No abstract

Atmospheric rivers, or long but narrow regions of enhanced water vapor transport, are an important component of the hydrologic cycle as they are responsible for much of the poleward transport of water vapor and result in precipitation, sometimes extreme in intensity. Despite their importance, much uncertainty remains in the detection of atmospheric rivers in large datasets such as reanalyses and century scale climate simulations. To understand this uncertainty, the Atmospheric River Tracking Method Intercomparison Project (ARTMIP) developed tiered experiments, including the Tier 2 Reanalysis Intercomparison that is presented here. Eleven detection algorithms submitted hourly tags‐‐binary fields indicating the presence or absence of atmospheric rivers‐‐of detected atmospheric rivers in the Modern Era Retrospective Analysis for Research and Applications, version 2 (MERRA‐2) and European Centre for Medium‐Range Weather Forecasts' Reanalysis Version 5 (ERA5) as well as six‐hourly tags in the Japanese 55‐year Reanalysis (JRA‐55). Due to a higher climatological mean for integrated water vapor transport in MERRA‐2, atmospheric rivers were detected more frequently relative to the other two reanalyses, particularly in algorithms that use a fixed threshold for water vapor transport. The finer horizontal resolution of ERA5 resulted in narrower atmospheric rivers and an ability to detect atmospheric rivers along resolved coastlines. The fraction of hemispheric area covered by ARs varies throughout the year in all three reanalyses, with different atmospheric river detection tools having different seasonal cycles.

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.

The Atmospheric River (AR) Tracking Method Intercomparison Project (ARTMIP) is a community effort to systematically assess how the uncertainties from AR detectors (ARDTs) impact our scientific understanding of ARs. This study describes the ARTMIP Tier 2 experimental design and initial results using the Coupled Model Intercomparison Project (CMIP) Phases 5 and 6 multi‐model ensembles. We show that AR statistics from a given ARDT in CMIP5/6 historical simulations compare remarkably well with the MERRA‐2 reanalysis. In CMIP5/6 future simulations, most ARDTs project a global increase in AR frequency, counts, and sizes, especially along the western coastlines of the Pacific and Atlantic oceans. We find that the choice of ARDT is the dominant contributor to the uncertainty in projected AR frequency when compared with model choice. These results imply that new projects investigating future changes in ARs should explicitly consider ARDT uncertainty as a core part of the experimental design.