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The Sentinel-3 altimetry (or surface topography) missions, uses radar altimetry, supported by a suite of other measurements, to provide measures of the height of the Earth's surfaces. This includes the ocean, where Sentinel-3 altimetry data is used to derive products relating to sea surface height, wind, and waves. In combination with other altimeters, the Sentinel-3 altimetry missions provides insight in to ocean physics, and vital inputs for weather forecasting.
The SAR Radar Altimeter (SRAL) emits burts of electromagnetic radiation in the c and ku radar bands, and subsequently records the patterns of their waveforms as they are reflected from the surface of the Earth. These waveforms give us invaluable information about the sea-surface topography. In SAR mode, SRAL provides an along track resolution of 300m resolution, at 1Hz and 20Hz frequency.
Further information on the sensor and its data can be found in the Sentinel-3 section of the EUMETSAT User Portal.
The learn-sral module consists of a collection of Python-based Jupyter notebooks designed to demonstrate the capability of the SAR Radar Altimeter (SRAL), carried by the Sentinel-3 satellites, and to help users begin to work with its data at level-1 and level-2. The module will introduce you to:
- the specifics of the SRAL sensor
- the ways in which you can access SRAL data
- the parameters that SRAL provides at level-1 and level-2
- approaches to working with SRAL data in common use cases
This module is based around a series of Jupyter Notebooks. These support high-level interactive learning by allowing us to combine code, text descriptions and data visualisations. If you have not worked with Jupyter Notebooks before, please look at the
Introduction to Python and Project Jupyter module to get a short introduction to their usage and benefits. Refer to this module's README for further information on how to set up Jupyter.
This module is split in to two parts, designed for:
- introductory users, who have basic knowledge of Python and are new to using SRAL data
- advanced users, who may be looking into more advanced use cases for the data.
There is a suggested order in which to access the notebooks, and pre-requisites where applicable are listed at the top of each notebook. However, not all notebooks may be relevant for every user, so we have tried to make each one as self contained as possible.
From this module, you can expect to learn:
- How to access SRAL data from both the EUMETSAT data services, and WEkEO
- The general file structure of SRAL products, and how to read them using Python
- How SRAL captures waveforms, and how these are used to derive geophysical products
- How to visualise SRAL data products, applying appropriate flags and quality levels
- The limitations and uncertainties associated with SRAL products