edu.ucar.opensky::articles:23127 UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact 2025-12-25T15:19:03.087747 ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data ISO 19115-2:2009(E) https://n2t.org/ark:/85065/d79w0jn1 https://doi.org/10.5065/D62R3QFS https Related Dataset #1 3-hourly MERRA2 IVT, uIVT, vIVT, IWV data computed for ARTMIP https://doi.org/10.5065/D6R78D1M https Related Dataset #2 Atmospheric River Tracking Method Intercomparison Project (ARTMIP) Tier 1 Catalogues The Atmospheric River Tracking Method Intercomparison Project (ARTMIP): Quantifying uncertainties in atmospheric river climatology 2019-12-27T00:00:00Z publication https://n2t.org/ark:/85065/d79w0jn1 https://doi.org/10.1029/2019JD030936 Rutz, J. J. author Shields, Christine A. author Lora, J. M. author Payne, Ashley E. author Guan, B. author Ullrich, P. author O'Brien, T. author Leung, L. R. author Ralph, F. M. author Wehner, M. author Brands, S. author Collow, A. author Goldenson, N. author Gorodetskaya, I. author Griffith, H. author Kashinath, K. author Kawzenuk, B. author Krishnan, H. author Kurlin, V. author Lavers, D. author Magnusdottir, G. author Mahoney, K. author McClenny, E. author Muszynski, G. author Nguyen, P. D. author Prabhat, M. author Qian, Y. author Ramos, A. M. author Sarangi, C. author Sellars, S. author Shulgina, T. author Tome, R. author Waliser, D. author Walton, D. author Wick, G. author Wilson, A. M. author Viale, M. author UCAR/NCAR - Library publisher 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. UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact PDF Text theme Resource Type 2016-01-01T00:00:00Z publication Copyright 2020 American Geophysical Union. None eng geoscientificInformation