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Climate
Special Issues
Wind‑Speed Variability from Tropopause to Surface
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Wind‑Speed Variability from Tropopause to Surface

A special issue of Climate (ISSN 2225-1154). This special issue belongs to the section "Weather, Events and Impacts".

Deadline for manuscript submissions: 31 January 2026 | Viewed by 735

Special Issue Editors

Dr. Zhi-Bo Li

E-Mail Website
Guest Editor
Department of Earth Sciences, University of Gothenburg, 40530 Gothenburg, Sweden
Interests: wind climate; renewable energy; monsoon dynamics; atmospheric circulation; paleoclimate simulation
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Paul D. Williams

E-Mail Website
Guest Editor
Department of Meteorology, University of Reading, Earley Gate, Reading RG6 6ET, UK
Interests: geophysical fluid dynamics; climate change; numerical modelling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Tropospheric winds knit together the atmosphere from the tropopause’s jet‑stream corridors and the turbulence‑rich atmospheric surface layer. Variations in wind speed across this vertical column regulate moisture transport, cloud formation, boundary‑layer mixing, and the distribution of heat, aerosols, and pollutants. Resolving how wind speed changes with height and location is therefore crucial for accurate weather prediction, climate‑system understanding, renewable‑energy planning, and impact assessment. Despite major advances in observing systems, reanalyses, and high‑resolution modeling, key gaps remain in quantifying multiscale wind speed variability and its drivers, especially under accelerating climate change. This Special Issue gathers interdisciplinary studies that define, explain, and predict wind‑speed variability extending continuously from the tropopause down to Earth’s surface. By integrating theory, observation, and modeling, this collection will illuminate physical mechanisms, emerging trends, and practical consequences of vertical wind speed structure, fully supporting the journal’s mission to advance holistic climate and atmospheric science.

We invite original research articles, comprehensive reviews, technical notes, data descriptors, and perspective pieces that feature wind speed explicitly, including, but not limited to, the following: long‑term reanalysis and paleoclimate reconstructions of global and regional wind‑speed trends; extreme wind speed events, gust climatology, and probabilistic hazard assessment; mesoscale and large‑eddy simulations resolving vertical wind speed structure in jet streaks, convective downdrafts, and boundary‑layer turbulence; machine learning or data assimilation techniques for retrieving or gap‑filling satellite, radar, and lidar wind speed observations; the attribution of observed wind speed changes to anthropogenic forcing or natural modes of variability; the downscaling of CMIP6 wind speed projections for wind‑energy siting and infrastructure resilience; and the impacts of wind speed variability on ocean circulation, ecosystem dynamics, aviation operations, urban air quality, and socio‑economic risk. Submissions that apply novel tools, provide cross‑disciplinary perspectives, or locate present and future wind‑speed variability within a broader climatic context are especially welcome.

You may choose our Joint Special Issue in Meteorology.

Dr. Zhi-Bo Li
Prof. Dr. Paul Williams
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. Climate is an international peer-reviewed open access monthly 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 1800 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

  • wind speed variability
  • tropopause and jet‑stream dynamics
  • boundary layer turbulence
  • extreme wind gusts
  • model evaluations and projections
  • wind energy resource
  • reanalysis and paleoclimate winds
  • data assimilation and machine learning

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Published Papers (3 papers)

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Research

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17 pages, 4652 KiB  
Article
Challenge and Bias Correction for Surface Wind Speed Prediction: A Case Study in Shanxi Province, China
by Zengyuan Guo, Zhuozhuo Lyu and Yunyun Liu
Climate 2025, 13(7), 150; https://doi.org/10.3390/cli13070150 - 17 Jul 2025
Viewed by 173
Abstract
Accurate prediction of wind speed is critical for wind power generation and bias correction serves as an effective tool to enhance the precision of climate model forecasts. This study evaluates the effectiveness of three bias correction methods—Quantile Regression at the 50th percentile (QR50), [...] Read more.
Accurate prediction of wind speed is critical for wind power generation and bias correction serves as an effective tool to enhance the precision of climate model forecasts. This study evaluates the effectiveness of three bias correction methods—Quantile Regression at the 50th percentile (QR50), Linear Regression (LR), and Optimal Threat Score (OTS)—for improving wind speed predictions at a height of 70 m from the NCEP CFSv2 model in Shanxi Province, China. Using observational data from nine wind towers (2021–2024) and corresponding model hindcasts, we analyze systematic biases across lead times of 1–45 days. Results reveal persistent model errors: overestimation of low wind speeds (<6 m/s) and underestimation of high wind speeds (>6 m/s), with the Root Mean Square Error (RMSE) exceeding 1.5 m/s across all lead times. Among the correction methods, QR50 demonstrates the most robust performance, reducing the mean RMSE by 11% in October 2023 and 10% in February 2024. Correction efficacy improves significantly at longer lead times (>10 days) and under high RMSE conditions. These findings underscore the value of regression-based approaches in complex terrain while emphasizing the need for dynamic adjustments during extreme wind events. Full article
(This article belongs to the Special Issue Wind‑Speed Variability from Tropopause to Surface)
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18 pages, 2010 KiB  
Article
Frequency Analysis and Trend of Maximum Wind Speed for Different Return Periods in a Cold Diverse Topographical Region of Iran
by Leila Alimohamadian and Raoof Mostafazadeh
Climate 2025, 13(7), 138; https://doi.org/10.3390/cli13070138 - 2 Jul 2025
Viewed by 284
Abstract
This study examines the trends and statistical characteristics of daily maximum wind speed across various synoptic stations in Ardabil Province, Iran, with diverse topography. Using daily wind speed data from multiple synoptic stations, the research focuses on three primary objectives: assessing changes in [...] Read more.
This study examines the trends and statistical characteristics of daily maximum wind speed across various synoptic stations in Ardabil Province, Iran, with diverse topography. Using daily wind speed data from multiple synoptic stations, the research focuses on three primary objectives: assessing changes in daily maximum wind speed, fitting various statistical distributions to the data, and estimating wind speed values for different return periods. In this research, the temporal changes were evaluated while analyzing the frequency of the data, and then the maximum wind speed values were calculated and analyzed for different return periods by fitting frequency distributions. The analysis reveals notable variability in maximum wind speeds across stations. The trend analysis, conducted using the nonparametric Mann–Kendall method, reveals significant positive trends in maximum wind speed at Meshgin-Shahr and Sareyn (p < 0.05). Meanwhile, data from Khalkhal station displays a significant decreasing trend, while other stations, like Ardabil and Parsabad, show no meaningful trends. According to the statistical distributions analysis, the Fisher–Tippett T2 mirrored distribution demonstrates the best fit for Ardabil, with an absolute difference of 2.52%, while the Laplace distribution yields the lowest discrepancies for Bilesavar (3.50%) and Ardabil Airport (3.83%). This ranking indicates that, despite similar first-ranked distributions in some stations, secondary models show variability, suggesting localized influences on wind speed that modify distributional fit. As a conclusion, the Laplace (std) distribution stands out as the best-fit model for several stations, showing relative consistency across several stations. These findings demonstrate the necessity of site-specific statistical modeling to accurately represent wind speed patterns across the diverse landscapes of Ardabil Province. Based on the results, comparing the wind characteristics in the study area with those of other regions in Iran, as well as analyzing the reported trends, can be useful in determining the impact of the region’s climatic conditions and topography on wind patterns. This research offers key insights into wind speed variability and trends in Ardabil, crucial for climate adaptation and risk management of extreme wind events. Full article
(This article belongs to the Special Issue Wind‑Speed Variability from Tropopause to Surface)
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Review

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30 pages, 459 KiB  
Review
Recent Advances in Long-Term Wind-Speed and -Power Forecasting: A Review
by Jacqueline Muthoni Mbugua and Yusuke Hiraga
Climate 2025, 13(8), 155; https://doi.org/10.3390/cli13080155 - 23 Jul 2025
Abstract
This review examines advancements and methodologies in long-term wind-speed and -power forecasting. It emphasizes the importance of these techniques in integrating wind energy into power systems. Covering a range of forecasting timeframes from monthly to multiyear projections, this paper highlights the diversity of [...] Read more.
This review examines advancements and methodologies in long-term wind-speed and -power forecasting. It emphasizes the importance of these techniques in integrating wind energy into power systems. Covering a range of forecasting timeframes from monthly to multiyear projections, this paper highlights the diversity of applications and approaches. These applications and approaches are essential for managing the inherent variability and unpredictability of wind energy. Various forecasting methods, including statistical models, machine-learning techniques, and hybrid models, are discussed in detail. The review demonstrates how these methods improve forecast accuracy and reliability across different temporal and geographical scales. It also identifies significant challenges such as model complexity, data limitations, and the need to accommodate regional variations. Future improvements in wind forecasting include enhancing model integration, employing higher resolution data, and fostering collaborative research to further refine forecasting methodologies. This comprehensive analysis aims to advance knowledge on wind forecasting, facilitate the efficient integration of wind power into global energy systems, and contribute to sustainable energy development goals. Full article
(This article belongs to the Special Issue Wind‑Speed Variability from Tropopause to Surface)
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