2026/03/14 by Hassanpreet Dhaliwal, S Pal · 1 voice
Earth and Planetary Sciences · Environmental Science · #Atmospheric aerosols and clouds #Atmospheric chemistry and aerosols #Meteorological Phenomena and Simulations
paper · doi:10.1016/j.atmosres.2026.108932
openalex publication_date 2026/03/14 · openalex created_date 2026/03/15 · openalex updated_date 2026/04/09
Atmospheric aerosols affect air quality, radiation balance, weather, and climate, making accurate global monitoring of aerosol optical depth (AOD) essential. Regional AOD variability reflects both local emissions and synoptic-scale transport, including monsoons and frontal passages, which redistribute aerosols through advection, convergence, and boundary layer mixing. Conventional satellite AOD evaluations across seasonal to interannual timescales often average over diverse meteorological conditions, obscuring systematic weather-dependent biases. To address this, we introduced a weather-regime-specific evaluation framework and evaluated AOD from the Visible Infrared Imaging Radiometer Suite (VIIRS) over the southwest United States using Aerosol Robotic Network (AERONET) and collocated meteorological observations from 2018 to 2022. Based on the encroachment model of boundary layer growth, near-surface heating rates ( d θ v dt ) were used to distinguish synoptically active regimes from classical fair-weather conditions. The regional baseline assessment showed strong agreement between VIIRS and AERONET AOD (R ≈ 0.7), low RMSE(≈0.05), and minimal bias (≈ − 0.005). However, a systematic error was observed. A positive bias (≈0.02; p < 0.0001) occurred at low AERONET AOD (<0.2) on days with lower d θ v dt , driven by residual cloud contamination and inadequate representation of rapidly evolving aerosol fields during frontal passages. In contrast, days with higher d θ v dt exhibited a modest negative bias (≈ − 0.006) at high AERONET AOD (>0.2), characteristic of typical weather conditions. Analysis of aerosol type contributions showed that mixed aerosols had a positive bias (≈0.08) under the non-classical regime, while the overall negative bias was mainly linked to smoke and background aerosols. Our work highlights how readily available weather-scale metrics can aid in diagnosing and improving satellite AOD retrievals. • Weather-aware evaluation of satellite-retrieved AOD reveals hidden biases. • Overall AOD retrievals show a negligible negative bias under typical conditions. • Positive AOD biases emerge during synoptically active weather regimes. • Mixed aerosol types produce the largest retrieval errors under synoptic forcing. • In-situ meteorological observations offer a pathway to improved cloud screening.