OpenSearch

Using the NASA EOSDIS Common Metadata Repository

Collection Search

  • ADT - Absolute Dynamic Topography

    https://cmr.earthdata.nasa.gov/search/concepts/C1214586177-SCIOPS.xml
    Description:

    Contents: along-track sea surface heights above geoid; dynamic topography is the sum of sea level anomaly (SLA) and mean dynamic topography (MDT, Rio05 here) Use: study of the general circulation (ocean gyres ...) The data are global mono altimeter satellite products, homogeneous with other satellites, available in near-real time and in delayed time in NetCDF format. In delayed time, two types of products are available: - "Ref" (Reference) series: homogeneous datasets based on two satellites (Topex/Poseidon, Jason-1 + ERS, Envisat) with the same groundtrack. Sampling is stable in time. - "Upd" (Updated) series: up-to-date datasets with up to four satellites at a given time (adding GFO and/or Topex/Poseidon on its new orbit). Sampling and Long Wavelength Errors determination are improved, but quality of the series is not homogeneous. Regional products with an improved quality are available in local areas ("http://www.aviso.oceanobs.com/html/donnees/produits/hauteurs/regional/")

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: -90 -180 90 180

    SCIOPS Short Name: AVISO_ADT Version ID: Not provided Unique ID: C1214586177-SCIOPS

  • CDDIS_DORIS_data_cycle

    https://cmr.earthdata.nasa.gov/search/concepts/C1000000000-CDDIS.xml
    Description:

    Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS) was developed by the Centre National d'Etudes Spatiales (CNES) with cooperation from other French government agencies. The system was developed to provide precise orbit determination and high accuracy location of ground beacons for point positioning. DORIS is a dual-frequency Doppler system that has been included as an experiment on various space missions such as TOPEX/Poseidon, SPOT-2, -3, -4, and -5, Envisat, and Jason satellites. Unlike many other navigation systems, DORIS is based on an uplink device. The receivers are on board the satellite with the transmitters are on the ground. This creates a centralized system in which the complete set of observations is downloaded by the satellite to the ground center, from where they are distributed after editing and processing. An accurate measurment is made of the Doppler shift on radiofrequency signals emitted by the ground beacons and received on the spacecraft.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: -90 -180 90 180

    CDDIS Short Name: CDDIS_DORIS_data_cycle Version ID: 1 Unique ID: C1000000000-CDDIS

  • CDDIS_DORIS_products_positions

    https://cmr.earthdata.nasa.gov/search/concepts/C1000000020-CDDIS.xml
    Description:

    Station position and velocity solutions (weekly and cumulative) in Software INdependent EXchange (SINEX) format derived from analysis of Doppler Orbitography by Radiopositioning Integrated on Satellite (DORIS) data. The solutions include daily values of Earth Orientation Parameters (EOPs). These products are the generated by analysis centers in support of the International DORIS Service (IDS). Time series of station coordinate solutions in Station Coordinate Difference (STCD) are also generated by the IDS analysis centers. Weekly solutions represent the IDS contribution to the International Terrestrial Reference Frame (ITRF) determination.

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    Minimum Bounding Rectangle: -90 -180 90 180

    CDDIS Short Name: CDDIS_DORIS_products_positions Version ID: 1 Unique ID: C1000000020-CDDIS

  • CDDIS_DORIS_products_stcd

    https://cmr.earthdata.nasa.gov/search/concepts/C1000000080-CDDIS.xml
    Description:

    Station position time series solutions in DORIS Station Coordinate Difference (STCD) format derived from analysis of Doppler Orbitography by Radiopositioning Integrated on Satellite (DORIS) data. These products are the generated by analysis centers in support of the International DORIS Service (IDS).

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: -90 -180 90 180

    CDDIS Short Name: CDDIS_DORIS_products_stcd Version ID: 1 Unique ID: C1000000080-CDDIS

  • CDDIS_GNSS_satellite_data

    https://cmr.earthdata.nasa.gov/search/concepts/C1000000024-CDDIS.xml
    Description:

    Global Navigation Satellite System (GNSS) data consists of the U.S. Global Positioning System (GPS) and the Russian GLObal NAvigation Satellite System (GLONASS) (plus other international systems) data sets. The Global Positioning System, developed by the U.S. Department of Defense, has been fully operational since 1994. GPS consists of a constellation of 24 satellites and three active spares each traveling in a 12 hour circular orbit, 20,200 kilometers above the Earth. The satellites are positioned so that six are observable nearly 100 percent of the time from any point on the Earth. The GLObal NAvigation Satellite System (GLONASS), managed and deployed by the Russian Federation, is similar to the U. S. Global Positioning System (GPS) in terms of the satellite constellation, orbits, and signal structure. GNSS receivers detect, decode, and process signals from the GNSS satellites. The satellites transmit the ranging codes on two radio-frequency carriers, allowing the locations of GNSS r

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: -90 -180 90 180

    CDDIS Short Name: CDDIS_GNSS_satellite_data Version ID: 1 Unique ID: C1000000024-CDDIS

  • CDDIS_SLR_predictions

    https://cmr.earthdata.nasa.gov/search/concepts/C1000000025-CDDIS.xml
    Description:

    Predicted satellite orbits for Satellite Laser Ranging (SLR) tracking of satellites equipped with corner cube retroreflectors. SLR stations download these prediction files and coordinate tracking schedules for satellite acquisition. The predicted orbit files typically contain orbit information for multiple days and are issued on a daily or sub-daily basis.

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    Minimum Bounding Rectangle: -90 -180 90 180

    CDDIS Short Name: CDDIS_SLR_predictions Version ID: 1 Unique ID: C1000000025-CDDIS

  • ESA Lakes Climate Change Initiative (Lakes_cci): Lake products, Version 1.0

    https://cmr.earthdata.nasa.gov/search/concepts/C2548142668-FEDEO.xml
    Description:

    This dataset contains various global lake products (1992-2019) produced by the European Space Agency (ESA) Lakes Climate Change Initiative (Lakes_cci) project.Lakes are of significant interest to the scientific community, local to national governments, industries and the wider public. A range of scientific disciplines including hydrology, limnology, climatology, biogeochemistry and geodesy are interested in distribution and functioning of the millions of lakes (from small ponds to inland seas), from the local to the global scale. Remote sensing provides an opportunity to extend the spatio-temporal scale of lake observation. The five thematic climate variables included in this dataset are:• Lake Water Level (LWL): a proxy fundamental to understand the balance between water inputs and water loss and their connection with regional and global climate changes.• Lake Water Extent (LWE): a proxy for change in glacial regions (lake expansion) and drought in many arid environments, water extent relates to local climate for the cooling effect that water bodies provide.• Lake Surface Water temperature (LSWT): correlated with regional air temperatures and a proxy for mixing regimes, driving biogeochemical cycling and seasonality. • Lake Ice Cover (LIC): freeze-up in autumn and advancing break-up in spring are proxies for gradually changing climate patterns and seasonality. • Lake Water-Leaving Reflectance (LWLR): a direct indicator of biogeochemical processes and habitats in the visible part of the water column (e.g. seasonal phytoplankton biomass fluctuations), and an indicator of the frequency of extreme events (peak terrestrial run-off, changing mixing conditions).Data generated in the Lakes_cci project are derived from data from multiple instruments and multiple satellites including; TOPEX/Poseidon, Jason, ENVISAT, SARAL, Sentinel, Landsat, ERS, Terra/Aqua, Suomi NPP, Metop and Orbview. For more information please see the product user guide in the documents.

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    Minimum Bounding Rectangle: -90 -180 90 180

    FEDEO Short Name: 3c324bb4ee394d0d876fe2e1db217378 Version ID: NA Unique ID: C2548142668-FEDEO

  • ESA Lakes Climate Change Initiative (Lakes_cci): Lake products, Version 1.1

    https://cmr.earthdata.nasa.gov/search/concepts/C2548142828-FEDEO.xml
    Description:

    This dataset contains various global lake products (1992-2019) produced by the European Space Agency (ESA) Lakes Climate Change Initiative (Lakes_cci) project. This is version 1.1 of the dataset.Lakes are of significant interest to the scientific community, local to national governments, industries and the wider public. A range of scientific disciplines including hydrology, limnology, climatology, biogeochemistry and geodesy are interested in distribution and functioning of the millions of lakes (from small ponds to inland seas), from the local to the global scale. Remote sensing provides an opportunity to extend the spatio-temporal scale of lake observation. The five thematic climate variables included in this dataset are:• Lake Water Level (LWL): a proxy fundamental to understand the balance between water inputs and water loss and their connection with regional and global climate changes.• Lake Water Extent (LWE): a proxy for change in glacial regions (lake expansion) and drought in many arid environments, water extent relates to local climate for the cooling effect that water bodies provide.• Lake Surface Water temperature (LSWT): correlated with regional air temperatures and a proxy for mixing regimes, driving biogeochemical cycling and seasonality. • Lake Ice Cover (LIC): freeze-up in autumn and advancing break-up in spring are proxies for gradually changing climate patterns and seasonality. • Lake Water-Leaving Reflectance (LWLR): a direct indicator of biogeochemical processes and habitats in the visible part of the water column (e.g. seasonal phytoplankton biomass fluctuations), and an indicator of the frequency of extreme events (peak terrestrial run-off, changing mixing conditions).Data generated in the Lakes_cci project are derived from data from multiple instruments and multiple satellites including; TOPEX/Poseidon, Jason, ENVISAT, SARAL, Sentinel, Landsat, ERS, Terra/Aqua, Suomi NPP, Metop and Orbview. For more information please see the product user guide in the documents.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: -90 -180 90 180

    FEDEO Short Name: ef1627f523764eae8bbb6b81bf1f7a0a Version ID: NA Unique ID: C2548142828-FEDEO

  • ESA Sea Level Climate Change Initiative (Sea_Level_cci): A database of coastal sea level anomalies and associated trends from Jason satellite altimetry from 2002 to 2018

    https://cmr.earthdata.nasa.gov/search/concepts/C2548142874-FEDEO.xml
    Description:

    This dataset contains 17-year-long (June 2002 to May 2018 ), high-resolution (20 Hz), along-track sea level dataset in coastal zones of six regions: Mediterranean Sea, Northeast Atlantic, West Africa, North Indian Ocean, Southeast Asia and Australia. Up to now, satellite altimetry has provided global gridded sea level time series up to 10-15 km from the coast only, preventing the estimation of how sea level changes very close to the coast on interannual to decadal time scales. This dataset has been derived from the ESA SL_cci+ v1.1 dataset of coastal sea level anomalies (also available in the catalogue, DOI:10.5270/esa-sl_cci-xtrack_ales_sla-200206_201805-v1.1-202005), which is based on the reprocessing of raw radar altimetry waveforms from the Jason-1, Jason-2 and Jason-3 satellite missions to derive satellite-sea surface ranges as close as possible to the coast (a process called ‘retracking’) and optimization of the geophysical corrections applied to the range measurements to produce sea level time series. This large amount of coastal sea level estimates has been further analysed to produce the present dataset: it consists in a selection of 429 portions of satellite tracks crossing land for which valid sea level time series are provided at monthly interval together with the associated sea level trends over the 17-year time span at each along-track 20-Hz point, from 20 km offshore to the coast.The main objective of this dataset is to analyze the sea level trends close to the coast and compare them with the sea level trends observed in the open ocean and to determine the causes of the potential differences.The product has been developed within the sea level project of the extension phase of the European Space Agency (ESA) Climate Change Initiative (SL_cci+). See 'The Climate Change Coastal Sea Level Team (2020). Sea level anomalies and associated trends estimated from altimetry from 2002 to 2018 at selected coastal sites. Scientific Data (Nature), in press'.This dataset has a DOI: https://doi.org/10.17882/74354

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    Minimum Bounding Rectangle: -45 -30 60 160

    FEDEO Short Name: a386504aa8ae492f9f2af04c109346e9 Version ID: NA Unique ID: C2548142874-FEDEO

  • ESA Sea Level Climate Change Initiative (Sea_Level_cci): Altimeter along-track high resolution sea level anomalies in some coastal regions (2002-2018) from the JASON satellites, v1.1

    https://cmr.earthdata.nasa.gov/search/concepts/C2548143583-FEDEO.xml
    Description:

    This dataset contains along-track sea level anomalies derived from satellite altimetry. Altimeter along-track sea level measurements from the Jason-1, Jason -2 and Jason-3 satellite missions have been processed to produce high resolution (20 Hz, corresponding to an along-track distance of ~300m) sea level anomalies, in order to provide long-term homogeneous sea level time series as close to the coast as possible in six different coastal regions (North-East Atlantic, Mediterranean Sea, Western Africa, North Indian Ocean, South-East Asia and Australia). These six time series cover the period from 15 January 2002 to 30 May 2018.The product benefits from the spatial resolution provided by high-rate data, the Adaptive Leading Edge Subwaveform Retracker (ALES) and the post-processing strategy of the along-track (X-TRACK) algorithm, both developed for the processing of coastal altimetry data, as well as the best possible set of geophysical corrections. The main objective of this product is to provide accurate altimeter Sea Level Anomalies (SLA) time series as close to the coast as possible in order to assess whether the coastal sea level trends experienced at the coast are similar to the observed sea level trends in the open ocean and to determine the causes of the potential discrepancies.The product has been developed within the sea level project of the extension phase of the European Space Agency (ESA) Climate Change Initiative (SL_cci+). During the project, the product will be extended in spatial coverage and with additional altimeter missions. This version of the dataset is v1.1. (DOI: 10.5270/esa-sl_cci-xtrack_ales_sla-200206_201805-v1.1-202005)

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: -45 -30 60 160

    FEDEO Short Name: 222cf11f49a94d2da8a6da239df2efc4 Version ID: NA Unique ID: C2548143583-FEDEO