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https://doi.org/10.5194/egusphere-2023-1155
https://doi.org/10.5194/egusphere-2023-1155
06 Jul 2023
 | 06 Jul 2023

Sensitivity of atmospheric rivers to aerosol treatment in regional climate simulations: Insights from the AIRA identification algorithm

Eloisa Raluy-López, Juan Pedro Montávez, and Pedro Jiménez-Guerrero

Abstract. This study analyzed the sensitivity of Atmospheric Rivers (ARs) to aerosol treatment in regional climate simulations. Three experiments covering the Iberian Peninsula for the period 1991 to 2010 were examined, each including prescribed aerosols (BASE), direct and semi-direct aerosol effects (ARI), and direct, semi-direct, and indirect aerosol effects (ARCI). A new regional-scale AR identification algorithm, AIRA, was developed and used to identify around 250 ARs in each experiment. The results showed that spring and autumn ARs were the most frequent, intense, and long-lasting, and that ARs could explain up to a 30 % of the total accumulated precipitation. The inclusion of aerosols was found to redistribute precipitation, with increases in the areas of AR occurrence. The analysis of common AR events showed that the differences between simulations were minimal in the most intense cases, and a negative correlation was found between mean direction and mean latitude differences. The joint analysis and classification of dust and sea salt aerosol distributions allowed clustering of common events into eight main aerosol configurations in ARI and ARCI. The sensitivity of ARs to different aerosol treatments was observed to induce spatial deviations and intensity reinforcements/attenuations depending on the aerosol configuration. The correct inclusion of aerosol effects is thus important for the simulation of AR behavior at both global and regional scales, which is essential for meteorological predictions and climate change projections.

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Journal article(s) based on this preprint

19 Feb 2024
Sensitivity of atmospheric rivers to aerosol treatment in regional climate simulations: insights from the AIRA identification algorithm
Eloisa Raluy-López, Juan Pedro Montávez, and Pedro Jiménez-Guerrero
Geosci. Model Dev., 17, 1469–1495, https://doi.org/10.5194/gmd-17-1469-2024,https://doi.org/10.5194/gmd-17-1469-2024, 2024
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Short summary
Atmospheric Rivers (ARs) represent a significant source of water but are also related with...
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