Day 4

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Paper title Space-derived climate data for a sustainable future
  1. Josh Gilbert Sust Global Speaker
  2. Gopal Erinjippurath Sust Global
Form of presentation Poster
  • D1. Managing Risks
    • D1.03 Satellite EO for Disaster Risk Transfer & Insurance
Abstract text Satellite EO is one of the most valuable tools for managing climate risk, and will play a key role in building the foundation for sustainable decision making. Over the past year, Sust Global has been part of the ESA ARTES 4.0 Business application program, delivering the project, “Sustainability Monitoring of Commodities using Geospatial Analytics (SMOCGEO)”. This project has driven machine learning-based transformations on data collections from active ESA space programs, enabling climate risk awareness and adaptation measures. Initial applications have targeted intelligence outcomes across the supply chains for global commodities, and further usage has the potential to help Ministries of Finance manage physical and transition climate risk.

Through their flagship Copernicus missions and sentinel satellites, ESA has pioneered earth observation programs, harnessing a rich catalogue of data on land surface, oceans and the atmosphere. Together, these analysis-ready datasets provide unique inputs to help monitor global climate change and sustainable operations. Sust Global has bridged these earth observation datasets with commercial applications focused on sustainability monitoring and climate intelligence, developing new climate adaptation measures. This will allow financial institutions and other users to include credible climate data in their decision making.

Through this project, Sust Global has explored the following:
• Climate Model validation: Validation and back testing of physical risk from climate change across multiple climate scenarios
• Metrics refinement: Define sustainability metrics derived from a combination of earth observation, emissions monitoring and projections from frontier climate models
• Summarized reporting: Heat mapping of high-risk nodes of operation within the supply chain of commodities with exposure to extreme climate peril
• Alerting and notifications: Near real time alerting based on near term climate risks and emissions exceeding thresholds validated using earth observation data
As we develop our capabilities in climate intelligence, we see the clear need for validation of projections from frontier climate models with reliable observations. Satellite-based observations of events and activities on the ground are valuable sources of reference for climate related hazards.

In addition to these mature offerings, developed over a decade of research, and development within the earth observation community, we see increasing application from the emergence of new data sources, in particular, Sentinel-5p. Through the L3 emissions profiling datasets, orthorectified area-averaged time series of nitrogen dioxide, methane and sulphur dioxide emissions from industrial sources is now possible. Bringing together these visible, multi-spectral and emissions profiles will enable us to uniquely monitor the sustainability of industrial operations across the globe.

Using ESA’s services and datasets, we are able to validate and back test projections of frontier models and model ensembles across different climate scenarios. Such validation builds confidence and provides a measure of tolerance on our forward-looking projections of climate hazards.

The SMOCGEO project began with exploring source sites for metal commodities. We found operations in metal commodities uniquely interesting due to their long time horizons, large sizes and isolated sources.
Through past and existing efforts like EO4SD, ESA has supported and pioneered the use of EO for sustainable development. SMOCGEO has brought innovation on the next wave of such vertical focused applications by bringing together the space derived observations with data from frontier climate science for global sustainability monitoring, exploiting the full potential of the Sentinel missions and building the foundation for climate disaster risk management.