Journal of Atmospheric and Solar-Terrestrial Physics最新文献_第3页

Optimized fuzzy logic algorithm for classifying meteorological and non-meteorological echoes in CINRAD/SA data in Poyang Lake region 鄱阳湖地区CINRAD/SA数据气象与非气象回波分类的优化模糊逻辑算法

IF 1.9 4区地球科学 Q3 GEOCHEMISTRY & GEOPHYSICS

Journal of Atmospheric and Solar-Terrestrial Physics

Pub Date : 2026-01-01 DOI: 10.1016/j.jastp.2025.106708

Landi Zhong , Haibo Zou , Xiaoyou Long , Jiaxin Wang , Yige Huang

This study presents an improved fuzzy logic-based algorithm, originally developed for the U.S. Weather Surveillance Radar-1988 Doppler (WSR-88D) system, to classify meteorological echoes (MS) and non-meteorological echoes (non-MS) in S-band dual-polarization radar data from China New Generation Weather Radar (CINRAD) with S-band of type A (SA). In the improvement process, the "true" MS and non-MS are identified firstly using the combination of a single-polarization radar technique for distinguishing the MS and non-MS from 73,423 radar records and then manual inspection. Subsequently, a statistical analysis of dual-polarization variables and their derived parameters is conducted to obtain the characteristics of the MS and non-MS. Finally, the membership function parameters in the fuzzy logic-based algorithm are refined based on these characteristics. The performance of the improved algorithm is evaluated under four weather scenarios: clear-sky, weak precipitation, heavy precipitation and typhoon. The results demonstrate that the improved algorithm effectively distinguishes between non-MS and MS, with outcomes that align well with real echo data. In practical applications, the improved algorithm markedly reduces residual non-MS contamination while preserving the MS. In order to assess the improved algorithm more comprehensively, 7339 radar samples randomly collected at Nanchang radar station from January to November 2023 are used for the statistical evaluation of the algorithm. Results reveal that the improved algorithm eliminates the majority of the non-MS while maintaining the integrity of MS structures. In contrast, the original algorithm has limited capability in filtering the non-MS, particularly near radar stations and mountainous regions. Overall, the results demonstrate that the improved algorithm substantially enhances data quality control and accuracy in the application of CINRAD/SA radar products.

本文提出了一种改进的基于模糊逻辑的算法，该算法最初是为美国气象监视雷达-1988多普勒（WSR-88D）系统开发的，用于对中国新一代天气雷达（CINRAD） s波段A型（SA）双极化雷达数据中的气象回波（MS）和非气象回波（non-MS）进行分类。在改进过程中，首先结合单偏振雷达技术从73,423条雷达记录中区分质谱和非质谱，然后进行人工检测，确定“真”质谱和非质谱。然后，对双极化变量及其衍生参数进行统计分析，得到质谱和非质谱的特性。最后，根据这些特征对模糊逻辑算法中的隶属函数参数进行细化。在晴空、弱降水、强降水和台风4种天气情景下，对改进算法的性能进行了评价。结果表明，改进后的算法能有效区分非MS和MS，结果与真实回波数据吻合良好。在实际应用中，改进后的算法在保留ms的同时显著降低了残留的非ms污染。为了更全面地评估改进后的算法，采用2023年1 - 11月南昌雷达站随机采集的7339个雷达样本对改进后的算法进行统计评价。结果表明，改进算法在保持质谱结构完整性的同时，消除了大部分非质谱。相比之下，原始算法对非ms的滤波能力有限，特别是在雷达站附近和山区。结果表明，改进后的算法大大提高了CINRAD/SA雷达产品应用中的数据质量控制和精度。

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引用次数: 0

From drought to deluge: Understanding the atmospheric and climatic forces behind the United Arab Emirates' recent flood event 从干旱到洪水：了解阿拉伯联合酋长国最近洪水事件背后的大气和气候力量

IF 1.9 4区地球科学 Q3 GEOCHEMISTRY & GEOPHYSICS

Journal of Atmospheric and Solar-Terrestrial Physics

Pub Date : 2026-01-01 DOI: 10.1016/j.jastp.2025.106712

Farahnaz Fazel-Rastgar , Masoud Rostami , Venkataraman Sivakumar , Bijan Fallah

On April 16, 2024, Dubai and surrounding regions experienced unprecedented rainfall, with some areas receiving up to 2.5 times their average annual rainfall in just 24 h, leading to devastating floods and a tragic loss of life. This study investigates the meteorological mechanisms behind this extreme event using multiple reanalysis datasets. This work identifies the key roles played by a deep cold-core cut-off low (COL) system and an anomalous northward shift of the Intertropical Convergence Zone (ITCZ). The COL, originating from the subtropical jet over Saudi Arabia, combined with an intensified Siberian High, created a strong surface pressure gradient and facilitated the influx of moist tropical air into the region. This interaction drove instability, deep convection, and atmospheric river (AR) activity, resulting in record-breaking precipitation. Observations indicate that the COL was characterized by high potential vorticity (∼7.5 PVU), low temperatures (∼204K) at the tropopause, and enhanced stratosphere-troposphere exchange processes. Aerosol optical depth measurements suggest significant stratospheric aerosol injection, likely amplifying the cooling effect in the lower stratosphere. Due to the high potential for deep convection associated with strong updrafts, the tropospheric air was transported across the tropopause during the folding. This study highlights the coupling of tropical and mid-latitude weather systems, exacerbated by climate change, as a crucial driver of such extreme hydrometeorological events. Improved understanding of these mechanisms is vital for enhancing predictive capabilities and mitigating risks in similar arid regions. This study contributes to identifying the occurrence and dynamics of cold weather in subtropical regions, as opposed to a strong warming trend.

2024年4月16日，迪拜及周边地区经历了前所未有的降雨，一些地区在短短24小时内降雨量达到年平均降雨量的2.5倍，导致毁灭性的洪水和悲惨的生命损失。本研究利用多个再分析数据集调查了这一极端事件背后的气象机制。这项工作确定了深冷核切断低压（COL）系统和热带辐合带（ITCZ）的异常北移在其中发挥的关键作用。源自沙特阿拉伯上空的副热带急流的冷空气，与增强的西伯利亚高压相结合，形成了强大的地面压力梯度，促进了潮湿热带空气流入该地区。这种相互作用驱动了不稳定、深对流和大气河（AR）活动，导致了破纪录的降水。观测结果表明，此次冷空气的特征是高位涡度（~ 7.5 PVU）、对流层顶低温（~ 204K）和平流层-对流层交换过程增强。气溶胶光学深度测量表明，平流层有大量气溶胶注入，可能放大了平流层下层的冷却效应。由于与强上升气流相关的深对流的高潜力，对流层空气在折叠期间被输送穿过对流层顶。这项研究强调了热带和中纬度天气系统的耦合，气候变化加剧了这种耦合，是这种极端水文气象事件的关键驱动因素。改善对这些机制的了解对于提高类似干旱地区的预测能力和减轻风险至关重要。这项研究有助于确定亚热带地区寒冷天气的发生和动态，而不是强烈的变暖趋势。

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引用次数: 0

Physicochemical analysis and source apportionment of PM1.0 and PM2.5 in Harbin 哈尔滨市PM1.0和PM2.5的理化分析及来源解析

IF 1.9 4区地球科学 Q3 GEOCHEMISTRY & GEOPHYSICS

Journal of Atmospheric and Solar-Terrestrial Physics

Pub Date : 2026-01-01 DOI: 10.1016/j.jastp.2025.106711

Likun Huang , Zhouyu Guo , Yan Wang , Guangzhi Wang , Dongdong Wang , Jingyi Zhang , Xinyu Feng

Fine particulate matter (PM_1.0 and PM_2.5) warrants concern due to its health impacts and atmospheric reactivity, yet their source contributions and seasonal variations remain unclear. To investigate their characteristics, sources, and interrelationships, we collected concurrent PM_1.0 and PM_2.5 samples at an urban site in Harbin from November 2014 to November 2015. The samples were analyzed for mass concentrations, water-soluble ions via ion chromatography, inorganic elements using ICP-OES/ICP-MS, particle morphology by scanning electron microscopy (SEM), and source apportionment using the Positive Matrix Factorization (PMF) model. The results showed that PM_1.0 and PM_2.5 exhibited similar seasonal trends, with the highest concentrations in winter and the lowest in summer. PM_1.0 accounted for 60–90 % of PM_2.5, indicating that most pollutants were concentrated in the finer fraction. Major water-soluble ions included SO₄²⁻, NO₃⁻, and NH₄⁺, suggesting significant secondary aerosol formation. Inorganic element analysis revealed elevated concentrations of crustal elements such as Al, Ca, Fe, K, Mg, Na, and Si, pointing to soil dust as a major contributor. SEM observations showed that particles were predominantly irregular mineral grains and spherical fly ash, indicating contributions from both soil dust and coal combustion. PMF source apportionment further revealed distinct seasonal patterns: soil dust and industrial emissions were dominant in spring and summer, while biomass burning, vehicle exhaust, and coal combustion were the primary sources in autumn and winter. This study provides scientific evidence and technical support for targeted fine particulate pollution control and regional air quality management in Harbin and other similar cold-climate cities.

细颗粒物（PM1.0和PM2.5）由于其健康影响和大气反应性值得关注，但其来源贡献和季节变化尚不清楚。为了研究它们的特征、来源和相互关系，我们于2014年11月至2015年11月在哈尔滨的一个城市站点同时采集了PM1.0和PM2.5样本。通过离子色谱分析样品的质量浓度、水溶性离子、ICP-OES/ICP-MS分析样品的无机元素、扫描电子显微镜（SEM）分析样品的颗粒形态，并使用正矩阵分解（PMF）模型分析样品的来源。结果表明：PM1.0和PM2.5具有相似的季节变化趋势，冬季浓度最高，夏季浓度最低；PM1.0占PM2.5的60 - 90%，说明大部分污染物集中在细颗粒物中。主要的水溶性离子包括SO42−、NO3−和NH4+，表明有重要的二次气溶胶形成。无机元素分析显示，地壳元素如Al、Ca、Fe、K、Mg、Na和Si的浓度升高，表明土壤粉尘是主要因素。扫描电镜观察表明，颗粒主要为不规则矿物颗粒和球形粉煤灰，表明土壤粉尘和煤炭燃烧都有贡献。春季和夏季以土壤扬尘和工业排放为主，秋季和冬季以生物质燃烧、机动车尾气和燃煤为主。本研究为哈尔滨市及类似寒冷气候城市细颗粒物污染定向控制和区域空气质量管理提供了科学依据和技术支撑。

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引用次数: 0

Corrigendum to “Three-dimensional lightning channel structure reconstruction: An efficient matching TOA algorithm for VHF pulses” [J. Atmos. Sol. Terr. Phys. 278 (2026) 106702] “三维闪电信道结构重建：一种有效的VHF脉冲匹配TOA算法”[J]。大气压。索尔,恐怖分子。物理学报，278 (2026)106702]

IF 1.9 4区地球科学 Q3 GEOCHEMISTRY & GEOPHYSICS

Journal of Atmospheric and Solar-Terrestrial Physics

Pub Date : 2026-01-01 DOI: 10.1016/j.jastp.2025.106707

Yueyang Wang, Yun Li, Shi Qiu, Shuangjiang Du, Zheng Sun, Lihua Shi

引用次数: 0

Research on rainfall prediction near Qinyang-Yichuan expressway based on deep learning 基于深度学习的秦益高速公路附近降水预测研究

IF 1.9 4区地球科学 Q3 GEOCHEMISTRY & GEOPHYSICS

Journal of Atmospheric and Solar-Terrestrial Physics

Pub Date : 2025-12-31 DOI: 10.1016/j.jastp.2025.106716

Mingfei Zhang , Jiaheng Wang , Xiaogang Wei , Guotao Dou , Xiaorui Wang

In response to the challenges posed by complex terrain and the strong non-stationarity of rainfall—factors that complicate prediction efforts near the Qinyang-Yichuan Expressway and can easily trigger engineering disasters such as tunnel water ingress and slope landslides—this study aims to develop a high-precision rainfall prediction model for disaster prevention in engineering applications. Utilizing historical rainfall data from the region, we propose a hybrid model that integrates Empirical Mode Decomposition (EMD) and the Coyote Optimization Algorithm (COA) with Long Short-Term Memory (LSTM) networks (EMD-COA-LSTM), alongside a Comprehensive Index (CI). A comparative study of 13 deep learning models reveals that traditional models generally underestimate rainfall amounts in complex terrain predictions. The EMD-COA-LSTM model (CI = 5.78) effectively mitigates this bias and demonstrates significantly superior overall performance compared to the worst-performing baseline LSTM model (CI = 209.11). Further analysis shows that the ranking of overall model prediction performance and most evaluation metrics does not fully correspond with the coefficient of determination (R²), indicating that R² alone is insufficient for assessing model performance and should be combined with other metrics. Evaluation based on the CI indicator provides a more accurate reflection of the model's overall effectiveness. The findings of this study offer a more reliable scientific basis for geological disaster risk early warning, tunnel flood-season construction, and engineering safety management along expressway corridors, demonstrating substantial practical engineering value.

针对秦益高速公路沿线地形复杂、降雨非平稳性强等因素使预测工作复杂化、容易引发隧道突水、边坡滑坡等工程灾害的挑战，建立高精度的降雨预测模型，用于工程防灾应用。利用该地区的历史降雨数据，我们提出了一个将经验模态分解（EMD）和Coyote优化算法（COA）与长短期记忆（LSTM）网络（EMD-COA-LSTM）以及综合指数（CI）相结合的混合模型。一项对13种深度学习模型的比较研究表明，传统模型在复杂地形预测中通常低估了降雨量。EMD-COA-LSTM模型（CI = 5.78）有效地减轻了这种偏差，与表现最差的基线LSTM模型（CI = 209.11）相比，显示出显著优于整体性能。进一步分析发现，模型整体预测性能和大部分评价指标的排序与决定系数R2并不完全对应，说明单独使用R2不足以评价模型性能，应与其他指标结合使用。基于CI指标的评估可以更准确地反映模型的整体有效性。研究结果为高速公路沿线地质灾害风险预警、隧道汛期施工和工程安全管理提供了更为可靠的科学依据，具有较强的工程实用价值。

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引用次数: 0

Sequence of space storm effects in ionospheric anomalies and geomagnetic activity 空间风暴对电离层异常和地磁活动的影响序列

IF 1.9 4区地球科学 Q3 GEOCHEMISTRY & GEOPHYSICS

Journal of Atmospheric and Solar-Terrestrial Physics

Pub Date : 2025-12-24 DOI: 10.1016/j.jastp.2025.106710

T.L. Gulyaeva

Ionospheric inhomogeneities have shown asymmetry in the Arctic and Antarctic, but the extent of similar effects from pole to magnetic equator remains less investigated. Here we present a Net Volume index (NT) characterizing the deviation of the total electron content, dTEC, from the quiet reference in 6 bands of magnetic latitude, Φ: two auroral zones exceeding ±60°, two ranges in the middle latitudes between ±40° and ±60°, and two subequatorial zones from ±2.5° to ±37.5°. The NT instantaneous index is derived from the JPL GIM-TEC converted to a geomagnetic coordinate system. The observed dTEC ionospheric anomalies during three severe magnetic storms (May 11, 2024, January 1, 2025, and June 1, 2025) illustrate the diversity of NT storm profiles across six magnetic latitude ranges. The total sample of 97 intense storms was selected according to the criteria of synchronous occurrence of the merged interplanetary electric field Em ≥ 5 mW/m, geomagnetic indices Hpo ≥ 7 i.u., Apo ≥ 132 nT, Dst ≤ −100 nT and the planetary ionospheric index Wp ≥ 5 i.u. from 1995 to 2025. Superimposed epoch analysis was performed with zero epoch time, t₀ = 0, set at Apo peak, main storm phase within 24 h preceding t₀, and recovering phase within 47 h thereafter. The reference quiet TECq was selected from GIM-TEC during 24 h before the main phase, from t₀-48h to t₀-25h. Asymmetry of the ionospheric anomalies of the positive peak dTECp > 0 and the negative peak dTECn < 0 was observed in the Northern and Southern hemispheres in all 6 Φ zones, with the intensity gradually decreasing from pole to magnetic equator. For the first time in the literature, the intensity of the geomagnetic storm, Apo peak, is determined by ionospheric anomalies (range ΔdTEC = dTECmax – dTECmin) and the intensity of the interplanetary electric field Em during the main phase of the storm. The opposite scenario is used to estimate the intensity of the ionospheric storm, dTECp and dTECn, in six magnetic latitudinal zones depending on the peak of Apo and season (day of year) during the recovery phase.

电离层的不均匀性在北极和南极已经显示出不对称，但是从磁极到磁赤道的类似影响的程度仍然很少被研究。在此，我们提出了一个净体积指数（NT），表征了总电子含量（dTEC）在6个磁纬度（Φ）波段与宁静参考的偏差：两个超过±60°的极光区，两个在±40°和±60°之间的中纬度范围，以及两个在±2.5°到±37.5°的赤道以下区域。NT瞬时指数是由JPL的jim - tec转换成地磁坐标系得到的。在2024年5月11日、2025年1月1日和2025年6月1日三次强磁暴期间观测到的dTEC电离层异常说明了6个磁纬范围内NT风暴剖面的多样性。以合并行星际电场Em≥5 mW/m、地磁指数Hpo≥7 i.u、Apo≥132 nT、Dst≤−100 nT、行星电离层指数Wp≥5 i.u为标准，选取了97个强风暴样本。叠加历元分析采用零历元时间，t0 = 0，设于Apo峰值，在t0之前24 h内的主风暴期，在t0之后47 h内的恢复期。参考安静的TECq选择在主相前24 h，从10 -48h到10 -25h的gimm - tec。在所有6个Φ区，南北半球均存在正峰dTECp >； 0和负峰dTECn <； 0的电离层异常不对称性，且强度从极向磁赤道逐渐减弱。地磁风暴的强度，Apo峰值，首次由电离层异常（范围ΔdTEC = dTECmax - dTECmin）和风暴主阶段行星际电场Em强度决定。使用相反的情景来估计电离层风暴的强度，dTECp和dTECn，在六个磁纬带，取决于Apo的峰值和季节（一年中的一天）在恢复阶段。

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引用次数: 0

Urbanization-driven secondary climatic changes: Re-envisioning response of fast growing cities of Northern India 城市化驱动的次生气候变化：对印度北部快速发展城市的再展望

IF 1.9 4区地球科学 Q3 GEOCHEMISTRY & GEOPHYSICS

Journal of Atmospheric and Solar-Terrestrial Physics

Pub Date : 2025-12-18 DOI: 10.1016/j.jastp.2025.106706

Koyel Sur, Sarabjit Singh, Vipan Kumar Verma, Brijendra Pateriya

Urbanization and climatic changes are concomitant to each other. Urbanization induces climate change through enhanced greenhouse gas emissions, industrial processes, and energy consumptions. In developing countries like India, with the increase in population and change in lifestyle, there has been substantial rise in demand and use of energy and fuel, which consequently leads to conversion of agricultural land to built up area. This leads to rise in land surface temperature (LST) and adversely impact the micro-climate of a region in close vicinity of urban entities. The present study aims to analyze the association between built-up, green cover and land surface temperature for selected cities and corresponding districts i.e. Amritsar, Jalandhar, and Ludhiana of Punjab State, India, the main contributors to green revolution. Adopting remote sensing based approach, district-level analysis of the normalized differential built-up index (NDBI), normalized differential vegetation index (NDVI) and land surface temperature (LST) was carried out using Landsat 5 for the years 1990, 1999 and 2009, and Landsat 8 (OLI/TIRS) for 2019. To analyze the relationship between built-up and green cover with LST, correlation analysis was carried out indicating (a) alarming rising trend of built-up is 1.72 % in Amritsar, 2.99 % in Jalandhar and 3.3 % in Ludhiana (b) relatively higher temperature in core and the peri-urban built-up areas generate warmer surface temperatures than the surroundings (c) reduced area under agricultural land and (d) rising stress on water bodies.

城市化与气候变化是相辅相成的。城市化通过增加温室气体排放、工业过程和能源消耗来诱发气候变化。在像印度这样的发展中国家，随着人口的增加和生活方式的改变，对能源和燃料的需求和使用大幅增加，结果导致农业用地转为建成区。这导致地表温度升高，并对城市实体附近区域的小气候产生不利影响。本研究旨在分析选定城市和相应地区（即印度旁遮普邦的阿姆利则、贾兰达尔和卢迪亚纳）的建筑、绿色覆盖和地表温度之间的关系，这些城市和地区是绿色革命的主要贡献者。采用基于遥感的方法，利用1990年、1999年和2009年的Landsat 5和2019年的Landsat 8 （OLI/TIRS）对归一化差异建筑指数（NDBI）、归一化差异植被指数（NDVI）和地表温度（LST）进行地区级分析。为了分析建成区和绿化覆盖与地表温度的关系，进行了相关分析，结果表明：(a)阿姆利则建成区的上升趋势为1.72%，贾兰达尔建成区为2.99%，卢迪亚纳为3.3%;(b)核心区和城郊建成区的地表温度相对较高；(c)农业用地面积减少；(d)水体压力增加。

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引用次数: 0

Assessment of a simple wave-amplitude approximation for tsunami-generated gravity waves at all levels of viscosity in the thermosphere 热层中所有黏度水平上海啸产生的重力波的简单波幅近似的评估

IF 1.9 4区地球科学 Q3 GEOCHEMISTRY & GEOPHYSICS

Journal of Atmospheric and Solar-Terrestrial Physics

Pub Date : 2025-12-18 DOI: 10.1016/j.jastp.2025.106704

Dave Broutman , Harold K. Knight , James W. Rottman , Stephen D. Eckermann

A wave-amplitude approximation adapted from inviscid WKB (Wentzel–Kramers–Brillouin) theory is tested for tsunami-generated gravity waves in the thermosphere up to 500 km altitude. The idea is to use a standard inviscid WKB wave-amplitude term

m^{- 1 / 2}

, where

m (z)

is the vertical wavenumber and

z

is the altitude, but to replace the inviscid

m

with an

m

obtained from a viscous and thermally diffusive dispersion relation. The

m^{- 1 / 2}

approximation is implemented in an anelastic Fourier model for two-dimensional steady-state solutions in the tsunami reference frame. Comparisons are made with a more accurate numerical multilayer model giving solutions to a linearized system of anelastic governing equations. Though there is no perturbation analysis supporting the

m^{- 1 / 2}

approximation for viscous

m

, the approximation compares well with numerical multilayer solutions except for overestimating wave amplitudes in very strong viscosity. The overestimate is due to the neglect by the

m^{- 1 / 2}

approximation of a coupling between upgoing gravity-wave and dissipative modes.

根据无粘性WKB （wentzel - kramer - brillouin）理论，对500千米高度的热层中海啸产生的重力波进行了波幅近似测试。我们的想法是使用标准的无粘性WKB振幅项m−1/2，其中m(z)是垂直波数，z是高度，但用从粘性和热扩散色散关系中获得的m代替无粘性m。m−1/2近似在海啸参考系中二维稳态解的非弹性傅立叶模型中实现。并与较精确的多层数值模型作了比较，给出了线性化非弹性控制方程组的解。虽然没有摄动分析支持m−1/2近似的粘性m，但近似与数值多层解相比，除了在非常强的粘性下高估了波幅值。过高估计是由于忽略了上升重力波和耗散模式之间耦合的m−1/2近似。

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引用次数: 0

Short-term wind speed combination prediction based on decomposition and reconstruction 基于分解与重构的短期风速组合预测

IF 1.9 4区地球科学 Q3 GEOCHEMISTRY & GEOPHYSICS

Journal of Atmospheric and Solar-Terrestrial Physics

Pub Date : 2025-12-16 DOI: 10.1016/j.jastp.2025.106705

Dezhi Hao

Wind speed forecasting is a research hotspot in meteorology, which is of great importance in the fields of energy industry, environment, architecture and so on. For the power system, accurate short-term wind speed foreasting is directly related to the operation efficiency and stability of wind farms. This study designes a short-term wind speed prediction approach based on decomposition and reconstruction. Firstly, considering the non-stationary characteristics of short-term wind speed samples, the complete ensemble empirical mode decomposition with adaptive noise algorithm is used to decompose the samples, and multiple components containing different local feature information are generated, which effectively reduces the complexity of the original samples. Then, the decomposed components are input into the bidirectional long short-term memory model with attention mechanism for prediction. The introduction of attention mechanism can not only capture the long-term dependence on the historical short-term wind speed samples, but also deal with importance-based sampling and improve the prediction ability of the model. The particle swarm optimization algorithm is used to optimize the hyper-parameters of the bidirectional long short-term memory model to further reduce the prediction error. Finally, the forecasted results of these components are added to generate the expected predicted values. Two sets of public short-term wind speed datasets are served as experiment object, and a variety of evaluation indicators are adopted and compared with state-of-the-art models. The results reveal that for different two datasets, the predicted error of the designed prediction approach is smaller, and it has outbalance results than other comparision models, which verifies the foreasting accuracy of the proposed approach.

风速预报是气象学的一个研究热点，在能源工业、环境、建筑等领域具有重要意义。对电力系统而言，准确的短期风速预报直接关系到风电场的运行效率和稳定性。本文设计了一种基于分解和重构的短期风速预测方法。首先，考虑到短期风速样本的非平稳特性，采用自适应噪声算法对样本进行完全集合经验模态分解，生成包含不同局部特征信息的多个分量，有效降低了原始样本的复杂度；然后，将分解后的成分输入到具有注意机制的双向长短期记忆模型中进行预测。引入注意机制，既能捕获对历史短期风速样本的长期依赖，又能处理基于重要度的采样，提高模型的预测能力。采用粒子群优化算法对双向长短期记忆模型的超参数进行优化，进一步减小预测误差。最后，将这些分量的预测结果相加，生成预期预测值。以两组公共短期风速数据集为实验对象，采用多种评价指标，并与最先进的模型进行比较。结果表明，对于不同的两个数据集，所设计的预测方法的预测误差较小，并且其结果优于其他比较模型，验证了所提出方法的预测精度。

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引用次数: 0

Influence of target spectrum selection in wind spectrum fitting on fatigue damage assessment accuracy for wind turbine blades 风谱拟合中目标谱选择对风力机叶片疲劳损伤评估精度的影响

IF 1.9 4区地球科学 Q3 GEOCHEMISTRY & GEOPHYSICS

Journal of Atmospheric and Solar-Terrestrial Physics

Pub Date : 2025-12-10 DOI: 10.1016/j.jastp.2025.106703

Jiantao Liu , Yibing Liu , Chao Zhou , Qingfeng Gao , Haolin Yin

In wind turbine fatigue damage assessment, commonly used wind spectrum models often deviate from actual wind power spectral density (PSD). Directly using these spectra to generate simulated wind fields leads to deviations in fatigue assessment results. Addressing this issue, this study focuses on wind turbine blades to compare damage fatigue accuracy under different fitting target spectra. First, the integral scale parameter-related terms and denominator exponent terms in the Kaimal spectrum were designated as parameters to be fitted, proposing a three-parameter fitting model. Then, the classic periodogram-estimated spectrum of measured wind speed data was calculated, and blade damage values under the wind field generated from this spectrum were regarded as estimated actual damage values. Finally, damage assessment accuracy was compared between least squares fitted spectra using the classic periodogram-estimated spectrum as the target spectrum and those using the Welch-estimated spectrum as the target spectrum, while quantitatively comparing their improvement degrees over the Kaimal spectrum.

在风力机疲劳损伤评估中，常用的风谱模型与实际的功率谱密度（PSD）存在较大偏差。直接使用这些光谱来模拟风场会导致疲劳评估结果的偏差。针对这一问题，本研究以风力发电机叶片为研究对象，比较不同拟合目标谱下的损伤疲劳精度。首先，将Kaimal谱中的积分尺度参数相关项和分母指数项指定为拟合参数，提出三参数拟合模型；然后，计算实测风速数据的经典周期图估计谱，并将该谱生成的叶片在风场作用下的损伤值作为估计的实际损伤值。最后，比较了以经典周期图估计谱为目标谱的最小二乘拟合谱与以welch估计谱为目标谱的最小二乘拟合谱的损伤评估精度，并定量比较了两者相对于Kaimal谱的改进程度。

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