Aerosol atmospheric rivers: patterns, impacts, and societal insights

Area of Science:

• Atmospheric Science
• Environmental Science
• Climate Science

Background:

• Long-range aerosol transport significantly influences air quality and climate.
• Extreme aerosol events, such as aerosol atmospheric rivers (AARs), require dedicated detection methods.
• Understanding the spatiotemporal distribution and drivers of AARs is crucial for impact assessment.

Purpose of the Study:

• To develop and apply an algorithm for detecting aerosol atmospheric rivers (AARs) for key aerosol species.
• To analyze the global occurrence, intensity, and societal impacts of AARs from 2015-2022.
• To investigate the potential applications of AAR identification in climate and health studies.

Main Methods:

• Adapted the integrated vapour transport (IVT) based atmospheric river (AR) algorithm to create an integrated aerosol transport (IAT) algorithm.
• Detected AARs for black carbon (BC), organic carbon (OC), dust (DU), sea salt (SS), and sulphate (SU).
• Analyzed global AAR data at a spatiotemporal resolution of 1.5° × 1.5° and 6-hour intervals.

Main Results:

• A total of 128,261 AARs were detected globally for key aerosol species.
• BC, OC, and SU AARs are frequent in densely populated regions like the IBG plains, Eastern China, and Japan.
• DU AARs are prevalent in Northern Africa and the USA, while SS AARs are intense over oceans at higher latitudes.

Conclusions:

• Aerosol atmospheric rivers exhibit distinct spatial patterns influenced by aerosol type and geographical factors.
• AARs have significant implications for snow darkening, accelerated melting, and quantifying air pollution health risks.
• The IAT algorithm provides a valuable tool for studying extreme aerosol transport events and their consequences.