remotesensing-logo

Journal Browser

Journal Browser

Remote Sensing of Clouds and Aerosols: Techniques and Applications

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Atmospheric Remote Sensing".

Deadline for manuscript submissions: 15 June 2025 | Viewed by 759

Special Issue Editors


E-Mail Website
Guest Editor
German Research Centre for Geosciences, Telegrafenberg, 14473 Potsdam, Germany
Interests: cloud remote sensing; aerosol remote sensing; trace gas remote sensing; snow remote sensing; radiative transfer
Special Issues, Collections and Topics in MDPI journals
1. The International Research Center of Big Data for Sustainable Development Goals, Beijing, China
2. Institute of Environmental Physics, University of Bremen, Bremen, Germany
Interests: atmospheric remote sensing; polar remote sensing; climate change; SDGs; big data
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
IMK-ASF, Karlsruhe Institute for Technology, Karlsruhe, Germany
Interests: remote sensing of aerosols; remote sensing of clouds; secondary ice production; climate model evaluation; aerosol climatology and event analysis

Special Issue Information

Dear Colleagues,

The remote sensing of clouds and aerosols is of central importance for studying climate system processes and changes. Reliable information on climate-relevant parameters, such as aerosol and cloud optical thickness, layer height, particle size, liquid or ice water path, and vertical particulate matter columns, is required. A number of challenges and unsolved problems remain in regard to algorithms and their applications. This includes the remote sensing of clouds and aerosols with respect to 3D effects, the remote sensing of polluted and mixed clouds, the combination of ground-based and satellite-based systems, and the creation of long-term uniform global records.

This Special Issue is aimed at the discussion of current developments, challenges, and opportunities in aerosol and cloud remote sensing using active and passive remote sensing systems. The Special Issue collects an expanded version of the papers published in session AS3.29 of The General Assembly 2024 of the European Geosciences Union (EGU). The best contributions from leading experts in these fields of study are expanded into full journal articles, collected, and presented. Other researchers and practitioners who are unable to attend this meeting are also invited to submit their original manuscripts on the topics covered in this Special Issue.

This Special Issue is focused on the latest developments in cloud and aerosol remote sensing. We therefore invite papers on the following topics:

  • Radiative transfer modeling of polluted and mixed-phase clouds;
  • Particle scattering measurements and modeling;
  • Development of cloud and aerosol retrieval algorithms;
  • The derivation of aerosol and cloud  products for various (i.e., passive and/or active) satellite, airborne, and/or ground-based remote sensing instruments;
  • Application of remote sensing observations to characterize aerosol and cloud properties;
  • Aerosol–cloud interactions;
  • Climatic effects of aerosols and clouds.

Dr. Alexander Kokhanovsky
Dr. Linlu Mei
Dr. Yasmin Aboel Fetouh
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • clouds
  • precipitation
  • cloud pollution
  • remote sensing
  • radiative transfer
  • light scattering
  • atmospheric ice crystals
  • aerosol remote sensing
  • air quality
  • climate change

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Other

15 pages, 4108 KiB  
Technical Note
Extinction Coefficient Inversion Algorithm with New Boundary Value Estimation for Horizontal Scanning Lidar
by Le Chen, Zhibin Yu, Shihai Wang, Chunhui He, Mingguang Zhao, Aiming Liu and Zhangjun Wang
Remote Sens. 2025, 17(10), 1736; https://doi.org/10.3390/rs17101736 - 15 May 2025
Viewed by 81
Abstract
Lidar has been used for many years to study the optical properties of aerosols, but estimating the boundary values requires solving the lidar elastic scattering equation, which remains a challenge. The boundary values are often determined by fitting to uniform regions of the [...] Read more.
Lidar has been used for many years to study the optical properties of aerosols, but estimating the boundary values requires solving the lidar elastic scattering equation, which remains a challenge. The boundary values are often determined by fitting to uniform regions of the atmosphere. This method typically excludes low signal-to-noise ratio (SNR) signals because it classifies them as non-uniform, reducing the effective detection range of the lidar. On the other hand, directly fitting low SNR signals to estimate the boundary values can introduce significant errors. The method is based on maximizing the lidar detection distance and determines the boundary value using a new estimation algorithm with the averaging of multiple fitted results in the low SNR region to reduce the impact of noise. Simulations demonstrate that the new method reduces the relative error in the boundary value estimation by approximately 5% and improves the accuracy of the extinction coefficient profile inversion compared with the method of directly fitting all-sample signals. Field comparison experiments with forward-scattering sensors further verify that the algorithm improves the retrieval accuracy by 17.3% under extremely low signal-to-noise ratio (SNR) conditions, while performing comparably to the traditional method in high SNR homogeneous atmospheres. Additionally, based on the scanned lidar signals, the algorithm can provide detailed information on the spatial distribution of sea fog and offer valuable insights for an in-depth understanding of the physical evolution of sea fog. Full article
(This article belongs to the Special Issue Remote Sensing of Clouds and Aerosols: Techniques and Applications)
Show Figures

Figure 1

Back to TopTop