Subseasonal‐to‐Seasonal Hindcast Skill Assessment of Ridging Events Related to Drought Over the Western United States

Abstract

Persistent atmospheric ridging events centered near the western United States are associated with widespread precipitation deficits and meteorological drought. Due to the relatively low skill of dynamical models in forecasting precipitation on subseasonal-to-seasonal (S2S) time scales across this region, forecasts of ridging are explored in this study as a potential bridge for early warning drought prediction. To assess skill, we evaluate deterministic and probabilistic S2S hindcasts (out to 6 week lead time) of ridging events and geopotential height anomalies over the western United States in five ensemble hindcast systems. Prediction skill for ridging events is shown to be highly variable across models. For some models, longer-time-averaged patterns of geopotential height anomalies across the first 6 weeks can be skillfully simulated, when evaluated probabilistically against climatology. The most skillful models show modest skill in forecasting above normal ridging occurrences at lead times of Weeks 3-4 and Weeks 5-6, with some sensitivity to the specific ridge location and method for determining skill. Using the European Centre for Medium-Range Weather Forecasts (ECMWF) model as a case study, longer lead time forecast busts are shown to often occur under extended periods of highly active La Nina-like tropical convection. Model errors at simulating these tropical convection features may have a disproportionately large impact and degrade downstream forecasts over the western United States. Despite the documented model shortcomings, our results highlight an opportunity to target skillful ridging forecasts from dynamical models for improving early warning drought forecasting at S2S lead times.

Winter wet–dry weather patterns driving atmospheric rivers and Santa Ana winds provide evidence for increasing wildfire hazard in California

“…Dynamical models have been shown capable of producing skillful forecasts of large-scale circulation features at lead times of 2.5 weeks (e.g. Ferranti et al 2018Ferranti et al , 2019 to several weeks (Gibson et al 2020b). Additional lead time and higher confidence in long-lead forecasts can be translated by forecasters into improved impact-based decision support (Uccellini and Hoeve 2019) to partner agencies and used to provide earlier warning to the public before extreme events (e.g., Lambrecht et al 2019Lambrecht et al , 2021.…”

Weather Patterns Driving Atmospheric Rivers, Santa Ana Winds, Floods, and Wildfires During California Winters Provide Evidence for Increasing Fire Risk

“…Dynamical models have been shown capable of producing skillful forecasts of large-scale circulation features at lead times of 2.5 weeks (e.g. Ferranti et al 2018Ferranti et al , 2019 to several weeks (Gibson et al 2020b). Additional lead time and higher con dence in long-lead forecasts can be translated by forecasters into improved impact-based decision support (Uccellini and Ten Hoeve 2019) to partner agencies and used to provide earlier warning to public audiences through social media before extreme events (e.g., Lambrecht et al 2019Lambrecht et al , 2021).…”

Multi‐Model Subseasonal Prediction Skill Assessment of Water Vapor Transport Associated With Atmospheric Rivers Over the Western U.S.

“…Recent studies have investigated the regional S2S prediction skill of surface temperature anomalies, ridging events, and jet patterns over the North Pacific and the western U.S. (Albers et al., 2021; Gibson et al., 2020; Z. Zhang, Pierce, & Cayan, 2019). In addition, given the increased societal demands (e.g., water management, flood‐risk reduction) in this region, there has been a growing need for improved longer lead time forecasts for atmospheric rivers (ARs, Ralph et al., 2020; Ralph et al., 2017a; Ralph et al., 2004; Zhu & Newell, 1998).…”

“…Recent studies have investigated the regional S2S prediction skill of surface temperature anomalies, ridging events, and jet patterns over the North Pacific and the western U.S. (Albers et al, 2021;Gibson et al, 2020;Z. Zhang, Pierce, & Cayan, 2019).…”