Applying global warming levels of emergence to highlight the increasing population exposure to temperature and precipitation extremes

Abstract. Global temperatures exceeded pre-industrial conditions by 1.1 °C during the decade 2011–2020 and further warming is projected by climate models. An increasing number of climate variables exhibit significant changes compared to the past decades, even beyond the noise of internal climate variability. To determine the year when climate change signals can be detected, the concept of time of emergence (ToE) is well established. Additionally, climate projections are communicated increasingly frequently through global warming levels (GWLs) rather than time horizons. Yet, ToE and GWL have barely been combined so far. Here, we apply five Single Model Initial-condition Large Ensembles (SMILEs) to derive global warming levels of emergence (GWLoE) of four temperature and precipitation indices. We show that the concept of GWLoE is particularly promising to constrain temperature projections and proves a viable tool to communicate scientific results. We find that >75 % of the global population is exposed to emerged signals for nighttime temperatures at a GWL of 1.5 °C, increasing to >95 % at 2.0 °C. Daily maximum temperature follows a similar, yet less pronounced path. Emerged signals for mean and extreme precipitation start appearing at current GWLs and increase steadily with further warming (~20 % population exposed at 2.0 °C). Related probability ratios for the occurrence of extremes indicate a strong increase where temperature extremes reach widespread saturation (extremes occur every year) particularly in (sub)tropical regions below 2.5 °C warming. These results indicate that current times are a critical period for climate action as every fraction of additional warming substantially increases the adverse effects on human wellbeing.