Precipitation accumulations, integrated over rainfall events, can be affected by both intensity and duration of the storm event. Thus, although precipitation intensity is widely projected to increase under global warming, a clear framework for predicting accumulation changes has been lacking, despite the importance of accumulations for societal impacts. Theory for changes in the probability density function (pdf) of precipitation accumulations is presented with an evaluation of these changes in global climate model simulations. We show that a simple set of conditions implies roughly exponential increases in the frequency of the very largest accumulations above a physical cutoff scale, increasing with event size. The pdf exhibits an approximately power-law range where probability density drops slowly with each order of magnitude size increase, up to a cutoff at large accumulations that limits the largest events experienced in current climate. The theory predicts that the cutoff scale, controlled by the interplay of moisture convergence variance and precipitation loss, tends to increase under global warming. Thus, precisely the large accumulations above the cutoff that are currently rare will exhibit increases in the warmer climate as this cutoff is extended. This indeed occurs in the full climate model, with a 3 • C end-of-century global-average warming yielding regional increases of hundreds of percent to >1,000% in the probability density of the largest accumulations that have historical precedents. The probabilities of unprecedented accumulations are also consistent with the extension of the cutoff.precipitation accumulation | global warming | extreme events | stochastic modeling | first-passage process O ccurrences of intense precipitation are projected to increase (1-8) associated with higher atmospheric moisture content (9, 10) under global warming. Measures of precipitation intensity, coarse-grained to 1-to 5-d intervals, exhibit end-of-century increases on the order of 20% for wettest annual 5-d rainfall (8) or 10% in average wet-day intensity (11) or 17%• C in the 99.9th to 99.999th percentiles of daily precipitation (12) in businessas-usual anthropogenic forcing scenarios. Associated with this, substantial increases in frequency of high-rain-rate events can occur (13-15), and the return times of events exceeding a given threshold decrease (16).Time-integrated accumulation, the amount of precipitation that falls during a single event, is of concern for many societal impacts (17). Because more intense precipitation could, in principle, yield shorter event durations (10), the expected change in accumulation probabilities is unclear. Here, we derive a stochastic prototype from a fundamental climate model equation. This leads to an explanation of key properties of the probability density function (pdf) of accumulations noted in station observations (18-20)-why the pdf of accumulation size drops slowly with increasing size over many orders of magnitude before reaching a cutoff scale, after which the pdf drops...

A branch‐run perturbed‐physics ensemble in the Community Earth System Model estimates impacts of parameters in the deep convection scheme on current hydroclimate and on end‐of‐century precipitation change projections under global warming. Regional precipitation change patterns prove highly sensitive to these parameters, especially in the tropics with local changes exceeding 3 mm/d, comparable to the magnitude of the predicted change and to differences in global warming predictions among the Coupled Model Intercomparison Project phase 5 models. This sensitivity is distributed nonlinearly across the feasible parameter range, notably in the low‐entrainment range of the parameter for turbulent entrainment in the deep convection scheme. This suggests that a useful target for parameter sensitivity studies is to identify such disproportionately sensitive “dangerous ranges.” The low‐entrainment range is used to illustrate the reduction in global warming regional precipitation sensitivity that could occur if this dangerous range can be excluded based on evidence from current climate.

Summertime wildfire activity is increasing in boreal forest and tundra ecosystems in the Northern Hemisphere. However, the impact of long range transport and deposition of wildfire aerosols on biogeochemical cycles in the Arctic Ocean is unknown. Here, we use satellite-based ocean color data, atmospheric modeling and back trajectory analysis to investigate the transport and fate of aerosols emitted from Siberian wildfires in summer 2014 and their potential impact on phytoplankton dynamics in the Arctic Ocean. We detect large phytoplankton blooms near the North Pole (up to 82°N in the eastern Eurasian Basin). Our analysis indicates that these blooms were induced by the northward plume transport and deposition of nutrient-bearing wildfire aerosols. We estimate that these highly stratified surface waters received large amounts of wildfire-derived nitrogen, which alleviated nutrient stress in the phytoplankton community and triggered an unusually large bloom event. Our findings suggest that changes in wildfire activity may strongly influence summertime productivity in the Arctic Ocean.