Earth System Science Data (Mar 2024)

The Tibetan Plateau space-based tropospheric aerosol climatology: 2007–2020

  • H. Pan,
  • H. Pan,
  • H. Pan,
  • H. Pan,
  • H. Pan,
  • H. Pan,
  • J. Huang,
  • J. Li,
  • Z. Huang,
  • M. Wang,
  • M. Wang,
  • M. Wang,
  • M. Wang,
  • M. Wang,
  • A. Mamtimin,
  • A. Mamtimin,
  • A. Mamtimin,
  • A. Mamtimin,
  • A. Mamtimin,
  • W. Huo,
  • W. Huo,
  • W. Huo,
  • W. Huo,
  • W. Huo,
  • F. Yang,
  • F. Yang,
  • F. Yang,
  • F. Yang,
  • F. Yang,
  • T. Zhou,
  • K. R. Kumar

DOI
https://doi.org/10.5194/essd-16-1185-2024
Journal volume & issue
Vol. 16
pp. 1185 – 1207

Abstract

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A comprehensive and robust dataset of tropospheric aerosol properties is important for understanding the effects of aerosol–radiation feedback on the climate system and reducing the uncertainties of climate models. The “Third Pole” of Earth (Tibetan Plateau, TP) is highly challenging for obtaining long-term in situ aerosol data due to its harsh environmental conditions. Here, we provide the more reliable new vertical aerosol index (AI) parameter from the spaceborne-based lidar CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) on board CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) for daytime and nighttime to investigate the aerosol's climatology over the TP region during 2007–2020. The calculated vertical AI was derived from the aerosol extinction coefficient (EC), which was rigorously quality-checked and validated for passive satellite sensors (MODIS) and ground-based lidar measurements. Generally, our results demonstrated that there was agreement of the AI dataset with the CALIOP and ground-based lidar. In addition, the results showed that, after removing the low-reliability aerosol target signal, the optimized data can obtain the aerosol characteristics with higher reliability. The data also reveal the patterns and concentrations of high-altitude vertical structure characteristics of the tropospheric aerosol over the TP. They will also help to update and make up the observational aerosol data in the TP. We encourage climate modelling groups to consider new analyses of the AI vertical patterns, comparing the more accurate datasets, with the potential to increase our understanding of the aerosol–cloud interaction (ACI) and aerosol–radiation interaction (ARI) and their climate effects. Data described in this work are available at https://doi.org/10.11888/Atmos.tpdc.300614 (Huang, 2023).