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Advancements in Satellite and Ground-Based Retrievals for Aerosol and Cloud Characterization

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

Deadline for manuscript submissions: 30 November 2026 | Viewed by 2242

Editors


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Guest Editor
Institute of Advanced Studies in Science and Technology, Universitatea Babes-Bolyai, Cluj-Napoca, Romania
Interests: aerosol physics; radiative forcing; aerosol–cloud–climate interaction; remote sensing; climate modeling

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Guest Editor
Department of Atmospheric & Oceanic Science, University of Maryland, College Park, MD, USA
Interests: boundary layer clouds; aerosol-cloud interactions; low cloud feedback; machine learning; LES and climate modeling

Special Issue Information

Dear Colleagues,

Aerosols and clouds are critical components of the Earth's atmosphere, playing vital roles in climate regulation, weather patterns, and air quality. Accurate characterization of their properties, including their optical, microphysical, and radiative characteristics, as well as their spatial and temporal distribution, is essential for addressing key environmental challenges. Both satellite and ground-based remote sensing techniques provide unique and valuable perspectives for observing these atmospheric constituents. Satellite platforms offer global and continuous coverage, while ground-based instruments provide high sensitivity, detailed vertical information, and crucial validation capabilities. Continued advancements in retrieval algorithms and observational techniques for both satellite and ground-based platforms are crucial for improving our understanding of aerosols and clouds and their complex interactions. Furthermore, the synergistic use of these complementary datasets holds immense potential for more comprehensive and accurate characterization.

This Special Issue aims to showcase the latest advancements in the retrieval of aerosol and cloud properties from both satellite and ground-based measurements. We welcome contributions that focus on novel algorithm development, innovative observational strategies, validation efforts, and studies that leverage the unique strengths of each data source. We also encourage submissions that explore synergistic approaches to enhance aerosol and cloud characterization. The subject of this Special Issue directly aligns with the journal's scope in remote sensing, emphasizing the cutting-edge use of remotely sensed data and related surface-based observations for atmospheric and environmental research.

We encourage submissions covering a wide range of topics, including, but not limited to the following:

  • Novel satellite retrieval algorithms for aerosol and cloud properties, including those which address uncertainties and limitations.
  • Advancements in ground-based remote sensing techniques (lidar, radar, sun photometers, etc.) for detailed aerosol and cloud characterization.
  • Validation and intercomparison of satellite and ground-based aerosol and cloud products.
  • Synergistic studies that combine satellite and ground-based measurements for enhanced aerosol and cloud property retrievals.
  • Investigations into aerosol–cloud interactions using both satellite and ground-based observations.
  • Retrieval of aerosol and cloud properties in challenging environments or under specific atmospheric conditions.
  • Development and applications of new instrumentation and observational networks for aerosol and cloud monitoring.
  • Studies focusing on the retrieval of specific aerosol or cloud properties (e.g., aerosol composition, ice cloud microphysics).
  • Applications of advanced data processing and machine learning techniques for improving aerosol and cloud retrievals from both platforms.

Dr. Deaconu Lucia
Dr. Haipeng Zhang
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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized 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

  • aerosols
  • clouds
  • satellite remote sensing
  • ground-based measurements
  • aerosol–cloud interactions
  • validation
  • machine learning
  • retrieval algorithms

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Published Papers (2 papers)

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Research

19 pages, 3195 KB  
Article
Comparative Analysis of Orographic Cirrus Clouds over Major Mountainous Regions Using Satellite Observations
by Xiaoyu Hu, Tao Du, Leyi Wang, Yuanyuan Zuo, Jiajing Du, Chen Wang and Zihang Han
Remote Sens. 2026, 18(11), 1701; https://doi.org/10.3390/rs18111701 - 25 May 2026
Viewed by 488
Abstract
Orographic cirrus clouds frequently occur over mountainous regions and can influence the radiative balance of the upper troposphere, yet their characteristics and regional variability remain insufficiently understood on a global scale. In this study, we investigate the occurrence, vertical structure, and microphysical and [...] Read more.
Orographic cirrus clouds frequently occur over mountainous regions and can influence the radiative balance of the upper troposphere, yet their characteristics and regional variability remain insufficiently understood on a global scale. In this study, we investigate the occurrence, vertical structure, and microphysical and optical properties of orographic cirrus over four major mountainous regions, namely the Rocky Mountains, the Andes, the Alps, and the Himalayas, using the Identification and Classification of Cirrus (IC-CIR) framework together with satellite observations from MODIS, CloudSat, and CALIPSO. The results reveal clear regional differences in both occurrence and structure. Cloud cover is higher over the Himalayas and the Alps and lower over the Andes, while seasonal variability is strongest over the Himalayas and the Alps and weakest over the Andes. In terms of vertical structure, cirrus over the Andes reaches higher cloud tops and exhibits a bimodal distribution. The Andes also show smaller values of ice water path, optical depth, and cirrus reflectance. These results provide a unified comparison of orographic cirrus clouds across four representative major mountainous regions and highlight substantial regional differences in their characteristics and potential radiative influence under different topographic and dynamical environments. Full article
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16 pages, 16344 KB  
Article
Investigating the Effects of Aerosol Dry Deposition Schemes on Aerosol Simulations
by Lei Zhang, Jingyue Mo, Ali Mamtimin, Qiaoqiao Jing, Sunling Gong, Tianliang Zhao, Yu Zheng, Huabing Ke, Junjian Liu, Huizheng Che and Xiaoye Zhang
Remote Sens. 2026, 18(4), 544; https://doi.org/10.3390/rs18040544 - 8 Feb 2026
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Abstract
Aerosol dry deposition is an important sink for particulate matter and a source of uncertainty in air quality modeling. Using the Weather Research and Forecasting model coupled with CUACE (WRF-CUACE), we quantified how three aerosol dry deposition schemes and satellite-based leaf area index [...] Read more.
Aerosol dry deposition is an important sink for particulate matter and a source of uncertainty in air quality modeling. Using the Weather Research and Forecasting model coupled with CUACE (WRF-CUACE), we quantified how three aerosol dry deposition schemes and satellite-based leaf area index (LAI) information affected PM2.5 dry removal and near-surface PM2.5 over central and eastern China in January 2022. The schemes were abbreviated as Z01, E20, and PZ10, respectively. A fourth simulation (PZ10_MLAI) used PZ10 but replaced the baseline LAI dataset with a Moderate Resolution Imaging Spectroradiometer (MODIS) constrained LAI field. Hourly PM2.5 was evaluated with the China National Environmental Monitoring Center network. The schemes produced pronounced, size-dependent differences in deposition velocities, with a pronounced spread in the 0 to 2.5 µm average and more than one order of magnitude spread in the accumulation mode diagnostic, leading to distinct regional mean PM2.5 dry deposition fluxes. The mean PM2.5 flux increased by 5.9% in E20 relative to Z01 and decreased by 54.4% in PZ10. The MODIS LAI adjustment changed the PZ10 mean flux by 0.42%. The flux contrasts yielded coherent PM2.5 responses, with E20 reducing near-surface concentrations by about 10 to 30% and PZ10 increasing them by about 20 to 60%, reaching about 80 to 100% in parts of southern China. Domain mean correlations ranged from 0.61 to 0.65 and PZ10-based simulations exhibited near-zero mean bias. Although MODIS LAI effects were modest for this winter month, local PM2.5 differences commonly remained within about 4% and approached 6 to 10%, indicating that satellite LAI constraints can be important for multi-year and decadal applications. Full article
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