Cutting-Edge Research in Severe Weather Forecast

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Meteorology".

Deadline for manuscript submissions: closed (30 September 2025) | Viewed by 1159

Special Issue Editors

Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, Norman, OK 73019, USA
Interests: cloud microphysics; radar meteorology; severe weather forecast; numerical modeling
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Guest Editor
1. Cooperative Institute for Severe and High-Impact Weather Research and Operations (CIWRO), University of Oklahoma, Norman, OK 73072, USA
2. National Severe Storms Laboratory (NSSL), National Oceanic & Atmospheric Administration, Norman, OK 73072, USA
Interests: radar data assimilation; regional NWP; convective-allowing model; high-performance computing
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Special Issue Information

Dear Colleagues,

This Special Issue, ‘Cutting-Edge Research in Severe Weather Forecast’, aims to bring together cutting-edge research on the prediction, modeling, and analysis of severe weather events, including tropical cyclones, tornadoes, thunderstorms, blizzards, and extreme precipitation. The accurate forecasting of these events is critical for mitigating risks to life and property. We welcome contributions that leverage numerical weather prediction, machine learning, data assimilation, and observational techniques to improve forecasting accuracy and lead time. Studies exploring novel visualization methods, risk communication strategies, and the integration of high-resolution simulations with real-world applications are also encouraged. This issue seeks to foster interdisciplinary collaboration among meteorologists, climate scientists, emergency managers, and policymakers to enhance our ability to predict and respond to severe weather threats.

Dr. Jiaxi Hu
Dr. Yunheng Wang
Guest Editors

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Keywords

  • severe weather forecasting
  • numerical weather prediction
  • extreme weather events
  • machine learning in meteorology
  • risk communication

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Published Papers (1 paper)

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Research

19 pages, 7431 KB  
Article
Weather Regimes of Extreme Wind Speed Events in Xinjiang: A 10–30 Year Return Period Analysis
by Yajie Li, Dagui Liu, Donghan Wang, Sen Xu, Bin Ma, Yueyue Yu, Jianing Li and Yafei Li
Atmosphere 2025, 16(10), 1117; https://doi.org/10.3390/atmos16101117 - 24 Sep 2025
Viewed by 898
Abstract
Xinjiang is a critical wind energy region in China. This study characterizes extreme wind speed (EWS) events in Xinjiang by using ERA5 reanalysis (1979–2023) and station observations (2022–2023). Through k-means clustering and wind power density classification, four distinct regions and representative nodes were [...] Read more.
Xinjiang is a critical wind energy region in China. This study characterizes extreme wind speed (EWS) events in Xinjiang by using ERA5 reanalysis (1979–2023) and station observations (2022–2023). Through k-means clustering and wind power density classification, four distinct regions and representative nodes were identified, aligned with the “Three Mountains and Two Basins” topography: Region #1 (eastern wind-rich corridor), Region #2 (Tarim Basin, west–east increasing wind power density), Region #3 (northern valleys), and Region #4 (mountainous areas with weakest wind power density). Peaks-over-threshold analysis revealed 10~30-year return levels varying regionally, with 10-year return level for Node #1 reaching Beaufort Scale 11 but only Scale 6 for Node #4. Since 2001, EWS occurrences increased, with Nodes #2–4 showing doubled 10-year event occurrences in 2012–2023. Events exhibit consistent afternoon peaks and spring dominance (except Node #2 with summer maxima). Such long-term trends and diurnal and seasonal preferences of EWS could be partly explained by diverging synoptic drivers: orographic effects and enhanced pressure gradients (Node #1 and #3) associated with Ural blocking and polar vortex shifts, both showing intensification trends; thermal lows in the Tarim Basin (Node #2) accounting for their summer prevalence; boundary-layer instability that leads to localized wind intensification (Node #4). The results suggest the necessity of region-specific forecasting strategies for wind energy resilience. Full article
(This article belongs to the Special Issue Cutting-Edge Research in Severe Weather Forecast)
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