Abstract Atmospheric rivers (ARs) manifest as transient filaments of intense water vapor transport that contribute to synoptic‐scale extremes and interannual variability of precipitation. Despite these influences, the synoptic‐ to planetary‐scale processes that lead to ARs remain inadequately understood. In this study, North Pacific ARs within the November–April season are objectively identified in both reanalysis data and the Community Earth System Model Version 2, and atmospheric patterns preceding AR landfalls beyond 1 week in advance are examined. Latitudinal dependence of the AR processes is investigated by sampling events near the Oregon (45°N, 230°E) and southern California (35°N, 230°E) coasts. Oregon ARs exhibit a pronounced anticyclone emerging over Alaska 1–2 weeks before AR landfall that migrates westward into Siberia, dual midlatitude cyclones developing over southeast coastal Asia and the northeast Pacific, and a zonally elongated band of enhanced water vapor transport spanning the entire North Pacific basin that guides anomalous moisture toward the North American west coast. The precursor high‐latitude anticyclone corresponds to a significant increase in atmospheric blocking probability, suppressed synoptic eddy activity, and an equatorward‐shifted storm track. Southern California ARs also exhibit high‐latitude blocking but have an earlier‐developing and more intense northeast Pacific cyclone. Compared to reanalysis, Community Earth System Model Version 2 underestimates Northeast Pacific AR frequencies by 5–20% but generally captures AR precursor patterns well, particularly for Oregon ARs. Collectively, these results indicate that the identified precursor patterns represent physical processes that are central to ARs and are not simply an artifact of statistical analysis. 
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                            Spatial bias in medium-range forecasts of heavy precipitation in the Sacramento River basin: Implications for water management
                        
                    
    
            Forecasts of heavy precipitation delivered by atmospheric rivers (ARs) are becoming increasingly important for both flood control and water supply management in reservoirs across California. This study examines the hypothesis that medium-range forecasts of heavy precipitation at the basin scale exhibit recurrent spatial biases that are driven by mesoscale and synoptic-scale features of associated AR events. This hypothesis is tested for heavy precipitation events in the Sacramento River basin using 36 years of NCEP medium-range reforecasts from 1984 to 2019. For each event we cluster precipitation forecast error across western North America for lead times ranging from 1 to 15 days. Integrated vapor transport (IVT), 500-hPa geopotential heights, and landfall characteristics of ARs are composited across clusters and lead times to diagnose the causes of precipitation forecast biases. We investigate the temporal evolution of forecast error to characterize its persistence across lead times, and explore the accuracy of forecasted IVT anomalies across different domains of the North American west coast during heavy precipitation events in the Sacramento basin. Our results identify recurrent spatial patterns of precipitation forecast error consistent with errors of forecasted synoptic-scale features, especially at long (5–15 days) leads. Moreover, we find evidence that forecasts of AR landfalls well outside of the latitudinal bounds of the Sacramento basin precede heavy precipitation events within the basin. These results suggest the potential for using medium-range forecasts of large-scale climate features across the Pacific–North American sector, rather than just local forecasts of basin-scale precipitation, when designing forecast-informed reservoir operations. 
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                            - Award ID(s):
- 1803563
- PAR ID:
- 10170350
- Date Published:
- Journal Name:
- Journal of hydrometeorology
- Volume:
- 21
- Issue:
- 7
- ISSN:
- 1525-755X
- Page Range / eLocation ID:
- 1405-1423
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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