Atmospheric rivers and Australian precipitation: Impact of detection algorithm choice

• The relationship between Atmospheric Rivers (ARs) and precipitation varies between detection algorithms. • ARs contribute substantially to precipitation in Australia. • The algorithms developed by Mundhenk and Reid appear more effective in identifying AR-precipitation interactions in Australia. Atmospheric Rivers (ARs) play a pivotal role in precipitation dynamics, often leading to hazardous flood events. While much research has investigated the relationship between ARs and precipitation in the northern hemisphere, the role of ARs in modulating Australia’s precipitation has received little attention. The ambiguity surrounding AR definition and identification criteria has resulted in the emergence of various algorithms, differing in prerequisite thresholds. This study focuses on refining AR detection algorithm choice with a specific emphasis on the precipitation-AR relationship for Australia. Using data from 1980 to 2019, we examine seven AR selection algorithms, investigating the impact of Integrated Vapor Transport (IVT), a key indicator of AR activity, as well as ARs, on precipitation activity across Australia. We find a robust positive relationship, with a correlation of 0.5 to 1, between annual IVT and precipitation anomalies across Australia. Our findings also reveal a positive correlation between ARs and precipitation on an annual scale. While ARs consistently align with the top 25 % of precipitation, indicative of their association with heavy precipitation events, our study highlights a substantial difference between detection algorithms in the likelihood of AR occurrence on days with and without precipitation – varying from approximately 10 % to almost 40 %. Our results demonstrate that, although ARs are typically associated with heavy precipitation, this association varies greatly between detection algorithms. We anticipate these findings will have implications for our understanding of the role of ARs in hydrologic assessments, particularly related to heavy precipitation events leading to flooding.

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Publication Details

Journal
Journal of Hydrology
Published
2024-12-25
DOI
https://doi.org/10.1016/j.jhydrol.2024.132586
Citations
5
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
1.41

Funders

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article

Atmospheric rivers and Australian precipitation: Impact of detection algorithm choice

Shekhar Pradhan, Conrad Wasko, Murray Cameron Peel
5 citations
Journal of Hydrology
Climate variability and models
1.41
article

Atmospheric rivers and Australian precipitation: Impact of detection algorithm choice

Shekhar Pradhan, Conrad Wasko, Murray Cameron Peel
article en
5 citations

Abstract

• The relationship between Atmospheric Rivers (ARs) and precipitation varies between detection algorithms. • ARs contribute substantially to precipitation in Australia. • The algorithms developed by Mundhenk and Reid appear more effective in identifying AR-precipitation interactions in Australia. Atmospheric Rivers (ARs) play a pivotal role in precipitation dynamics, often leading to hazardous flood events. While much research has investigated the relationship between ARs and precipitation in the northern hemisphere, the role of ARs in modulating Australia’s precipitation has received little attention. The ambiguity surrounding AR definition and identification criteria has resulted in the emergence of various algorithms, differing in prerequisite thresholds. This study focuses on refining AR detection algorithm choice with a specific emphasis on the precipitation-AR relationship for Australia. Using data from 1980 to 2019, we examine seven AR selection algorithms, investigating the impact of Integrated Vapor Transport (IVT), a key indicator of AR activity, as well as ARs, on precipitation activity across Australia. We find a robust positive relationship, with a correlation of 0.5 to 1, between annual IVT and precipitation anomalies across Australia. Our findings also reveal a positive correlation between ARs and precipitation on an annual scale. While ARs consistently align with the top 25 % of precipitation, indicative of their association with heavy precipitation events, our study highlights a substantial difference between detection algorithms in the likelihood of AR occurrence on days with and without precipitation – varying from approximately 10 % to almost 40 %. Our results demonstrate that, although ARs are typically associated with heavy precipitation, this association varies greatly between detection algorithms. We anticipate these findings will have implications for our understanding of the role of ARs in hydrologic assessments, particularly related to heavy precipitation events leading to flooding.

Journal of HydrologyVol. 651
The University of Sydney (AU), The University of Melbourne (AU)
Australian Research Council
Climate action
Openalex Percentile: Top 18%
Climate variability and models
1.41
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