The Atmospheric River Tracking Method Intercomparison Project (ARTMIP): Quantifying uncertainties in atmospheric river climatology

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.

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Related Dataset #1 : 3-hourly MERRA2 IVT, uIVT, vIVT, IWV data computed for ARTMIP

Related Dataset #2 : Atmospheric River Tracking Method Intercomparison Project (ARTMIP) Tier 1 Catalogues

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Author Rutz, Jonathan J.
Shields, Christine A.
Lora, Juan M.
Payne, Ashley E.
Guan, Bin
Ullrich, Paul
O’Brien, Travis
Leung, L. Ruby
Ralph, F. Martin
Wehner, Michael
Brands, Swen
Collow, Allison
Goldenson, Naomi
Gorodetskaya, Irina
Griffith, Helen
Kashinath, Karthik
Kawzenuk, Brian
Krishnan, Harinarayan
Kurlin, Vitaliy
Lavers, David
Magnusdottir, Gudrun
Mahoney, Kelly
McClenny, Elizabeth
Muszynski, Grzegorz
Nguyen, Phu Dinh
Prabhat, Mr.
Qian, Yun
Ramos, Alexandre M.
Sarangi, Chandan
Sellars, Scott
Shulgina, T.
Tome, Ricardo
Waliser, Duane
Walton, Daniel
Wick, Gary
Wilson, Anna M.
Viale, Maximiliano
Publisher UCAR/NCAR - Library
Publication Date 2019-12-27T00:00:00
Digital Object Identifier (DOI) Not Assigned
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Topic Category geoscientificInformation
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Metadata Date 2023-08-18T18:12:46.390502
Metadata Record Identifier edu.ucar.opensky::articles:23127
Metadata Language eng; USA
Suggested Citation Rutz, Jonathan J., Shields, Christine A., Lora, Juan M., Payne, Ashley E., Guan, Bin, Ullrich, Paul, O’Brien, Travis, Leung, L. Ruby, Ralph, F. Martin, Wehner, Michael, Brands, Swen, Collow, Allison, Goldenson, Naomi, Gorodetskaya, Irina, Griffith, Helen, Kashinath, Karthik, Kawzenuk, Brian, Krishnan, Harinarayan, Kurlin, Vitaliy, Lavers, David, Magnusdottir, Gudrun, Mahoney, Kelly, McClenny, Elizabeth, Muszynski, Grzegorz, Nguyen, Phu Dinh, Prabhat, Mr., Qian, Yun, Ramos, Alexandre M., Sarangi, Chandan, Sellars, Scott, Shulgina, T., Tome, Ricardo, Waliser, Duane, Walton, Daniel, Wick, Gary, Wilson, Anna M., Viale, Maximiliano. (2019). The Atmospheric River Tracking Method Intercomparison Project (ARTMIP): Quantifying uncertainties in atmospheric river climatology. UCAR/NCAR - Library. http://n2t.net/ark:/85065/d79w0jn1. Accessed 24 June 2025.

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