Meteorological Applications最新文献

{"title":"Evaluating Satellite and Reanalysis Rainfall Estimates for Climate Services in Agriculture: A Comprehensive Methodology","authors":"Danny Parsons,&nbsp;David Stern,&nbsp;Denis Ndanguza,&nbsp;Mouhamadou Bamba Sylla,&nbsp;James Musyoka,&nbsp;John Bagiliko,&nbsp;Graham Clarkson,&nbsp;Peter Dorward","doi":"10.1002/met.70170","DOIUrl":"https://doi.org/10.1002/met.70170","url":null,"abstract":"<p>High-resolution rainfall estimates from satellite and reanalysis data sources (SRE) could play a major role in improving climate services for agriculture. This is particularly relevant in regions that predominantly rely on rain-fed farming but lack a dense network of ground-based measurements to provide localised historical climate information, as in most of the Global South. However, there is a need for a framework which practitioners can use to determine the suitability of these estimated data for specific agricultural applications. This paper presents a comprehensive methodology for evaluating the ability of SRE to provide historical rainfall information for agricultural applications, primarily through comparison with ground-based measurements. The methodology comprises five main steps: data selection and pre-processing, spatial and temporal consistency checks, quantitative SRE-gauge comparisons, bias correction, and application specific summaries. The methodology makes use of graphical summaries, standard comparison metrics, and Markov chain models. We describe how users can apply this methodology to evaluate rainfall estimates for specific applications, complementing existing validation studies. Evaluation cases are presented to demonstrate the methodology using five widely used satellite and reanalysis rainfall products and ground-based measurements from 12 stations in Africa and the Caribbean. The case studies demonstrate how the methodology can be applied to examine multiple aspects of the rainfall estimates. While previous validation studies ask “Does the SRE estimate the true rainfall well?”, this methodology provides means of establishing “To what extent can an SRE be used for this specific purpose?” and a comprehensive framework for achieving this. This meets a major need for location specific rainfall information to improve climate information services for millions of small-holder farming households.</p>","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"33 2","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://rmets.onlinelibrary.wiley.com/doi/epdf/10.1002/met.70170","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147566548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Interactions Between Air Pollution and Weather/Climate From Urban to Global Scales","authors":"Meng Gao,&nbsp;Xin Huang,&nbsp;Yucong Miao,&nbsp;Mengmeng Li,&nbsp;Claudio Mazzoleni","doi":"10.1002/met.70161","DOIUrl":"https://doi.org/10.1002/met.70161","url":null,"abstract":"<p>Air pollution and meteorology are intricately linked. Weather modulates the formation, transport, and removal of pollutants, while aerosols and trace gases modify radiation balance, cloud microphysics, boundary-layer structure, and other factors. These two-way interactions span scales from urban to global and have important consequences. The papers collected in this special issue of Meteorological Applications examine how interactions between weather and pollution at various scales affect visibility, pollutant transport, crop yields, and other outcomes, collectively highlighting the crucial role of the interplay between air pollution and meteorology.</p>","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"33 2","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://rmets.onlinelibrary.wiley.com/doi/epdf/10.1002/met.70161","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147565886","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"For a Future Informed by Science at the Climate-Ecology Interface","authors":"Victoria L. Boult,&nbsp;Gerbrand Koren,&nbsp;Michael C. Dietze,&nbsp;James M. Bullock,&nbsp;Luke Christopher Evans","doi":"10.1002/met.70167","DOIUrl":"https://doi.org/10.1002/met.70167","url":null,"abstract":"&lt;p&gt;The Earth is facing climate and nature crises. In 2024, global mean temperatures surpassed 1.5°C above pre-industrial levels for the first time, and unprecedented extreme weather events—many attributable to climate change—were experienced around the world (World Meteorological Organization &lt;span&gt;2025&lt;/span&gt;). Concurrently, the IUCN Red List recognises 47,000 species threatened by extinction, of which climate change and extreme weather are known to be contributing to extinction risk for more than 7500 species (IUCN &lt;span&gt;2025&lt;/span&gt;).&lt;/p&gt;&lt;p&gt;Climate change is an increasingly important driver of declines in species and ecosystems (Isbell et al. &lt;span&gt;2023&lt;/span&gt;; Thierry et al. &lt;span&gt;2022&lt;/span&gt;). In turn, biodiversity loss fundamentally undermines crucial climate change resilience building and adaptation strategies (Seddon &lt;span&gt;2022&lt;/span&gt;). Climate-resilient development depends on healthy, functioning ecosystems, which in turn rely on intact species assemblages and resulting ecological processes (Isbell et al. &lt;span&gt;2023&lt;/span&gt;; Pecl et al. &lt;span&gt;2017&lt;/span&gt;).&lt;/p&gt;&lt;p&gt;The mechanisms tying climate and nature together are complex and diverse, but it is clear that the fates of both, and that of society, are inextricably linked. The Sixth Assessment Report of the IPCC's Working Group II was the first of its kind to recognise the interdependence of climate, ecosystems, biodiversity and society (IPCC &lt;span&gt;2022&lt;/span&gt;), and relevant to the aims of this special issue, situated the discussion of climate change risks and adaptation within the concurrently unfolding biodiversity crisis. Meaningfully and effectively understanding, predicting and preparing for the impacts of climate change is impossible without consideration of nature, and vice versa (Pettorelli et al. &lt;span&gt;2021&lt;/span&gt;). Addressing these joint crises therefore necessitates an interdisciplinary approach.&lt;/p&gt;&lt;p&gt;This special issue emerged from conversations started at the Climate Science for Ecological Forecasting Symposium, jointly organised by the British Ecological Society and the Royal Meteorological Society (Boult et al. &lt;span&gt;2022&lt;/span&gt;). The symposium highlighted the incredible potential for interdisciplinary collaboration to improve both ecological and climate prediction, and in turn, enable evidence-based decision-making to mitigate climate change and minimise biodiversity loss.&lt;/p&gt;&lt;p&gt;The papers published in this special issue demonstrate innovative approaches at the climate-ecology interface. Papers fall into three broad categories: (1) those predicting future climate change impacts on ecology, (2) those demonstrating the importance of ecosystems for climate change mitigation and adaptation and (3) those proposing methodological advances for the benefit of science and practice at the climate-ecology interface. Below, we use these categories to thematically structure our discussion of key aspects of the papers in this special issue. We hope that this joint special issue acts to cros","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"33 2","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://rmets.onlinelibrary.wiley.com/doi/epdf/10.1002/met.70167","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147565172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"N-FOREWARNS: Regional Nowcasting of Surface Water Flooding With a 3-h Lead Time Predictability Limit","authors":"Joseph Smith,&nbsp;Cathryn Birch,&nbsp;Julia Perez,&nbsp;Linda Speight,&nbsp;John Mooney,&nbsp;Ben Maybee,&nbsp;John Marsham","doi":"10.1002/met.70157","DOIUrl":"https://doi.org/10.1002/met.70157","url":null,"abstract":"<p>Surface water flooding is generally caused when intense rainfall overwhelms drainage systems and/or floods areas before reaching a major watercourse. A key driver of surface water flooding is rapidly developing, localised convection, which is poorly represented in numerical weather prediction models. Nowcasting uses current atmospheric observations to make more accurate predictions of future convective activity on hourly timescales, making it a well-suited approach for surface water flood (SWF) prediction. This study presents Nowcasting-FOREWARNS (N-FOREWARNS), a development of the daily Flood fOREcasts for Surface WAter at a RegioNal Scale (FOREWARNS) tool, which has been modified here to produce hourly SWF nowcasts for lead times of 1–6 h. User feedback from a nowcast comparison testbed indicated that N-FOREWARNS produced few false SWF predictions. When predictions were made by N-FOREWARNS, they were reported to have high spatial accuracy, with users noting an incorrect location only 7% of the time. However, users also reported that N-FOREWARNS missed a high proportion of smaller-scale SWF events with minor impacts. Quantitative verification shows that N-FOREWARNS's 1 h lead time nowcasts produce useful skill, comparable to FOREWARNS, but N-FOREWARNS reaches a limit of predictability at 3 h lead time, and that the skill is primarily limited by the accuracy of its rainfall inputs. Overall, these results show promise for nowcasting regional-scale SWFing and provide a benchmark for further development, which should focus on improving the accuracy of convective rainfall inputs.</p>","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"33 2","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://rmets.onlinelibrary.wiley.com/doi/epdf/10.1002/met.70157","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147564717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diagnostic Evaluation of Spread–Skill Relationships for Convection-Permitting Ensemble Prediction System","authors":"Jingzhuo Wang,&nbsp;Jing Chen,&nbsp;Fajing Chen,&nbsp;Guo Deng,&nbsp;Chen Liang","doi":"10.1002/met.70166","DOIUrl":"https://doi.org/10.1002/met.70166","url":null,"abstract":"<p>Accurate representation of forecast uncertainty is essential for effective ensemble forecasting. To quantify the strengths and weaknesses of the China Meteorological Administration (CMA) convection-permitting ensemble prediction system (CPEPS) in representing spread–skill relationships and to identify avenues for improvement, this study applied multidimensional diagnostic metrics—temporal evolution, spatial distribution, spread–skill of perturbations applied at different scales, and point-to-point distributions of the spread–skill relationships between the ensemble mean root mean square error (RMSE) and ensemble spread—to operational CMA-CPEPS data for the period January–June 2025. The results revealed that the CMA-CPEPS is under-dispersive for most variables except 500-hPa geopotential height. Temperature exhibits a poorer spread–skill relationship than that of wind variables, and near-surface variables show a poorer relationship than that of variables at mid- and low-tropospheric levels. Spread–skill relationships vary regionally, with larger spreads and higher spread–skill ratios over China north of 30° N but smaller spreads and under-dispersion over China south of 30° N. However, the higher spread–skill ratio over northern China does not yield uniformly larger correlation coefficients between the RMSE and ensemble spread. The point-to-point distributions effectively explain the observed six-month averaged spread–skill relationships. Moreover, contributions of perturbations at different scales on the relationships differ across variables and forecast lead times. Based on these diagnostics, we have identified potential areas for improvements to enhance the spread–skill relationships in the CMA-CPEPS. The diagnostic methods can be extended to evaluations of other ensemble prediction systems, providing a foundation for continuously improving EPSs.</p>","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"33 2","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://rmets.onlinelibrary.wiley.com/doi/epdf/10.1002/met.70166","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147563355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rainfall Variability and Extremes in the Hamassa Sub-Basin, Ethiopia: Past Trends and Future Risks","authors":"Barana Babiso Badesso,&nbsp;Muluken Mekuyie,&nbsp;Kebede Wolka","doi":"10.1002/met.70164","DOIUrl":"https://doi.org/10.1002/met.70164","url":null,"abstract":"<p>Rainfall variability and recurrent droughts pose escalating challenges for smallholder farmers in Ethiopia, where climate extremes threaten crop yields, water security, and livelihoods. This study assessed rainfall variability, extremes, and drought characteristics in the Hamassa sub-basin (1986–2023) and evaluated future precipitation dynamics to capture evolving hydroclimatic risks. Observed station data, Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS v2.0), and Climate Models Intercomparison Project Phase Six (CMIP6) simulations were analyzed across multiple timescales. Modified Mann–Kendall (MMK) tests quantified rainfall trends; droughts were characterized using the Standardized Precipitation Evapotranspiration Index (SPEI), and spatial patterns were mapped using Geographic Information Systems (GIS). Teleconnections with El Niño-Southern Oscillation indices (ENSO) were examined to identify seasonal climate controls. Observed records revealed moderate summer rainfall variability, while spring and annual rainfall exhibited moderate to very high variability. The sub-basin experienced recurring moderate droughts and less frequent but prolonged extreme droughts lasting up to 26 months. Extreme rainfall indices indicated a significant decline in yearly rainfall at high elevations, contrasted by intensified and more frequent heavy storms in lowland areas, elevating flood and erosion risks. ENSO demonstrated weak annual but strong seasonal influence on rainfall anomalies. Among CMIP6 simulations, the multi-model ensemble achieved the highest skill (<i>r</i> = 0.75, KGE = 0.57, PBIAS = +4.21%, RMSE = 6.16 mm/year). Projections suggest rising winter rainfall and amplified seasonal fluctuations under warming-enhanced moisture conditions and potential monsoon shifts. This implies that the sub-basin is undergoing multifaceted hydro-climatic transformations marked by intertwined risks of declining seasonal rainfall, intensifying extremes, and heightening vulnerability to droughts, floods, and ENSO-driven anomalies. These stress the need for climate-smart agriculture, early-warning systems, and locally tailored adaptation strategies to strengthen smallholder resilience under increasing climate variability.</p>","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"33 2","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://rmets.onlinelibrary.wiley.com/doi/epdf/10.1002/met.70164","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147563228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of the Structure and Genesis of the June 23, 2016, Funing Tornado Based on 100-Meter-Scale Numerical Simulation","authors":"Jialin Ying,&nbsp;Xulin Ma,&nbsp;Jie He,&nbsp;Fei Fan,&nbsp;Chuqian Zhang,&nbsp;Bing Chen","doi":"10.1002/met.70163","DOIUrl":"https://doi.org/10.1002/met.70163","url":null,"abstract":"<p>Tornadoes are characterized by short duration and small spatial scales, while conventional observational data exhibits inadequate spatiotemporal resolution for detailed analysis, presenting a significant challenge to mechanistic studies. In this study, the June 23, 2016, EF4 Funing tornado was simulated using the WRF model driven by ERA5 reanalysis data, by employing hectometer-scale grid spacing and optimized numerical schemes. Based on the simulation results, the structural characteristics of the occurrence and development of the tornado were analyzed. The three-dimensional dynamics of the tornado vortex and the intensification of its rotation were further investigated through diagnostic equations. Results show that the Funing tornado occurred under the typical circulation situation of the Meiyu period, and the hook-shaped echoes and other features of the individual tornado were successfully reproduced on the 111 m grid. The cyclonic circulation driven by gust fronts and cold surges played a crucial role, revealing that the main energy for the formation and development of tornadoes originated from the lower troposphere. In addition, during the genesis and evolution of tornadoes, there were two tornado-like vortices (TLV), accompanied by an increase in the vertical acceleration of low-level small-scale airflows and an enhancement of near-surface vortices. The mature TLV exhibited the typical characteristics of sinking in the middle and rising in the periphery. The stretching term of the vorticity equation played a dominant role in the intensity variation of the TLV near the ground, while the tilting term affected the vertical structure formation of the tornado vortex at upper levels. Together, they drove the tornado from its inception to maturity. These results have significant implications for better understanding and analysis of tornadoes.</p>","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"33 2","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://rmets.onlinelibrary.wiley.com/doi/epdf/10.1002/met.70163","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147562330","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Radar Maxima: Calibrated Area-Based Probabilistic Forecasts for Heavy Precipitation","authors":"Reinhold Hess","doi":"10.1002/met.70162","DOIUrl":"https://doi.org/10.1002/met.70162","url":null,"abstract":"<p>We present, motivate and evaluate Radar Maxima, a calibrated area-based probabilistic forecast product for heavy precipitation. It is designed to overcome inherent limitations of point-based forecasts, which often yield low probabilities for extreme events due to spatial displacement errors. The method aggregates radar-derived precipitation within 40 km neighbourhoods to statistically upscale forecasts from DWD's ensemble system ICON-D2-EPS. Evaluation considers both objective verification metrics and feedback from operational weather forecasters based on case studies. Results are compared against both pointwise and spatially aggregated uncalibrated ensemble forecasts in order to disentangle the effects of spatial aggregations and statistical calibration. Spatial aggregation yields improved predictability, reliability and forecast sharpness, while the impact of calibration is mixed. Feedback from forecasters confirms that Radar Maxima provides operational value in specific situations.</p>","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"33 2","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://rmets.onlinelibrary.wiley.com/doi/epdf/10.1002/met.70162","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147562475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Solar and Wind Energy Variability in Tropical South America: Seasonal Ocean-Atmospheric Modulators","authors":"Nicolás Duque-Gardeazabal,&nbsp;Stefan Brönnimann,&nbsp;Andrew R. Friedman,&nbsp;Edgar Dolores-Tesillos,&nbsp;Olivia Martius","doi":"10.1002/met.70165","DOIUrl":"https://doi.org/10.1002/met.70165","url":null,"abstract":"<p>Interannual climate variability strongly influences renewable energy availability, making it a critical factor for achieving UN Sustainable Development Goals (SDGs). However, our knowledge about the potential solar and wind energy production in tropical South America and its relation to ocean-atmospheric modes of variability is limited; modes such as El Niño/Southern Oscillation (ENSO), the Atlantic Meridional Mode (AMM), among others. Therefore, we investigate the influence of these modes on solar and wind energy. We apply partial correlations and composite analyses to reanalysis and satellite data to identify the processes connecting large-scale ocean-atmospheric variability to seasonal anomalies in renewable power generation. Our study identifies three energy hubs as regions with high climatological mean energy availability: The north Caribbean (NC), eastern Brazil (EB) and western Perú/Bolivia (WPB). ENSO influences the sea level pressure (SLP) gradients, generating wind anomalies that directly affect the wind capacity factor (CF). ENSO also affects the solar CF through reduced atmospheric moisture transport and convergence, which results in fewer clouds leading to higher-than-average surface radiation or by atmospheric subsidence. ENSO impacts the NC and EB hubs, with weaker effects in the WPB hub. The AMM is associated with cross-equatorial wind anomalies that modulate wind CF, as well as moisture convergence and cloud cover, thereby influencing solar CF. Wind CF in the NC and EB hubs is inversely modulated by the AMM, weakening winds and reducing radiation over the NC and strengthening winds and increasing radiation on the EB. The Atlantic equatorial El Niño mode (Atl3) exerts minor effects, with anomalies confined to the equatorial Atlantic. Overall, we find limited complementarity between solar and wind energy at interannual time-scale. Our results provide insights for forecasting energy production and managing energy storage for periods of low renewable energy availability.</p>","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"33 2","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://rmets.onlinelibrary.wiley.com/doi/epdf/10.1002/met.70165","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147562114","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Gust Factor of Typhoon in the South China Sea: Based on Data From a Small Island","authors":"Guo-Zhang Wang,&nbsp;Lei Li,&nbsp;Pak-Wai Chan,&nbsp;Qian-Jin Zhou,&nbsp;Li-li Zhang,&nbsp;Chen-xiao Shi","doi":"10.1002/met.70160","DOIUrl":"https://doi.org/10.1002/met.70160","url":null,"abstract":"<p>Current research on gust (<i>GF</i>) and peak (<i>g</i>) factors has mainly focused on landfalling typhoons, whereas studies related to offshore typhoons are relatively rare. They are critical in island architectural design. However, the underlying surfaces of islands have distinct characteristics compared to inland areas. Therefore, conclusions drawn from previous studies on coastal areas are less applicable to islands in open seas. This study explored the characteristics of <i>GF</i> and <i>g</i> in an island region based on tower observation data from an island in the South China Sea. The results indicate that: (1) Island topography can have a substantial influence on low-level winds during typhoons. The probability density function of ocean-side <i>GF</i> was concentrated around the low-value region. <i>GF</i> decreased with increasing height and conformed to generalized extreme value (GEV) distribution; (2) At wind speeds of about 12 m/s, <i>GF</i> was negatively correlated with mean wind speed (<i>U</i>), and the correlation was not significant when wind speeds were too fast or too slow. Under the influence of topography, the <i>GF</i> fluctuations of the wind field increased at each level; (3) When the ocean served as the underlying surface, the classic power-law model better described <i>GF</i> distribution changes with height. The exponent n of the power function model fitted to island-side wind was positive, whereas that fitted to ocean-side wind was negative, with higher wind speeds leading to larger absolute values of the exponent n; (4) The effect of island topography increased the slope <i>k</i> of the linear relationships for G<i>F-</i><span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msub>\u0000 <mi>I</mi>\u0000 <mi>u</mi>\u0000 </msub>\u0000 </mrow>\u0000 <annotation>$$ {I}_u $$</annotation>\u0000 </semantics></math> and <i>g-</i><span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msub>\u0000 <mi>I</mi>\u0000 <mi>u</mi>\u0000 </msub>\u0000 </mrow>\u0000 <annotation>$$ {I}_u $$</annotation>\u0000 </semantics></math><i>.</i></p>","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"33 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://rmets.onlinelibrary.wiley.com/doi/epdf/10.1002/met.70160","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147288238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}