </p> <p> C) assimilation of fSCA retrieved from Sentinel-2;</p> <p> D) assimilation of snow depth profiles retrieved with ICESat-2;</p> <p> J) joint assimilation of variables in C) and D).</p> <p> </p> <p>All the experiments assimilate the observations with the deterministic ensemble smoother with multiple data assimilation (DES-MDA) scheme.</p>
SDUST2021GRA: Global marine gravity anomaly model recovered from Ka-band and Ku-band satellite altimeter data
<p>SDUST2021GRA is the global marine gravity anomaly model on a grid of 1′×1′, which is established from the altimeter data of <strong> </strong>Ka-band and Ku-band altimetry satellite including HY-2A. Its spatial coverage is 80°S-80°N. Assessed by the shipborne gravity data, the accuracy of SDUST2021GRA in the global is 2.37 mGal, and that in the open ocean is about 1.5 mGal.</p>
Data for: Ensemble-based data assimilation of significant wave height from Sofar Spotters and satellite altimeters with a global operational wave model
<p>An ensemble-based method for wave data assimilation is implemented using significant wave height observations from the globally distributed network of Sofar Spotter buoys and satellite altimeters. The Local Ensemble Transform Kalman Filter (LETKF) method generates skillful analysis fields resulting in reduced forecast errors out to 2.5 days when used as initial conditions in a cycled wave data assimilation system. The LETKF method provides more physically realistic model state updates that better reflect the underlying sea state dynamics and uncertainty compared to methods such as optimal interpolation. Skill assessment far from any included observations and inspection of specific storm events highlights the advantages of LETKF over an optimal interpolation method for data assimilation. This advancement has immediate value in improving predictions of the sea state and, more broadly, enabling future coupled data assimilation and utilization of global surface observations across domains (atmosphere-wave-ocean).</p>
Normal and abnormal eddy dataset based on the intersection of altimeters and Argos
<p>The current mainstream identification method of eddy based on the altimeter is not completely certain in determining the polarity of eddies, so we use the Argo arrays covering the global ocean to screen out abnormal eddies with subsurface potential density anomaly features opposite to surface height anomaly features, including abnormal anticyclonic eddies and abnormal cyclonic eddies. Meanwhile, for further comparing the differences between the natures of normal and abnormal eddies, we also screen out the normal eddies whose subsurface potential density anomaly features are same as surface height anomaly features, including normal anticyclonic eddies and normal cyclonic eddies. The dataset stores the location coordinate, radius, amplitude and lifetime of the eddy, as well as the float number, profile number, location coordinate, date of record of the profile in this eddy and the potential density anomaly in the depth range of 0-1000 m.</p>
Data for: Ensemble-based data assimilation of significant wave height from Sofar Spotters and satellite altimeters with a global operational wave model
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The metre-scale roughness of asteroid (101955) Bennu from the OSIRIS-REx Laser Altimeter: Processed OLA v21 pointclouds for RMS deviation (L = 0.2 m to L = 20.0 m) [Dataset]
<p>Pointclouds:</p> <ul> <li>Pointcloud (.pcd) files for OLA RMS deviation calculation with fields: <br> <ul> <li>'Location': node points (XYZ points on Bennu's surface)</li> <li>'Intensity': height delta between the node and a neighbouring point at distance L from the node. 'Height' is defined as height above an orthogonally regressed plane fit to points within 2L of the node. </li> </ul> </li> </ul> <p> Tables:</p> <ul> <li>2020_06_bt_final_ma.xlsx: <ul> <li>Crater catalog from Bierhaus et al (2022)</li> </ul> </li> <li>bierhaus2023_craters_gt5m_lt80m_olav21_roi_flags.xlsx: <ul> <li>Subset of catalog from Bierhaus et al. (2022) with craters between 5 m - 80 m diameter used for interior-exterior roughness ratio in Bierhaus et al. (2023) and Rossmann et al. (2024).</li> </ul> </li> </ul> <p> </p>
Preliminary Results of Marine Gravity Anomaly and Bathymetry from SWOT Wide-Swath altimeter data
<p><span>We explore the potential of Ka-band radar interferometry (KaRIn) data from the SWOT mission for marine gravity and bathymetry applications. Our evaluation includes determining the deflection of vertical (DOV) using the least squares collocation (LSC) method, recovering gravity anomalies with the inverse Vening-Meinesz (IVM) approach, and predicting bathymetry through the gravity-geological method (GGM). SWOT-derived gravity anomalies in the study area, located between 20ºN - 30ºN and 135ºE - 145ºE, lies at the convergence of the Pacific and Eurasian tectonic plates. KaRIn data (only seven months) recovered gravity anomalies with an accuracy of 2.37 mGal, which is better than current models.</span></p> <p><span>The details of the method are discussed in a manuscript submitted to GRL.</span></p> <p> </p>
Code for paper 'Advances in Surface Water and Ocean Topography for Fine-Scale Eddy Identification from Altimeter Sea Surface Height Merging Maps'
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SWOT Level 2 Nadir Altimeter Interim Geophysical Data Record with Waveforms
The SWOT Level 2 Nadir Altimeter Interim Geophysical Data Record (IGDR) 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 IGDR 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 Medium-accuracy (preliminary) Orbit Ephemeris (MOE) and preliminary values for certain auxiliary data. The IGDR data are distributed as one file per half orbit in netCDF-4 file format with a nominal latency of < 1.5 days.<br>This collection is the parent collection to the following sub-collections: <br>https://podaac.jpl.nasa.gov/dataset/SWOT_L2_NALT_IGDR_SSHA_2.0 <br>https://podaac.jpl.nasa.gov/dataset/SWOT_L2_NALT_IGDR_GDR_2.0 <br>https://podaac.jpl.nasa.gov/dataset/SWOT_L2_NALT_IGDR_SGDR_2.0 <br>
Sentinel-6A MF Jason-CS L2 P4 Altimeter High Resolution (HR) STC Reduced Ocean Surface Topography
Provides L2 high resolution (HR) short time critical (STC; 36-hour latency) altimetry from the Poseidon-4 SAR altimeter on the Sentinel-6A Michael Freilich spacecraft. It contains Sea Surface Height (SSH), Sea Surface Height Anomalies (SSHA) and Significant Wave Height (SWH), along with 1 Hz Ku-band measurements processed from L1B altimetry including the range, orbital altitude, time, and water vapour. It also includes altimetry corrections, significant wave height and wind-speed from the AMR-C. This release is reduced to exclude the 20 Hz observations that are included in the standard product. The S6A STC product is analogous to the Jason-3 IGDR product.
SWOT Level 2 Nadir Altimeter Geophysical Data Record with Waveforms - SSHA, Version 1.0
Nadir Altimeter Geophysical Data Record (GDR) products similar to those from ongoing nadir altimeter missions such as Jason-3. Provide sea surface height, significant wave height and wind speed measurements from the nadir altimeter. GDR using restituted auxiliary data Uses the Precise Orbit Ephemeris (POE). Available with latency of < 90 days. Discrete measurements at nadir for each half orbit, along the ground track. Available in netCDF-4 file format.
Sentinel-6A MF Jason-CS L2 P4 Altimeter Low Resolution (LR) NRT Reduced Ocean Surface Topography
Provides low resolution (LR) near real time (NRT; 3-hour latency) measurements of sea surface height anomaly (SSHA), Significant Wave Height (SWH), and Wind Speed. The NRT product is analogous to the Jason-3 OGDR product.
Sentinel-6A MF Jason-CS L2 P4 Altimeter Low Resolution (LR) STC Reduced Ocean Surface Topography
Provides low resolution (LR) short time critical (STC; 36-hour latency) measurements of sea surface height anomaly (SSHA), Significant Wave Height (SWH), and Wind Speed. The STC product is analogous to the Jason-3 IGDR product.
SWOT Level 2 Nadir Altimeter Interim Geophysical Data Record with Waveforms - GDR Version D
Same as L2_NALT_GDR, using preliminary values for some auxiliary data. Uses Medium-accuracy (preliminary) Orbit Ephemeris (MOE). Available with latency of < 1.5 days. Discrete measurements at nadir for each half orbit, along the ground track. Available in netCDF-4 file format.<br>This collection is a sub-collection of its parent: https://podaac.jpl.nasa.gov/dataset/SWOT_L2_NALT_IGDR_D
Integrated Multi-Mission Ocean Altimeter Data for Climate Research Version 5.2
The Integrated Multi-Mission Ocean Altimeter Sea Surface Height (SSH) Version 5.2 dataset provides level 2 along track sea surface height anomalies (SSHA) for 10-day cycles from the TOPEX/Poseidon, Jason-1, OSTM/Jason-2, Jason-3, and Sentinel-6A missions geo-referenced to a mean reference orbit. It is produced by NASA Sea Surface Height (NASA-SSH) project investigators at Goddard Space Flight Center and Jet Propulsion Laboratory with support from NASA’s Physical Oceanography program, and was developed originally as an Earth System Data Record (ESDR) under the Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, which supported forward processing and incremental refinements through version 5.1 (released in April 2022).<br>Geophysical Data Records (GDRs) from each altimetry mission were interpolated to a common reference orbit with biases and cross-calibrations applied so that the derived SSHA are consistent between satellites to form a single homogeneous climate data record. The entire multi-mission data record covers the period from September 1992 to present; it is extended to include new observations approximately once each quarter. The previous release (version 5.1) integrated Jason-3 data and applied revised internal tides and pole tide across missions (GDR_F standard). The current release (version 5.2) includes the following revisions: a) GSFC std2006_cs21 orbit for all missions, b) GOT5.1 ocean tide model, c) TOPEX/Poseidon GDR_F data, d) Sentinel-6 LR version F08 data, e) Jason-3 re-calibrated radiometer wet troposphere correction. More information about the data content and derivation can be found in the v5.2 User’s Handbook (https://doi.org/10.5067/ALTUG-TJ152).<br>Please note that this collection contains the same data as https://doi.org/10.5067/ALTTS-TJA52, re-organized into one netCDF file per cycle for convenience.
GEOSAT Radar Altimeter DEM Atlas of Antarctica North of 72.1 degrees South, Version 1
The Antarctic atlas consists of 28 digital elevation maps which cover all of Antarctica north of 72.1 degrees south at a resolution of three kilometers. Each map contains surface elevations and coordinates for one atlas page covering 16 degrees of longitude. Data were acquired by the Geodetic Satellite (GEOSAT) Geodetic Mission (GM) from March 1985 through September 1986 and are available in both Universal Transverse Mercator (UTM) coordinates, and in latitude and longitude coordinates.Data were mapped using the UTM projection in atlas form to decrease the distortion that usually occurs at the poles. Many features of the Antarctic Ice Sheet are shown in more detail than in previous digital elevation models, especially along the margin of the East Antarctic Ice Sheet. A geostatistical mapping technique (Herzfeld et al. 1993) improved the accuracy of surface elevations compared to previous GEOSAT elevation data sets. This atlas will facilitate the monitoring of changes in surface elevation that could indicate mass changes in the Antarctic Ice Sheet.
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