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The Sierra Nevada and Southern Cascades—California's snowy mountains—are primary freshwater sources and natural reservoirs for the states of California and Nevada. These mountains receive precipitation overwhelmingly from wintertime storms including atmospheric rivers (ARs), much of it falling as snow at the higher elevations. Using a seven-decade record of daily observed temperature and precipitation as well as a snow reanalysis and downscaled climate projections, we documented historical and future changes in snow accumulation and snowlines. In four key subregions of California's snowy mountains, we quantified the progressing contribution of ARs and non-AR storms to the evolving and projected snow accumulation and snowlines (elevation of the snow-to-rain transition), exploring their climatology, variability and trends. Historically, snow makes up roughly a third of the precipitation affecting California's mountains. While ARs make up only a quarter of all precipitating days and, due to their relative warmth, produce snowlines higher than do other storms, they contribute over 40% of the total seasonal snow. Under projected unabated warming, snow accumulation would decline to less than half of historical by the late twenty-first century, with the greatest snow loss at mid elevations (from 1500 to 3300 m by the mountain sub-regions) during fall and spring. Central and Southern Sierra Nevada peaks above 3400 m might see occasionally extreme snow accumulations in January–February resulting entirely from wetter ARs. AR-related snowlines are projected to increase by more than 700 m, compared to about 500 m for other storms. We discuss likely impacts of the changing climate for water resources as well as for winter recreation. [ABSTRACT FROM AUTHOR]

Floods caused by atmospheric rivers and wildfires fanned by Santa Ana winds are common occurrences in California with devastating societal impacts. In this work, we show that winter weather variability in California, including the occurrence of extreme and impactful events, is linked to four atmospheric circulation regimes over the North Pacific Ocean previously named and identified as the "NP4 modes". These modes come in and out of phase with each other during the season, resulting in distinct weather patterns that recur throughout the historical record. Some phase combinations favor atmospheric river landfalls and extreme daily or multi-day precipitation, while other phase combinations favor anomalously hot weather and drying Santa Ana wind conditions over Southern California. This historical perspective of atmospheric circulation and impacts over 70 years reveals that weather patterns are changing in a way that enhances wildfire hazard in California, while the frequency of weather patterns linked to historical floods is not diminishing. These changes highlight the rising hazards of cascading weather extremes in California's present and future. [ABSTRACT FROM AUTHOR]

An increasingly volatile hydroclimate increases California's reliance on precipitation from atmospheric rivers (ARs) for water resources. Here, we simulate the AR that contributed to the Oroville Dam crisis in early February 2017 under global climate conditions representing preindustrial, present‐day, mid‐, and late‐21st century environments. This event consisted of two distinct AR pulses: the first snowy, westerly, and cool followed by a southwesterly and warm pulse resulting in copious rain‐on‐snow. We estimate that climate change to date results in ∼11% and ∼15% increase in precipitation over the Feather River Basin in Northern California for the first and second pulses, respectively, with late‐21st century enhancements upwards of ∼21% and ∼59%, respectively. Although both pulses were enhanced by the imposed climate changes, the thermodynamic response and subsequent precipitation increases were most substantial during the second pulse. The disparate changes demonstrated here highlight that not all ARs will respond similarly in a warmer world. Plain Language Summary: California's reliance on precipitation from atmospheric rivers is expected to increase as our climate warms. Understanding how climate change is impacting this increasingly dominant mode of precipitation is vitally important for water‐resource management throughout the state, across the North American West Coast, and for other similarly impacted regions. Our case study of an impactful atmospheric river from early February 2017 that contributed to the Oroville Dam crisis in Northern California, modeled under preindustrial, present‐day, mid‐, and late‐21st century unabatedly warming environments, demonstrates an overwhelming increase in precipitation throughout the event. This particular storm was comprised of two distinct pulses, and while both pulses of the storm are enhanced in the warmer future epochs, the estimated precipitation increases are disproportionately higher for the second pulse due to larger increases in temperature and moisture. Our results therefore suggest that not all atmospheric rivers are similarly affected by climate change and point to specific directions for relevant future research. Key Points: Climate change enhanced the precipitation associated with the February 2017 atmospheric river over Northern CaliforniaThe two distinct pulses comprising this event were differentially impactedA stronger thermodynamic response during the second pulse enabled a precipitation increase more than double that of the first pulse [ABSTRACT FROM AUTHOR]

Precipitation in California is highly variable and not well forecasted on subseasonal‐to‐seasonal (S2S) timescales. Understanding relationships between synoptic‐scale atmospheric circulation and hydrometeorological extremes could improve predictability. This work demonstrates the importance of four North Pacific circulation regimes (called the NP4 modes) in modulating precipitation, flooding, and water resources in California. Here we demonstrate how, on daily timescales, interactions between the NP4 modes drive coastal flow that can result in dry conditions from atmospheric ridging or wet conditions associated with enhanced onshore flow and atmospheric river (AR) landfalls. Seasonally, the prevalence of certain NP4 phase relationships can tip the scale toward wet or dry conditions. Relationships between El Niño Southern Oscillation (ENSO) and the NP4 are explored, and we provide insight into the poorly forecasted Western US seasonal precipitation during the "Godzilla" El Niño winter of 2016 by examining climate‐weather linkages in a historical context. Plain Language Summary: The amount of precipitation that falls over California in a given water year is highly variable, which presents challenges for water resource management. Skill of both dynamical and statistical models in forecasting precipitation is low at lead times beyond 2 weeks. Recent research has explored relationships between atmospheric circulation patterns and precipitation extremes in the western United States, with the goal of improving predictability. This work demonstrates the importance of four North Pacific circulation regimes in modulating coastal flow patterns that ultimately determines the amount and spatial distribution of precipitation over California on daily and seasonal timescales. We show how the interaction between these modes on daily timescales drives wet and dry episodes within a season. Seasonally, we show how the daily variability occurs within certain constraints established by the larger, more slowly varying climate system, including (but not limited to) El Niño‐Southern Oscillation. This work improves understanding of climate‐weather relationships, which has implications for predictability of hydrometeorological extremes over California and the western United States. Key Points: Coastal vapor transport and California precipitation are modulated by four North Pacific circulation regimes on daily to seasonal timescalesThe most damaging California floods have occurred when these modes were jointly aligned to reinforce onshore flowSeasonally, these modes are influenced by ENSO but much variability occurs within the constraints set by the larger‐scale climate system [ABSTRACT FROM AUTHOR]

Precipitation extremes are projected to become more frequent along the U.S. West Coast due to increased atmospheric river (AR) activity, but the frequency of less intense precipitation events may decrease. Antecedent soilmoisture (ASM) conditions can have a large impact on flood responses, especially if prestorm precipitation decreases. Taken together with increased antecedent evaporative demand due to warming, this would result in reduced soil moisture at the onset of extreme precipitation events. We examine the impact of ASM on AR-related floods in a warming climate in three basins that form a transect along the U.S. Pacific Coast: the Chehalis River basin inWashington, the Russian River basin in Northern California, and the SantaMargarita River basin in Southern California. We ran the Distributed Hydrology Soil Vegetation Model (DHSVM) over the three river basins using forcings downscaled from 10 global climate models (GCMs). We examined the dynamic role of ASM by comparing the changes in the largest 50, 100, and 150 extreme events in two periods, 1951-2000 and 2050-99. In the Chehalis basin, the projected fraction of AR-related extreme discharge events slightly decreases. In the Russian basin, this fraction increases, however, and more substantially so in the Santa Margarita basin. This is due to increases in AR-related extreme precipitation events, as well as the fact that the relationship of extreme precipitation to extreme discharge is strengthened by projected increases in year-to-year volatility of annual precipitation in California, which increases the likelihood of concurrent occurrence of large storms and wet ASM conditions. [ABSTRACT FROM AUTHOR]

Understanding the role of climate variability in modulating the behavior of land-falling atmospheric rivers (ARs) is important for seasonal and subseasonal predictability for water resource management and flood control. We examine daily activity of ARs targeting the Northern California coast over six decades using observations of synoptic-scale circulation, high-resolution precipitation, and a long-term AR detection catalog to quantify distinct types of land-falling ARs categorized by their circulation features. We demonstrate how dramatically different atmospheric states evolve into landfalling ARs along distinct pathways that are modulated by interannual (El Niño/Southern Oscillation (ENSO) and the Pacific Decadal Oscillation) and subseasonal (Arctic Oscillation, Pacific North American Pattern, Western Pacific Oscillation, and the Eastern Pacific Oscillation) modes of large-scale climate variability. Different configurations of climate variability modes are shown to favor ARs having different characteristics in terms of synoptic evolution, integrated vapor transport and landfall orientation resulting in different patterns of precipitation over the landscape. In particular, our results show that while ENSO plays an important role in modulating the synoptic evolution of ARs and their orientation at landfall, subseasonal regional climate modes, which also influence landfall orientation as well as the position of the storm track, appear to be more influential than ENSO in modulating precipitation variability in California. This could have implications for seasonal to subseasonal (S2S) forecasting. Finally, we examine AR activity over the most recent and highly anomalous winter 2016–2017 and show how the unprecedented wet conditions in Northern California were at least partly due to the persistence of ARs characterized by a southward storm track and southerly orientation, which represent the type of ARs associated with heavy rainfall in California, and which are associated with the negative phase of subseasonal regional teleconnection patterns. [ABSTRACT FROM AUTHOR]

Many atmospheric river detection tools (ARDTs) have now been developed. However, their relative performance is not well documented. This paper compares a diverse set of ARDTs by applying them to a single location where a unique 12-year-long time-series from an atmospheric river observatory at Bodega Bay, California is available. The study quantifies the sensitivity of the diagnosed number, duration, and intensity of ARs at this location to the choice of ARDT, and to the choice of reanalysis data set. The ARDTs compared here represent a range of methods that vary in their use of different variables, fixed vs. percentile-based thresholds, geometric shape requirements, Eulerian vs. Lagrangian approaches, and reanalyses. The ARDTs were evaluated first using the datasets documented in their initial publication, which found an average annual count of 19 ± 7. Applying the ARDTs to the same reanalysis dataset yields an average annual count of 19 ± 4. Applying a single ARDT to three reanalyses of varying grid sizes (0.5°, 1.0°–2.5°) showed little sensitivity to the choice of reanalysis. While the annual average AR event count varied by about a factor of two (10–25 per year) depending on the ARDT, average AR duration and maximum intensity varied by less than ± 10%, i.e., 24 ± 2 h duration; 458 ± 44 kg m− 1 s− 1 maximum IVT. ARDTs that use a much higher threshold for integrated vapor transport were compared separately, and yielded just 1–2 ARs annually on average. Generally, ARDTs that include either more stringent geometric criteria or higher thresholds identified the fewest AR events. [ABSTRACT FROM AUTHOR]