By Robin Hamaker-Taylor and Jennifer Steeves
Working with financial institutions to understand analyse and disclose physical climate risks and opportunities to loans, investments and across portfolios demands the application of the most up-to-date climate data and information. By deploying data from historic climate observations, modelled projections of future climate and various social, environmental and economic datasets it is possible to begin to build a picture of risk exposure to financial institutions. In recent years, Acclimatise has also been working with new data sources such as Earth Observation (EO) data, which offer the potential to develop our understanding of real-time risk exposure, especially in areas where other data is sparse.
Acclimatise worked with leading programmes, such as the European Space Agency’s Earth Observation for Sustainable Development Climate Resilience (EO4SD CR) cluster, to demonstrate the potential of EO data to build climate resilience. The potential of EO data is enormous, and the developments in the temporal and spatial resolution of satellite data is a powerful tool of analysis. In recognition of this, Acclimatise this month became an Associate Member of Group on Earth Observations (GEO). The GEO is an intergovernmental partnership that improves the availability, access and use of EOs for a sustainable planet.
What is EO and EO data?
EO is the collection, analysis and presentation of information about the Earth’s physical, chemical and biological systems and has the capability to do so across remote and inaccessible terrain. It involves monitoring and assessing the status of and changes in the natural and man-made environment. There are now thousands of data buoys operating in the world’s oceans, hundreds of thousands of land-based environmental monitoring stations, tens of thousands of observations from aircraft platforms and numerous environmental satellites orbiting the globe, according to GEOSS and other academic research.
EO satellites can collect real-time data on a wide range of indicators such as water distribution, land use, water cycles, atmospheric profiles, heat mapping, sea surface evaluations, and global-regional energy exchanges. EO data provide large quantities of timely and accurate environmental information, which, when combined with other datasets, can give unique insights into managing climate risks.
Of the 50 Global Climate Observing System (GCOS) essential climate variables, roughly half can only be observed from space, making EO an irreplaceable component of climate monitoring. EO datasets are critical in regions where insufficient information is available from weather stations (which is often the case), and its consistency facilitates coordination of information sharing. It is also very useful where on-the-ground assessments of infrastructure are not possible, for example, due to safety concerns.
Why is EO data useful for financial institutions?
Financial institutions (FIs) are accustomed to integrating data from various sources into their risk screening processes. As FIs become increasingly aware of the need to consider physical climate risks in their assessments, EO data offers enormous potential. FIs often lend or invest in diverse geographies with varying levels of available climate hazard data.
EO datasets can complement data held by FIs on their borrowers or investments including data on physical assets, on-site operations, supply chains, markets and logistics. High-quality data on climate parameters combined with other critical investment-relevant information helps investors and asset managers understand current and future risks to their investments across sectors. EO data is often used for post-disaster damage assessment. EO data can also be integrated into existing tools platforms and analyses used by FIs.
Evidence from current uses of EO data by financial institutions
To date, EO data has been used in the context of climate risk primarily by development finance institutions (DFIs), which indicates how commercial FIs could eventually use this type of data. The EO4SD Climate Resilience Cluster provides EO-based products and services to DFIs that have investments in developing countries to support climate resilience. DFIs and other agencies supported through the project include the World Bank, Asian Development Bank (ADB), Inter-American Development Bank (IDB), African Risk Capacity (ARC), Multilateral Investment Guarantee Agency (MIGA) and the International Finance Corporation (IFC).
For example, the EO4SD project is collaborating with a World Bank urban development initiative in Greater Monrovia, Liberia to provide EO-based products and services. An example of this is a coastal erosion service involving 41km of shoreline evolution monitored through a 34-year satellite series, which has been acquired through analysis of satellite images from Landsat, Sentinel 2 and Worldview 3. The analysis estimates that the land loss area from 1984 to 2019 in the 50 km coastline of Greater Monrovia is 0.8 km2. This can be overlaid with data on population and critical infrastructure to aid investment planning.
Flood mapping is also benefiting from EO-based services as EO data provides consistent historical information on floods. The 34-year high-resolution sea-level rise data was also used to identify coastal and inland flood risk areas in parts of Monrovia. The model integrates sea level rise projections to 2030, mapped against a digital terrain model to identify high flood risk areas. These flood maps help the World Bank and local authorities identify the most effective flood management actions and enable better planning decisions to avoid unnecessary development in risky areas.
The direction of travel: What next for EO?
EO data can help banks and lenders around the world understand and prepare for climate change impacts, accounting for future climate risks and opportunities in investment and lending decisions. As EO data gets easier to extract and apply, its use in climate risk assessments will continue to unfold.
One exciting potential application of EO data is in the context of trend analysis where past events are correlated to experienced losses to help paint a picture of risk. There is also potential to develop statistical information using EO data for certain climate hazards such as flooding. Processed climate data will soon be available on flood return periods, for example, as will statistics on flood extent and flood duration. Acclimatise are now gearing up for phase 2 of the EO4SD project, which will build the capacity of DFIs and partner agencies in the practical application of EO data.
Stay in touch with how this project unfolds and how we are using EO to build climate resilience here.