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:

• Data link
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Temporal Extent:

Start: 1990-03-31T00:00:00.000Z

Spatial Extent:

Minimum Bounding Rectangle: -90 -180 90 180

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

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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:

• Data link
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Temporal Extent:

Start: 1990-03-31T00:00:00.000Z

Spatial Extent:

Minimum Bounding Rectangle: -90 -180 90 180

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

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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.

Links:

• Data link

Temporal Extent:

Start: 1998-01-01T00:00:00.000Z

Spatial Extent:

Minimum Bounding Rectangle: -90 -180 90 180

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

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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:

• Data link
• Data link
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• ef1627f523764eae8bbb6b81bf1f7a0a

Temporal Extent:

Start: 1992-09-15T00:00:00.000Z

End: 2019-12-31T23:59:59.000Z

Spatial Extent:

Minimum Bounding Rectangle: -90 -180 90 180

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

Description:

This dataset contains a 17-year-long (January 2002 to December 2019 ), high-resolution (20 Hz), along-track sea level dataset in coastal zones of: Northeast Atlantic, Mediterranean Sea, whole African continent, North Indian Ocean, Southeast Asia, Australia and North and South America. 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 a new version of the ESA SL_cci+ dataset of coastal sea level anomalies 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: a total of 756 altimetry-based virtual coastal stations have been selected and sea level anomalies time series together with associated coastal sea level trends have been computed over the study time span. 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 is v2.2 of the data and is a copy of the v2.2 data published on the SEANOE (SEA scieNtific Open data Edition) website (https://doi.org/10.17882/74354#98856). The dataset should be cited as: Cazenave Anny, Gouzenes Yvan, Birol Florence, Legér Fabien, Passaro Marcello, Calafat Francisco M, Shaw Andrew, Niño Fernando, Legeais Jean François, Oelsmann Julius, Benveniste Jérôme (2022). New network of virtual altimetry stations for measuring sea level along the world coastlines. SEANOE. https://doi.org/10.17882/74354In addition,it would be appreciated that the following work(s) be cited too, when using this dataset in a publication : - Cazenave Anny, Gouzenes Yvan, Birol Florence, Leger Fabien, Passaro Marcello, Calafat Francisco M., Shaw Andrew, Nino Fernando, Legeais Jean François, Oelsmann Julius, Restano Marco, Benveniste Jérôme (2022). Sea level along the world’s coastlines can be measured by a network of virtual altimetry stations. Communications Earth & Environment, 3 (1). https://doi.org/10.1038/s43247-022-00448-z - Benveniste Jérôme, Birol Florence, Calafat Francisco, Cazenave Anny, Dieng Habib, Gouzenes Yvan, Legeais Jean François, Léger Fabien, Niño Fernando, Passaro Marcello, Schwatke Christian, Shaw Andrew (2020). Coastal sea level anomalies and associated trends from Jason satellite altimetry over 2002–2018. Scientific Data, 7 (1). https://doi.org/10.1038/s41597-020-00694-w

Links:

• Data link
• Data link
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• 90049a6555d1480bb5ce9637051dede8

Temporal Extent:

Start: 2002-01-01T00:00:00.000Z

End: 2019-12-31T23:59:59.000Z

Spatial Extent:

Minimum Bounding Rectangle: -90 -180 90 180

FEDEO Short Name: 90049a6555d1480bb5ce9637051dede8 Version ID: NA Unique ID: C3327359934-FEDEO