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Extreme sea level implications of 1.5 °c, 2.0 °c, and 2.5 °c temperature stabilization targets in the 21st and 22nd centuries
2018, Rasmussen, D.J., Bittermann, Klaus, Buchanan, Maya K., Kulp, Scott, Strauss, Benjamin H., Kopp, Robert E., Oppenheimer, Michael
Sea-level rise (SLR) is magnifying the frequency and severity of extreme sea levels (ESLs) that can cause coastal flooding. The rate and amount of global mean sea-level (GMSL) rise is a function of the trajectory of global mean surface temperature (GMST). Therefore, temperature stabilization targets (e.g. 1.5 °C and 2.0 °C of warming above pre-industrial levels, as from the Paris Agreement) have important implications for coastal flood risk. Here, we assess, in a global network of tide gauges, the differences in the expected frequencies of ESLs between scenarios that stabilize GMST warming at 1.5 °C, 2.0 °C, and 2.5 °C above pre-industrial levels. We employ probabilistic, localized SLR projections and long-term hourly tide gauge records to estimate the expected frequencies of historical and future ESLs for the 21st and 22nd centuries. By 2100, under 1.5 °C, 2.0 °C, and 2.5 °C GMST stabilization, the median GMSL is projected to rise 48 cm (90% probability of 28–82 cm), 56 cm (28–96 cm), and 58 cm (37–93 cm), respectively. As an independent comparison, a semi-empirical sea level model calibrated to temperature and GMSL over the past two millennia estimates median GMSL rise within 7–8 cm of these projections. By 2150, relative to the 2.0 °C scenario and based on median sea level projections, GMST stabilization of 1.5 °C spares the inundation of lands currently home to about 5 million people, including 60 000 individuals currently residing in Small Island Developing States. We quantify projected changes to the expected frequency of historical 10-, 100-, and 500-year ESL events using frequency amplification factors that incorporate uncertainty in both local SLR and historical return periods of ESLs. By 2150, relative to a 2.0 °C scenario, the reduction in the frequency amplification of the historical 100 year ESL event arising from a 1.5 °C GMST stabilization is greatest in the eastern United States, with ESL event frequency amplification being reduced by about half at most tide gauges. In general, smaller reductions are projected for Small Island Developing States.
Powers of 10: seeking ‘sweet spots’ for rapid climate and sustainability actions between individual and global scales
2020, Bhowmik, Avit K., McCaffrey, Mark S., Ruskey, Abigail M., Frischmann, Chad, Gaffney, Owen
Achieving the goals of the Paris Agreement and related sustainability initiatives will require halving of global greenhouse gas emissions each decade from now on through to 2050, when net zero emissions should be achieved. To reach such significant reductions requires a rapid and strategic scaling of existing and emerging technologies and practices, coupled with economic and social transformations and novel governance solutions. Here we present a new ‘Powers of 10’ (P10) logarithmic framework and demonstrate its potential as a practical tool for decision makers and change agents at multiple scales to inform and catalyze engagement and actions, complementing and adding nuance to existing frameworks. P10 assists in identifying the suitable cohorts and cohort ranges for rapidly deploying climate and sustainability actions between a single individual and the globally projected ∼ 10 billion persons by 2050. Applying a robust dataset of climate solutions from Project Drawdown’s Plausible scenario that could cumulatively reduce greenhouse gas emissions by 1051 gigatons (Gt) against a reference scenario (2190 Gt) between 2020 and 2050, we seek to identify a ‘sweet spot’ where these climate and sustainability actions are suitably scaled. We suggest that prioritizing the analyzed climate actions between community and urban scales, where global and local converge, can help catalyze and enhance individual, household and local practices, and support national and international policies and finances for rapid sustainability transformations.