Synthetic Aperture Radar systems, such as those on the Copernicus Sentinel-1 satellites, are a powerful tool for observing the sea surface at high spatial resolution over large areas—thus providing wind speed and direction measurements in the ocean, especially in marine coastal areas.
Within the framework of the myECOSYSTEM showcase of the H2020 e-shape project, derived Sea Surface Wind data are experimented to support the management and the environmental assessment of selected Coastal Protected Areas.
Sea Surface Wind (SSW), i.e., speed and direction, is a physical Essential Climate Variable (ECV), which crucially contributes to the characterisation of Earth’s climate system and its changes. SSW measurements may be provided by several different sources, such as in situ stations, spaceborne active microwave sensors (i.e., scatterometers and radar altimeters), and numerical weather prediction (NWP) models.
In situ stations are unfortunately costly and sparse, and not deployable in areas that are difficult to access. They are typically used for in situ validation of wind estimates, derived from other techniques such as modelling and other sources. Satellite scatterometers and radar altimeters, on the other hand, are suitable for synoptic and mesoscale observations of the ocean wind.
However, the main weaknesses of scatterometers and altimeters are a lack of accurate data near the shore and the temporal sampling. As a consequence, wind estimates from those spaceborne systems are not useful for studies focused on near-shore processes. Furthermore, NWP models (mainly global or at scales of an EU sea basin) may suffer from problems of precision and accuracy in marine coastal areas, and so would not be adequate for lower scale coastal dynamics.
Synthetic Aperture Radar (SAR) systems, like those on the Sentinel-1 satellites of the European Union’s Copernicus Programme, can provide wind speed and direction measurements in the ocean, especially in marine coastal areas.
The importance of SAR derived SSW retrievals is recognised, at both global and local scale, in a wide range of applications such as marine meteorology, oceanography, oil spill monitoring and in view of wind resources assessment for renewable energy plant operations and coastal dynamics modelling.
In the research activities conducted within the framework of the myECOSYSTEM showcase of the H2020 e-shape (EuroGEO Showcases: Applications Powered by Europe) project, which intends to provide remote sensing based information able to support the management of selected Protected Areas and environmental assessment in benchmark ecosystems, the SAR-based algorithm Multi Scale (MS) LG-Mod was fully developed (Rana et al., 2021).
A “local” multi-scale analysis of wind-aligned SAR patterns was introduced, with the aim to improve the LG-Mod sensitivity (Rana et al., 2019) to SAR backscattering modulations, occurring with various spatial wavelengths especially in coastal areas.
The assessment of the MS LG-Mod algorithm for SSW direction retrievals was performed on both simulated SAR images and a high-resolution (10 m by 10 m) Copernicus Sentinel-1 dataset, exploiting in situ wind observations gathered by the National Oceanic and Atmospheric Administration National Data Buoy Center (NOAA NDBC) for validation.
By adopting the Directional Accuracy Maximisation Criterion (DAMC), the MS LG-Mod proved able to automatically select the local processing scale, which may be regarded as optimal for pattern enhancement in order to provide the best achievable local directional estimation, once a set of processing scales has been fixed.
The use of the Copernicus Sentinel-1 products allows the developed algorithm to provide a spatial distribution of both SSW direction and the related uncertainty. In turn, the spatial distribution of both SSW speed along with the corresponding uncertainty map, may be also obtained in order to fulfil the further lack of wind accuracy information.
The MS LG-Mod algorithm was applied on two study areas of the e-shape project, La Palma and the Wadden Sea (shown in the following images), with the aim to evaluate the suitability of Copernicus Sentinel-1 high resolution data to reproduce the local wind spatial variability in marine coastal areas.
The latter capability was confirmed by comparison with global European Centre for Medium-Range Weather Forecasts (ECMWF) model data, which may not adequately resolve the wind speed and/or direction dynamics when used in complex coastal areas (e.g., in cases of marked orography).
In addition, NWP models are able to provide all the wind estimates only with a unique maximum value of uncertainty (e.g., 20° for direction and 2 m/s for speed, in the case of ECMWF). The MS LG-Mod algorithm, in comparison, is capable of providing SSW direction and speed maps and their uncertainty maps as well.
Dr Tijani Khalid, researcher with Geophysical Application Processing - GAP Srl, states, “High resolution sea surface wind fields derived from high quality Copernicus Sentinel-1 data may be fruitfully used to improve model tracking of oil spill events, especially for the conservation of coastal protected areas”.
About the Copernicus Sentinels
The Copernicus Sentinels are a fleet of dedicated EU-owned satellites, designed to deliver the wealth of data and imagery that are central to the European Union's Copernicus environmental programme.
The European Commission leads and coordinates this programme, to improve the management of the environment, safeguarding lives every day. ESA is in charge of the space component, responsible for developing the family of Copernicus Sentinel satellites on behalf of the European Union and ensuring the flow of data for the Copernicus services, while the operations of the Copernicus Sentinels have been entrusted to ESA and EUMETSAT.
Did you know that?
Earth observation data from the Copernicus Sentinel satellites are fed into the Copernicus Services. First launched in 2012 with the Land Monitoring and Emergency Management services, these services provide free and open support, in six different thematic areas.
The Copernicus Marine Environment Monitoring Service (CMEMS) provides regular and systematic reference information on the physical and biogeochemical state, variability and dynamics of the ocean and marine ecosystems for the global ocean and the European regional seas.
Scientific references:
Rana, F. M., & Adamo, M. (2021). Multi-Scale LG-Mod Analysis for a More Reliable SAR Sea Surface Wind Directions Retrieval. Remote Sensing, 13(3), 410. https://doi.org/10.3390/rs13030410.
Rana, F.M., Adamo, M., Lucas, R., & Blonda, P. (2019). Sea surface wind retrieval in coastal areas by means of Sentinel-1 and numerical weather prediction model data. Remote Sensing of Environment, 225, 379-391. https://doi.org/10.1016/j.rse.2019.03.019.