Extreme Weather Events
A special issue of Climate (ISSN 2225-1154). This special issue belongs to the section "Weather, Events and Impacts".
Deadline for manuscript submissions: closed (1 February 2022) | Viewed by 54438
Special Issue Editors
Interests: air-sea interaction; atmospheric turbulence; remote sensing; atmospheric boundary layer
Interests: multi-scale atmospheric dynamics; deterministic chaos; mesoscale numerical weather prediction; extreme weather; weather analysis and forecasting
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Extreme events such as heatwaves, droughts, tornadoes, snowstorms, extreme rainfalls, and hurricanes have affected human life since the dawn of time. An increasing number of extreme events have been observed around the world over the past few decades, some of them arguably attributed to changes in global temperatures during the 21st century. There is general agreement that changes in the frequency or intensity of extreme weather events are likely to have profound impacts on society and the environment. Nonetheless, there are still many difficulties in analysis, data availability, data quality, and consistency that make it difficult to derive a clear picture of changes in worldwide extreme weather and climate events. Observations are often not well-constrained, and critical gaps exist in the amount, quality, consistency, and availability of observations, especially with respect to extremes. There is a need to collate and better disseminate data from all existing sources that are relevant for extremes and to identify regions and time periods where we can fill in gaps and better understand uncertainties. Better quantification of these processes through closer interaction between the relevant research communities is essential to reduce forecast uncertainties and improve sub-seasonal and decadal predictability of extreme events, as well as the attribution of past trends and individual events. This is addressed by assessing changes in global or large-scale models of the frequency or intensity of extreme events and using event attribution methods.
This Special Issue will collect data on weather extremes around the world, both past and present, analyze their relationship to climate change and assess forecasting capabilities.We encourage a variety of approaches using observation, reanalysis, and numerical modeling to assess the characteristics and processes of extreme events.
Potential topics include, but not limited to the following:
- Statistics and climatology of extreme weather events, including wind extremes, wet and dry spells, droughts, floods, as well as of heatwaves and cold spells
- Variability of wind, precipitation, and temperature and the occurrence of extremes at different temporal and spatial scales
- The role of the modern climate changes for extreme events
- Cold outbreaking and polar low in the high latitudes
- Hazardous weather events in coastal zones
- Physical mechanisms associated with genesis weather extreme events
- Multiscale numerical simulation of extremes
- Using remote sensing data to diagnose and predict extreme events
- Risks, vulnerability, and impacts: assessment, mitigation, and adaptation strategies
Dr. Irina Repina
Prof. Dr. Michael L. Kaplan
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.
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Keywords
- extreme weather events
- statistics and climatology
- climate change
- observations
- modeling
- remote sensing
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