AI Applications to Remote Sensing of Cloud and Precipitation: Monitoring, Modeling, and Prediction
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Atmospheric Remote Sensing".
Deadline for manuscript submissions: 30 December 2025 | Viewed by 231
Special Issue Editors
Interests: climate variability; climate change; extreme climate events; extreme precipitation; drought; moisture cycle; atmospheric water vapor; evapotranspiration
Special Issues, Collections and Topics in MDPI journals
Interests: convective cloud; hydrometeors; cumulus
Interests: radar meteorology; cloud and precipitation physics
Special Issues, Collections and Topics in MDPI journals
Interests: cloud and precipitation; convection; cloud physics; Tibetan Plateau; cloud macro- and microphysical properties
Special Issues, Collections and Topics in MDPI journals
Interests: clouds; cold weather systems; cloud microphysics; precipitation; arctic weather; aviation meteorology; aircraft and ground-based in situ and remote sensing observations of the atmosphere, including satellites, radars, lidars, as well as microwave radiometers
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Clouds and precipitation are integral components of Earth's hydrological and energy cycles, exerting profound impacts on climate dynamics, weather extremes, water resource management, and disaster mitigation. Over recent decades, remote sensing technologies—including satellite-based sensors, ground-based radars, and in situ airborne platforms—have revolutionized our ability to observe and quantify atmospheric processes at the mesoscales to global scales. However, the complexity and variability of cloud microphysics, precipitation systems, and their interaction with land/ocean surfaces continue to pose significant challenges to accurate observing, monitoring, numerical modeling, and prediction. The advance of artificial intelligence (AI), particularly deep learning (DL) and linear models (LMs), has led to new frontiers in addressing these challenges. AI-driven approaches enhance the extraction of actionable insights from vast, heterogeneous remote sensing datasets, enabling improved spatiotemporal resolution, real-time processing, and predictive capabilities. Integrating AI techniques with remote sensing observations may offer unprecedented opportunities to advance our understanding of cloud-precipitation microphysics, dynamics, and thermodynamics, refining forecast and climate models, improving the effectiveness of cloud water utilization, and developing applications for sustainable resource management and disaster resilience.
In this Special Issue, we invite submissions of scientific research papers that use remote sensing analysis and those on AI methodologies to address cloud and precipitation monitoring and prediction challenges. The scope for this Special Issue includes the following research directions:
- Remote sensing of clouds and precipitation;
- AI applications and ML;
- Multi-sensor data fusion and assimilation;
- Precipitation nowcasting ;
- Cloud macro- and microphysics
- Aerosol–cloud–precipitation interactions;
- RS applications to cloud seeding theories and techniques;
- Hydrological modeling and water resource management;
- Satellite analysis in extreme precipitation forecasting;
- Extreme weather event detection (floods, droughts, cyclones, etc.);
- RS applications in studying climate change impacts on precipitation regimes;
- GPS/GNSS meteorology.
Dr. Junqiang Yao
Dr. Jinfang Yin
Dr. Haoran Li
Dr. Chang Yi
Dr. Ismail Gultepe
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
- remote sensing techniques
- clouds and precipitation
- AI applications for RS
- cloud microphysics
- cloud seeding
- extreme weather events
- data fusion and assimilation
- RS for hydrological analysis
- atmospheric water vapor/moisture
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