<div>Fig. 10. Change in outdoor days with different definitions. Normalized
change in annual outdoor days in 1991–2020 with respect to 1961-1990.
Various definitions considered in this study are indicated in each plot.
The changes are normalized by the 1961-1990 mean. These global maps are
derived from ERA5.</div><div>5. Conclusions</div><div>Here, we used the state-of-the-art reanalysis data and projections from
60 GCMs (31 CMIP5 and 29 CMIP6) to propose that the climate hazard
associated with the change in outdoor days (i.e., the number of days
with pleasant weather that allows for outdoor activities by most people)
could contribute to the north-south disparity that sustains inequality
and injustice of climate change. We project that this disparity is
expected to increase considerably in the future, assuming the high
emissions scenarios.</div><div>Our results have important implications for the injustice of climate
change. That is, the negative impacts of climate change accompanied by
the decreased outdoor days will significantly affect tropical countries,
including Colombia, Brazil, Ivory Coast, Nigeria, Sudan, Indonesia,
Bangladesh, and India, which are developing countries with large
populations but relatively minor emitters of carbon dioxide (Figs. S3
and S9). Meanwhile, some of the historically largest emitters of carbon
dioxide, including the United States, Canada, the European Union,
Russia, and Japan may benefit to varying degrees from the increased
outdoor days. It is important to note that climate risk inferred from
the existing literature may be substantially underestimated, especially
in tropical regions since they do not consider risk caused by the
climate hazard related to outdoor days, as evident from our analysis.</div><div>The findings reported here are not only important from the point of view
of climate risk and how it varies spatially and temporally, but they
also contribute to informing the ongoing discussions regarding
compensations for loss and damage imposed by climate change.</div><div>Acknowledgments.</div><div>We acknowledge support from the Abdul Latif Jameel Water and Food
Systems Lab (J-WAFS) at MIT, and the MIT Climate Grand Challenges
project: Jameel Observatory- Climate Resilience Early Warning System
Network (CREWSnet).</div><div>Data Availability Statement.</div><div>All original CMIP5 GCMs, CMIP6 GCMs, and the ERA5 reanalysis used in
this study are publicly available at
https://esgf-node.llnl.gov/projects/cmip5/,
https://esgf-node.llnl.gov/projects/cmip6/,
https://doi.org/10.24381/cds.adbb2d47, respectively. CMIP5 and CMIP6
models used in this study are listed in Table S1. The gridded population
density of the world is from the Center for International Earth Science
Information Network (CIESIN 2018). The gridded global datasets for GDP
are available from Kummu et al. (2018). GDP per capita and
CO<sub>2</sub> emissions per capita are from
https://ourworldindata.org/grapher/gdp-per-capita-maddison-2020 and
https://ourworldindata.org/grapher/co-emissions-per-capita,
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