Uncertainties in Atmospheric River Life Cycles by Detection Algorithms: Climatology and Variability

Abstract:

Atmospheric rivers (ARs) are strong moisture transport in the atmosphere that is one of the dominant processes conveying water vapor from the tropics to high latitudes. In the past decade, 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. We compare 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 event number, lifetime, intensity, and frequency distribution are discussed. Notably, the number of AR events per year over the Northern Hemisphere can vary by a factor of 5 with different algorithms. Although all selected algorithms show similar AR frequency distribution with maximum origin (termination) frequency over the northwestern (northeastern) ocean basin, 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 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 landfalling activity) to low-frequency climate variabilities are consistent among algorithms.