- All Categories (1662)
- Data (21)
- News (29)
- Missions (2)
- Events (16)
- Tools (10)
- Activities (7)
- Campaigns (1)
- Documents (1576)
News - Infographics
Showcasing Fundamental Data Records for Altimetry
ESA has developed a comprehensive suite of Earth system data records as part of the Fundamental Data Records for Altimetry (FDR4ALT) project.
News - General News
ESA's improved Earth system data records: what is in store for the future?
Fundamental Data Records (FDRs) are instrumental in advancing our understanding of Earth systems and for addressing societal challenges effectively. These long-term records contain uncertainty-quantified, calibrated and geo-located multi-instrument/multi-platform satellite sensor data spanning several decades to support climate-related applications.
News - How to guides
HEDAVI Discover: a step-by-step guide
The Heritage Data Visualisation tool (HEDAVI) is a platform developed by the French Science Consulting for Earth Observation group, VisioTerra, which allows users to freely access over 40 years of ESA Earth Observation Heritage data, Third Party Missions and some Copernicus data.
News - Maintenance News
ESA EO Dissemination Services - Maintenance on 25 and 26 March 2024
Scheduled software maintenance on ESA EO Dissemination Services on 25 and 26 March 2024
Document - Newsletter
Earth Online Newsletter - 08 March 2024
This issue of the Earth Online Newsletter covers a selection of the latest news and events from ESA.
News - Data Release news
FDR4ALT - ESA unveils new cutting-edge ERS/Envisat Altimeter and Microwave Radiometer Datasets
The European Space Agency (ESA) has developed a comprehensive suite of innovative Earth system data records as part of the Fundamental Data Records for Altimetry project - FDR4ALT.
Document - Product Document
FDR4ALT-Validation-Report-TDP-Sea-Ice
FDR4ALT Product Validation Report: Sea-Ice TDP
Document - Product Document
FDR4ALT-Validation-Report-TDP-Ocean-Waves
FDR4ALT Product Validation Report: Ocean Waves TDP
Document - Product Document
FDR4ALT-Validation-Report-TDP-Ocean-Coastal
Product Validation Report: Ocean & Coastal TDP
Document - Product Document
FDR4ALT-Validation-Report-TDP-Land-Ice
FDR4ALT Product Validation Report: Land-Ice TDP
Document - Product Document
FDR4ALT-Validation-Report-TDP-Inland-Waters
FDR4ALT Product Validation Report: Inland Waters TDP
Document - Product Document
FDR4ALT-Validation-Report-TDP-Atmosphere
FDR4ALT Product Validation Report: Atmosphere TDP
Document - Product Document
FDR4ALT-Uncertainties-Characterisations
FDR4ALT Uncertainty Characterisation Report
Document - Product Specifications
FDR4ALT-Product-Requirements-Format-Specifications
FDR4ALT Products Requirements and Format Specification
Document - Detailed Processing Model
FDR4ALT-Detailed-Processing-Model
FDR4ALT Detailed Processing Model
Data - EO Sign In Authentication (Open)
Fundamental Data Records for Radiometry [MWR_FDR___]
This dataset is a Fundamental Data Record (FDR) resulting from the ESA FDR4ALT project. The Fundamental Data Record for Radiometry V1 products contain intercalibrated Top of the Atmosphere brightness temperatures at 23.8 and 36.5 GHz. The collection covers data for the ERS-1, ERS-2 and Envisat missions, and is built upon a new processing of Level 0 data, incorporating numerous improvements in terms of algorithms, flagging procedures, and corrections. Compared to existing datasets, the Radiometry FDR demonstrates notable improvements in several aspects: New solutions for instrumental effects (ERS Reflector loss, Skyhorn, and Sidelobe corrections) Native sampling rate of 7Hz with enhanced coverage The FDR4ALT products are available in NetCDF format. Free standard tools for reading NetCDF data can be used. Information for expert altimetry users is also available in a dedicated NetCDF group within the products. Please consult the FDR4ALT Product User Guide before using the data. The FDR4ALT datasets represent the new reference data for the ERS/Envisat altimetry missions, superseding any previous mission data. Users are strongly encouraged to make use of these datasets for optimal results.
