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Unraveling Aerosol and Low-Level Cloud Interactions Under Multi-Factor Constraints at the Semi-Arid Climate and Environment Observatory of Lanzhou University
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Unraveling Aerosol and Low-Level Cloud Interactions Under Multi-Factor Constraints at the Semi-Arid Climate and Environment Observatory of Lanzhou University
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Journal Article
Unraveling Aerosol and Low-Level Cloud Interactions Under Multi-Factor Constraints at the Semi-Arid Climate and Environment Observatory of Lanzhou University
2025
Overview
The response of low-level cloud properties to aerosol loading remains ambiguous, particularly due to the confounding influence of meteorological factors and water vapor availability. We utilize long-term data from Ka-band Zenith Radar, Clouds and the Earth’s Radiant Energy System, Modern-Era Retrospective analysis for Research and Applications Version 2, and European Centre for Medium-Range Weather Forecasts Reanalysis v5 to evaluate aerosol’s effects on low-level clouds under the constrains of meteorological conditions and liquid water path (LWP) over the Semi-Arid Climate and Environment Observatory of Lanzhou University during 2014–2019. To better constrain meteorological variability, we apply Principal Component Analysis to derive the first principal component (PC1), which strongly correlates with cloud properties, thereby enabling more accurate assessment of aerosol–cloud interaction (ACI) under constrained meteorological conditions delineated by PC1. Analysis suggests that under favorable meteorological conditions for low-level cloud formation (low PC1) and moderate LWP levels (25–150 g/m2), ACI is characterized by a significantly negative ACI index, with the cloud effective radius (CER) increasing in response to rising aerosol concentrations. When constrained by both PC1 and LWP, the relationship between CER and the aerosol optical depth shows a distinct bifurcation into positive and negative correlations. Different aerosol types show contrasting effects: dust aerosols increase CER under favorable meteorological conditions, whereas sulfate, organic carbon, and black carbon aerosols consistently decrease it, even under high-LWP conditions.
Publisher
MDPI AG
Subject
/ Aerosols
/ Aridity
/ Carbon
/ Climate
/ Clouds
/ Datasets
/ Earth
/ principal component analysis
/ Principal components analysis
/ Water
