Remote Sensing-Driven Advances from Mesoscale to Convective-Scale Predictions: Process Modelling, Observations, Data Assimilation and Machine Learning
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 2026
Special Issue Editors
Interests: mesoscale meteorology; atmospheric physics and atmospheric environment; earth system and global change; boundary layer meteorology
Interests: atmospheric radiative transfer; satellite; airborne and ground-based remote sensing; retrieval of atmospheric and surface properties; electromagnetic scattering theory; cirrus; operational satellite data assimilation; numerical methods; big data; machine learning techniques
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Mesoscale convective systems (MCSs), known as organized groupings of thunderstorms, frequently occur across the global tropics, subtropics, and mid-latitudes that span thousands of square kilometres. MCSs are responsible for much hazardous weather, including extreme rainfall, flooding, and, sometimes, tornadoes and hail, all of which have significant impacts, posing severe threats to economic and social development. While a large number of previous efforts have increased understanding of MCSs over the past several decades, state-of-the-art weather numerical models still struggle to obtain reliable forecasts, partly due to limited observations.
The availability of more remote sensing datasets could provide the potential for deep insights into underlying MCSs. Therefore, this Special Issue aims to deepen our understanding of MCSs, from the aspects of modelling, observations, assimilation, and machine learning, drawing on satellite and radar data in particular.
We welcome the submission of original research, review articles, and MCS case studies utilizing remote sensing observations, AI technologies, and other advanced methodologies. By integrating multidisciplinary research findings, this Special Issue aims to deepen understanding of the mechanisms driving the evolution of MCSs, while also developing new forecasting skills.
Topics of interest for this Special Issue include, but are not limited to, the following:
- Routine observations (from remote sensing platforms, such as radars and satellites) and targeted field campaigns;
- Analysis related to the formation and evolution of MCSs;
- Assimilating or integrating new datasets into numerical models;
- Development of sophisticated methods for modelling output;
- Utilization of AI (Artificial Intelligence) technology for MCS forecasting.
Dr. Bin Chen
Dr. Stephan Havemann
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
- mesoscale convective systems
- data assimilation
- numerical modelling
- physical mechanisms
- artificial intelligence
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