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<p>This study analyzes key meteorological parameters and aerosol classifications over the LHAASO region from 2021 to 2023 using satellite-based remote sensing. The meteorological parameters, average temperature (Tavg), relative humidity (RH), wind speed (WS), and precipitation, play a vital role in influencing aerosol behavior, distribution, and transformation processes. Data were sourced from Land Data Assimilation System FLDAS, the Global Land Assimilation System GLDAS model, and Aerosol in Some Contexts AIRS, enabling a comprehensive monthly and annual analysis of atmospheric conditions. Among the aerosol types examined, Dust Column Mass Density consistently dominated the aerosol composition, ranging from 70.34 to 82.66%. Notable interannual variations were observed in Carbon Column Mass Density, while Sulfate Emission and SO₄ Surface Mass Concentration remained relatively low, between 0.01% and 2%. Biomass burning demonstrated substantial yearly variation, contributing 56.31%, 16.55%, and 37.24% over the study period. Key findings include a positive correlation between Tavg and precipitation (0.768), Tavg and RH (0.947), and a negative correlation between Tavg and WS (-0.741), impacting aerosol distribution and transformation. The Generalized Additive Model (GAM) shows that Tavg significantly influences SO₄, Dust, and Biomass, with WS affecting SO₄. Precipitation and RH significantly impact Dust (precipitation: <i>p</i> = 0.00663, RH: <i>p</i> = 0.00223), with RH showing a marginal influence on Biomass (<i>p</i> = 0.0645). Integrating satellite-based observations with meteorological data, this study improves understanding of aerosol variability and its potential impacts on regional climate and air quality, offering perspectives for future atmospheric research and environmental monitoring in high-altitude environments.</p>

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Study of meteorological parameters and classification of aerosols using remote sensing over LHAASO

  • 期刊论文

  • 发表日期：

    2025年6月16日

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  • Andleeb Masood,
  • F. R. Zhu,
  • Zulfaqar Sa’adi,
  • Md. Abdullah Al Mamun Hridoy,
  • Irfan Ullah

摘要

This study analyzes key meteorological parameters and aerosol classifications over the LHAASO region from 2021 to 2023 using satellite-based remote sensing. The meteorological parameters, average temperature (Tavg), relative humidity (RH), wind speed (WS), and precipitation, play a vital role in influencing aerosol behavior, distribution, and transformation processes. Data were sourced from Land Data Assimilation System FLDAS, the Global Land Assimilation System GLDAS model, and Aerosol in Some Contexts AIRS, enabling a comprehensive monthly and annual analysis of atmospheric conditions. Among the aerosol types examined, Dust Column Mass Density consistently dominated the aerosol composition, ranging from 70.34 to 82.66%. Notable interannual variations were observed in Carbon Column Mass Density, while Sulfate Emission and SO₄ Surface Mass Concentration remained relatively low, between 0.01% and 2%. Biomass burning demonstrated substantial yearly variation, contributing 56.31%, 16.55%, and 37.24% over the study period. Key findings include a positive correlation between Tavg and precipitation (0.768), Tavg and RH (0.947), and a negative correlation between Tavg and WS (-0.741), impacting aerosol distribution and transformation. The Generalized Additive Model (GAM) shows that Tavg significantly influences SO₄, Dust, and Biomass, with WS affecting SO₄. Precipitation and RH significantly impact Dust (precipitation: p = 0.00663, RH: p = 0.00223), with RH showing a marginal influence on Biomass (p = 0.0645). Integrating satellite-based observations with meteorological data, this study improves understanding of aerosol variability and its potential impacts on regional climate and air quality, offering perspectives for future atmospheric research and environmental monitoring in high-altitude environments.