Observational and Model-Based Extreme Precipitation Analysis
A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Climatology".
Deadline for manuscript submissions: 26 July 2026 | Viewed by 871
Special Issue Editor
Interests: hydrological and hydraulic analysis and modeling; hydroclimatology; sustainable water resources management; risk analysis and decision making
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Hydrological extreme events (including heavy precipitation) have the potential to cause disruption in ecosystem function, compromise infrastructure, and public safety. Impacts from such extreme events include significant damage to bridges, culverts, levees, and other national infrastructure, resulting in economic losses, population displacements, and a variety of public health issues. Furthermore, extreme precipitation is expected to intensify with global warming. To this end, understanding the observed changes in extreme precipitation events and anticipating future risks are critical in developing ecosystems resilient to extremes. This Special Issue of Atmosphere focuses on extreme precipitation analysis using innovative statistical methods focused on trends, modeling, and dynamics. Particularly, we welcome topics of observational and model-based studies that could provide useful information on extreme precipitation under changing climate, as well as dynamical and synoptic characteristics. Studies are welcome across global to local scales, whether methodological or applied, focusing on physical principle-based and/or data analysis-based research (including machine learning).
Dr. Nirajan Dhakal
Guest Editor
Manuscript Submission Information
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Keywords
- extreme precipitation risk
- climate change
- observational and model-based studies
- machine learning
- dynamical and synoptic characteristics
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