RESUMEN
We consider alternative history scenarios in which explicit climate mitigation begins before the present day, estimating the total costs to date of delayed action. Considering a 2(1.5) degree Celsius stabilization target, peak costs are greater and reached sooner with a later start to mitigation, reaching 15(17)% of global GDP in 2085(2070) for a 1990 start and 18(35)% in 2080(2035) for a 2020 start. Further mitigation delay costs a best estimate of an additional 0.5(5) trillion dollars per year. Additional simulations show how optimal mitigation pathways evolve without imposing a warming limit, finding that median abatement levels and costs are not strongly dependent on start date. However, whereas 18(5) percent of optimal solutions starting in 1980 meet the 2(or 1.5) degree target, 5(or 0)% of 2020 simulations meet the goals. Discounted damages due to delayed mitigation action rise by 0.6 trillion US dollars per year in 2020.
RESUMEN
The changing risk of extreme precipitation is difficult to project. Events are rare by definition, and return periods of heavy precipitation events are often calculated assuming a stationary climate. Furthermore, ensembles of climate model projections are not large enough to fully categorize the tails of the distribution. To address this, we cluster the contiguous United States into self-similar hydroclimates to estimate changes in the expected frequency of extremely rare events under scenarios of global mean temperature change. We find that, although there is some regional variation, record events are projected in general to become more intense, with 500-year events intensifying by 10-50% under 2 °C of warming and by 40-100% under 4 °C of warming. This analysis could provide information to inform regional prioritization of resources to improve the resilience of U.S. infrastructure.
RESUMEN
Understanding changes in precipitation variability is essential for a complete explanation of the hydrologic cycle's response to warming and its impacts. While changes in mean and extreme precipitation have been studied intensively, precipitation variability has received less attention, despite its theoretical and practical importance. Here, we show that precipitation variability in most climate models increases over a majority of global land area in response to warming (66% of land has a robust increase in variability of seasonal-mean precipitation). Comparing recent decades to RCP8.5 projections for the end of the 21st century, we find that in the global, multi-model mean, precipitation variability increases 3-4% K-1 globally, 4-5% K-1 over land and 2-4% K-1 over ocean, and is remarkably robust on a range of timescales from daily to decadal. Precipitation variability increases by at least as much as mean precipitation and less than moisture and extreme precipitation for most models, regions, and timescales. We interpret this as being related to an increase in moisture which is partially mitigated by weakening circulation. We show that changes in observed daily variability in station data are consistent with increased variability.
