A temperature binning approach for multi-sector climate impact analysis

Abstract

Characterizing the future risks of climate change is a key goal of climate impacts analysis. Temperature binning provides a framework for analyzing sector-specific impacts by degree of warming as an alternative or complement to traditional scenario-based approaches in order to improve communication of results, comparability between studies, and flexibility to facilitate scenario analysis. In this study, we estimate damages for nine climate impact sectors within the contiguous United States (US) using downscaled climate projections from six global climate models, at integer degrees of US national warming. Each sector is analyzed based on socioeconomic conditions for both the beginning and the end of the century. The potential for adaptive measures to decrease damages is also demonstrated for select sectors; differences in damages across adaptation response scenarios within some sectors can be as much as an order of magnitude. Estimated national damages from these sectors based on a reactive adaptation assumption and 2010 socioeconomic conditions range from $600 million annually per degree of national warming for winter recreation to $8 billion annually per degree of national warming for labor impacts. Results are also estimated per degree of global temperature change and for 2090 socioeconomic conditions.

Projecting the Suicide Burden of Climate Change in the United States

“…This study builds on climate and suicide‐focused mental health research to quantify and monetize changes in annual suicide incidence across the U.S. in response to global warming between 1 and 6°C. We present estimates by the degree of warming to decouple the impacts of changing climate from the impacts of timing, scenario, or climate model used to develop the estimate (Sarofim et al., 2021 ). Averaging over 24 projections (based on six global climate models and four health impact functions) and assuming the 2015 population size, 1–6°C of warming could result in an annual increase of 283 (CI 90%: 249–314)–1,660 (CI 90%: 1,430–1,850) additional suicide cases.…”

Advancing the estimation of future climate impacts within the United States

“…Second, we consider how the sensitivity to socioeconomic drivers continues beyond 2090 through 2300 on a sector-specific basis (the supplement provides a full tabular summary of socioeconomic extensions for all FrEDI sectors). In general, health-based sectors (e.g., extreme temperature mortality) are driven by population which enters linearly; infrastructure sectors (e.g., rail) are driven by population for passenger use and GDP for freight use; and coastal infrastructure is adjusted by expected real property price appreciation, using GDP per capita and 410 income elasticity of 0.45, consistent with the underlying Neumann et al, (2021). For many sectors, economic valuation is a separable process from the overall damage calculation in FrEDI -for example willingness to pay to reduce fatality risk (referred to as the value of statistical life or VSL) is adjusted based on the projection of GDP per capita and a default income elasticity of 1.0.…”

“…Since this work incorporates multiple disciplines, emission projections, climate modeling, impact modeling, and economic communities, it has the potential to be a useful tool in bridging the research gap between 385 these communities and helping to address some of the omitted climate change risks currently within this field (Rising et al, 2022). FrEDI was calibrated to estimate impacts for detailed 21 st century scenarios and trajectories, as described in Sarofim et al (2021). Extending the FrEDI approach to 2300 requires two adjustments to adapt the sensitivity of the model to climate drivers and to socioeconomic conditions beyond the 21 st century.…”

“…The Framework for Evaluating Damages and Impacts (FrEDI) is a reduced complexity model that assesses and quantifies future impacts to the U.S. from a changing climate. As described in detail in the Technical Documentation (EPA, 2021b), FrEDI uses a temperature binning approach and data from previously published 125 climate impact studies (Sarofim et al, 2021) to develop relationships between climate-driven changes in CONUS temperature or global mean sea level rise and the resulting physical and economic damages across 20 sectors (Table A1) in seven U.S. regions. FrEDI also provides insight into differences in impacts under various adaptation scenarios and contains a module that can be used to quantify impacts to socially vulnerable populations.…”

“…Temperature binning provides an alternative framework for analysing sector-specific impacts by degree of warming, which complements traditional scenariobased approaches. This framing can improve communication of results, comparability between models and studies, and flexibility for new scenario analysis (Sarofim et al, 2021). The recently developed Framework for 60…”