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Variability of Summer Apparent Temperature in China 中国夏季视温的变率
IF 2.8 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2025-09-30 DOI: 10.1002/joc.70129
Xiaohan Liu, Juan Feng, Feng Shi, Shuang Wang, Su Yang

The apparent temperature (APT) has significant impacts on human health; however, its variability across China, in particular, based on in situ observations, remains unclear. Based on daily meteorological station observation datasets, this study analysed the variability and spatial distribution of summer APT in China during 1960–2019, which is a compound variable combining surface air temperature (SAT), relative humidity, and wind speed. The contribution of SAT, relative humidity, and wind speed to the variation of APT is examined. It is shown that the variation of SAT plays a determining role in the variation of APT, whereas it displays strong regional differences from the impacts of relative humidity and wind speed. The leading mode of APT displays a mono-sign pattern throughout China, explaining 31.6% of the variance, which is significantly related to the Pacific Decadal Oscillation (PDO) and the Atlantic Multidecadal Oscillation (AMO). The combination of the negative phase of PDO and the positive phase of AMO is associated with higher APT in China, whereas the negative AMO and positive PDO phases tend to accompany with lower APT. Results show that the combination of the opposite phases of AMO and PDO is associated with anomalous teleconnections and surface conditions. Anomalous cyclonic circulation is observed over China during the PDO–AMO+ phase, and abnormal thermal low pressure exists in the lower troposphere. Meanwhile, the soil moisture and cloud cover decreased, allowing more solar radiation to reach the ground. This causes an increase in SAT and water vapour convergence, resulting in an increase in the humidity and leading to an increase in APT. An opposite situation is found in the associated circulation pattern and surface conditions during the PDO + AMO-phase, contributing to decreased APT. The above results provide scientific insights into the long-term variability of summer APT in China, highlighting the modulation of natural variability in impacting the variation of summer APT over China.

视温(APT)对人体健康有重大影响;然而,基于现场观测,其在中国各地的变化仍不清楚。基于逐日气象站观测资料,分析了1960-2019年中国夏季气温(SAT)、相对湿度和风速的复合变量)的变率和空间分布特征。研究了SAT、相对湿度和风速对APT变化的贡献。结果表明,SAT的变化对APT的变化起决定性作用,而相对湿度和风速的影响则表现出较强的区域差异。APT的领先模态在全国范围内呈现单号模式,解释了31.6%的方差,与太平洋年代际涛动(PDO)和大西洋多年代际涛动(AMO)显著相关。在中国,PDO负相和AMO正相的组合与较高的APT相关,而AMO负相和PDO正相的组合往往伴随着较低的APT。结果表明,AMO和PDO相反相的组合与异常远连和表面条件有关。在PDO-AMO +阶段,中国上空存在异常的气旋环流,对流层下层存在异常的热低压。与此同时,土壤水分和云量减少,使更多的太阳辐射到达地面。这导致SAT和水汽辐合增加,导致湿度增加,导致APT增加。PDO + amo阶段的相关环流型和地面条件则相反,导致APT减少。上述结果为中国夏季APT的长期变率提供了科学的认识,突出了自然变率对中国夏季APT变化的调节作用。
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引用次数: 0
The Enhancing ‘Heat Dome’ Effect Is Reinforcing the Sustained Surface Summer O3 Pollution in North China “热穹”效应的增强强化了华北夏季地表O3污染的持续
IF 2.8 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2025-09-30 DOI: 10.1002/joc.70132
Hui Gao, Ting Ding, Tiejun Xie, Linhai Sun, Wenjing Li

The air pollution transmission channel in North China, also termed the ‘2 + 26’ cities, has the most severe pollution problem in China. Based on the meteorological and environmental observation data from 2014 to 2022, the spatial–temporal features of the air quality index (AQI) in the ‘2 + 26’ cities are first compared to reveal the different changes in winter and summer. Since the issue of the Air Pollution Prevention and Control Action Plan in China in 2013, the winter AQI averaged at the ‘2 + 26’ cities shows a significant decreasing trend of −9.725 μg m−3 per year from 2014 to 2022, but it shows much slight variation in summer. In summer, the ozone (O3) pollutant is the major contributor to the AQI. Results indicate that higher Tmax and lower relative humidity (RH) are conducive to higher O3 concentration and more severe air pollution. The averaged Tmax at these cities has a significant increasing trend of 0.28°C per decade, while RH decreases also significantly at a rate of −1.08% per decade. This may be the main reason why the summer O3 concentration maintains stability at a high level in the recent 9 years. Results also indicate that the ‘heat dome’ effect, characterised by a persistent high pressure and warming air subsidence from the upper to lower troposphere, is reinforcing in recent years, and this is favourable for the occurrence of long-lasting dry-type high temperatures and the enhancement of O3 pollution. Projections from 19 CMIP6 models show that the high pressure system will remarkably strengthen in the near, middle, and long terms under the moderate emission scenario (SSP2-4.5). Therefore, the ‘heat dome’ effect will exacerbate the ozone pollution in the future.

中国北方的空气污染传输通道,也被称为“2 + 26”城市,污染问题在中国最严重。基于2014 - 2022年的气象环境观测资料,首先对比了“2 + 26”城市空气质量指数(AQI)的时空特征,揭示了冬季和夏季的不同变化。自2013年《中国大气污染防治行动计划》发布以来,2014 - 2022年“2 + 26”城市冬季平均AQI呈显著下降趋势,为- 9.725 μ m - 3 /年,但夏季变化不大。在夏季,臭氧(O3)污染物是AQI的主要贡献者。结果表明,较高的Tmax和较低的相对湿度有利于O3浓度的升高和空气污染的加剧。这些城市的平均Tmax以0.28°C / a的速率显著增加,而RH也以- 1.08% / a的速率显著降低。这可能是近9年来夏季O3浓度稳定在较高水平的主要原因。研究结果还表明,近年来,以持续高压和从对流层上层到下层的暖空气沉降为特征的“热穹”效应正在加强,这有利于长期干燥型高温的发生和O3污染的加剧。19个CMIP6模式的预估表明,在中等排放情景(SSP2-4.5)下,近、中期和长期高压系统将显著加强。因此,“热穹”效应将在未来加剧臭氧污染。
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引用次数: 0
Projected Temperature and Precipitation Changes in Central Asia From High-Resolution WRF Simulation Under 2 SSP Scenarios 2种SSP情景下高分辨率WRF模拟预估中亚温度和降水变化
IF 2.8 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2025-09-29 DOI: 10.1002/joc.70096
Jiewei Zhou, Jianbin Huang, Yao Yao, Wen Shi, Huihui Yuan, Chen Qiao, Yong Luo

The Central Asian region, characterised by its arid climate and fragile ecological environment, is highly sensitive to climate change, necessitating focused research on its future climate. This study utilises one global climate model (MPI-ESM1.2-HR) simulation from the sixth Coupled Model Intercomparison Project (CMIP6) to drive the regional climate model WRF for high-resolution (25 km) simulations within the Coordinated Regional Downscaling Experiment (CORDEX) program. These simulations target future climate changes under both low and high emission scenarios, SSP1-2.6 and SSP5-8.5. The historical simulation (1995–2014) was evaluated, indicating that the WRF model can reproduce better spatial and temporal patterns of temperature and precipitation in Central Asia compared to the global model, with reduced mean biases and more detailed topography insights, especially in mountainous regions. Future climate projections (2021–2060) indicate a significant temperature increase across Central Asia, correlating with rising greenhouse gas concentrations. Under SSP1-2.6, the average annual temperature rise for the mid-term future (2041–2060) is projected at 1.47°C, and under SSP5-8.5, it could reach 1.99°C. Winter warming is most rapid, especially in the central regions (approximately 43°N–47°N), while the southeastern high-altitude areas experience the biggest warming in summer. The spatial distribution of seasonal warming is very consistent with the reduction of surface albedo. The study also predicts an overall increase in average annual precipitation, with the most significant rise in the southwestern region and a decrease in the northeast. Both SSP1-2.6 and SSP5-8.5 scenarios project a precipitation increase, which is more pronounced in the mid-term than the near-term future (2021–2040). Precipitation is expected to rise in winter across Central Asia, while in summer it shows a varied pattern of increase in the west and decrease in the east, which is probably contributed to the changes of moisture flux.

中亚地区气候干旱,生态环境脆弱,对气候变化高度敏感,需要重点研究其未来气候。本研究利用来自第六期耦合模式比对项目(CMIP6)的一个全球气候模式(MPI-ESM1.2-HR)模拟,驱动区域气候模式WRF在协调区域降尺度实验(CORDEX)项目中进行高分辨率(25公里)模拟。这些模拟的目标是低排放情景和高排放情景(SSP1-2.6和SSP5-8.5)下的未来气候变化。对1995-2014年的历史模拟结果进行了评估,结果表明,与全球模式相比,WRF模式可以更好地再现中亚地区的温度和降水时空格局,并且具有更小的平均偏差和更详细的地形信息,特别是在山区。未来气候预测(2021-2060年)表明,中亚地区气温将显著升高,这与温室气体浓度上升有关。在SSP1-2.6下,中期(2041-2060)年平均升温预估为1.47°C,在SSP5-8.5下,年平均升温可达1.99°C。冬季增温最为迅速,特别是在中部地区(约43°N - 47°N),而东南部高海拔地区夏季增温最大。季节增温的空间分布与地表反照率的降低非常一致。该研究还预测,年平均降水量将总体增加,西南地区增幅最大,东北地区减少。SSP1-2.6和SSP5-8.5情景均预估降水增加,且中期比近期(2021-2040)更为明显。预计中亚地区冬季降水将增加,而夏季降水将呈现西增东减的变化格局,这可能与水汽通量的变化有关。
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引用次数: 0
Comparative Analysis of Machine Learning Methods for Imputing Missing Daily Rainfall Data in Complex Himalayan Terrain 喜马拉雅复杂地形缺失日降水数据的机器学习方法对比分析
IF 2.8 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2025-09-28 DOI: 10.1002/joc.70122
Rahul Sharma, S. Sreekesh

Rainfall data plays a pivotal role in modelling complex and nonlinear hydro-meteorological systems. In this process, the availability and fidelity of rainfall data at different spatial and temporal scales are of utmost importance. Gaps in the rainfall data are inevitable, resulting from human errors and instrumental/sensor malfunctions. The sparse availability of station data in the complex terrains of the Himalayas compounds the problem. The imputation of these gaps requires robust methods with higher accuracy and precision to capture the observed rainfall skewness in frequency and magnitude. This study has considered gap-filling of missing data at different elevations under three agro-climatic zones in Himachal Pradesh, India. For that, seven machine learning methods were used to estimate the missing daily rainfall data, including multiple linear regression (MLR), support vector regression with radial basis function kernel (SVR-RBF), K-nearest neighbours (KNN), random forest (RF), multilayer perceptron (MLP), extreme gradient boosting (XGBoost) and Lasso regression. For a comprehensive evaluation of the estimations, the analysis was structured into two tiers: overall (the entire time series) and RIC (rainfall-intensity-classes) assessments, ensuring a more robust comparison of the imputation methods. The methods were evaluated using the coefficient of determination (R2), correlation coefficient (r), root mean square error (RMSE) and mean absolute error (MAE). The results showed that, in both overall and RIC analyses, MLP consistently demonstrated higher accuracy and lower estimation errors, making it the most suitable method for imputing missing daily rainfall data across different elevation zones in the complex Himalayan terrain considered in this study.

降雨数据在复杂和非线性水文气象系统建模中起着关键作用。在此过程中,不同时空尺度的降雨数据的可用性和保真度至关重要。由于人为错误和仪器/传感器故障,降雨数据的差距是不可避免的。喜马拉雅山地形复杂,观测站数据稀少,这使问题更加复杂。这些差距的估算需要具有更高精度和精度的稳健方法来捕获观测到的降雨在频率和幅度上的偏度。本研究考虑了印度喜马偕尔邦三个农业气候带下不同海拔缺失数据的缺口填补。为此,采用多元线性回归(MLR)、径向基函数核支持向量回归(SVR-RBF)、k近邻回归(KNN)、随机森林(RF)、多层感知器(MLP)、极端梯度增强(XGBoost)和Lasso回归等7种机器学习方法对缺失的日降雨量数据进行估计。为了对估计进行全面评估,分析分为两层:总体(整个时间序列)和RIC(降雨强度等级)评估,确保对估算方法进行更可靠的比较。采用决定系数(R2)、相关系数(r)、均方根误差(RMSE)和平均绝对误差(MAE)对方法进行评价。结果表明,在整体分析和RIC分析中,MLP始终表现出更高的精度和更低的估计误差,使其成为本研究中考虑的喜马拉雅复杂地形中不同高程区域缺失日降雨量数据的最合适方法。
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引用次数: 0
Construction and Application of Intensity-Duration-Area-Frequency Curves at Seasonal and Annual Precipitation in Yangtze River Basin 长江流域季、年降水强度-持续时间-面积-频率曲线的构建与应用
IF 2.8 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2025-09-28 DOI: 10.1002/joc.70117
Ping Yao, Peng Yang, Jun Xia, Heqing Huang, Caiyuan Wang, Lu Chen, Kaiya Sun, Yanchao Zhu, Xixi Lu

Extreme precipitation aggregated in time and space will lead to the superposition and amplification of disaster risks, causing significant impacts on social economy and ecological environment. Incorporating the area factor into the extreme precipitation risk assessment framework using intensity-duration-area-frequency (IDAF) curves can effectively evaluate the superposition and amplification effects of extreme precipitation events. Therefore, this study utilised high spatiotemporal resolution precipitation data (i.e., 0.1° × 0.1° and 3 h) from the Yangtze River basin (YRB) in the period of 1979 to 2020 to establish seasonal and annual IDAF curves at multiple spatiotemporal scales (i.e., 3–96 h and 144–961 km2) for the first time in the YRB. The extreme precipitation intensity at different spatiotemporal scales and return periods was estimated, and the patterns of its variation with spatiotemporal scales were also investigated. The results indicated that: (1) The goodness-of-fit of the Extended Generalised Pareto Distribution –IDAF (EGPD-IDAF) model exhibited significant seasonality and scale dependency, with the best fitting effect in summer and at the mesoscale (i.e., 24 h and 144 km2); (2) At the 3–6 h scale, extreme precipitation return levels in the YRB exhibited higher sensitivity to variations in area, showing greater fluctuations, whereas as the temporal scale increased, the impact of area variation gradually weakened; (3) The maximum return levels of extreme precipitation in the eastern sub-basins of the YRB occurred at the spatiotemporal scale of 3 h and 144 km2, representing local short-duration heavy precipitation, while those in the inland sub-basins occurred at the large scale of 961 km2 with a temporal scale of 24 or 48 h. This study elucidates the area effect of extreme precipitation events in the YRB and establishes the relationship between extreme precipitation return levels and duration and area, offering significant value for regional climate services and disaster risk management.

极端降水在时间和空间上的聚集会导致灾害风险的叠加和放大,对社会经济和生态环境造成重大影响。利用强度-持续时间-面积-频率(IDAF)曲线将面积因子纳入极端降水风险评价框架,可以有效评价极端降水事件的叠加效应和放大效应。因此,本研究首次利用长江流域1979 ~ 2020年的高时空分辨率降水资料(即0.1°× 0.1°和3 h),在长江流域建立了3 ~ 96 h和144 ~ 961 km2的多时空尺度的季节和年IDAF曲线。估算了不同时空尺度和回归期的极端降水强度,并研究了其随时空尺度的变化规律。结果表明:(1)扩展广义Pareto分布-IDAF (EGPD-IDAF)模型的拟合优度表现出显著的季节性和尺度依赖性,其中夏季和中尺度(即24 h和144 km2)拟合效果最好;(2)在3 ~ 6 h尺度上,长江三角洲极端降水回归水平对面积变化的敏感性较高,波动幅度较大,但随着时间尺度的增加,面积变化的影响逐渐减弱;(3)长江三角洲东部子流域极端降水最大回归水平为3 h和144 km2,代表局地短持续强降水,内陆子流域极端降水最大回归水平为961 km2,时间尺度为24或48 h。本研究阐明了长江三角洲极端降水事件的区域效应,建立了极端降水回归水平与持续时间和面积的关系,对区域气候服务和灾害风险管理具有重要价值。
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引用次数: 0
Intercomparison of Daily Maximum and Minimum Temperature Gridded Products Over Mainland Spain 西班牙大陆日最高和最低气温格网产品的对比
IF 2.8 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2025-09-27 DOI: 10.1002/joc.70111
Sixto Herrera, Fidel González Rouco, Roberto Serrano-Notivoli, Juan Luís Garrido, Santiago Beguería, José M. Gutiérrez, Pere Quintana-Seguí, Maialen Iturbide, Esteban Rodríguez, Ana Morata, Candelas Peral

The sensitivity to the observational reference has been reported in recent studies, highlighting the importance of observational uncertainty in climate research. These studies stress the importance of properly comparing available datasets, recognising their respective strengths and limitations. Here, we conduct a comprehensive analysis of the various datasets of maximum and minimum daily temperatures available for mainland Spain. We examined 10 publicly available daily gridded datasets of maximum and minimum temperatures, analysing multiple evaluation dimensions to identify the key strengths and limitations of each dataset: statistical distribution, extreme events, temporal structure and spells and spatial patterns. We conclude that observational uncertainty is greater for minimum temperatures than for maximum temperatures. This uncertainty is not strictly linked to the type of dataset (interpolation, analysis or reanalysis) or its spatial domain (national, European or global) but rather to specific datasets which vary depending on the analysis dimension. Overall, the most stable dataset across all evaluated indices is STEAD, whereas the PTI-Clima v0 dataset exhibits some underestimation of extremes and spells but performs well in capturing central parameters and temporal correlations.

最近的研究报告了对观测参考的敏感性,强调了观测不确定性在气候研究中的重要性。这些研究强调了适当比较现有数据集的重要性,认识到它们各自的优势和局限性。在这里,我们对西班牙大陆的各种最高和最低日气温数据集进行了全面的分析。我们研究了10个公开可用的最高和最低温度的每日网格数据集,分析了多个评估维度,以确定每个数据集的主要优势和局限性:统计分布、极端事件、时间结构和时间和空间模式。我们的结论是,最低温度的观测不确定性大于最高温度。这种不确定性与数据集类型(插值、分析或再分析)或其空间域(国家、欧洲或全球)没有严格联系,而是与具体的数据集有关,这些数据集因分析维度而异。总体而言,在所有评估的指数中,最稳定的数据集是STEAD,而PTI-Clima v0数据集显示出对极端值和周期的一些低估,但在捕获中心参数和时间相关性方面表现良好。
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引用次数: 0
The Extreme Spring Drought Over Northern China in 2022: Characteristics and Possible Mechanisms 2022年中国北方春季极端干旱:特征及可能机制
IF 2.8 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2025-09-25 DOI: 10.1002/joc.70126
Haotong Jing, Jianqi Sun, Shui Yu

In spring of 2022, northern China experienced much warmer temperatures and a severe precipitation deficit, which led to an extreme drought over the region. Our analysis indicates that this extreme spring drought is associated with the extreme La Niña event and unprecedented warming sea surface temperature (SST) anomalies in the mid-latitude North Pacific and North Atlantic. On the interannual time scale, the La Niña could lead to an anomalous cyclone over the western North Pacific and strengthen the southern part of the East Asian trough. The resultant downward motion and water vapour divergence anomalies dominate northern China, which cause an increase in air temperature and potential evapotranspiration (PET) and a decrease in precipitation, consequently intensifying the spring drought over northern China. In contrast, the warm SST anomalies over the mid-latitude North Pacific and North Atlantic influence the northern China spring drought on the interdecadal time scale. Both the warm SST anomalies over the two oceans are related to a Rossby wave train that causes an anomalous anticyclone over the upstream of northern China. As a result, there are anomalous downward motions over northern China, favouring the increase in regional air temperature and PET. Accordingly, the warm SST anomalies over the mid-latitude North Pacific and North Atlantic could aggravate the spring drought over northern China. Leave-one-out validation analysis indicates that the aforementioned SST anomalies are potential predictors for the spring drought over northern China.

2022年春季,中国北方气温升高,降水严重不足,导致该地区极端干旱。分析表明,此次春季极端干旱与La Niña极端事件以及北太平洋和北大西洋中纬度地区前所未有的海温增温异常有关。在年际时间尺度上,La Niña可能导致北太平洋西部出现一个异常气旋,并加强东亚槽南部。由此产生的向下运动和水汽辐散异常在华北地区占主导地位,导致气温和潜在蒸散(PET)升高,降水减少,从而加剧了华北地区的春季干旱。中纬度北太平洋和北大西洋海温异常在年代际时间尺度上影响中国北方春旱。两洋的温暖海温异常都与引起中国北方上游异常反气旋的罗斯比波列有关。因此,华北上空存在异常的下行运动,有利于区域气温和PET的升高。因此,北太平洋和北大西洋中纬度海温异常可能加剧中国北方的春季干旱。留一验证分析表明,上述海温异常是中国北方春季干旱的潜在预测因子。
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引用次数: 0
Weakened Relationship Between Spring Asian-Pacific Oscillation and Summer Precipitation in the Eastern Part of the Arid Region of Northwest China Since 2000 2000年以来中国西北干旱区东部春季亚太涛动与夏季降水的减弱关系
IF 2.8 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2025-09-25 DOI: 10.1002/joc.70130
Yinuo Miao, Yong Zhao, Yong Li, Lixia Meng

Based on observational monthly precipitation data at 21 stations in the eastern part of the arid region of Northwest China (ARNWC), the NCEP/NCAR reanalysis atmospheric circulation data, and ERA5-land reanalysis surface soil moisture and sensible heat flux data during 1961–2022, we examine the interdecadal change in the relationship between spring Asia-Pacific Oscillation (APO) and summer precipitation in the eastern part of the ARNWC. Results show the relationship between spring APO and summer precipitation in the eastern part of the ARNWC has weakened significantly since 2000. The southward (northward) shift of the subtropical westerly jet over East Asia and anomalous anticyclone (cyclone) over the Mongolia Plateau play an important role in modulating the dynamical and water vapour conditions responsible for the summer precipitation in the eastern part of the ARNWC during 1961–1999 and 2000–2022. The soil moisture can “memorise” the anomalous signal of APO from spring to summer and feedback to the atmosphere via influencing the summer surface sensible heat in the Tibetan Plateau during 1961–1999. Therefore, the spring APO-related atmospheric circulation can contribute to favourable dynamical and water vapour conditions responsible for the summer precipitation in the eastern part of the ARNWC. However, the land-atmosphere interaction in the Tibetan Plateau cannot retain the signal of spring APO and release it in summer during 2000–2022. Therefore, the APO loses its close relationship with summer precipitation in the eastern part of the ARNWC in this period.

基于1961—2022年西北干旱区东部21个站点逐月降水观测资料、NCEP/NCAR再分析大气环流资料和ERA5-land再分析表层土壤水分和感热通量资料,研究了春季亚太涛动(APO)与西北干旱区东部夏季降水关系的年代际变化。结果表明,自2000年以来,ARNWC东部春季APO与夏季降水的关系明显减弱。东亚副热带西风急流的南(北)移和蒙古高原上的异常反气旋(气旋)对1961-1999年和2000-2022年ARNWC东部夏季降水的动力和水汽条件起着重要的调节作用。因此,与春季apo相关的大气环流可以为ARNWC东部夏季降水提供有利的动力和水汽条件。因此,在此期间,APO与ARNWC东部夏季降水失去了密切的关系。
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引用次数: 0
Storm Frequency and Intensity in the Faroe Islands Between 1940 and 2024: A Method for Establishing a Storm Record Based on the ERA5 Reanalysis Data 1940 - 2024年法罗群岛风暴频率和强度:基于ERA5再分析资料建立风暴记录的方法
IF 2.8 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2025-09-24 DOI: 10.1002/joc.70125
Rico Kongsager, Daniel Krieger, Bárður A. Niclasen, Frauke Feser, Andreas Nyholm, Sebastian Mernild

This comprehensive study establishes a detailed storm record for the Faroe Islands from 1940 to 2024 using ERA5 and NORA3 reanalysis data, as well as in situ observations. Over these 85 years, the Faroe Islands experienced 396 storms, averaging 4.8 yearly. The data revealed that storm events occur most years, with notable periods of heightened activity. The majority of storms were classified as stormy weather (20.8–24.4 m/s), with fewer (1.4 yearly) but significant occurrences of severe storms (≥ 24.5 m/s), with a higher number of severe storms in specific areas. Predominant wind directions from the southwest and west highlight the influence of Atlantic weather systems, with storms mainly occurring in the winter months. Comparing wind observations from Tórshavn with ERA5 data calibrated with the high-resolution NORA3 reanalysis highlighted the accuracy and limitations of ERA5 in capturing storm events. While the calibrated ERA5 data provided reliable estimates of average wind speeds, it tended to smooth out fluctuations, underrepresenting the variability and intensity of extreme wind conditions. Applying a gust factor, derived from detailed observations, adjusted ERA5 wind speeds to reflect true conditions better. The study also demonstrated the utility of geostrophic wind speed records derived from pressure measurements to construct a long-term storm activity index. A trend analysis reveals almost no discernible long-term trend in frequency and intensity, indicating minimal change over time. Overall, this study emphasises the need for continued monitoring and refinement in storm identification and classification methods to improve the accuracy of storm event representations, crucial for the mitigation of severe storm impacts in the region.

这项综合研究利用ERA5和NORA3再分析数据以及现场观测,建立了1940年至2024年法罗群岛的详细风暴记录。在这85年里,法罗群岛经历了396次风暴,平均每年4.8次。数据显示,风暴事件在大多数年份都会发生,有明显的活动加剧期。大多数风暴被归类为暴风雨天气(20.8-24.4 m/s),较少(每年1.4次)但显著发生强风暴(≥24.5 m/s),特定地区的强风暴次数较多。来自西南和西部的主要风向突出了大西洋天气系统的影响,风暴主要发生在冬季。将Tórshavn的风观测数据与用高分辨率NORA3再分析校准的ERA5数据进行比较,突出了ERA5在捕获风暴事件方面的准确性和局限性。虽然经校准的ERA5数据提供了对平均风速的可靠估计,但它倾向于消除波动,未能充分反映极端风条件的可变性和强度。应用来自详细观测的阵风因子,调整ERA5风速以更好地反映真实情况。该研究还证明了由气压测量得出的地转风速记录在构建长期风暴活动指数方面的效用。趋势分析显示,在频率和强度方面几乎没有明显的长期趋势,表明随时间的变化很小。总体而言,本研究强调需要继续监测和改进风暴识别和分类方法,以提高风暴事件表征的准确性,这对于减轻该地区严重风暴影响至关重要。
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引用次数: 0
Evaluation and Visualisation of Unusual Weather in a Compound Framework - a Methodology Based on Hungarian Station Data 复合框架下异常天气的评估和可视化——基于匈牙利站数据的方法
IF 2.8 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2025-09-24 DOI: 10.1002/joc.70091
Márk Zoltán Mikes, Zsuzsanna Dezső, Roland Hollós, Rita Pongrácz

In this paper, we introduce a set of definitions together with a data visualisation platform, which can be used to evaluate past weather conditions and to visualise unusual periods in a simplified, easy-to-understand manner. To achieve this, four main objectives are set: (1) the definitions of unusual phenomena must be based on relative thresholds and take into account seasonality; (2) the reference climatology must be relevant spatially; (3) the results should not be bound to specific calendar years or months; (4) unusual phenomena should be visualised simultaneously (hence provide a compound framework). The expression ‘unusual’ is used in this study to describe anomalous values in contrast to the more commonly used ‘extreme’, because we aim to highlight periods with non-absolute weather extremes. As input, daily meteorological data available at 70 stations across Hungary from 2002 to 2024 are used to create the methodology, where a total of 9 unusual weather phenomena are defined using temperature, precipitation and wind gust as basic variables. The main motivation behind this study is to analyse compound climatic events, which are spatially and/or temporally connected. Additionally, the methodology serves as the meteorological basis for a science communication platform that combines complex information with simplicity. The approach described in this paper can serve as inspiration for further studies aiming to evaluate weather extremes in the past.

在本文中,我们引入了一组定义以及一个数据可视化平台,该平台可用于评估过去的天气状况,并以简化,易于理解的方式可视化异常时期。为实现这一目标,设定了四个主要目标:(1)异常现象的定义必须基于相对阈值并考虑季节性;(2)参考气候学必须具有空间相关性;(三)结果不受特定历年或月份的约束;(4)不寻常的现象应同时可视化(从而提供一个复合框架)。在本研究中,“不寻常”一词用于描述异常值,而不是更常用的“极端”,因为我们的目标是突出非绝对极端天气的时期。作为输入,匈牙利从2002年到2024年的70个站点的每日气象数据被用于创建方法,其中共有9种不寻常的天气现象被定义为使用温度,降水和阵风作为基本变量。这项研究背后的主要动机是分析复合气候事件,这些事件在空间和/或时间上是相互联系的。此外,该方法还可以作为科学传播平台的气象基础,将复杂信息与简单信息结合起来。本文所描述的方法可以为旨在评估过去极端天气的进一步研究提供灵感。
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引用次数: 0
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International Journal of Climatology
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