Heat Risk
High-level Summary: Compound Heat Risk
This section presents the compounded risk categorization (0-4) of temperature-based heat + population or temperature and humidity-based heat + population, enabling users to understand where and when risks may occur. Compound risk presentation can be investigated spatially via the map (depicting the maximum heat risk categorization across the year). Investigations in the specific seasonality of risk based on monthly categorizations is shown via the circle graph. Notice how seasonality of highest heat risks may expand later in the century, particularly for higher emission pathways. Individual elements contributing to the compound risk (i.e., heat conditions and population) are presented separately in the following sections.
Section I: Extreme Heat Conditions
Capturing ‘heat risk’ in a comprehensive way requires looking across a range of temperature and humidity related conditions that may occur over a 24-hour period, a season, or year. We present multi-threshold metrics for day-time maximum temperatures, nighttime minimum temperatures, and a combined heat index (a measure of air temperature and humidity) as a baseline to evaluate changing and intensifying heat risk conditions for an area. Key is to understand where extreme heat conditions are more likely to occur, and when in the seasonal cycle as well as over time higher heat conditions are to be expected.
The top row presents the mean number of days for each of the heat thresholds, the bottom row condenses the different threshold information into systematic categories (0-4).
Section II: Population and Poverty Dynamics
This section explores the socio-economic backdrop against which one needs to later assess heat risks. Presented are: population (density: persons/ km2 and counts) and poverty classifications. Understanding where populations are located, and what their relative level of poverty is (using percentage of population below poverty classifications at thresholds: $1.90, $3.20, $5.50 of income per day), can aid decision-makers in identifying key areas of need.
Past to present population and poverty data largely reflect census and survey-based outcomes (roughly up to 2010 in the presentations here). Future projections were crafted in association with the formulation of societal development narratives under the Shared Socioeconomic Pathways (SSPs). The goal of the SSPs is to depict a range of plausible societal futures where different technological, political and environmental trajectories are described. Within each of these storylines, a trajectory of demographic changes is generated, which then, based on an assumption of technologies, lead to likely emissions patterns to reflect that pathway. From these emission lines, a suite of most representative likely radiative forcing levels at the end of the 21st century are then selected to provide the input to climate models. The SSPs reflect the most advanced iteration of socioeconomic narratives offered to date. They consider societal factors such as demographics, human development, economic growth, inequality, governance, technological change and policy orientations. While most factors are given as narratives that sketch broad patterns of change globally and for large world regions, a subset (population1 , GDP, urbanization and educational attainment) are provided as quantitative, country-specific projections. These variables were chosen based on their common use as inputs to emissions or impact models and their relationships to each other. See O’Neill et al. 2017 for more information on scenarios and scenario development. Data presented below depicts population growth, poverty scales, age and sex classifications per each SSP.