Atmospheric and Oceanic Science Letters最新文献

An effective deep-learning prediction of Arctic sea-ice concentration based on the U-Net model 基于U-Net模型的北极海冰浓度深度学习预测

IF 3.2 4区地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES

Atmospheric and Oceanic Science Letters

Pub Date : 2025-07-17 DOI: 10.1016/j.aosl.2025.100691

Yifan Xie , Ke Fan , Hongqing Yang , Yi Fan , Shengping He

Current shipping, tourism, and resource development requirements call for more accurate predictions of the Arctic sea-ice concentration (SIC). However, due to the complex physical processes involved, predicting the spatiotemporal distribution of Arctic SIC is more challenging than predicting its total extent. In this study, spatiotemporal prediction models for monthly Arctic SIC at 1- to 3-month leads are developed based on U-Net—an effective convolutional deep-learning approach. Based on explicit Arctic sea-ice–atmosphere interactions, 11 variables associated with Arctic sea-ice variations are selected as predictors, including observed Arctic SIC, atmospheric, oceanic, and heat flux variables at 1- to 3-month leads. The prediction skills for the monthly Arctic SIC of the test set (from January 2018 to December 2022) are evaluated by examining the mean absolute error (MAE) and binary accuracy (BA). Results showed that the U-Net model had lower MAE and higher BA for Arctic SIC compared to two dynamic climate prediction systems (CFSv2 and NorCPM). By analyzing the relative importance of each predictor, the prediction accuracy relies more on the SIC at the 1-month lead, but on the surface net solar radiation flux at 2- to 3-month leads. However, dynamic models show limited prediction skills for surface net solar radiation flux and other physical processes, especially in autumn. Therefore, the U-Net model can be used to capture the connections among these key physical processes associated with Arctic sea ice and thus offers a significant advantage in predicting Arctic SIC.

摘要

准确地预测北极海冰密集度 (SIC) 对北极航运, 旅游和资源开发等十分重要. 由于北极海冰的复杂多变, 预测北极SIC的时空分布比预测海冰范围更具有挑战性. 基于一个有效的卷积类机器学习模型—U-Net, 本文研制了可用于预测未来1至3个月北极SIC的模型. 基于北极海–冰–气物理过程, 本文选取了前期11个与北极海冰变化密切相联的变量作为预测因子, 包括北极SIC, 大气, 海洋和热通量等变量. 较CFSv2和NorCPM而言, 本文研制的U-Net模型具有更高的预测技巧. 此外, 诊断各预测因子的相对重要性显示, 提前1个月的预测模型更依赖于前期的SIC, 但提前2和3个月的预测模型则更依赖于前期的地表净短波辐射通量. 然而, 动力模式对地表净短波辐射和其相关物理过程的预测技能有限, 这可能是U-Net模型预测技巧较动力模式更高的原因之一. 本研究既有利于提升对北极SIC空间分布的预测能力, 也有助于进一步认识动力模式对海冰预测效能有限的原因.

当前的航运、旅游和资源开发需求要求对北极海冰浓度（SIC）进行更准确的预测。然而，由于涉及复杂的物理过程，预测北极SIC的时空分布比预测其总范围更具挑战性。在本研究中，基于u - net（一种有效的卷积深度学习方法）开发了1至3个月的北极月SIC时空预测模型。基于明确的北极海冰-大气相互作用，选择了与北极海冰变化相关的11个变量作为预测因子，包括1- 3个月前观测到的北极SIC、大气、海洋和热通量变量。通过检查平均绝对误差（MAE）和二进制精度（BA），评估了测试集（2018年1月至2022年12月）每月北极SIC的预测能力。结果表明，与CFSv2和NorCPM两种动态气候预测系统相比，U-Net模式对北极SIC的MAE较低，BA较高。通过对各预测因子的相对重要性分析，预测精度主要依赖于1个月前的SIC，而主要依赖于2 ~ 3个月前的地表净太阳辐射通量。然而，动态模式对地表净太阳辐射通量和其他物理过程的预测能力有限，特别是在秋季。因此，U-Net模式可用于捕捉与北极海冰相关的这些关键物理过程之间的联系，从而在预测北极SIC方面具有显著优势。（原文如此），（原文如此）【中文译文】基于一个有效的卷积类机器学习模型-U-Net,本文研制了可用于预测未来1至3个月北极SIC的模型。基于北极海-冰-气物理过程,本文选取了前期11个与北极海冰变化密切相联的变量作为预测因子,包括北极原文如此,大气,海洋和热通量等变量。较CFSv2和NorCPM而言,本文研制的U-Net模型具有更高的预测技巧。此外,诊断各预测因子的相对重要性显示,提前1个月的预测模型更依赖于前期的原文如此,但提前2和3个月的预测模型则更依赖于前期的地表净短波辐射通量。然而,动力模式对地表净短波辐射和其相关物理过程的预测技能有限,这可能是U-Net模型预测技巧较动力模式更高的原因之一。本研究既有利于提升对北极SIC空间分布的预测能力,也有助于进一步认识动力模式对海冰预测效能有限的原因。

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引用次数: 0

Forecast errors of tropical cyclone track and intensity by the China Meteorological Administration from 2013 to 2022 2013 - 2022年中国气象局热带气旋路径和强度预报误差

IF 3.2 4区地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES

Atmospheric and Oceanic Science Letters

Pub Date : 2025-07-04 DOI: 10.1016/j.aosl.2025.100675

Huanmujin Yuan , Hong Wang , Yubin Li , Kevin K.W. Cheung , Zhiqiu Gao

This study presents a comprehensive evaluation of tropical cyclone (TC) forecast performance in the western North Pacific from 2013 to 2022, based on operational forecasts issued by the China Meteorological Administration. The analysis reveals systematic improvements in both track and intensity forecasts over the decade, with distinct error characteristics observed across various forecast parameters. Track forecast errors have steadily decreased, particularly for longer lead times, while error magnitudes have increased with longer forecast lead times. Intensity forecasts show similar progressive enhancements, with maximum sustained wind speed errors decreasing by 0.26 m/s per year for 120 h forecasts. The study also identifies several key patterns in forecast performance: typhoon-grade or stronger TCs exhibit smaller track errors than week or weaker systems; intensity forecasts systematically overestimate weaker TCs while underestimating stronger systems; and spatial error distributions show greater track inaccuracies near landmasses and regional intensity biases. These findings highlight both the significant advances in TC forecasting capability achieved through improved modeling and observational systems, and the remaining challenges in predicting TC changes and landfall behavior, providing valuable benchmarks for future forecast system development.

摘要

本文系统评估了中国气象局在2013至2022年间对西北太平洋热带气旋的预报能力. 结果表明: 过去十年间路径和强度预报均取得显著进步, 其中120小时强度预报误差年均降低0.26 m/s. 研究发现三个关键特征: (1) 台风级以上强热带气旋的路径预报误差小于弱气旋; (2) 强度预报存在系统性偏差, 对弱气旋预报偏强而对强气旋预报偏弱; (3) 近海区域路径预报误差较大. 这些结果反映出近年来对热带气旋预报能力的进步, 也指出了未来预报系统发展的关键方向.

本文基于中国气象局发布的业务预报，对2013 - 2022年北太平洋西部热带气旋预报效果进行了综合评价。分析表明，在过去十年中，路径和强度预报都有系统的改进，在各种预报参数中观察到明显的误差特征。跟踪预测误差稳步下降，特别是较长的提前期，而误差幅度随着预测提前期的延长而增加。强度预报也显示出类似的逐步增强，在120 h预报中，最大持续风速误差每年减少0.26 m/s。该研究还确定了预报性能的几个关键模式：台风级或更强的tc比周级或更弱的系统显示出更小的路径误差；强度预测系统地高估了较弱的tc，而低估了较强的系统；空间误差分布表明，在大陆和区域强度偏差附近，航迹误差更大。这些发现突出了通过改进的建模和观测系统在预测TC变化和登陆行为方面取得的重大进展，以及预测TC变化和登陆行为方面仍然存在的挑战，为未来预测系统的发展提供了有价值的基准。结果表明:过去十年间路径和强度预报均取得显著进步,其中120小时强度预报误差年均降低0.26 m / s。研究发现三个关键特征: (1) 台风级以上强热带气旋的路径预报误差小于弱气旋; (2) 强度预报存在系统性偏差, 对弱气旋预报偏强而对强气旋预报偏弱; (3) 近海区域路径预报误差较大. 这些结果反映出近年来对热带气旋预报能力的进步, 也指出了未来预报系统发展的关键方向.

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引用次数: 0

The extreme windstorm of April 2025 in northern and central-eastern China: Historical ranking and synoptic origins 中国北部和中东部2025年4月极端风暴：历史排序和天气成因

IF 3.2 4区地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES

Atmospheric and Oceanic Science Letters

Pub Date : 2025-06-30 DOI: 10.1016/j.aosl.2025.100672

Shenming Fu , Tingting Huang , Bo Wang , Xiao Li , Nan Zhang , Zhongcan Chen , Jingxue Wang , You Dong , Jianhua Sun

In mid-April 2025, northern and central-eastern China experienced a catastrophic compound disaster marked by Beaufort 8 or greater wind gusts affecting ∼3.5 × 10⁶ km², exposing ∼610 million residents to extreme conditions, with Typhoon-equivalent Beaufort 12 gusts battering Beijing’s Yanshan Mountains and Beaufort 14–15 winds devastating Inner Mongolia. This unprecedented event surpassed historical extremes at 64 weather stations, impacting 996 monitoring sites with winds exceeding the 99th percentile, including 478 stations recording historic top-three maxima. Concurrently, sandstorms engulfed ∼4.3 × 10⁶ km², reaching 18°N, while Hulunbuir faced a 1.5-m snowpack—a 30-year April record. Cascading infrastructure failures resulted in 1884 uprooted trees, approximately ¥16.6 million in urban damages (in Beijing), and the collapse of utility-scale photovoltaic systems across northern China and the Huang-Huai region, exacerbating the multi-faceted crisis. A brief analysis indicates the event was primarily driven by a vertically coupled cyclone system featuring a cold vortex at the middle and upper troposphere dynamically aligned with a lower-level cyclone/mesoscale vortex. The intense, deeply coupled cyclone system sustained the wind intensification primarily through its enhanced pressure gradient force and subsidence-induced downward transport of kinetic energy (KE) behind the cyclone’s core. Clarifying the controlling synoptic-scale weather systems and dominant physical mechanisms governing such extreme wind generation is critical for refining predictive models of these high-impact events while advancing the understanding of dynamic interactions within extreme wind regimes.

摘要

2025年4月中旬, 中国北部和中东部地区遭遇由8级以上阵风引发的复合型灾害, 影响范围约3.5 × 10⁶平方公里, 波及约6.1亿人口. 北京燕山山脉出现12级 (台风级) 阵风, 内蒙古局部地区风力达14–15级. 此次事件在64个气象站突破历史极值, 996个监测站点风速超过第99百分位 (478个站点创观测史前三极值) . 伴随沙尘暴影响范围达4.3 × 10⁶平方公里, 南扩至18°N; 呼伦贝尔出现1.5米积雪, 为30年来4月最深纪录. 灾害导致1884株树木倒伏, 北京城市设施损失约1660万元, 并造成华北, 黄淮地区光伏系统大面积损毁. 研究表明, 该事件由垂直耦合气旋系统驱动, 中高层冷涡与低层气旋/中尺度涡旋动力耦合, 通过增强气压梯度及下沉动能传输维持强风. 阐明此类极端风的天气系统及物理机制, 对改进预测模型及深化风场动力学认知具有重要意义.

2025年4月中旬，中国北部和中东部经历了一场灾难性的复合灾害，其特征是波弗特8或更大的阵风影响了~ 3.5 × 106平方公里，使~ 6.1亿居民暴露在极端条件下，相当于台风的波弗特12阵风袭击了北京燕山，波弗特14-15阵风袭击了内蒙古。这一史无前例的事件超过了64个气象站的历史极端值，影响了996个监测点，风速超过了第99百分位数，其中478个监测点记录了历史前三名的最大值。与此同时，沙尘暴席卷了约4.3 × 106 km2，达到18°N，呼伦贝尔面临1.5米的积雪，这是30年来4月的记录。接连不断的基础设施故障导致1884棵树被连根拔起，（在北京）城市损失约1660万元人民币，中国北方和黄淮地区公用事业规模的光伏系统崩溃，加剧了多方面的危机。简要分析表明，这次事件主要是由一个垂直耦合的气旋系统驱动的，其特征是对流层中高层的冷涡与低层气旋/中尺度涡动态对齐。强烈的、深度耦合的气旋系统主要通过其增强的压力梯度力和下沉引起的气旋核心后方动能（KE）的向下输送来维持风的增强。澄清控制天气尺度天气系统和控制这种极端风力产生的主要物理机制，对于完善这些高影响事件的预测模型，同时推进对极端风力系统内动态相互作用的理解至关重要。摘要2025年4月中旬,中国北部和中东部地区遭遇由8级以上阵风引发的复合型灾害,影响范围约3.5×10⁶平方公里,波及约6.1亿人口。北京燕山山脉出现12级 (台风级) 阵风, 内蒙古局部地区风力达14–15级. 此次事件在64个气象站突破历史极值, 996个监测站点风速超过第99百分位 (478个站点创观测史前三极值) . 3 × 10⁶；30个月，4个月，1个月，1个月。灾害导致1884株树木倒伏, 北京城市设施损失约1660万元, 并造成华北, 黄淮地区光伏系统大面积损毁. 研究表明, 该事件由垂直耦合气旋系统驱动, 中高层冷涡与低层气旋/中尺度涡旋动力耦合, 通过增强气压梯度及下沉动能传输维持强风. 阐明此类极端风的天气系统及物理机制, 对改进预测模型及深化风场动力学认知具有重要意义.

{"title":"The extreme windstorm of April 2025 in northern and central-eastern China: Historical ranking and synoptic origins","authors":"Shenming Fu , Tingting Huang , Bo Wang , Xiao Li , Nan Zhang , Zhongcan Chen , Jingxue Wang , You Dong , Jianhua Sun","doi":"10.1016/j.aosl.2025.100672","DOIUrl":"10.1016/j.aosl.2025.100672","url":null,"abstract":"<div><div>In mid-April 2025, northern and central-eastern China experienced a catastrophic compound disaster marked by Beaufort 8 or greater wind gusts affecting ∼3.5 × 10<sup>6</sup> km<sup>2</sup>, exposing ∼610 million residents to extreme conditions, with Typhoon-equivalent Beaufort 12 gusts battering Beijing’s Yanshan Mountains and Beaufort 14–15 winds devastating Inner Mongolia. This unprecedented event surpassed historical extremes at 64 weather stations, impacting 996 monitoring sites with winds exceeding the 99th percentile, including 478 stations recording historic top-three maxima. Concurrently, sandstorms engulfed ∼4.3 × 10<sup>6</sup> km<sup>2</sup>, reaching 18°N, while Hulunbuir faced a 1.5-m snowpack—a 30-year April record. Cascading infrastructure failures resulted in 1884 uprooted trees, approximately ¥16.6 million in urban damages (in Beijing), and the collapse of utility-scale photovoltaic systems across northern China and the Huang-Huai region, exacerbating the multi-faceted crisis. A brief analysis indicates the event was primarily driven by a vertically coupled cyclone system featuring a cold vortex at the middle and upper troposphere dynamically aligned with a lower-level cyclone/mesoscale vortex. The intense, deeply coupled cyclone system sustained the wind intensification primarily through its enhanced pressure gradient force and subsidence-induced downward transport of kinetic energy (KE) behind the cyclone’s core. Clarifying the controlling synoptic-scale weather systems and dominant physical mechanisms governing such extreme wind generation is critical for refining predictive models of these high-impact events while advancing the understanding of dynamic interactions within extreme wind regimes.</div><div>摘要</div><div>2025年4月中旬, 中国北部和中东部地区遭遇由8级以上阵风引发的复合型灾害, 影响范围约3.5 × 10⁶平方公里, 波及约6.1亿人口. 北京燕山山脉出现12级 (台风级) 阵风, 内蒙古局部地区风力达14–15级. 此次事件在64个气象站突破历史极值, 996个监测站点风速超过第99百分位 (478个站点创观测史前三极值) . 伴随沙尘暴影响范围达4.3 × 10⁶平方公里, 南扩至18°N; 呼伦贝尔出现1.5米积雪, 为30年来4月最深纪录. 灾害导致1884株树木倒伏, 北京城市设施损失约1660万元, 并造成华北, 黄淮地区光伏系统大面积损毁. 研究表明, 该事件由垂直耦合气旋系统驱动, 中高层冷涡与低层气旋/中尺度涡旋动力耦合, 通过增强气压梯度及下沉动能传输维持强风. 阐明此类极端风的天气系统及物理机制, 对改进预测模型及深化风场动力学认知具有重要意义.</div></div>","PeriodicalId":47210,"journal":{"name":"Atmospheric and Oceanic Science Letters","volume":"18 6","pages":"Article 100672"},"PeriodicalIF":3.2,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144903232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Synoptic background conditions and moisture transport for producing the extreme heavy rainfall event in Valencia in 2024 产生2024年瓦伦西亚极端强降雨事件的天气背景条件和水汽输送

IF 3.2 4区地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES

Atmospheric and Oceanic Science Letters

Pub Date : 2025-06-18 DOI: 10.1016/j.aosl.2025.100666

Tingting Huang , Shenming Fu , Xiao Li , You Dong , Yuanchun Zhang , Jianhua Sun

From 26 October to 2 November 2024, Spain experienced a record-breaking rainfall event, with the most intense episode appearing in Valencia Province. During the event, Turis station recorded a historic 24-hour precipitation of 710.8 mm, exceeding the national annual average. This resulting flood led to widespread disruption and significant societal impacts. Synoptic analyses reveal that the event was dominated by a deep cut-off low extending through the entire troposphere and persisting for approximately 186 h. Background conditions were characterized by upper-level divergence, mid-tropospheric warm advection, and a strong southeasterly low-level jet, which promoted vertical motion and sustained moisture transport. The steep, funnel-shaped terrain along the eastern Iberian coast further triggered and enhanced the local convection. A 10-day backward Lagrangian moisture tracing using the HYSPLIT model identified the Mediterranean Sea as the primary moisture source (78.1 %), followed by northwestern Africa (8.5 %) and central-eastern Europe/the Black Sea (6.2 %). Low-level moisture transport was mainly driven by the cut-off low and a persistent Mediterranean high, while mid- to upper-level trajectories were associated with a preceding low-pressure system over the Mediterranean and the subtropical Atlantic high. These systems acted in sequence to relay moisture toward the Valencia region, and under the influence of the strongly rotating and convergent cut-off low—along with terrain-induced lifting—this moisture was rapidly uplifted, ultimately triggering the extreme rainfall event.

摘要

2024年10月26日至11月2日, 西班牙瓦伦西亚省遭遇罕见极端降雨, Turis站24小时降水量达710.8毫米, 引发严重洪涝灾害. 此次事件由持续186小时的深厚切断低压主导, 在高层辐散, 中层暖平流与低空东南急流共同作用下形成强垂直运动, 东海岸漏斗地形进一步增强对流. HYSPLIT后向追踪显示, 水汽主要来自地中海 (贡献率78.1 %), 其次为非洲西北部 (8.5 %) 和欧洲中东部/黑海 (6.2 %). 水汽由多个天气系统接力输送至瓦伦西亚, 最终在切断低压旋转辐合和地形抬升作用下, 引发此次破纪录降雨事件.

从2024年10月26日至11月2日，西班牙经历了一次破纪录的降雨事件，其中最强烈的一次出现在瓦伦西亚省。在这次活动中，Turis站记录了历史性的24小时降水量710.8毫米，超过了全国年平均水平。由此产生的洪水造成了广泛的破坏和重大的社会影响。天气学分析表明，此次事件以一个贯穿整个对流层的深切断低压为主，持续时间约186 h。背景条件以高层辐散、对流层中暖流和强烈的东南低空急流为特征，促进了垂直运动和持续的水汽输送。东部伊比利亚海岸陡峭的漏斗状地形进一步触发和增强了局部对流。利用HYSPLIT模式进行的10天后向拉格朗日水汽追踪发现，地中海是主要的水汽来源（78.1%），其次是非洲西北部（8.5%）和中欧/东欧/黑海（6.2%）。低空水汽输送主要受切断低压和持续的地中海高压驱动，而中高层水汽输送则与地中海上空的低压系统和副热带大西洋高压有关。这些系统依次将水汽传递到瓦伦西亚地区，并在强烈旋转和辐合的切断低气压的影响下，以及地形引起的抬升作用下，水汽迅速上升，最终引发了极端降雨事件。摘要2024年10月26日至11月2日,西班牙瓦伦西亚省遭遇罕见极端降雨,Turis站24小时降水量达710.8毫米,引发严重洪涝灾害。此次事件由持续186小时的深厚切断低压主导, 在高层辐散, 中层暖平流与低空东南急流共同作用下形成强垂直运动, 东海岸漏斗地形进一步增强对流. HYSPLIT后向追踪显示,水汽主要来自地中海(贡献率78.1%),其次为非洲西北部(8.5%)和欧洲中东部/黑海(6.2%)。水汽由多个天气系统接力输送至瓦伦西亚, 最终在切断低压旋转辐合和地形抬升作用下, 引发此次破纪录降雨事件.

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引用次数: 0

State of the climate over the Three Gorges Region of the Yangtze River basin in 2024 长江流域三峡地区2024年气候状况

IF 2.3 4区地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES

Atmospheric and Oceanic Science Letters

Pub Date : 2025-06-17 DOI: 10.1016/j.aosl.2025.100664

Hongling Zeng, Xianyan Chen, Yundi Jiang, Xukai Zou, Tong Cui, Qiang Zhang, Linhai Sun

The Three Gorges Region (TGR) of the Yangtze River basin exhibited warm and dry climatic characteristics in 2024. The annual mean temperature in the TGR was 18.6 °C, which was 1.2 °C above normal and marked the highest level since 1961. All four seasons were warmer than normal, with spring and autumn both recording their highest temperatures since 1961. Additionally, the TGR recorded 57.2 high-temperature days in 2024, reaching a historic high since 1961 and exceeding the previous record set in 2022 by 2.4 days. Annual rainfall was 11.2 % below normal, with spring, summer, and autumn all being drier than normal. However, the number of heavy rain days was slightly higher than normal. The annual mean wind speed in the TGR ranked as the second-highest since 1961, only slightly lower than in 2022. The annual mean relative humidity was below normal and the number of fog days across large areas of the TGR decreased compared to 2023. In 2024, the TGR experienced extreme high-temperature events characterized by exceptional intensity and prolonged duration, accompanied by generally severe meteorological drought conditions. During the year, the TGR also experienced frequent and intense cooling events, an early onset of heavy rainfall (including severe convective weather), and exceptionally extreme rainstorm events.

摘要

2024年长江三峡地区的气候呈暖干特征, 年平均气温创下新的纪录, 达到18.6 °C, 较常年偏高1.2 °C. 四季气温均偏高, 其中春秋季平均气温均为1961年以来历史同期最高. 高温日数为57.2天, 也为1961年以来最多. 年降水量较常年偏少11.2 %, 春, 夏, 秋三季降水均偏少, 但暴雨日数较常年略偏多. 年平均风速为1961年以来第二大, 仅略低于2022年. 年平均相对湿度偏小, 大部地区雾日数较2023年有所减少. 2024年, 三峡地区经历极端高温事件, 高温强度强, 持续时间长, 气象干旱总体偏重; 强降温频次多, 强度强; 强降水 (强对流) 天气过程偏早, 暴雨极端性强.

长江流域三峡地区2024年气候呈现温暖干燥特征。三峡库区年平均气温18.6℃，比正常值高1.2℃，是1961年以来的最高水平。四个季节都比正常温度高，春季和秋季都创下了1961年以来的最高气温。此外，2024年TGR的高温天数为57.2天，创1961年以来的历史新高，比之前的记录（2022年）多2.4天。年降雨量比正常低11.2%，春、夏、秋均较正常偏干。然而，暴雨日数略高于正常水平。三峡库区年平均风速为1961年以来第二高，仅略低于2022年。年平均相对湿度低于正常值，三峡库区大面积雾日数较2023年有所减少。2024年，三峡库区发生了强度异常、持续时间长、气象干旱普遍严重的极端高温事件。年内，三峡水库还经历了频繁而强烈的降温事件，强降雨（包括强对流天气）提前发生，以及异常极端的暴雨事件。摘要2024年长江三峡地区的气候呈暖干特征,年平均气温创下新的纪录,达到18.6°C,较常年偏高1.2°C。四季气温均偏高, 其中春秋季平均气温均为1961年以来历史同期最高. 1 . 1961年1月1日年降水量较常年偏少11.2%,春,夏,秋三季降水均偏少,但暴雨日数较常年略偏多。年平均风速为1961年以来第二大, 仅略低于2022年. 年平均相对湿度偏小, 大部地区雾日数较2023年有所减少. 2024年, 三峡地区经历极端高温事件, 高温强度强, 持续时间长, 气象干旱总体偏重; 强降温频次多, 强度强; 强降水 (强对流) 天气过程偏早, 暴雨极端性强.

{"title":"State of the climate over the Three Gorges Region of the Yangtze River basin in 2024","authors":"Hongling Zeng, Xianyan Chen, Yundi Jiang, Xukai Zou, Tong Cui, Qiang Zhang, Linhai Sun","doi":"10.1016/j.aosl.2025.100664","DOIUrl":"10.1016/j.aosl.2025.100664","url":null,"abstract":"<div><div>The Three Gorges Region (TGR) of the Yangtze River basin exhibited warm and dry climatic characteristics in 2024. The annual mean temperature in the TGR was 18.6 °C, which was 1.2 °C above normal and marked the highest level since 1961. All four seasons were warmer than normal, with spring and autumn both recording their highest temperatures since 1961. Additionally, the TGR recorded 57.2 high-temperature days in 2024, reaching a historic high since 1961 and exceeding the previous record set in 2022 by 2.4 days. Annual rainfall was 11.2 % below normal, with spring, summer, and autumn all being drier than normal. However, the number of heavy rain days was slightly higher than normal. The annual mean wind speed in the TGR ranked as the second-highest since 1961, only slightly lower than in 2022. The annual mean relative humidity was below normal and the number of fog days across large areas of the TGR decreased compared to 2023. In 2024, the TGR experienced extreme high-temperature events characterized by exceptional intensity and prolonged duration, accompanied by generally severe meteorological drought conditions. During the year, the TGR also experienced frequent and intense cooling events, an early onset of heavy rainfall (including severe convective weather), and exceptionally extreme rainstorm events.</div><div>摘要</div><div>2024年长江三峡地区的气候呈暖干特征, 年平均气温创下新的纪录, 达到18.6 °C, 较常年偏高1.2 °C. 四季气温均偏高, 其中春秋季平均气温均为1961年以来历史同期最高. 高温日数为57.2天, 也为1961年以来最多. 年降水量较常年偏少11.2 %, 春, 夏, 秋三季降水均偏少, 但暴雨日数较常年略偏多. 年平均风速为1961年以来第二大, 仅略低于2022年. 年平均相对湿度偏小, 大部地区雾日数较2023年有所减少. 2024年, 三峡地区经历极端高温事件, 高温强度强, 持续时间长, 气象干旱总体偏重; 强降温频次多, 强度强; 强降水 (强对流) 天气过程偏早, 暴雨极端性强.</div></div>","PeriodicalId":47210,"journal":{"name":"Atmospheric and Oceanic Science Letters","volume":"18 5","pages":"Article 100664"},"PeriodicalIF":2.3,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144696952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

State of China’s climate in 2024 2024年中国气候状况

IF 2.3 4区地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES

Atmospheric and Oceanic Science Letters

Pub Date : 2025-06-09 DOI: 10.1016/j.aosl.2025.100661

Yundi Jiang, Lin Zhao, Xiucang Li, Xianyan Chen, Xukai Zou, Yiran Wang, Hongling Zeng, Tong Cui, Hailing Zhong

The year 2024 witnessed remarkable climatic anomalies across China, characterized by pronounced warm and wet conditions. The annual mean temperature soared to a record high since 1951, with seasonal temperatures in spring, summer, and autumn all exceeding historical extremes. Meanwhile, the annual precipitation ranked as the fourth highest on record, with all four seasons experiencing above-average rainfall. Notably, the Yangtze River Basin and Jiangnan region encountered their most intense precipitation event since 1961. Extreme weather events were particularly striking: An unusually early and severe heatwave swept through central and eastern China, becoming the second most intense high-temperature event in recorded history. Autumn typhoon activity also displayed exceptional intensity, with Typhoon Yagi triggering significant impacts in Hainan, Guangdong, and Guangxi. Although drought conditions were generally mild overall, notable seasonal and regional disparities emerged, especially in the winter–spring droughts affecting southwestern China. Conversely, cold outbreaks occurred more frequently than usual, and convective weather events exhibited heightened activity. Moreover, dust storm activity remained relatively limited.

摘要

2024年中国气候异常特征显著, 呈现突出的暖湿气候态势. 全国平均气温创1951年以来历史新高, 春, 夏, 秋三季气温均为历史最高; 年降水量位列历史第四高位, 四季降水均偏多, 其中长江流域和江南地区降水量更创1961年以来最强纪录, 极端天气事件尤为突出: 中东部地区遭遇历史罕见的早发强高温天气, 高温强度居历史第二; 秋季台风活动异常活跃, 台风"摩羯"给海南, 广东, 广西带来显著影响. 尽管全年干旱总体偏轻, 但季节性和区域性差异明显, 西南地区冬春连旱尤为显著. 与此同时, 冷空气过程较常年偏多, 强对流天气呈现高发态势, 而沙尘天气则相对偏少.

2024年中国气候异常明显，气候偏暖偏湿。年平均气温创1951年以来新高，春、夏、秋三季气温均超过历史极端值。与此同时，年降水量为有记录以来第四高，四季降水量均高于平均水平。值得注意的是，长江流域和江南地区遭遇了1961年以来最强烈的降水事件。极端天气事件尤其引人注目：中国中东部地区出现了一场异乎寻常的早期严重热浪，成为有记录以来第二强烈的高温事件。秋季台风活动也异常强烈，其中台风八木在海南、广东、广西等地造成较大影响。旱情总体温和，但存在明显的季节和区域差异，尤其是西南地区的冬春干旱。相反，寒冷的爆发比平时更频繁，对流天气事件表现出更高的活动性。此外，沙尘暴活动仍然相对有限。摘要2024年中国气候异常特征显著, 呈现突出的暖湿气候态势. 全国平均气温创1951年以来历史新高, 春, 夏, 秋三季气温均为历史最高; 年降水量位列历史第四高位, 四季降水均偏多, 其中长江流域和江南地区降水量更创1961年以来最强纪录, 极端天气事件尤为突出: 中东部地区遭遇历史罕见的早发强高温天气, 高温强度居历史第二; 秋季台风活动异常活跃, 台风"摩羯"给海南, 广东, 广西带来显著影响. 尽管全年干旱总体偏轻, 但季节性和区域性差异明显, 西南地区冬春连旱尤为显著. 与此同时, 冷空气过程较常年偏多, 强对流天气呈现高发态势, 而沙尘天气则相对偏少.

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引用次数: 0

Mechanisms of ENSO’s cross-seasonal modulation of winter–spring atmospheric river activity over East Asia ENSO对东亚地区冬春季大气河流活动的跨季节调节机制

IF 3.2 4区地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES

Atmospheric and Oceanic Science Letters

Pub Date : 2025-06-06 DOI: 10.1016/j.aosl.2025.100659

Yuliang Zhou, Wentao Jia, Weimin Zhang, Huizan Wang

In this study, based on MERRA-2 reanalysis data and a multi-algorithm integrated atmospheric river (AR) identification method, the authors reveal the cross-seasonal regulation mechanism of El Niño–Southern Oscillation (ENSO) on winter–spring AR activities in East Asia. The results show that ENSO asymmetrically modulates AR activity through teleconnection and hysteresis effects, and has significant enhancement/inhibition effects on ARs in different regions. At the onset of El Niño, enhanced southwesterly flow at the western edge of the western Pacific subtropical high (WPSH) leads to enhanced AR activity in the western Pacific, and anomalous southerly winds in the Indian Ocean promote northward transport of water vapor in the Arabian Sea and Bay of Bengal. With a three-month lag, the weakening and eastward retreat of the WPSH weakens the low-latitude AR activity, but persistent southerly winds in the Bay of Bengal maintain the AR activity over Southwest China. The mid- to high-latitude AR response exhibits delayed dynamics, initially dominated by the synergistic effect of the southward deviation of the upper-air rapids and the low-level convergence (double-rapid-flow effect) and later modulated by the Pacific–North American teleconnection (PNA)-triggered East Asian ridge, which enhances the precipitation efficiency through prolonged frontal activity and enhanced cold–warm airmass convergence. Overall, El Niño promotes the development of low- and midlatitude AR activity in East Asia, while La Niña promotes (maritime continental) AR activity in the tropics. This study establishes the “ENSO teleconnection → circulation adjustment → East Asian AR response” chain, revealing a cross-seasonal lagged response mechanisms of East Asian AR activity, and provides a theoretical basis for winter and spring climate prediction and extreme precipitation forecasting.

摘要

本研究基于MERRA-2再分析数据及多算法融合的AR识别方法, 揭示ENSO通过遥相关效应对东亚冬春季大气河活动的跨季节调控机制. 厄尔尼诺初期, 西太平洋副高西侧增强的西南风激发西太平洋AR活动, 同时印度洋偏南风异常促进阿拉伯海-孟加拉湾水汽北输; 滞后3个月后, WPSH东退削弱低纬AR, 但孟加拉湾持续南风维持西南地区AR活动. 中高纬AR响应初期受高空急流南偏与低层辐合 (双急流效应) 协同作用, 后期由PNA遥相关触发的东亚脊调制, 通过延长锋面活动及增强冷暖空气辐合提升降水效率. 总体而言, 厄尔尼诺促进东亚中低纬AR发展, 拉尼娜则增强热带海洋性大陆AR活动. "ENSO遥相关-环流调整-东亚AR响应"机制链为冬春季气候预测及极端降水预报提供理论基础.

本文基于MERRA-2再分析数据和多算法综合大气河（AR）识别方法，揭示了El Niño-Southern涛动（ENSO）对东亚冬春AR活动的跨季节调节机制。结果表明，ENSO通过远连接和滞后效应不对称调节AR活性，并在不同区域对AR具有显著的增强/抑制作用。在El Niño开始时，西太平洋副热带高压（WPSH）西部边缘的西南气流增强导致西太平洋AR活动增强，印度洋的异常南风促进了阿拉伯海和孟加拉湾的水汽向北输送。在3个月的滞后时间内，副高的减弱和东退减弱了低纬AR活动，但孟加拉湾持续的南风维持了西南地区的AR活动。中高纬度AR响应表现出延迟动力学特征，最初受高空急流南下偏和低层辐合（双快流效应）的协同作用主导，后受太平洋-北美远连（PNA）触发的东亚高压脊调节，通过延长锋面活动和增强冷暖气团辐合增强降水效率。总体而言，El Niño促进东亚低纬度和中纬度AR活动的发展，而La Niña促进热带（海洋大陆）AR活动。本研究建立了“ENSO遥相关→环流调整→东亚AR响应”链，揭示了东亚AR活动的跨季节滞后响应机制，为冬春季气候预报和极端降水预报提供了理论依据。摘要本研究基于MERRA-2再分析数据及多算法融合的AR识别方法,揭示ENSO通过遥相关效应对东亚冬春季大气河活动的跨季节调控机制。厄尔尼诺初期,西太平洋副高西侧增强的西南风激发西太平洋基于“增大化现实”技术的活动,同时印度洋偏南风异常促进阿拉伯海——孟加拉湾水汽北输;“”“”“”“”“”“”“”中高纬AR响应初期受高空急流南偏与低层辐合(双急流效应)协同作用,后期由机构遥相关触发的东亚脊调制,通过延长锋面活动及增强冷暖空气辐合提升降水效率。【中文翻译】：中文翻译：“enso。”

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引用次数: 0

Different effects of eastern and central Pacific El Niño events on the surface shortwave radiation over southern China in winter 东太平洋和中太平洋El Niño事件对冬季华南地面短波辐射的不同影响

IF 3.2 4区地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES

Atmospheric and Oceanic Science Letters

Pub Date : 2025-05-26 DOI: 10.1016/j.aosl.2025.100655

Ming Cheng , Ziniu Xiao , Xinyi Lai , Jingjing Xu , Siyu Lu , Baorong Zhou , Weisi Deng

This study investigates the distinct impacts of eastern Pacific (EP) and central Pacific (CP) El Niño events on winter shortwave solar radiation (SSR) in southern China, revealing different spatial distributions and underlying mechanisms. The results show that, during the developing winter of EP El Niño, significant SSR reductions occur in southwestern China and the east coast of southern China due to a strong, zonally extended Northwest Pacific anticyclone that transports moisture from the tropical Northwest Pacific and North Indian Ocean, while the northeast of southern China experiences a weak increase in SSR. In contrast, during the developing winter of CP El Niño, SSR decreases in the east of southern China with a significant decrease in the lower basin of the Yangtze River but an increase in the west of southern China with a remarkable increase in eastern Yunnan. The pronounced east–west dipole pattern in SSR anomalies is driven by a meridionally elongated Northwest Pacific anticyclone, which enhances northward moisture transport to the east of southern China while leaving western areas drier. Further research reveals that distinct moisture anomalies during the developing winter of EP and CP events result in divergent SSR distributions across southern China, primarily through modulating the total cloud cover. These findings highlight the critical need to differentiate between El Niño types when predicting medium and long-term variability of radiation in southern China.

摘要

东部型 (EP) 和中部型 (CP) 厄尔尼诺发展年冬季中国南方地区地表太阳短波辐射 (SSR) 的空间分布特征存在明显差异. 在EP厄尔尼诺发展年冬季, 受西北太平洋反气旋异常西伸的影响, 来自热带西北太平洋和北印度洋的水汽输送增强, 导致中国西南和华南沿海SSR明显减少, 中国南方东北部SSR微弱增加; 在CP厄尔尼诺事件发展年冬季, 中国南方东部SSR减少 (长江下游流域尤为显著), 而西部SSR增加 (滇东地区增幅突出), 该偶极型异常分布与经向延伸的西北太平洋反气旋加强了中国南方东部的水汽北向输送有关. 研究指出, 两类厄尔尼诺事件发展年冬季水汽异常存在明显差异, 并通过调控总云量导致中国南方SSR空间分布的差异.

本文研究了东太平洋（EP）和中太平洋（CP） El Niño事件对中国南方冬季短波太阳辐射（SSR）的不同影响，揭示了不同的空间分布及其机制。结果表明，在EP El Niño冬季发展过程中，由于西北太平洋强反气旋输送来自热带西北太平洋和北印度洋的水汽，中国西南和华南东海岸的SSR显著减少，而华南东北部的SSR微弱增加。在CP El Niño发展冬季，华南东部SSR减少，长江下游流域显著减少，而华南西部SSR增加，云南东部显著增加。一个经向拉长的西北太平洋反气旋驱动了SSR异常中明显的东西偶极子型，该气旋增强了华南东部向北的水汽输送，同时使西部地区更加干燥。进一步研究表明，EP和CP事件发展冬季的明显湿度异常，主要通过调节总云量导致了华南地区SSR分布的差异。这些发现强调了在预测中国南方中期和长期辐射变化时区分El Niño类型的关键必要性。摘要东部型(EP)和中部型(CP)厄尔尼诺发展年冬季中国南方地区地表太阳短波辐射(SSR)的空间分布特征存在明显差异。在EP厄尔尼诺发展年冬季,受西北太平洋反气旋异常西伸的影响,来自热带西北太平洋和北印度洋的水汽输送增强,导致中国西南和华南沿海SSR明显减少,中国南方东北部SSR微弱增加;在CP厄尔尼诺事件发展年冬季,中国南方东部SSR减少(长江下游流域尤为显著),而西部SSR增加(滇东地区增幅突出),该偶极型异常分布与经向延伸的西北太平洋反气旋加强了中国南方东部的水汽北向输送有关。研究指出,两类厄尔尼诺事件发展年冬季水汽异常存在明显差异,并通过调控总云量导致中国南方SSR空间分布的差异。

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引用次数: 0

A novel deep learning-based framework for five‐day regional weather forecasting 基于深度学习的五天区域天气预报新框架

IF 3.2 4区地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES

Atmospheric and Oceanic Science Letters

Pub Date : 2025-05-26 DOI: 10.1016/j.aosl.2025.100653

Congqi Cao , Ze Sun , Lanshu Hu , Liujie Pan , Yanning Zhang

Deep learning-based methods have become alternatives to traditional numerical weather prediction systems, offering faster computation and the ability to utilize large historical datasets. However, the application of deep learning to medium-range regional weather forecasting with limited data remains a significant challenge. In this work, three key solutions are proposed: (1) motivated by the need to improve model performance in data-scarce regional forecasting scenarios, the authors innovatively apply semantic segmentation models, to better capture spatiotemporal features and improve prediction accuracy; (2) recognizing the challenge of overfitting and the inability of traditional noise-based data augmentation methods to effectively enhance model robustness, a novel learnable Gaussian noise mechanism is introduced that allows the model to adaptively optimize perturbations for different locations, ensuring more effective learning; and (3) to address the issue of error accumulation in autoregressive prediction, as well as the challenge of learning difficulty and the lack of intermediate data utilization in one-shot prediction, the authors propose a cascade prediction approach that effectively resolves these problems while significantly improving model forecasting performance. The method achieves a competitive result in The East China Regional AI Medium Range Weather Forecasting Competition. Ablation experiments further validate the effectiveness of each component, highlighting their contributions to enhancing prediction performance.

摘要

深度学习逐渐替代传统数值天气预报 (NWP) 系统, 但在数据有限的中期天气预报中仍面临挑战。为此, 本文提出三项创新: 首先, 引入语义分割模型增强时空特征捕捉能力, 提高预测精度; 其次, 设计可学习的高斯噪声机制, 解决过拟合问题并突破传统噪声增强的局限性; 最后, 提出级联预测方法, 平衡预测精度与误差控制, 缓解自回归预测的误差累积问题。该方法在华东区域AI中期气象预报竞赛中表现优异, 实验验证了各模块的有效性, 其中语义分割降低温度预测误差9.3%, 噪声机制提升降水预测F1-score 6.8%, 级联策略减少风速预测均方误差12.5%。此研究为数据受限的区域气象预报提供了新路径。

基于深度学习的方法已经成为传统数值天气预报系统的替代品，提供更快的计算速度和利用大型历史数据集的能力。然而，将深度学习应用于有限数据的中期区域天气预报仍然是一个重大挑战。本文提出了三个关键解决方案：(1)基于数据稀缺区域预测场景下提高模型性能的需要，创新性地应用语义分割模型，更好地捕捉时空特征，提高预测精度；(2)认识到过拟合的挑战和传统的基于噪声的数据增强方法无法有效增强模型的鲁棒性，引入了一种新的可学习高斯噪声机制，使模型能够自适应优化不同位置的扰动，确保更有效的学习；(3)针对自回归预测中存在的误差积累问题，以及单次预测中存在的学习困难和中间数据利用率不足的问题，提出了一种级联预测方法，有效解决了这些问题，同时显著提高了模型的预测性能。该方法在华东地区人工智能中期天气预报比赛中取得了竞赛成绩。烧蚀实验进一步验证了各部分的有效性，突出了它们对提高预测性能的贡献。。为此, 本文提出三项创新: 首先, 引入语义分割模型增强时空特征捕捉能力, 提高预测精度; 其次, 设计可学习的高斯噪声机制, 解决过拟合问题并突破传统噪声增强的局限性; 最后, 提出级联预测方法, 平衡预测精度与误差控制, 缓解自回归预测的误差累积问题。该方法在华东区域人工智能中期气象预报竞赛中表现优异,实验验证了各模块的有效性,其中语义分割降低温度预测误差9.3%,噪声机制提升降水预测F1-score 6.8%,级联策略减少风速预测均方误差12.5%。此研究为数据受限的区域气象预报提供了新路径。

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引用次数: 0

Decadal shift in Northeast China’s precipitation around 2000 2000年前后东北降水的年代际变化

IF 3.2 4区地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES

Atmospheric and Oceanic Science Letters

Pub Date : 2025-05-22 DOI: 10.1016/j.aosl.2025.100650

Yawen Liao , Tianbao Zhao , Jingpeng Zhang , Yankun Sun

Northeast China (NEC), a critical agricultural and ecological zone, has experienced intensified hydrological variability under global warming, with cascading impacts on food security and ecosystem resilience. This study utilized observational data and two new generation reanalysis products (i.e., the fifth major global reanalysis produced by ECMWF (ERA5) and the Japanese Reanalysis for Three Quarters of a Century (JRA-3Q)) to investigate the shift changes in precipitation in NEC around 2000 and associated water vapor transport. The analysis identified a pivotal interdecadal shift in 1998/99, transitioning from moderate increases (17.5 mm/10 yr during 1980–1998) to accelerated but more variable precipitation growth (85.4 mm/10 yr post-1999). While the mean precipitation during the post-shift period decreased, enhanced anticyclonic circulation amplified moisture divergence over continental NEC, redirecting vapor flux toward coastal regions. Crucially, trajectory analysis demonstrated regime-dependent moisture sourcing: midlatitude westerlies dominated during wet extremes (44% of trajectories in 1998), whereas East Asian monsoon flows prevailed in drought years (36 % of trajectories in 2007). The post-1998 period exhibited increased reliance on localized recycling (45 % of mid-tropospheric trajectories), reflecting weakened monsoonal inflow. These findings highlight NEC’s growing vulnerability to competing moisture pathways and atmospheric blocking—a dual mechanism that explains rising extremes despite declining mean precipitation. By reconciling dataset discrepancies (ERA5 vs. JRA-3Q trends) and elucidating circulation-precipitation linkages, this work provides actionable insights for climate-resilient agriculture in NEC’s water-stressed ecosystems.

摘要

东北地区作为中国重要的农业生态区之一, 在区域变暖背景下降水呈现显著波动. 该论文基于CN05.1观测数据与ERA5, JRA-3Q再分析资料, 发现东北地区降水在1998/99年发生关键转折: 降水量增速由前期的17.5 mm/10年 (1980−1998年) 跃升至85.4 mm/10年 (1999−2022年). 反气旋环流增强导致大陆区水汽辐散, 向沿海输送增加.轨迹分析显示水汽来源存在显著年际差异: 1998年丰水期44 %水汽源自西风带, 2007年旱季36 %水汽来自东亚季风.

全球变暖背景下，中国东北地区作为重要的农业生态带，其水文变率加剧，对粮食安全和生态系统恢复力产生连锁影响。本研究利用观测资料和两个新一代再分析产品（ECMWF第5次全球再分析（ERA5）和日本四分之三世纪再分析（JRA-3Q））研究了2000年前后东北地区降水的转移变化及其相关的水汽输送。分析确定了1998/99年的关键年代际转变，从中度增加（1980-1998年期间17.5 mm/10年）过渡到加速但变化更大的降水增长（1999年后85.4 mm/10年）。在转变后平均降水减少的同时，增强的反气旋环流放大了大陆NEC上空的水汽辐散，使水汽通量向沿海地区转移。至关重要的是，轨迹分析证明了依赖于地区的水汽来源：中纬度西风带在极端潮湿年份占主导地位（1998年占44%的轨迹），而东亚季风流在干旱年份占主导地位（2007年占36%的轨迹）。1998年后时期对局部再循环的依赖增加（对流层中层轨迹的45%），反映出季风流入减弱。这些发现突出了NEC对竞争湿度路径和大气阻塞的日益脆弱——这是一种双重机制，解释了尽管平均降水减少，但极端天气却在增加。通过协调数据集差异（ERA5与JRA-3Q趋势）和阐明循环-降水联系，这项工作为NEC缺水生态系统中的气候适应型农业提供了可行的见解。摘要东北地区作为中国重要的农业生态区之一, 在区域变暖背景下降水呈现显著波动. 该论文基于CN05.1观测数据与ERA5, JRA-3Q再分析资料,发现东北地区降水在1998/99年发生关键转折:降水量增速由前期的17.5毫米/ 10年(1980−1998年)跃升至85.4毫米/ 10年(1999−2022年)。反气旋环流增强导致大陆区水汽辐散, 向沿海输送增加.轨迹分析显示水汽来源存在显著年际差异: 1998年丰水期44 %水汽源自西风带, 2007年旱季36 %水汽来自东亚季风.

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引用次数: 0