Uncertainties in Atmospheric River Lifecycles by Detection Algorithms: Climatology and Variability:Climatology and Variability

Zhou, Yang, O'Brien, Travis A., Ullrich, Paul A., Collins, William D. ORCID: https://orcid.org/0000-0002-4463-9848, Patricola, Christina M. and Rhoades, Alan M. (2021) Uncertainties in Atmospheric River Lifecycles by Detection Algorithms: Climatology and Variability:Climatology and Variability. Journal of Geophysical Research: Atmospheres, 126 (8). ISSN 2169-897X

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Abstract

Atmospheric rivers (ARs) are long and narrow filaments of vapor transport that are responsible for most poleward moisture transport outside of the tropics. Many AR detection algorithms have been developed to automatically identify ARs in climate data. The diversity of these algorithms has introduced appreciable uncertainties in quantitative measures of AR properties and thereby impedes the construction of a unified and internally consistent climatology of ARs. This paper compares nine global AR detection algorithms from the perspective of AR lifecycles following the propagation of ARs from origin to termination in the MERRA2 reanalysis over the period 1980–2017. Uncertainties in AR lifecycle characteristics, including event number, lifetime, intensity, and frequency distribution are discussed. Notably, the number of AR events per year in the Northern Hemisphere can vary by a factor of 5 with different algorithms. Although all algorithms show that the maximum AR origin (termination) frequency is located over the western (eastern) portion of ocean basins, significant disagreements appear in regional distribution. Spreads are large in AR lifetime and intensity. The number of landfalling AR events produced by the algorithms can vary from 16 to 80 events per year, although the agreement improves for stronger ARs. By examining the ARs' connections with the Madden-Julian Oscillation and El Niño Southern Oscillation, we find that the overall responses of ARs (such as changes in AR frequency, origin, and landfall activity) to climate variability are consistent among algorithms.

Item Type:	Article
Additional Information:	Data Availability Statement: All ARTMIP data are available from the Climate Data Gateway, DOI:10.5065/D6R78D1M (ARTMIP Tier 1 Catalogs) The OLR data set is provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, from their Web site at https://psl.noaa.gov/data/gridded/data.interp_OLR.html. The Extended Reconstructed SST v5 data is provided by the NOAA/OAR/ESRL PSL, Boulder, Colorado, USA, from their Web site at https://psl.noaa.gov/data/gridded/data.noaa.ersst.v5.html. The Real-time Multivariate MJO index is obtained from the Bureau of Meteorology from Australian Government at http://www.bom.gov.au/climate/mjo/graphics/rmm.74toRealtime.txt.
Uncontrolled Keywords:	artmip,atmospheric river,moisture transport,tracking,uncertainty,geophysics,atmospheric science,space and planetary science,earth and planetary sciences (miscellaneous),sdg 13 - climate action ,/dk/atira/pure/subjectarea/asjc/1900/1908
Faculty \ School:	Faculty of Science > School of Environmental Sciences
Related URLs:	https://www.scopus.com/pages/publication...
Depositing User:	LivePure Connector
Date Deposited:	08 Jul 2026 14:48
Last Modified:	12 Jul 2026 23:02
URI:	https://ueaeprints.uea.ac.uk/id/eprint/103793
DOI:	10.1029/2020JD033711

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