Search

Atmospheric rivers (ARs) often generate extreme precipitation, with AR temperature strongly influencing hydrologic impacts by altering the timing and magnitude of runoff. Long‐term changes in AR temperatures therefore have important implications for regional hydroclimate—especially in locations where a shift to more rain‐dominated AR precipitation could affect flood risk and/or water storage in snowpack. In this study, we provide the first climatology of AR temperature across five U.S. West Coast subregions. We then assess trends in landfalling AR temperatures for each subregion from 1980 to 2016 using three reanalysis products. We find AR warming at seasonal and monthly scales. Cool‐season warming ranges from 0.69 to 1.65 °C over the study period. We detect monthly scale warming of >2 °C, with the most widespread warming occurring in November and March. To understand the causes of AR warming, we quantify the density of AR tracks from genesis to landfall and analyze along‐track AR temperature for each month and landfall region. We investigate three possible influences on AR temperature trends at landfall: along‐track temperatures prior to landfall, background temperatures over the landfall region, and AR temperature over the coastal ocean adjacent to the region of landfall. Generally, AR temperatures at landfall more closely match coastal and background temperature trends than along‐track AR temperature trends. The seasonal asymmetry of the AR warming and the heterogeneity of influences have important implications for regional water storage and flood risk—demonstrating that changes in AR characteristics are complex and may not be directly inferred from changes in the background climate. Atmospheric river (AR) storms are well known for their ability to accumulate snowpack, provide drought relief, and generate extreme precipitation and flooding along the West Coast of the United States. AR temperature is an important variable for determining the water resource impacts of a given event, such as the ratio of rain to snow delivered by an individual storm. As a result, changes in AR temperature have implications for both water storage and flood risk. We find substantial warming in ARs at both the seasonal and monthly scales, as well as seasonal and regional variations in the amount of warming along the U.S. West Coast. To understand the warming of ARs at the landfall regions, we compare these trends with trends in temperature along the AR tracks, background temperature over the landfall region, and temperature over the coastal ocean adjacent to the landfall region. The most robust warming occurs in November and March, which has important implications for increased regional flood risk and decreased water storage, and motivates further investigation in other AR‐prone regions around the globe. All U.S. West Coast subregions exhibit positive atmospheric river (AR) temperature trends, with warming ranging from 0.69 to 1.65 °C over the study periodAR warming magnitude exhibits seasonal and regional asymmetry; ARs have warmed by more than 2 °C in some months, particularly in MarchAR warming at landfall is influenced by temperature trends over the coastal ocean, over the landfall region, and along the AR tracks

In the United States, severe weather poses a threat to society, producing tornadoes and hail that can result in hundreds of casualties and billions of dollars in damages. Fortunately, skillful predictions of severe weather for short lead times of 0–8 days and longer lead times exceeding 1 month have been realized. However, this leaves a forecast gapat subseasonal to seasonal lead times of 2–5 weeks, when early‐action decision making by stakeholders is typically made. Here we develop an empirical prediction model that fills this gap during March–June when severe weather is most prevalent across the United States. We demonstrate skillful weekly forecasts of opportunity with lead times of 2–5 weeks of environmental parameters favorable to severe weather, as well as actual tornado and hail activity. To attain this skill, we use as a predictor the current state of active phases of the Madden‐Julian Oscillation, known to have physical teleconnections with future weather over the United States. The model has significant skill in regions such as the Plains and the Southeast, providing stakeholders with valuable extended forewarning. In the United States, severe thunderstorms produce tornadoes and large hail, responsible for hundreds of deaths and injuries and many billions of dollars in damages on average each year. Because of these devastating impacts, there is a keen interest to accurately forecast when and where severe thunderstorms are likely to occur. While meteorologists and computer models do reasonably well in forecasting severe thunderstorm activity up to a week in advance, their forecasts are less reliable in the 2‐ to 5‐week time frame. In our study, we develop a technique that can accurately forecast severe thunderstorm activity in this time frame by using knowledge of the current state of weather in the tropics. These accurate, extended forecasts offer valuable forewarning to both the general public and stakeholders of when and where potentially deadly severe thunderstorm activity is likely to occur. An active Madden‐Julian Oscillation (MJO) modulates springtime tornado and hail activity over the next 2–5 weeks across the United StatesUsing the MJO as a predictor, skillful weekly forecasts of severe weather with lead times of 2–5 weeks can be realizedThese subseasonal to seasonal (S2S) forecasts offer important forewarning to stakeholders of when and where severe weather is likely

Atmospheric rivers (ARs) can cause wide-ranging impacts upon landfall at high northern latitudes, but comparatively little is known about the dynamics supporting these ARs in contrast to their midlatitude counterparts. Here ARs near the U.S. West Coast and the Gulf of Alaska during 1979–2015 are compared. ARs are found to occur in both regions with similar frequency, but with different seasonality. Composited atmospheric conditions from the NASA Modern-Era Retrospective Analysis for Research and Applications data set reveal that a broad height anomaly over the northeast Pacific is influential to AR activity in both regions. When a positive height anomaly exists over the northeast Pacific, AR activity is often deflected poleward toward Alaska, while the U.S. West Coast experiences a decrease in AR activity. The opposing relationship also applies; that is, AR activity is decreased near Alaska and increased along the U.S. West Coast in the presence of a negative height anomaly. Quantitatively, nearly 79% of Gulf of Alaska ARs are associated with a positive northeast Pacific height anomaly and 86% of U.S. West Coast ARs are associated with a negative anomaly. Results suggest that this relationship applies across a range of time scales, to include subseasonal and interannual, not just with respect to individual transient waves. Both ARs and height anomalies are found to be associated with Rossby wave breaking, thereby dynamically linking AR activity with broader North Pacific dynamics. Atmospheric rivers occur near Alaska and the U.S. West Coast with similar frequency, but with different seasonalityNortheast Pacific height anomalies modulate atmospheric river activity over a range of time scalesRossby wave breaking links height anomalies and atmospheric river activity with broader North Pacific dynamics