Estimating Global Lifetime Exposure to Climate Extremes Using Grid-Scale Exposure Projections across Trajectories and Birth Years
Estimating lifetime exposure to extreme events requires crossing life expectancy data at the country level with grid-scale exposure projections. For each GMT trajectory (1.5–3.5 °C, 0.1 °C intervals), birth year (1960–2020) and country (177), exposures are summed across lifetimes at the grid scale. Life expectancy is assumed to be homogeneity across each country. Exposure during the death years is also included in this sum by multiplying these exposure projections by the fraction of the final year lived. In the analysis, maps of lifetime exposure at the grid scale are produced for each trajectory and birth year.
All demographic datasets are modified to represent lifetimes annually, beginning from 1960 to 2020. The life expectancies for each country are first assumed to be based on the values of the original five-year groups, which are representative of the middle group. Furthermore, we add 5 years to annual life expectancies to capture the life expectancy of each cohort since birth, as the original data begin at age 5. As the maximum UNWPP life expectancy for people born in 2020 prescribes the final year in this analysis (2113), annual population totals must be extrapolated to reach this year. If you take the mean of the preceding 10 years of the dataset for population numbers, they are the mean of 2101 and beyond. For cohort sizes in each country, we interpolate annual cohort sizes from the initial 5-year age groups and divide total age totals by 5 to maintain original population sizes in this dataset and linearly estimate 2113. The absolute numbers of 0- to 100-year-olds have been provided.
Source: Global emergence of unprecedented lifetime exposure to climate extremes
IsIMIP2b: An inter-sectoral impact model intercomparison project with extreme event definitions and GCM input data
The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) provides a simulation protocol for projecting the impacts of climate change across sectors such as biomes, agriculture, lakes, water, fisheries, marine ecosystems and permafrost (www.isimip.org). The impact models for these sectors in ISIMIP2b were built with the help of a set of bias-adjusted global climate models that were selected from the 5th phase of the CMIP5 project. Pre-industrial control and historical and future periods have impact simulations run. The simulations are based on the GCM input datasets. Global projections of annual, grid-scale fractions of exposure to each extreme event category are calculated from ISIMIP2b impact simulations and GCM input data. For the full details of these computations, we refer to ref. 12, but we summarize extreme event definitions below.
We then identify 20% quantile ranges (that is, (0–20], (20–40], … (80–100]) for the lifetime GDP of each birth year and for the singular GRDI map (assumed to align with 2020 population totals). To apply the vulnerability indicators to our birth cohort totals, we had to rank them and do it for the matching year. The lifetime mean GDP of the 2020 birth cohort is aligned with the population totals of newborns in 2020. It is not possible to achieve perfect bin sizes given the sums of grid-scale population totals, so we put the vulnerable indicators into five groups with similar population totals. This groups the richest and poorest and least and most deprived into the aforementioned quantile ranges. The quantile range of each vulnerability indicator is then a map that can be used to mask the existing locations of ULE, such as birth years and all GMT pathways. We compare the lowest and highest 20% of each indicator by population.
The co-author told Nature that they did not stop reporting the findings even after theyTrademarkiaTrademarkiaTrademarkiaTrademarkiaTrademarkiaTrademarkiaTrademarkiaTrademarkiaTrademarkiaTrademarkiaTrademarkiaTrademarkiaTrademarkiaTrademarkiaTrademarkiaTrademarkiaTrademarkiaTrademarkiaTrademarkiaTrademarkiaTrademarkiaTrademarkiaTrademarkiaTrademarkiaTrademarkiaTrademarkiaTrademarkiaTrademarkiaTrademarkiaTrademarkiaTrademarkiaTrademarkiaTrademarkiaTrademarkiaTrademarkiaTrademarkiaTrademarkiaTrademarkiaTrademarkiaTrademarkiaTrademarkia The scientists took their research to the charity Save the Children, which advocates for and supports vulnerable children all over the world. UN member states must now take urgent and ambitious action to get the 1.5 C target, and allocate US$300 billion a year in climate finance, according to a senior adviser with the charity.
The researchers have performed this analysis for every country, and the results are devastating. Some 111 million children born in 2020 will have what the authors call “an unprecedented life” of heatwave exposure in a world where temperatures increase to 3.5 °C. The researchers say that represents 92% of that birth cohort. Unprecedented heatwave exposure will still be experienced by around 62 million children born in 2020 even with 1.5 °C of warming.