How can data inform your climate change adaptation decisions?
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Climate change is a complex and urgent challenge that requires effective and adaptive responses from various sectors and stakeholders. As an environmental designer, you need to consider how your projects can contribute to reducing greenhouse gas emissions and enhancing resilience to climate impacts. Data can be a powerful tool to inform your climate change adaptation decisions, but how can you use it effectively? In this article, we will explore some of the benefits and challenges of using data for climate adaptation, and provide some tips and examples of how to apply data-driven approaches in your environmental design practice.
Data can help you understand the current and future risks and opportunities related to climate change in your project area. By using data from different sources, such as climate models, historical records, remote sensing, surveys, and stakeholder feedback, you can gain insights into the trends, patterns, and uncertainties of climate variables and their impacts on natural and human systems. Data can also help you evaluate the effectiveness and feasibility of different adaptation options, by comparing their costs, benefits, trade-offs, and co-benefits. Data can support your decision-making process by providing evidence, transparency, and accountability for your adaptation actions.
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Batu Varlik
Consultant for Technological Finance and Business Development
Using data and data science would help where the current change in global life conditions have been directed. However, since the climate change will make many unexpected and unseen changes in our planet it also needs very experienced human intuition. So, basically we should not trust only data.
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Ashley Gamarra
ABM Specialist @ SustainaBase | Sustainability and ESG Reporting
Our clients continually inspire us by harnessing environmental data to drive transformative change within their organizations and industries. One long-standing partner exemplifies this by leveraging our insights to make informed choices on new sustainability practices. Their achievements are substantial: recycling over 8 million pounds of waste, rerouting 30 million pounds of products to donation centers instead of landfills, transitioning their truck fleet to compressed natural gas, transforming nearly a million pounds of plastic into reusable materials, and slashing carbon emissions by 20% on their journey to net-zero. Such impactful decisions, once merely aspirational, are now grounded in reality, guided by the vital data we provide.
Data is not a one-stop solution for all climate adaptation problems. It comes with some challenges and limitations, such as data quality, availability, and complexity. Data can be incomplete, inaccurate, outdated, inconsistent, or biased, which can affect your analysis and interpretation. It can also be scarce, inaccessible, or incompatible. Additionally, data can be overwhelming, confusing, or ambiguous. To address these issues, you need to check the sources and methods behind the data you use and assess their reliability and validity. You also need to identify the data gaps and needs for your project and explore ways to obtain, share, or integrate data from different sources and formats. Lastly, you must simplify, visualize, and contextualize the data you use to explain the key messages and implications clearly and convincingly.
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Gerhard Mulder
CEO & Co-founder at Climate Risk Services | we're hiring
Yes, data is a challenge but we can't wait for perfect data to start the process. The biggest data challenge in our experience is that banks do not know where the assets of their clients are located. But there is a lot of publicly available data out there. But it sometimes requires specialised skills to make sense out of it and turn it into decision useful information.
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Hayri T.
Credit Risk Governance Professional | Expert in Climate Risk and ESG | Leading Green Asset Ratio Development
Data helps our decision process but we are not sure about how to use climate data outputs with limited understanding of nature. The biggest problem is how we will classify materiality. (GreenhouseGases , emissions already formulated by scientists, no more clues)
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In order to make the most of data for climate adaptation, there are some tips to follow in environmental design practices. It is important to define objectives and questions before collecting or analyzing data so that only the most relevant and useful data is used. Additionally, multiple and diverse data should be used to capture the complexity and uncertainty of climate change. This includes data from different sources, scales, and perspectives, as well as combining quantitative and qualitative data. Finally, it is important to adapt and update data regularly in order to keep up with the changing and dynamic nature of climate change. This will allow for monitoring and evaluating adaptation progress, as well as adjusting actions and plans accordingly.
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Ashley Gamarra
ABM Specialist @ SustainaBase | Sustainability and ESG Reporting
Beginning with the concept that "sustainability" is synonymous with "waste reduction" can pivot a company's perspective toward cost-saving strategies. Enhancing sustainability metrics invariably leads to diminished waste, which translates into significant financial gains. This approach not only appeals to the environmentally conscious but also presents a compelling case for fiscal efficiency that resonates with executives and board members. It's a universal win-win, aligning ecological responsibility with economic benefits—motivating stakeholders across the spectrum by showcasing the tangible rewards of sustainability.
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Gerhard Mulder
CEO & Co-founder at Climate Risk Services | we're hiring
They key thing is that you need data on hazards (what is the probability and severity of a certain hazard happening somewhere - say, a flood or hurricane). But then you also need a sensitivity score. Different asset types and economic activities have different sensitivities to different hazards. Agriculture is sensitive to droughts, but manufacturing less so. If you are a bank, to get around the data challenge of asset locactions, you can also use provinces, regions, or even countries, to calculate the hazards.
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To illustrate how data can inform climate change adaptation decisions, here are three examples of data-driven climate adaptation projects in environmental design. The Climate Ready Boston initiative uses data from climate projections, vulnerability assessments, and community engagement to identify and prioritize the most exposed and sensitive areas and populations in Boston and develop strategies to enhance the city's resilience and livability. The Resilient by Design Bay Area Challenge uses data from sea level rise scenarios, flood maps, ecological assessments, and stakeholder input to generate design solutions that address the current and future challenges of sea level rise and flooding in the San Francisco Bay Area. Additionally, the Adaptation Atlas tool employs spatial analysis, landscape typologies, and adaptation measures to provide a framework for planners and designers to explore and select suitable adaptation strategies for different coastal contexts in California.
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Maha Qasim
Founder & CEO
The Glacial Lake Outburst Floods (GLOF) risk reduction projects in Northern Pakistan is an example of a data-driven climate adaptation project. Due to rising temperatures, glaciers in Pakistan’s Hindu Kush, Himalayas and Karakorum mountain ranges are melting rapidly. Around 3,044 glacial lakes have developed of which, 33 are prone to hazardous glacial lake outburst flooding (GLOF). These sudden events can release millions of cubic metres of water and debris, leading to the loss of lives, property and livelihoods amongst remote and impoverished mountain communities. Weather-monitoring stations are used to collect meteorological data in catchment areas. This data informs hydrological modelling and helps develop village hazard watch groups.
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Gerhard Mulder
CEO & Co-founder at Climate Risk Services | we're hiring
One great tool that have been developed in the Netherlands is the Climate Impact Atlas: www.klimaateffectatlas.nl. It is a public service and everyone can download the data. The data is now used by banks to determine, for example, the risk of soil subsidence and how this may impact the housing stock. About 1 million houses are at risk from destabilizing as a result of soil subsidence.
We hope this article has provided some insight and guidance on how to use data to inform climate change adaptation decisions. Data can be a beneficial asset for your environmental design practice, but it must be used carefully and critically. To improve your data skills and knowledge, you can learn from the best practices of other data-driven climate adaptation projects and practitioners. Additionally, seek out and collaborate with data experts and partners who can support and advise you on data collection, analysis, and communication. Moreover, ensure that stakeholders and beneficiaries are engaged in the data process, so that their feedback and input can be taken into consideration for the data you use and produce.
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Gerhard Mulder
CEO & Co-founder at Climate Risk Services | we're hiring
Companies should start with collecting asset location data, and then determine how sensitive each asset is to various climate hazards. Then organize workshops and similate a mock climate disaster. What is the impact? Will your tailing dams hold if you are a mining company? How do you manage the impact of a hurricane? Climate risk should be integrated into risk management, both at banks and non-financial companies.