On 29th July at 10:00 EDT, Acclimatise CEO John Firth will be moderating an EO4SD-led panel discussion as part of the World Bank’s Innovate4Climate virtual conference. This will take stock of the use of Earth Observation (EO) data in climate resilience, and look to the future in regards to what development practitioners will find useful next in terms of EO products and services.
Introduce and encourage the use of earth observation (EO) products and services for the purposes of building climate resilience, particularly in a development setting
Catalyse the innovative deployment EO products and services across the project life cycle and across a range of decision-making contexts, from finance mobilisation to monitoring and evaluation
Enable our audience to learn about cost-effective EO climate data and platforms, and how these can be accessed and used.
In an article released on 9 April 2020, the World Meteorological Organization (WMO) expressed its concerns on the impacts that the COVID-19 pandemic is having on the Earth Observing System, which has major implications on weather observations and forecasts, as well as on the monitoring of atmospheric processes and climate change.
On the positive side,
a significant portion of the WMO’s global observing system is either partly or
fully automated. For instance, space-based observations and many ground-based
observing networks are highly automated and are not expected to be impacted by
the effects of the pandemic. Currently, there are 30 meteorological and 200
research satellites, continuously providing observations, and in most developed
countries, surface-based weather observations are nearly fully automated.
However, the WMO
article explains that some parts of the global observing system have already
been severely affected. The most significant reduction in weather measurements
corresponds to in-flight measurements of temperature, wind speed and wind
direction, and in some cases, humidity and turbulence – all important variables
for both weather prediction and climate monitoring. Commercial airlines are
part of the WMO Aircraft Meteorological Data Relay programme (AMDAR) gathering
over 800,000 observations per day. Due to the flight restrictions set by
countries on commercial flights, many parts of the world have seen a decrease
in measurements between 50% and 80% over the past two weeks.
immediate decrease of in-flight observations caused by the pandemic, there are
also concerns that if the pandemic persists for several weeks, maintenance and
supply work, as well as scheduled redeployments will be affected.
In many developing
countries, ground-based observations have been affected by the pandemic due to
their reliance on manual reporting by weather observers. The WMO article points
out that the WMO’s global observation system has seen a
significant decrease in the availability of this type of manual observations
over the last two weeks. Some of this may be attributable to the current
coronavirus situation, but it is not yet clear whether other factors may play a
role as well. WMO is currently investigating this. Lars Peter Riishojgaard,
Director, Earth System Branch in WMO’s Infrastructure Department said: “At the
present time, the adverse impact of the loss of observations on the quality of
weather forecast products is still expected to be relatively modest. However,
as the decrease in availability of aircraft weather observations continues and
expands, we may expect a gradual decrease in reliability of the forecasts”.
“The same is true if the
decrease in surface-based weather observations continues, in particular if the
COVID-19 outbreak starts to more widely impact the ability of observers to do
their job in large parts of the developing world. WMO will continue to monitor
the situation, and the organization is working with its Members to mitigate the
impact as much as possible,” he said.
mitigate the impact of the sudden decrease in observations, some WMO members ,such
as Europe, have increased the launches of radiosondes. These radiosondes are
attached to weather balloons, which can fly from the surface up to 20 to 30 km
into the atmosphere, transmitting measurements of some critical meteorological
These additional WMO efforts are critical for monitoring climate change. COVID-19 has caused positive short-term environmental impacts such as a significant reduction of greenhouse gas emissions and a worldwide increase in air quality. Capturing these impacts with high-quality observations, thanks to the mitigation efforts of the WMO, can help shed light on the advantages that a systemic shift to a more sustainable economy can have on climate change and the planet.
In 2018, the Asian Development Bank (ADB) and the Urban Climate Change Resilience Trust Fund (UCCRTF) launched the Spatial Data Analysis Explorer (SPADE), an interactive cloud-based platform that can host geospatial information.
A collaboration with the Sustainable Development and Climate Change Department and operations departments, SPADE could be an essential tool for ADB staff and consultants for project identification and preparation, due diligence, engineering design, and project monitoring.
The platform uses open-source technology, so the information is easily accessible to registered users and can also accept new or updated data. Currently, SPADE has spatial information for 21 project cities.
UCCRTF, who manages the platform, has been stepping up efforts to promote the use of SPADE and increase its content. In December 2019, they hosted a training workshop for ADB staff to provide an overview of geographic information systems (GIS), available tools and platforms, and its application for various stages in the ADB project cycle. The training highlighted the need for stronger user uptake and skill transfer of these spatial tools within ADB.
SPADE offers several advantages for project officers and those working at the city level. First, it can be used as a tool to inform strategic decisions on project design and investment prioritization. For example, SPADE has a mobile app version and this was used to collect data on rain- and flood-induced landslide hazards for a community-led project in La Trinidad, Philippines. Hazard maps were then produced from these data to improve the design of the project.
Second, SPADE can be used to conduct due diligence, project implementation, and monitoring. Consultants, for instance, can take photos and notes of the construction site during a field visit and upload these to SPADE using their mobile phone. Photos are geotagged to show the precise locations on the platform’s map. This allows project officers to view the progress on site from their desks at the resident mission or in ADB headquarters.
For more on the other benefits of SPADE, view the infographic below or download it here.
The science is far from settled. The jet stream can vary wildly from week to week, or from year to year, and questions remain over whether any signal from the Arctic can yet be seen over the background “noise” of natural variability. (The latest study on the topic, for example, suggests the link is “insignificant”.)
The current winter provides an interesting, if trivial, example. In the Arctic, the steady decline of sea ice continues, with the January 2020 average extent among the lowest 10 years in the satellite record. According to some of the most widely reported theories, we might expect the jet to have been weaker and more “wavy” this winter as a result. But the reality is quite the opposite. So far this season, the jet has mostly been strong and straight, bringing mild and stormy weather to much of northern Europe.
Of course, lots of this is just ‘weather’ – we expect a certain randomness in the jet stream – and this is a key reason why influences, such as Arctic warming, are so hard to pin down. But, intriguingly, the jet this winter seems to have been highly predictable, with early warnings of such a pattern first being made in the autumn.
We cannot say for certain what has caused this yet, but most meteorological eyes are directed away from the Arctic, towards the south. And, in fact, there is possibly an even more important influence on our weather under a changing climate: the tropics.
Ultimately, the jet stream derives its energy from the contrast in temperatures between the warm air over the equator and the cold conditions of the Arctic. And is it intimately tied to conditions in the tropics.
Blessed with a surplus of energy pouring in from the sun, the tropics are in many ways the powerhouse of the Earth’s climate. Somewhere near the equator, depending on season, the surface will face directly towards the sun and so the air here will be heated more than anywhere else, becoming lighter and rising upwards as a result. This forms a giant convection cell in the atmosphere, known as the Hadley cell, with air rising above the equator before moving away, to both the north and south, and then sinking again.
George Hadley was a London lawyer, pondering science questions in his spare time, when he hit upon the basic mechanism explaining the “trade winds”. These are the year-round east-to-west winds that blow across the tropics, on which traders sailing across the Atlantic relied for a swift passage to the Americas. Hadley described the theory in his seminal paper, published by the Royal Society in 1735.
Hadley first theorised the existence of the cell which now bears his name and also that the near-surface air moving towards the equator would be turned by the rotation of the Earth, forming the trade winds. He also predicted that, on the flip side of his cell, there should be strong winds blowing from west to east far above the surface, which he named the “anti-trades”. Today, of course, we call this the jet stream.
(Cartoons of the atmosphere typically feature two jets, one linked to the Hadley cell and one further north linked to a much weaker feature called the polar cell. Although this picture is useful, the two jets are, in reality, often merged into one dominant structure in the mid-latitudes, simply referred to as the jet stream.)
While scientists are still pondering how variations in the Arctic may affect the jet, the influence of the tropics is abundantly clear.
We need look no further than the dramatic weather disruption caused by El Niño events in the Pacific Ocean, when the balance between the tropical trade winds and the warm equatorial ocean currents is upset. By shifting the locations of the powerful convection driving the Hadley cell, these events send “waves” along the jet stream that can temporarily alter weather patterns around much of the world.
El Niño is the poster-child of climate variability, responsible for much of the skill in our long-range “seasonal” forecasts, which aim to predict average conditions for the season ahead. But there is more to the tropics than just El Niño. The tropical atmosphere is much less stable than that over the Arctic, enabling powerful storm systems to reach up and shunt around air masses up at the heights where the jet is strongest.
For example, it seems likely that weather patterns in the tropics have helped to nudge the jet into its strong and straight configuration this winter, and it is this signal which enabled early warnings for Europe in the autumn of 2019. Specifically, this year’s events are quite consistent with some previousstudies of the influence of Indian Ocean weather patterns on the jet stream.
And what about climate change? Might we be seeing changes in the jet stream already because of how the tropics are responding to warming?
The tropics are indeed changing, although there is more uncertainty over how exactly than there is in the Arctic. For example, George Hadley’s great circulation cell has been expanding over recent decades, its boundaries inching slightly, but detectably, polewards.
While this is exactly the signal we expect to arise from climate change, our best assessment is currently that much of the recent changes reflect natural variations, at least in the northern hemisphere. (In the southern hemisphere, the climate change signal is clearer, especially as it is boosted by the effects of stratospheric ozone depletion.)
Climate models generally predict the tropical Pacific will warm most strongly in the east, close to South America, while the observed trends show strongest warming instead in the west. Given the sensitivity to these regions evidenced by El Niño, this discrepancy has serious implications for our ability to predict the details of changing weather patterns.
Some new evidence suggests that the observed pattern of stronger western warming might be a signature of climate change, regardless of what the models say. Given the extent to which the details really matter in the tropical Pacific, however, uncertainty is likely to remain here for some time.
Keeping this uncertainty in mind, though, has the warming of the tropical oceans had any effect on the jet stream yet?
Some of our recent work suggests, potentially, yes. El Niño peaks in the northern hemisphere winter – it was originally named after the infant Jesus by Peruvian fishermen – but it also has important impacts in summer by sending giant, continent-sized waves along the jet stream.
For example, a series of extreme weather events rocked Eurasia in 2010, from the searing Russian heatwave to the torrential Pakistan floods, and it seems the climate dice were loaded for these events by La Niña, the so-called “little sister” to El Niño.
Crucially, the pathway for these influences seems to have shifted and strengthened in recent decades, due to a subtle shift of the jet, so that El Niño and La Niña now affect parts of Eurasia in summer that they did not reach before. This is associated with a subtle southward shift of the jet over southeast Asia, which makes it more sensitive to weather disturbances from over the Pacific.
We have been able to reproduce this change in climate model experiments but – importantly – this occurs only when the observed warming of the tropical oceans and the subsequent influence on the jet is included.
It is early days for this type of research, and many uncertainties remain, but we might just be starting to see an example of how the tropics will affect jet stream variability under climate change.
In any case, both Hadley’s circulation cell and El Niño’s shockwaves demonstrate the power of the tropics over the jet stream. As weather patterns alter in our warming world, those of us in the northern mid-latitudes should be looking nervously to the south at least as much as to the north.
A new discussion paper prepared by AidData and the Group on Earth Observations explores the role of open Earth observations for sustainable urban development.
Prepared for UN-Habitat’s World Urban Forum in United Arab Emirates, this paper concentrates on examples where Earth observation (EO) data can complement or enhance traditional data sources for cities and urban areas.
According to the United Nations, nearly 70% of the world’s population will live in cities by 2050. Ensuring sustainable urban development will be key for urban planning, land management and the timely achievement of the SDGs and the New Urban Agenda.
The EO4SD Climate Resilience (CR) Cluster has embarked upon phase two of their mission to help countries around the world increase their climate resilience by using EO data. In collaboration with several International Financial Institutions (IFIs), the cluster has developed EO-based integrated climate screening and risk management products and services to help manage climate-related risks and capitalise on the opportunities that climate resilience can create. The cluster is also working to build the capacity of IFI staff and IFI client states, allowing stakeholders to autonomously use EO-based information for climate resilience decision making.
Part one’s scoping phase, identified the potential areas for EO data to increase climate resilience and set about designing systems that would enable this to inform decision making. Phase two will see further refinement of the tools and training and capacity building for staff in using the information generated from the tools. For example, in the Philippines, the pilot project used satellite-based, highly automated, open water surface inundation tools to detect both seasonal fluctuation of water bodies and long-term changes. This Inundation Monitoring Service (IMS) maps the extent of flooded areas over time, which can help build a picture of the flood response of an area. As the pilot has worked so well, the EO4SD CR cluster will work with the ADB over the next 12 months to identify more sites where the IMS can be implemented.
The Cluster has also worked with the World Bank in a pilot phase to seamlessly integrate high-resolution, global observed datasets for three climate-related variables into the World Bank’s Climate Change Knowledge Portal (CCKP), which is one of the most high-profile, publicly accessible, climate data platforms in the world. Data was chosen specifically to add depth to the portal’s observational data offer, enhancing the accessibility of reliable data whilst making sure to cater for different user skill levels. Phase two will develop new visualisations of the EO data accessible via the CCKP, and develop country-specific EO-based and climate projection data to inform sectoral risk assessment on the CCKP (including energy, water, agricultural, and health).
Data was also successfully integrated into the pre-existing platforms with International Finance Corporation (IFC) and the Multilateral Investment Guarantee Agency (MIGA), as well as Africa RiskView (ARV) in conjunction with African Risk Capacity (ARC). For ARV, the Cluster combined Earth Observation (EO) data with population vulnerability data to provide an early-warning model that measures food insecurity and estimates response costs, enabling decision-makers to plan and respond quickly and efficiently to drought stresses. In addition, access has been given to products available through the EO4SD Cluster’s own platform that can deliver precipitation, soil moisture, and sea surface temperature data which is being used to test the possibilities for integrating other products into the ARV. Based on this initial engagement and testing, the next steps are to further integrate EO data into the ARV tool, and refine the types of information it is able to provide. Similarly, the Cluster worked with International Finance Corporation (IFC) and the Multilateral Investment Guarantee Agency (MIGA) to integrate EO data into its risk screening tool, upgrading their ability to assess the materiality of climate impacts, past and future. Phase two work includes integrating more EO data into their screening tool, with the timeline and resolution of data enabling a more detailed analysis.
The Cluster has also helped AGRHYMET’s ability to have a comprehensive view of climate risk as a function of hazard, exposure and vulnerability by identifying several products and services that can be provided in support of its work. Combining EO data, climate projection derived information and socioeconomic data, AGRHMET can improve its understanding of factors affecting Sahelian food security, desertification control, and water control and management. As a result, the wetlands monitoring service was chosen as a pilot and has been implemented in a region in Mali with a temporal range of 2017 to 2018. This pilot successfully demonstrated that the product could be applied in practice and usefully deliver relevant information. Over the course of the next 12 months the Cluster will further refine the prototype products and identify other projects for which they might be usefully applied. The Cluster will work with AGRHYMET to implement a service that provides full coverage of a pilot area, covering some 3,800 km2 of the Inner Niger Delta wetlands at a resolution of 20 km2. This service will enable monthly monitoring of surface wetness and water bodies integrating observed and projected rainfall data as well as a Water and Wetness Probability Index (WWPI), which will further enable comparing monthly means with observed measurements.
In Greater Monrovia, EO data will be used to analyse the exposure of critical infrastructure to coastal hazards. This includes generating analysis and projections of coastal shoreline change, rates of coastal erosion, and land subsidence. By combining this analysis with other EO data (for example, Modified Normalized Difference Water Index, Digital Terrain Models, and bathymetry data), climate projections, and socio-economic data, the cluster will also develop analysis on the population exposure to coastal flooding. The World Bank are also working with the Cluster in supporting the Monrovia Integrated Development Project (MIDP) by understanding the region’s urban growth, and how, in conjunction with the shoreline analysis, other socioeconomic factors might contribute to climate vulnerability. The next phase is to integrate more EO data to better identify risks and estimate projected coastal erosion, vital for informing resilient interventions by stakeholders.
A vital part of phase two is to provide capacity building activities in order to increase the effectiveness of climate and disaster risk management. In order to do this, the Cluster will be helping partners by increasing the capacity of their staff to be able to provide better services and tools to local stakeholders (such as governmental bodies and other organisations with overlapping objectives). Capacity building activities will initially focus on the EO4SD CR platform, providing to staff training on how to access and test EO derived data. By showcasing examples of how EO derived information relates to daily operations, staff will understand how EO data can be used for assessment and awareness activities. These will be delivered via a series of introductory webinars and regional events, before curating dedicated webinars and ‘on demand’ webinars, acting as a helpdesk to the various stakeholders. For example, in the Philippines, specific capacity building options may include how EO services can feed into nature-based flood protection solutions by identifying suitable locations, and using real-time EO data to monitor rivers to strengthen early flood warning systems.
Our third article of top picks from our 2019 article
archive, features six articles related to climate data and analytics. As poor
populations living in developing countries face frequent extreme weather
events, such as droughts and floods, they are becoming increasingly vulnerable
to the threat of global climate change. Emerging climate data and analytics
services help in exposing these climate risks and vulnerabilities before
disaster strikes, whilst providing methods of applying these data to real-world
While demand for climate projections are growing,
alternative methods of contributing to our understanding of how to build
resilience to climate impacts are presenting themselves. Citizen science has emerged as a useful tool
for raising awareness, bridging data and capacity gaps and influencing
governments through actively engaging civil society in research and monitoring.
Acclimatise remains at the forefront of providing effective
climate analytics services. In fact, our analytics software division is
creating some of the first user-centric climate change risk assessment
applications, running on some of the world’s most sophisticated datasets. For
example, platforms such as our Aware platform is being used by Multilateral
Development Banks include the Asian Development Bank and the European
Investment Bank to screen their project and investments for climate risks.
Beyond climate models: Climate adaptation in the face of
By Erin Owain and Richard Bater
In recent years, demand has been placed on climate science
by policy makers to produce increasingly high-resolution climate projections to
inform shorter-term, local decisions. The authors of a recently published paper
argue that this is partly attributable to an over-estimation, on the part of
decision makers, of the level precision with which the current set of models
are able to project future change.
People Power: How citizen science is building climate
resilience in South Asia
By Uma Pal
While diverse and extensive ecosystems, climates and
socio-economic features in South Asia make it a challenge to collect adequate
data and conduct research on the impacts of climate change, citizen science can
be a useful tool for enabling more comprehensive research and resilience
building initiatives both at the individual level and at scale.
Using earth observation data in climate risk assessment
for financial institutions
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.
Resilience planning can uncover investment opportunities
at the city level
By Will Bugler
Countries in Asia are faced with a huge infrastructure
investment gap, primarily resulting from a lack of identifiable, bankable
projects at the city level. To address this, cities are in need of support to
develop robust, integrated, and climate-responsive infrastructure plans.
Investing in a resilience approach to urban planning can support municipal
governments to develop such plans and unlock a multitrillion-dollar investment
Earth Observation data: the new frontier in climate
By Acclimatise News
Earth observation is the gathering of information about the
Earth’s physical, chemical and biological systems and has the capability to do
so across remote and inaccessible terrain. Providing large quantities of timely
and accurate environmental information, EO data can help governments around the
world prepare for climate change impacts and inform sustainable and climate
resilient development planning to account for future climate risks.
This New Climate – Episode 3: OASIS & the
democratisation of climate data
By Acclimatise News
In the third episode of This New Climate, host Will Bugler
explores how the OASIS group of companies are seeking to transform our ability
to understand climate risk through a commitment to open source data.
A new framework for classifying and understanding types of current and potential climate data and information has been presented in a peer-reviewed journal article due to be published shortly (in press as of 8 January 2020). The framework put forth in the article can help professionals in the financial services, urban planning, and tourism sectors articulate their climate service preferences. It can also help identify challenges and opportunities for other climate service users and service providers. Due to be published in the journal Climate Services, the open-access article is titled ‘Matching supply and demand: A typology of climate services’. It is the result of research carried out in the EU’s Horizon 2020 EU-MACS project, where Acclimatise led the engagement with the financial services sector.
The European Roadmap for Climate Services defines ‘climate service’ as “…the transformation of climate-related data — together with other relevant information — into customised products such as projections, forecasts, information, trends, economic analysis, assessments (including technology assessment), counselling on best practices, development and evaluation of solutions and any other service in relation to climate that may be of use for the society at large. As such, these services include data, information and knowledge that support adaptation, mitigation and disaster risk management (DRM)”. The European MArket for Climate Services (EU-MACS) project sought to understand and develop the climate services market in Europe and beyond. The climate service market is currently undergoing rapid expansion and has the potential to be a rewarding space for both users and providers.
The article, led by researchers from
the University of Twente in the Netherlands, (Visscher and Stegmaier) indicates
that although the climate services market is growing and consolidating, there
has not yet been ‘extensive reflection on the kinds of services such a new
market could encompass, and on the ways in which formats can be created that
match supply and demand’ (pg. 1). Using a research approach based on Constructive
Technology Assessment (CTA), the article provides this by elaborating and illustrating
a typology of the current variety of climate services seen. Specifically, the
article presents a typology of climate services, including: ‘Maps & Apps’,
‘Expert Analysis’, ‘Climate-inclusive Consulting’, and ‘Sharing Practices’
types (see figure 1).
The typology provides a framework for the further development of climate services as it can be used by actual and potential providers of climate services to reflect upon the general outline of their services. In particular, the article goes some way to capture examples of climate service use cases and demand in the financial services, urban planning, and tourism sectors. These are also elaborated in more detail in the EU-MACS outputs. Additionally, policymakers can use the article to reflect upon the kind of services they want to stimulate through funding, procurement, or other measures. Supporting these services helps to professionalise climate services and to stimulate their uptake in complex and institutionalised settings (Visscher et al., inpress 2020).
Acclimatise’s Robin Hamaker-Taylor, a co-author of the article stated: ‘This research is an important and innovative effort to outline the contours of the climate services market. As the climate impacts are increasingly felt, climate data is proving increasingly useful, especially by those in the financial services sector. Apart from providers and policymakers, the framework we set out and illustrate in this article can be a useful starting point for users such as financial services firms who would like to begin their climate data journey and peer into the wide world of climate services.’
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.
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
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
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 Clusterprovides
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
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.
The GEO is an intergovernmental partnership that improves
the availability, access and use of Earth observations for a sustainable
planet. Promoting open, coordinated and sustained data sharing and
infrastructure for better research, the GEO offers all countries the
opportunity to benefit from collective knowledge, expertise and skills to
develop national Earth observations programmes.
“With the in-depth understanding of its wide-ranging clients’ analytics needs and long-standing industry experience, Acclimatise is uniquely positioned to take full advantage of the opportunities that the Associate Membership of the GEO would present,” said Head of Analytics Dr Xianfu Lu. “In particular, through leveraging the wealth of data, information and knowledge and the partnerships made possible by the GEO, Acclimatise aims to develop cutting-edging analytics tools that enable climate resilience solutions and investment opportunities.”
is unique in the Earth Observation community drawing on its fifteen years’
of experience advising corporates, financial institutions and governments to
develop climate resilience solutions based on EO-data. In doing so,
Acclimatise is able to provide significant added value through its unique focus
on cloud-based software to deploy EO-based data in combination with climate
projections and other socio-economic data sets. Such solutions will support the
efforts of governments, corporates and the financial services sectors in
delivering climate- and disaster-resilient development.
For more information, view the full list of GEO Associates here.