Abstract. The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) is an international collaborative effort to understand and quantify the uncertainties in atmospheric river (AR) science based on detection algorithm alone. Currently, there are many AR identification and tracking algorithms in the literature with a wide range of techniques and conclusions. ARTMIP strives to provide the community with information on different methodologies and provide guidance on the most appropriate algorithm for a given science question or region of interest. All ARTMIP participants will implement their detection algorithms on a specified common dataset for a defined period of time. The project is divided into two phases: Tier 1 will utilize the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) reanalysis from January 1980 to June 2017 and will be used as a baseline for all subsequent comparisons. Participation in Tier 1 is required. Tier 2 will be optional and include sensitivity studies designed around specific science questions, such as reanalysis uncertainty and climate change. High-resolution reanalysis and/or model output will be used wherever possible. Proposed metrics include AR frequency, duration, intensity, and precipitation attributable to ARs. Here, we present the ARTMIP experimental design, timeline, project requirements, and a brief description of the variety of methodologies in the current literature. We also present results from our 1-month “proof-of-concept” trial run designed to illustrate the utility and feasibility of the ARTMIP project.

Atmospheric rivers (ARs) are now widely known for their association with high‐impact weather events and long‐term water supply in many regions. Researchers within the scientific community have developed numerous methods to identify and track of ARs—a necessary step for analyses on gridded data sets, and objective attribution of impacts to ARs. These different methods have been developed to answer specific research questions and hence use different criteria (e.g., geometry, threshold values of key variables, and time dependence). Furthermore, these methods are often employed using different reanalysis data sets, time periods, and regions of interest. The goal of the Atmospheric River Tracking Method Intercomparison Project (ARTMIP) is to understand and quantify uncertainties in AR science that arise due to differences in these methods. This paper presents results for key AR‐related metrics based on 20+ different AR identification and tracking methods applied to Modern‐Era Retrospective Analysis for Research and Applications Version 2 reanalysis data from January 1980 through June 2017. We show that AR frequency, duration, and seasonality exhibit a wide range of results, while the meridional distribution of these metrics along selected coastal (but not interior) transects are quite similar across methods. Furthermore, methods are grouped into criteria‐based clusters, within which the range of results is reduced. AR case studies and an evaluation of individual method deviation from an all‐method mean highlight advantages/disadvantages of certain approaches. For example, methods with less (more) restrictive criteria identify more (less) ARs and AR‐related impacts. Finally, this paper concludes with a discussion and recommendations for those conducting AR‐related research to consider.

The wintertime Northern Hemisphere (NH) atmospheric circulation response to current (2007–12) and projected (2080–99) Arctic sea ice decline is examined with the latest version of the Community Atmospheric Model (CAM5). The numerical experiments suggest that the current sea ice conditions force a remote atmospheric response in late winter that favors cold land surface temperatures over midlatitudes, as has been observed in recent years. Anomalous Rossby waves forced by the sea ice anomalies penetrate into the stratosphere in February and weaken the stratospheric polar vortex, resulting in negative anomalies of the northern annular mode (NAM) that propagate downward during the following weeks, especially over the North Pacific. The seasonality of the response is attributed to timing of the phasing between the forced and climatological waves. When sea ice concentration taken from projections of conditions at the end of the twenty-first century is prescribed to the model, negative anomalies of the NAM are visible in the troposphere, both in early and late winter. This response is mainly driven by the large warming of the lower troposphere over the Arctic, as little impact is found in the stratosphere in this experiment. As a result of the thermal expansion of the polar troposphere, the westerly flow is decelerated and a weak but statistically significant increase of the midlatitude meanders is identified. However, the thermodynamical response extends beyond the Arctic and offsets the dynamical effect, such that the stronger sea ice forcing has limited impact on the intensity of cold extremes over midlatitudes.