Advances in Remote Sensing of Precipitation: Interactions Among Aerosols, Clouds, and Precipitation and Their Impact on Climate Systems

Dear Colleagues,

Understanding precipitation processes is critical for advancing our knowledge of the Earth’s climate system and addressing pressing challenges in water resource management, agriculture, and disaster risk reduction. Precipitation is a key component of the hydrological cycle, influenced by complex interactions between aerosols, clouds, and atmospheric dynamics. These processes not only regulate local and regional weather patterns but also have far-reaching impacts on climate variability and change. Recent advances in remote sensing technologies and computational techniques, such as artificial intelligence (AI) and machine learning (ML), have significantly enhanced our ability to monitor and analyze precipitation with unprecedented accuracy and spatio-temporal resolution.

We are pleased to invite you to contribute to this Special Issue, which focuses on cutting-edge research that leverages remote sensing to study precipitation processes, particularly the intricate interactions among aerosols, clouds, and precipitation.

This Special Issue aims to advance the scientific understanding of precipitation processes through the integration of remote sensing, AI/ML, and interdisciplinary approaches. The research contributions will explore how aerosols influence cloud formation and precipitation patterns, the feedback mechanisms involved, and their implications for climate systems. The issue aligns with the scope of Atmosphere, emphasizing atmospheric processes, remote sensing, and climate change impacts. By fostering a focused discussion on these topics, this Special Issue seeks to bridge gaps in current knowledge and provide innovative solutions for monitoring and mitigating the impacts of changing precipitation patterns.

We welcome submissions that address, but are not limited to, the following themes:

• Remote sensing innovations for precipitation monitoring, including AI/ML applications.
• Aerosol–cloud–precipitation interactions and their impact on regional and global climates.
• Effects of natural and anthropogenic aerosols on rainfall distribution and intensity.
• Changes in extreme precipitation regimes due to climate variability and warming.
• Use of geostationary satellites (e.g., MSG) for tracking precipitation and atmospheric aerosols.
• Interactions between dust, air quality, and precipitation during extreme weather events.
• Development of hybrid models combining physics-based and data-driven approaches for rainfall estimation.

We encourage original research articles, reviews, and case studies that provide novel insights into these areas and contribute to advancing the field.

Dr. Fethi Ouallouche
Prof. Dr. Karim Labadi
Prof. Dr. Mourad Lazri
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. Atmosphere is an international peer-reviewed open access monthly 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 2400 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.

• remote sensing
• rainfall estimation
• aerosol–cloud–precipitation interactions
• climate change
• extreme precipitation
• satellite meteorology
• artificial intelligence
• machine learning
• atmospheric aerosols
• dust and air quality