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\begin{document}

\title{Uncertainties in Atmospheric River Life Cycles by Detection Algorithms:
Climatology and Variability}



\author[1]{Yang Zhou}%
\author[2]{Travis O'brien}%
\author[3]{Paul Ullrich}%
\author[3]{William Collins}%
\author[4]{Christina Patricola}%
\author[1]{Alan Rhoades}%
\affil[1]{Lawrence Berkeley National Lab}%
\affil[2]{Indiana University}%
\affil[3]{University of California}%
\affil[4]{Iowa State University}%


\vspace{-1em}



  
  \date{May 22, 2024}


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\begin{abstract}
Atmospheric rivers (ARs) are long and narrow filaments of vapor
transport 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 eight global AR detection algorithms from the perspective of AR
life cycles following the propagation of ARs from origin to termination
in the MERRA2 reanalysis over the period 1980-2017. Uncertainties
related to lifecycle characteristics, including 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 origin (termination) frequency locates over the northwestern
(northeastern) Pacific, significant disagreements occur 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
78 events per cool season, i.e. by almost a factor of five, although the
agreement improves for stronger ARs. By examining the AR's connection
with the Madden-Julian Oscillation and El Ni\selectlanguage{ngerman}ño Southern Oscillation, we
find that the overall responses of ARs (such as changes in AR frequency,
origin, and landfalling activity) to low-frequency climate variabilities
are consistent among algorithms.%
\end{abstract}\selectlanguage{ngerman}%



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