A new framework for assessing climate change data helps real estate investors measure risks, including extreme weather events and the costs of transitioning to a low-carbon economy.
Real estate owners face pressing risks from climate change in the form of physical risks from the effects of climate change, as well as risks associated with the transition to a low-carbon economy.
Rising greenhouse-gas emissions (GHG) have lifted average global temperatures, melting glaciers, raising sea levels and shifting patterns of atmospheric currents. Meanwhile, worldwide economic losses from weather disasters rose to $258 billion in 2020, which was 29% higher than the 21st Century average.1 All of this has accentuated the physical risks that real estate investors face. In addition, with respect to transition risks, as new policies to reduce GHG emissions come into effect, investors will need to manage capital expenditures to prioritize energy efficiency and reduce buildings’ emissions to comply with new regulations. Designing effective climate adaptation and mitigation strategies are therefore integral to the success of real estate investing.
Amid growing urgency to incorporate climate-related risks into real estate due diligence and asset management, a number of data providers and analytical tools have emerged. However, navigating the complexity and distinctions among these solutions presents a new challenge for investors. A new report, jointly issued by the Morgan Stanley Institute for Sustainable Investing and Morgan Stanley Investment Management’s Global Real Assets Team, seeks to address this problem by providing real estate investors with a framework for assessing climate risk solutions.
Based on a comparison of several climate risk models for a sample real estate portfolio, Morgan Stanley observed four key findings:
- Low correlation between providers: Because data providers highlight different physical climate risks and use different estimates of weather model projections, there is low correlation between overall measures of climate impact. While there was greater alignment between providers for certain high-risk areas, stark differences emerged for geographically diversified portfolios. Careful analysis is required to establish a comprehensive view of climate risks to a real estate portfolio.
- Not all models include transition risk: Due to the complexities of anticipating future policy responses to climate change, not all solutions account for climate transition risk. However, real estate investors should carefully consider transition risks, such as the potential adoption of carbon pricing, in their projections of future building energy costs and capital expenditures needed to decarbonize buildings over time.
- Climate resiliency measures may not be incorporated: Specific asset- and community-level measures to mitigate climate risk, such as the use of floodgates or fire-resistant landscaping, are not incorporated by default into most climate provider assessments. As a result, estimated climate vulnerabilities may be overstated.
- Indirect risk goes largely ignored: In many cases, data providers only capture the potential direct impact of climate change on properties and not the indirect effects related to supply-chain disruptions or on surrounding communities.
Given these challenges, we recommend that real estate investors consider the following five takeaways when evaluating and selecting climate risk data providers:
- Use both catastrophe and climate risk models. Climate risk models can be classified in two broad categories: catastrophe models and climate change models. Catastrophe models—used widely in the insurance industry—emphasize current risk exposure, based on historical and statistical analyses. Newer and evolving climate models, however, seek to predict future risk exposure based on modeled weather patterns. Combining the use of both models may strengthen risk management.
- Clarify your investment time horizon. Climate models often consider different forward-looking scenarios for GHG emissions and corresponding reference years (e.g., 2020, 2030, 2050 or 2100). For certain real estate investors, a longer-term time horizon may be prudent. Investors should note that model accuracy decreases as time horizon increases.
- Identify which hazards matter most. Data providers consider different types of climate hazards in their models. For example, investors with significant exposure to coastal properties may want to better understand the risk of hurricanes and rising sea levels, whereas those with properties farther inland might be more interested in understanding heatwaves and extreme cold. Additionally, it is important to consider the effects that hazards may have on each other (e.g. heatwaves contributing to an increased likelihood of wildfires).
- Recognize that hazards are defined differently. Taking heat stress as an example, some data providers may report on the anticipated maximum increase in annual temperature, while others may report on the number of days per year that an asset would be exposed to extreme heat events. Investors should be prepared to interpret results accordingly, and choose providers based on which metrics are most relevant to their portfolios.
- Don’t forget about transition risks. Physical climate risks, such as natural disasters, have long concerned real estate investors, but as the global economy seeks to decarbonize, low-carbon policies and emissions targets can also impact net operating income and exit values of real estate investments.
Climate models are an increasingly powerful and available tool to help real estate investors manage risk. By understanding the range of solutions and carefully choosing the right combination of providers, real estate investors can holistically understand their portfolios’ exposure to rising physical and transition climate risks.