The Federated Earth System Simulation and Data Processing Platform provides a distributed infrastructure of data and compute providers to support the execution of Earth System Simulation and Data Processing workflows at scale.
It offers a flexible cloud-based data processing capacity to create and scale data processing pipelines that run on optimised execution environments near the data. Jupyter Notebooks and openEO API offer user friendly and intuitive processing of a wide variety of Earth Observation datasets on these computing providers, including the ability to integrate these data with modelling and forecasting workflows leveraging specialised compute resources.
Providers of the Copernicus Data Processing Platform already count with an extensive collection of Copernicus datasets, managed according to the FAIR principles, and may be further extended with new datasets requested by users of the platform.
C-SCALE has developed an easier mechanism in just one-step, to discover relevant scientific data in satellite data archives across Europe and across the C-SCALE Data Federation. This service will support scientists, researchers and any other user communities, to quickly find the data they were looking for in the huge offer of Copernicus Data.
The Metadata Query Service (MQS) implements a STAC API to accept and answer STAC-compliant queries for products available across the C-SCALE Data Federation. It is aware of individual sources of data in the federation, and can forward incoming queries to those sources (sites), receive their responses and combine them into a compound response, which is then returned to the user, indicating the availability of products matching their query across the federation.
The MQS can also be made aware of different sites’ focus in terms of geographical area, acquiring and retention policy, product type selection and similar factors, so that incoming queries do not need to be redistributed to all sites but rather only to those who are likely to possess matching products.
With this service a user can easily deploy a workflow that produces a monthly high resolution, seasonal, ensemble drought forecast for a river basin of interest.
The service has the following functionality:
2. Prepare the data for ingestion into the WFLOW hydrological model.
3. Produce a 50 member ensemble forecast using WFLOW.
4. Visualise the forecast in an interactive Jupyter Notebook displaying river discharge timeseries and interactive maps of soil moisture anomalies (in development).
The service is currently available for deployment on C-SCALE’s HTC infrastructure. Access is to (HTC) resources to deploy this service is achieved via SRAM.