Remote Sensing (Aug 2023)

Combined Characterization of Airborne Saharan Dust above Sofia, Bulgaria, during Blocking-Pattern Conditioned Dust Episode in February 2021

  • Zahari Peshev,
  • Anatoli Chaikovsky,
  • Tsvetina Evgenieva,
  • Vladislav Pescherenkov,
  • Liliya Vulkova,
  • Atanaska Deleva,
  • Tanja Dreischuh

DOI
https://doi.org/10.3390/rs15153833
Journal volume & issue
Vol. 15, no. 15
p. 3833

Abstract

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The wintertime outbreaks of Saharan dust, increasing in intensity and frequency over the last decade, have become an important component of the global dust cycle and a challenging issue in elucidating its feedback to the ongoing climate change. For their adequate monitoring and characterization, systematic multi-instrument observations and multi-aspect analyses of the distribution and properties of desert aerosols are required, covering the full duration of dust events. In this paper, we present observations of Saharan dust in the atmosphere above Sofia, Bulgaria, during a strong dust episode over the whole of Europe in February 2021, conditioned by a persistent blocking weather pattern over the Mediterranean basin, providing clear skies and constant measurement conditions. This study was accomplished using different remote sensing (lidar, satellite, and radiometric), in situ (particle analyzing), and modeling/forecasting methods and resources, using real measurements and data (re)analysis. A wide range of columnar and range/time-resolved optical, microphysical, physical, topological, and dynamical characteristics of the detected aerosols dominated by desert dust are obtained and profiled with increased accuracy and reliability by combining the applied approaches and instruments in terms of complementarity, calibration, and normalization. Vertical profiles of the aerosol/dust total and mode volume concentrations are presented and analyzed using the LIRIC-2 inversion code joining lidar and sun-photometer data. The results show that interactive combining and use of various relevant approaches, instruments, and data have a significant synergistic effect and potential for verifying and improving theoretical models aimed at complete aerosol/dust characterization.

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