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Optimizing the key parameter to accelerate the recovery of AMOC under a rapid increase of greenhouse gas forcing 优化关键参数,在温室气体强迫迅速增加的情况下加速恢复 AMOC
IF 2.3 4区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2025-01-01 DOI: 10.1016/j.aosl.2024.100509
Haolan Ren , Fei Zheng , Tingwei Cao , Qiang Wang
Atlantic Meridional Overturning Circulation (AMOC) plays a central role in long-term climate variations through its heat and freshwater transports, which can collapse under a rapid increase of greenhouse gas forcing in climate models. Previous studies have suggested that the deviation of model parameters is one of the major factors in inducing inaccurate AMOC simulations. In this work, with a low-resolution earth system model, the authors try to explore whether a reasonable adjustment of the key model parameter can help to re-establish the AMOC after its collapse. Through a new optimization strategy, the extra freshwater flux (FWF) parameter is determined to be the dominant one affecting the AMOC's variability. The traditional ensemble optimal interpolation (EnOI) data assimilation and new machine learning methods are adopted to optimize the FWF parameter in an abrupt 4×CO2 forcing experiment to improve the adaptability of model parameters and accelerate the recovery of AMOC. The results show that, under an abrupt 4×CO2 forcing in millennial simulations, the AMOC will first collapse and then re-establish by the default FWF parameter slowly. However, during the parameter adjustment process, the saltier and colder sea water over the North Atlantic region are the dominant factors in usefully improving the adaptability of the FWF parameter and accelerating the recovery of AMOC, according to their physical relationship with FWF on the interdecadal timescale.
摘要
大西洋经向翻转环流 (Atlantic Meridional Overturning Circulation, AMOC) 通过其经向的热量和水团输送, 在气候变化中起着关键作用. 然而, 气候模式模拟未来AMOC在温室气体强迫下的变化存在较大不确定性. 模式参数的不确定性是导致AMOC产生不确定性的主要因素之一. 因此, 本文采用简化的海气耦合模式首先探寻出模式中AMOC的最敏感参数为淡水通量系数 (Freshwater Flux, FWF), 再基于集合最优插值 (Ensemble Optimal Interpolation, EnOI) 探讨通过参数优化减小温室气体强迫下AMOC模拟不确定性的可行方案. 理想试验揭示了, 北大西洋海表温度和海表盐度在温室气体强迫下的增量可以有效地优化FWF, 进而使得AMOC相比默认参数能快速收敛, 减小其在未来气候预估中的不确定性.
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引用次数: 0
Interannual variability of boreal summer intraseasonal oscillation over the northwestern Pacific influenced by the Pacific Meridional Mode 受太平洋经向模式影响的西北太平洋北方夏季季内振荡的年际变化
IF 2.3 4区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2025-01-01 DOI: 10.1016/j.aosl.2024.100492
Haoyu Zhou, Pang-Chi Hsu, Lin Chen, Yitian Qian
During the boreal summer, intraseasonal oscillations exhibit significant interannual variations in intensity over two key regions: the central-western equatorial Pacific (5°S–5°N, 150°E–150°W) and the subtropical Northwestern Pacific (10°–20°N, 130°E–175°W). The former is well-documented and considered to be influenced by the ENSO, while the latter has received comparatively less attention and is likely influenced by the Pacific Meridional Mode (PMM), as suggested by partial correlation analysis results. To elucidate the physical processes responsible for the enhanced (weakened) intraseasonal convection over the subtropical northwestern Pacific during warm (cold) PMM years, the authors employed a moisture budget analysis. The findings reveal that during warm PMM years, there is an increase in summer-mean moisture over the subtropical northwestern Pacific. This increase interacts with intensified vertical motion perturbations in the region, leading to greater vertical moisture advection in the lower troposphere and consequently resulting in convective instability. Such a process is pivotal in amplifying intraseasonal convection anomalies. The observational findings were further verified by model experiments forced by PMM-like sea surface temperature patterns.
摘要
在北半球夏季, 西北太平洋地区的季节内振荡在两个主要区域呈现出显著的年际变率: 一个区域是赤道太平洋中西部 (5°S–5°N, 150°E–150°W), 另一区域为副热带西北太平洋 (10°–20°N, 130°E–175°W). 通过偏相关分析, 揭示了前者受到厄尔尼诺–南方涛动 (ENSO) 的影响, 而后者与太平洋经向模态 (PMM) 有关. 利用水汽方程诊断, 探讨了在PMM暖 (冷) 年期间, 副热带西北太平洋季节内对流活动增强 (减弱) 的物理过程. 结果表明, 在PMM暖年, 副热带西北太平洋地区的季节平均水汽增加与季节内垂直扰动的增强相互作用, 导致了对流层低层水汽垂直输送的增加, 进而引发对流不稳定性的增强, 促使季节内对流活动增强. 这一发现在以PMM海温为驱动的全球环流模式试验中也得到了验证.
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引用次数: 0
Satellite remote sensing reveals overwhelming recovery of forest from disturbances in Asia 卫星遥感揭示了亚洲森林受干扰后的巨大恢复力
IF 2.3 4区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2025-01-01 DOI: 10.1016/j.aosl.2024.100511
Yiying Zhu , Hesong Wang , Anzhi Zhang
Forest ecosystems play key roles in mitigating human-induced climate change through enhanced carbon uptake; however, frequently occurring climate extremes and human activities have considerably threatened the stability of forests. At the same time, detailed accounts of disturbances and forest responses are not yet well quantified in Asia. This study employed the Breaks For Additive Seasonal and Trend method—an abrupt-change detection method—to analyze the Enhanced Vegetation Index time series in East Asia, South Asia, and Southeast Asia. This approach allowed us to detect forest disturbance and quantify the resilience after disturbance. Results showed that 20 % of forests experienced disturbance with an increasing trend from 2000 to 2022, and Southeast Asian countries were more severely affected by disturbances. Specifically, 95 % of forests had robust resilience and could recover from disturbance within a few decades. The resilience of forests suffering from greater magnitude of disturbance tended to be stronger than forests with lower disturbance magnitude. In summary, this study investigated the resilience of forests across the low and middle latitudes of Asia over the past two decades. The authors found that most forests exhibited good resilience after disturbance and about two-thirds had recovered to a better state in 2022. The findings of this study underscore the complex relationship between disturbance and resilience, contributing to comprehension of forest resilience through satellite remote sensing.
摘要
目前对于亚洲森林在应对气候变化和人类活动干扰方面的研究相对较少. 本研究利用BFAST突变检测方法, 分析了东亚, 南亚和东南亚的增强植被指数 (EVI) 长时间序列中检测到的森林扰动和恢复情况. 结果显示, 2000年至2022年期间, 约20%的森林经历了扰动, 且受到扰动的森林面积呈增加趋势, 东南亚国家受扰动的影响更为严重. 在扰动事件发生后, 95%的森林具有较好的恢复能力, 能够在受到扰动后的一段时间后恢复过来, 其中约有三分之二的森林在2022年时已经恢复到了较扰动前更好的状态.
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引用次数: 0
Impacts of the annual cycle of background SST in the tropical Pacific on the phase and amplitude of ENSO 热带太平洋背景海温年周期对厄尔尼诺/南方涛动相位和振幅的影响
IF 2.3 4区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2025-01-01 DOI: 10.1016/j.aosl.2024.100496
Song Jiang , Congwen Zhu , Ning Jiang
The dominant annual cycle of sea surface temperature (SST) in the tropical Pacific exhibits an antisymmetric mode, which explains 83.4% total variance, and serves as a background of El Niño–Southern Oscillation (ENSO). However, there is no consensus yet on its anomalous impacts on the phase and amplitude of ENSO. Based on data during 1982–2022, results show that anomalies of the antisymmetric mode can affect the evolution of ENSO on the interannual scale via Bjerknes feedback, in which the positive (negative) phase of the antisymmetric mode can strengthen El Niño (La Niña) in boreal winter via an earlier (delayed) seasonal cycle transition and larger (smaller) annual mean. The magnitude of the SST anomalies in the equatorial eastern Pacific can reach more than ±0.3℃, regulated by the changes in the antisymmetric mode based on random sensitivity analysis. Results reveal the spatial pattern of the annual cycle associated with the seasonal phase-locking of ENSO evolution and provide new insight into the impact of the annual cycle of background SST on ENSO, which possibly carries important implications for forecasting ENSO.
摘要
基于1982–2022年资料分析, 本文发现, 热带太平洋海温年循环的主导模态为反对称模式, 是ENSO发展的背景场. 然而, 其对ENSO相位和振幅的异常影响尚未可知. 反对称模态异常可以通过Bjerknes反馈影响ENSO的年际变化, 其正 (负) 异常可以通过更早 (更晚) 的季节循环转变时间和更大 (更小) 的年平均值增强冬季El Niño (La Niña) 的强度. 根据随机敏感性实验分析, 与反对称模态变化有关的赤道中东太平洋海温异常可达±0.3℃以上. 研究结果为背景海温年循环对ENSO的影响提供了新的见解, 这可能对ENSO的预测具有重要意义.
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引用次数: 0
Application of the improved dung beetle optimizer, muti-head attention and hybrid deep learning algorithms to groundwater depth prediction in the Ningxia area, China 改进的蜣螂优化器、多头注意力和混合深度学习算法在中国宁夏地区地下水深度预测中的应用
IF 2.3 4区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2025-01-01 DOI: 10.1016/j.aosl.2024.100497
Jiarui Cai , Bo Sun , Huijun Wang , Yi Zheng , Siyu Zhou , Huixin Li , Yanyan Huang , Peishu Zong
Due to the lack of accurate data and complex parameterization, the prediction of groundwater depth is a challenge for numerical models. Machine learning can effectively solve this issue and has been proven useful in the prediction of groundwater depth in many areas. In this study, two new models are applied to the prediction of groundwater depth in the Ningxia area, China. The two models combine the improved dung beetle optimizer (DBO) algorithm with two deep learning models: The Multi-head Attention–Convolution Neural Network–Long Short Term Memory networks (MH-CNN-LSTM) and the Multi-head Attention–Convolution Neural Network–Gated Recurrent Unit (MH-CNN-GRU). The models with DBO show better prediction performance, with larger R (correlation coefficient), RPD (residual prediction deviation), and lower RMSE (root-mean-square error). Compared with the models with the original DBO, the R and RPD of models with the improved DBO increase by over 1.5%, and the RMSE decreases by over 1.8%, indicating better prediction results. In addition, compared with the multiple linear regression model, a traditional statistical model, deep learning models have better prediction performance.
摘要
本研究将两个新模型应用于位于中国西北干旱半干旱区的宁夏地区地下水深度预测. 这两个模型将改进的蜣螂优化 (DBO) 算法与两个深度学习模型相结合, 即多头注意力-卷积神经网络-长短期记忆网络和多头注意力-回旋神经网络-门控递归单元. 带有DBO的模型预测结果表现出更大的相关系数 (R) , 残差预测偏差 (RPD) 和较低的均方根误差 (RMSE) , 预测结果更好. 此外, 与DBO模型相比, 改进后的DBO模型的R和RPD增加了1.5%以上, RMSE降低了1.8%以上, 表明预测结果更好. 与传统的统计模型多元线性回归模型相比, 深度学习模型具有更好的预测性能.
{"title":"Application of the improved dung beetle optimizer, muti-head attention and hybrid deep learning algorithms to groundwater depth prediction in the Ningxia area, China","authors":"Jiarui Cai ,&nbsp;Bo Sun ,&nbsp;Huijun Wang ,&nbsp;Yi Zheng ,&nbsp;Siyu Zhou ,&nbsp;Huixin Li ,&nbsp;Yanyan Huang ,&nbsp;Peishu Zong","doi":"10.1016/j.aosl.2024.100497","DOIUrl":"10.1016/j.aosl.2024.100497","url":null,"abstract":"<div><div>Due to the lack of accurate data and complex parameterization, the prediction of groundwater depth is a challenge for numerical models. Machine learning can effectively solve this issue and has been proven useful in the prediction of groundwater depth in many areas. In this study, two new models are applied to the prediction of groundwater depth in the Ningxia area, China. The two models combine the improved dung beetle optimizer (DBO) algorithm with two deep learning models: The Multi-head Attention–Convolution Neural Network–Long Short Term Memory networks (MH-CNN-LSTM) and the Multi-head Attention–Convolution Neural Network–Gated Recurrent Unit (MH-CNN-GRU). The models with DBO show better prediction performance, with larger <em>R</em> (correlation coefficient), RPD (residual prediction deviation), and lower RMSE (root-mean-square error). Compared with the models with the original DBO, the <em>R</em> and RPD of models with the improved DBO increase by over 1.5%, and the RMSE decreases by over 1.8%, indicating better prediction results. In addition, compared with the multiple linear regression model, a traditional statistical model, deep learning models have better prediction performance.</div><div>摘要</div><div>本研究将两个新模型应用于位于中国西北干旱半干旱区的宁夏地区地下水深度预测. 这两个模型将改进的蜣螂优化 (DBO) 算法与两个深度学习模型相结合, 即多头注意力-卷积神经网络-长短期记忆网络和多头注意力-回旋神经网络-门控递归单元. 带有DBO的模型预测结果表现出更大的相关系数 (R) , 残差预测偏差 (RPD) 和较低的均方根误差 (RMSE) , 预测结果更好. 此外, 与DBO模型相比, 改进后的DBO模型的R和RPD增加了1.5%以上, RMSE降低了1.8%以上, 表明预测结果更好. 与传统的统计模型多元线性回归模型相比, 深度学习模型具有更好的预测性能.</div></div>","PeriodicalId":47210,"journal":{"name":"Atmospheric and Oceanic Science Letters","volume":"18 1","pages":"Article 100497"},"PeriodicalIF":2.3,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140794268","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}
引用次数: 0
Impact of ocean data assimilation on the seasonal forecast of the 2014/15 marine heatwave in the Northeast Pacific Ocean 海洋数据同化对东北太平洋 2014/15 年海洋热浪季节性预报的影响
IF 2.3 4区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2025-01-01 DOI: 10.1016/j.aosl.2024.100498
Tiantian Tang, Jiaying He, Huihang Sun, Jingjia Luo
A remarkable marine heatwave, known as the “Blob”, occurred in the Northeast Pacific Ocean from late 2013 to early 2016, which displayed strong warm anomalies extending from the surface to a depth of 300 m. This study employed two assimilation schemes based on the global Climate Forecast System of Nanjing University of Information Science (NUIST-CFS 1.0) to investigate the impact of ocean data assimilation on the seasonal prediction of this extreme marine heatwave. The sea surface temperature (SST) nudging scheme assimilates SST only, while the deterministic ensemble Kalman filter (EnKF) scheme assimilates observations from the surface to the deep ocean. The latter notably improves the forecasting skill for subsurface temperature anomalies, especially at the depth of 100–300 m (the lower layer), outperforming the SST nudging scheme. It excels in predicting both horizontal and vertical heat transport in the lower layer, contributing to improved forecasts of the lower-layer warming during the Blob. These improvements stem from the assimilation of subsurface observational data, which are important in predicting the upper-ocean conditions. The results suggest that assimilating ocean data with the EnKF scheme significantly enhances the accuracy in predicting subsurface temperature anomalies during the Blob and offers better understanding of its underlying mechanisms.
摘要
2013年底至2016年初, 东北太平洋上发生了历史上罕见的极端海洋热浪事件 (称为“Blob”事件) , 形成了从海表延伸至海洋深处300m的强烈且持续的海温暖异常. 本文利用南京信息工程大学全球气候预测系统1.0版本 (NUIST-CFS 1.0) , 采用两种海洋资料同化方案, 探究海洋资料同化差异对这一极端海洋热浪事件季节预测的影响. 本文采用的一种同化方案为仅同化海表面温度 (Surface sea temperature, SST) 的SST-nudging方案, 而另一种方案为在前一种方案的基础上加入确定性集合卡尔曼滤波 (Deterministic Ensemble Kalman Filter, DEnKF) , 同化更多海洋观测数据的EnKF方案. 主要结论为, 利用EnKF方案可显著提高对“Blob”期间次表层温度异常预测的准确性, 这主要源于EnKF方案在预测次表层的水平和垂直热传输方面表现出色. 该研究有助于更好地理解海洋热浪事件潜在物理机制及其季节预测水平.
{"title":"Impact of ocean data assimilation on the seasonal forecast of the 2014/15 marine heatwave in the Northeast Pacific Ocean","authors":"Tiantian Tang,&nbsp;Jiaying He,&nbsp;Huihang Sun,&nbsp;Jingjia Luo","doi":"10.1016/j.aosl.2024.100498","DOIUrl":"10.1016/j.aosl.2024.100498","url":null,"abstract":"<div><div>A remarkable marine heatwave, known as the “Blob”, occurred in the Northeast Pacific Ocean from late 2013 to early 2016, which displayed strong warm anomalies extending from the surface to a depth of 300 m. This study employed two assimilation schemes based on the global Climate Forecast System of Nanjing University of Information Science (NUIST-CFS 1.0) to investigate the impact of ocean data assimilation on the seasonal prediction of this extreme marine heatwave. The sea surface temperature (SST) nudging scheme assimilates SST only, while the deterministic ensemble Kalman filter (EnKF) scheme assimilates observations from the surface to the deep ocean. The latter notably improves the forecasting skill for subsurface temperature anomalies, especially at the depth of 100–300 m (the lower layer), outperforming the SST nudging scheme. It excels in predicting both horizontal and vertical heat transport in the lower layer, contributing to improved forecasts of the lower-layer warming during the Blob. These improvements stem from the assimilation of subsurface observational data, which are important in predicting the upper-ocean conditions. The results suggest that assimilating ocean data with the EnKF scheme significantly enhances the accuracy in predicting subsurface temperature anomalies during the Blob and offers better understanding of its underlying mechanisms.</div><div>摘要</div><div>2013年底至2016年初, 东北太平洋上发生了历史上罕见的极端海洋热浪事件 (称为“Blob”事件) , 形成了从海表延伸至海洋深处300m的强烈且持续的海温暖异常. 本文利用南京信息工程大学全球气候预测系统1.0版本 (NUIST-CFS 1.0) , 采用两种海洋资料同化方案, 探究海洋资料同化差异对这一极端海洋热浪事件季节预测的影响. 本文采用的一种同化方案为仅同化海表面温度 (Surface sea temperature, SST) 的SST-nudging方案, 而另一种方案为在前一种方案的基础上加入确定性集合卡尔曼滤波 (Deterministic Ensemble Kalman Filter, DEnKF) , 同化更多海洋观测数据的EnKF方案. 主要结论为, 利用EnKF方案可显著提高对“Blob”期间次表层温度异常预测的准确性, 这主要源于EnKF方案在预测次表层的水平和垂直热传输方面表现出色. 该研究有助于更好地理解海洋热浪事件潜在物理机制及其季节预测水平.</div></div>","PeriodicalId":47210,"journal":{"name":"Atmospheric and Oceanic Science Letters","volume":"18 1","pages":"Article 100498"},"PeriodicalIF":2.3,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140771707","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}
引用次数: 0
Arctic sea-ice extent: No record minimum in 2023 or recent years 北极海冰范围:2023 年或近年不会出现最低纪录
IF 2.3 4区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2025-01-01 DOI: 10.1016/j.aosl.2024.100499
Ola M. Johannessen , Tor I. Olaussen
Arctic sea-ice extent reaches its minimum each year in September. On 11 September 2023 the minimum was 4.969 million square kilometers (mill.km2). This was not a record low, which occurred in 2012, when the minimum was 4.175 mill.km2, 0.794 mill.km2 less than the minimum in 2023. However, the ice extent had decreased by 0.432 mill.km2 compared with 2022. Nevertheless, the summer melting in 2023 was remarkably less than expected when considering the strong heat waves in the atmosphere and ocean, with record temperatures set around the world. In general, there is a high correlation between the long-term decrease in sea-ice extent and the increasing CO2 in the atmosphere, where the increase of CO2 in recent decades explains about 80% of the decrease in sea ice in September, while the remainder is caused by natural variability.
{"title":"Arctic sea-ice extent: No record minimum in 2023 or recent years","authors":"Ola M. Johannessen ,&nbsp;Tor I. Olaussen","doi":"10.1016/j.aosl.2024.100499","DOIUrl":"10.1016/j.aosl.2024.100499","url":null,"abstract":"<div><div>Arctic sea-ice extent reaches its minimum each year in September. On 11 September 2023 the minimum was 4.969 million square kilometers (mill.km<sup>2</sup>). This was not a record low, which occurred in 2012, when the minimum was 4.175 mill.km<sup>2</sup>, 0.794 mill.km<sup>2</sup> less than the minimum in 2023. However, the ice extent had decreased by 0.432 mill.km<sup>2</sup> compared with 2022. Nevertheless, the summer melting in 2023 was remarkably less than expected when considering the strong heat waves in the atmosphere and ocean, with record temperatures set around the world. In general, there is a high correlation between the long-term decrease in sea-ice extent and the increasing CO<sub>2</sub> in the atmosphere, where the increase of CO<sub>2</sub> in recent decades explains about 80% of the decrease in sea ice in September, while the remainder is caused by natural variability.</div></div>","PeriodicalId":47210,"journal":{"name":"Atmospheric and Oceanic Science Letters","volume":"18 1","pages":"Article 100499"},"PeriodicalIF":2.3,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140790831","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}
引用次数: 0
Role of the Greenland Sea ice anomaly in the late-spring drought over Northwest China
IF 2.3 4区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2025-01-01 DOI: 10.1016/j.aosl.2024.100488
Yang Liu , Huopo Chen
Drought across Northwest China in late spring has exerted a vital effect on the local climate and agricultural production, and has been alleviated during the past decades. This study explored the influence of the preceding Arctic sea ice on the May drought in Northwest China caused by the precipitation deficit. Further analysis indicated that when the Greenland Sea ice concentration is abnormally high during February to April, the dry conditions in Northwest China tend to be alleviated. The increase of sea ice in the Greenland Sea can excite a meridional circulation, which causes sea surface temperature (SST) anomalies in the North Atlantic via the sea–air interaction, manifested as significant warm SST anomalies over the south of Greenland and the subtropical North Atlantic, but negative SST anomalies over the west of the Azores. This abnormal SST pattern maintains to May and triggers a zonal wave train from the North Atlantic through Scandinavia and Central Asia to Northwest China, leading to abnormal cyclones in Northwest China. Consequently, Northwest China experiences a more humid climate than usual.
摘要
晚春西北地区干旱的发生对西北地区气候和农业生产等具有重要的影响, 但在近几十年, 西北干旱状况呈现出缓解的趋势. 本文研究了前期北极海冰异常对5月中国西北地区 (降水短缺引起的) 干旱异常的影响. 进一步研究表明, 二至四月格陵兰海海冰偏多时, 西北地区干旱有所缓解. 偏多的格陵兰海海冰可激发出经向环流异常, 环流异常通过海–气相互作用在北大西洋产生海温异常, 主要表现为格陵兰岛以南和北大西洋副热带海温偏高, 亚速尔群岛以西海温偏低. 这种海温异常可持续到5月, 并引发从北大西洋经斯堪的纳维亚半岛和中亚至中国西北地区的纬向波列, 并在西北地区产生气旋环流异常, 从而导致该地区水汽辐合, 干旱状况有所缓解.
{"title":"Role of the Greenland Sea ice anomaly in the late-spring drought over Northwest China","authors":"Yang Liu ,&nbsp;Huopo Chen","doi":"10.1016/j.aosl.2024.100488","DOIUrl":"10.1016/j.aosl.2024.100488","url":null,"abstract":"<div><div>Drought across Northwest China in late spring has exerted a vital effect on the local climate and agricultural production, and has been alleviated during the past decades. This study explored the influence of the preceding Arctic sea ice on the May drought in Northwest China caused by the precipitation deficit. Further analysis indicated that when the Greenland Sea ice concentration is abnormally high during February to April, the dry conditions in Northwest China tend to be alleviated. The increase of sea ice in the Greenland Sea can excite a meridional circulation, which causes sea surface temperature (SST) anomalies in the North Atlantic via the sea–air interaction, manifested as significant warm SST anomalies over the south of Greenland and the subtropical North Atlantic, but negative SST anomalies over the west of the Azores. This abnormal SST pattern maintains to May and triggers a zonal wave train from the North Atlantic through Scandinavia and Central Asia to Northwest China, leading to abnormal cyclones in Northwest China. Consequently, Northwest China experiences a more humid climate than usual.</div><div>摘要</div><div>晚春西北地区干旱的发生对西北地区气候和农业生产等具有重要的影响, 但在近几十年, 西北干旱状况呈现出缓解的趋势. 本文研究了前期北极海冰异常对5月中国西北地区 (降水短缺引起的) 干旱异常的影响. 进一步研究表明, 二至四月格陵兰海海冰偏多时, 西北地区干旱有所缓解. 偏多的格陵兰海海冰可激发出经向环流异常, 环流异常通过海–气相互作用在北大西洋产生海温异常, 主要表现为格陵兰岛以南和北大西洋副热带海温偏高, 亚速尔群岛以西海温偏低. 这种海温异常可持续到5月, 并引发从北大西洋经斯堪的纳维亚半岛和中亚至中国西北地区的纬向波列, 并在西北地区产生气旋环流异常, 从而导致该地区水汽辐合, 干旱状况有所缓解.</div></div>","PeriodicalId":47210,"journal":{"name":"Atmospheric and Oceanic Science Letters","volume":"18 1","pages":"Article 100488"},"PeriodicalIF":2.3,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143137395","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}
引用次数: 0
Increase in the variability of terrestrial carbon uptake in response to enhanced future ENSO modulation 未来厄尔尼诺/南方涛动调制增强时陆地碳吸收变化的增加
IF 2.3 4区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2025-01-01 DOI: 10.1016/j.aosl.2024.100508
Younong Li , Li Dan , Jing Peng , Qidong Yang , Fuqiang Yang
El Niño–Southern Oscillation (ENSO) is a major driver of climate change in middle and low latitudes and thus strongly influences the terrestrial carbon cycle through land–air interaction. Both the ENSO modulation and carbon flux variability are projected to increase in the future, but their connection still needs further investigation. To investigate the impact of future ENSO modulation on carbon flux variability, this study used 10 CMIP6 earth system models to analyze ENSO modulation and carbon flux variability in middle and low latitudes, and their relationship, under different scenarios simulated by CMIP6 models. The results show a high consistency in the simulations, with both ENSO modulation and carbon flux variability showing an increasing trend in the future. The higher the emissions scenario, especially SSP5-8.5 compared to SSP2-4.5, the greater the increase in variability. Carbon flux variability in the middle and low latitudes under SSP2-4.5 increases by 30.9% compared to historical levels during 1951–2000, while under SSP5-8.5 it increases by 58.2%. Further analysis suggests that ENSO influences mid- and low-latitude carbon flux variability primarily through temperature. This occurrence may potentially be attributed to the increased responsiveness of gross primary productivity towards regional temperature fluctuations, combined with the intensified influence of ENSO on land surface temperatures.
摘要
ENSO是中低纬度地区气候系统的主要驱动因素, 对陆地碳循环有重要影响. 本研究基于10个CMIP6地球系统模式, 分析了不同情景下ENSO变率与中低纬度地区总初级生产力变率的关系. 结果显示, 未来ENSO变率和总初级生产力变率在未来多数模式均显示为增加. 在未来情境下(2051-2100年), 中低纬度地区的总初级生产力变率较历史时期(1951–2000年)增加了30.9%(SSP2-4.5), 58.2%(SSP5-8.5). 进一步分析表明, ENSO主要通过温度影响中低纬度碳通量变率. 这种现象可能归因于总初级生产力对温度的响应增强, 以及ENSO对陆地表面温度的影响.
{"title":"Increase in the variability of terrestrial carbon uptake in response to enhanced future ENSO modulation","authors":"Younong Li ,&nbsp;Li Dan ,&nbsp;Jing Peng ,&nbsp;Qidong Yang ,&nbsp;Fuqiang Yang","doi":"10.1016/j.aosl.2024.100508","DOIUrl":"10.1016/j.aosl.2024.100508","url":null,"abstract":"<div><div>El Niño–Southern Oscillation (ENSO) is a major driver of climate change in middle and low latitudes and thus strongly influences the terrestrial carbon cycle through land–air interaction. Both the ENSO modulation and carbon flux variability are projected to increase in the future, but their connection still needs further investigation. To investigate the impact of future ENSO modulation on carbon flux variability, this study used 10 CMIP6 earth system models to analyze ENSO modulation and carbon flux variability in middle and low latitudes, and their relationship, under different scenarios simulated by CMIP6 models. The results show a high consistency in the simulations, with both ENSO modulation and carbon flux variability showing an increasing trend in the future. The higher the emissions scenario, especially SSP5-8.5 compared to SSP2-4.5, the greater the increase in variability. Carbon flux variability in the middle and low latitudes under SSP2-4.5 increases by 30.9% compared to historical levels during 1951–2000, while under SSP5-8.5 it increases by 58.2%. Further analysis suggests that ENSO influences mid- and low-latitude carbon flux variability primarily through temperature. This occurrence may potentially be attributed to the increased responsiveness of gross primary productivity towards regional temperature fluctuations, combined with the intensified influence of ENSO on land surface temperatures.</div><div>摘要</div><div>ENSO是中低纬度地区气候系统的主要驱动因素, 对陆地碳循环有重要影响. 本研究基于10个CMIP6地球系统模式, 分析了不同情景下ENSO变率与中低纬度地区总初级生产力变率的关系. 结果显示, 未来ENSO变率和总初级生产力变率在未来多数模式均显示为增加. 在未来情境下(2051-2100年), 中低纬度地区的总初级生产力变率较历史时期(1951–2000年)增加了30.9%(SSP2-4.5), 58.2%(SSP5-8.5). 进一步分析表明, ENSO主要通过温度影响中低纬度碳通量变率. 这种现象可能归因于总初级生产力对温度的响应增强, 以及ENSO对陆地表面温度的影响.</div></div>","PeriodicalId":47210,"journal":{"name":"Atmospheric and Oceanic Science Letters","volume":"18 1","pages":"Article 100508"},"PeriodicalIF":2.3,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140776937","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}
引用次数: 0
Implications of 1.5 K climate warming on warm-season ozone exposure and atmospheric oxidation capacity in China 1.5 K 气候变暖对中国暖季臭氧暴露和大气氧化能力的影响
IF 2.3 4区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES Pub Date : 2024-11-01 DOI: 10.1016/j.aosl.2024.100556
Zhihao Shi , Lin Huang , Xiaodong Xie , Momei Qin , Jingyi Li , Bingye Xu , Lingling Jin , Jianlin Hu
Surface ozone (O3) poses significant threats to public health, agricultural crops, and plants in natural ecosystems. Global warming is likely to increase future O3 mainly by altering atmospheric photochemical reactions and enhancing biogenic volatile organic compound (BVOC) emissions. To assess the impacts of the future 1.5 K climate target on O3 concentrations and ecological O3 exposure in China, numerical simulations were conducted using the CMAQ (Community Multiscale Air Quality) model during April–October 2018. Ecological O3 exposure was estimated using six indices (i.e., M7, M24, N100, SUM60, W126, and AOT40f). The results show that the temperature rise increases the MDA8 O3 (maximum daily eight-hour average O3) concentrations by ∼3 ppb and the number of O3 exceedance days by 10–20 days in the North China Plain (NCP), Yangtze River Delta (YRD), and Sichuan Basin (SCB) regions. All O3 exposure indices show substantial increases. M24 and M7 in eastern and southern China will rise by 1–3 ppb and 2–4 ppb, respectively. N100 increases by more than 120 h in the surrounding regions of Beijing. SUM60 increases by greater than 9 ppm h−1, W126 increases by greater than 15 ppm h−1 in Shaanxi and SCB, and AOT40f increases by 6 ppm h−1 in NCP and SCB. The temperature increase also promotes atmospheric oxidation capacity (AOC) levels, with the higher AOC contributed by OH radicals in southern China but by NO3 radicals in northern China. The change in the reaction rate caused by the temperature increase has a greater influence on O3 exposure and AOC than the change in BVOC emissions.
摘要
地表臭氧(O₃)对公众健康, 农作物以及自然生态系统构成重大威胁. 全球变暖会增强大气光化学反应以及增加生物源挥发性有机化合物(BVOC)排放, 从而导致 O₃浓度增加. 为了评估未来 1.5 K 气候目标对中国 O₃浓度以及生态 O₃暴露的影响, 在 2018 年 4 月至 10 月期间使用 CMAQ模型进行了数值模拟. 使用六个指标(即 M7, M24, N100, SUM60, W126 和 AOT40f)估算生态 O₃暴露. 结果表明, 在华北平原,长江三角洲和四川盆地地区, 温度升高使每日最大8 小时平均 O₃浓度增加约 3 ppb, O₃超标天数增加 10–20 天. 所有 O₃暴露指标均显著增加. 中国东部和南部的 M24 和 M7 将分别增加 1–3 ppb 和 2–4 ppb. 北京周边地区的 N100 增加超过 120 小时. 陕西和四川盆地的 SUM60 增加超过 9 ppm h⁻¹, W126 增加超过 15 ppm h⁻¹, 华北平原和四川盆地的 AOT40f 增加 6 ppm h⁻¹. 温度升高还提升了大气氧化能力(AOC)水平, 在中国南部较高的 AOC 由羟基自由基贡献, 而在中国北部则由硝基自由基贡献. 由温度升高引起的反应速率变化对 O₃暴露和 AOC 的影响比 BVOC 排放增加带来的贡献更大.
地表臭氧(O3)对公众健康、农作物和自然生态系统中的植物构成重大威胁。全球变暖可能主要通过改变大气光化学反应和增加生物挥发性有机化合物(BVOC)排放来增加未来的臭氧浓度。为评估未来 1.5 K 气候目标对中国臭氧浓度和生态臭氧暴露的影响,2018 年 4 月至 10 月期间,利用 CMAQ(社区多尺度空气质量)模式进行了数值模拟。使用六个指数(即 M7、M24、N100、SUM60、W126 和 AOT40f)估算了生态 O3 暴露。结果表明,气温升高会使华北平原、长江三角洲和四川盆地的 MDA8 O3(最大日均 8 小时 O3)浓度增加 3 ppb,O3 超标天数增加 10-20 天。所有臭氧暴露指数都出现了大幅上升。华东和华南地区的 M24 和 M7 将分别上升 1-3 ppb 和 2-4 ppb。北京周边地区的 N100 将增加 120 小时以上。SUM60 增加超过 9 ppm h-1,W126 在陕西和南充增加超过 15 ppm h-1,AOT40f 在南京和南充增加 6 ppm h-1。温度的升高也促进了大气氧化能力(AOC)水平的提高,华南地区较高的大气氧化能力是由 OH 自由基造成的,而华北地区较高的大气氧化能力则是由 NO3 自由基造成的。与 BVOC 排放量的变化相比,气温升高引起的反应速率变化对 O3 暴露和 AOC 的影响更大.摘要地表臭氧(O₃)对公众健康、农作物以及自然生态系统构成重大威胁。全球变暖会增强大气光化学反应以及增加生物源挥发性有机化合物(BVOC)排放, 从而导致 o₃浓度增加。为了评估未来 1.5 k 气候目标对中国 o₃浓度以及生态 o₃暴露的影响, 在 2018 年 4 月至 10 月期间使用 cmaq 模型进行了数值模拟。使用六个指标(即 M7、M24、N100、SUM60、W126 和 AOT40f)估算生态 O₃暴露。结果表明,在华北平原, 长江三角洲和四川盆地地区, 温度升高使每日最大 8 小时平均 O₃浓度增加约 3 ppb, O₃超标天数增加 10-20 天。所有 O₃暴露指标均显著增加。中国东部和南部的 M24 和 M7 将分别增加 1-3 ppb 和 2-4 ppb。北京周边地区的 n100 增加超过 120 小时。陕西和四川盆地的 SUM60 增加超过 9 ppm h-¹,W126 增加超过 15 ppm h-¹,华北平原和四川盆地的 AOT40f 增加 6 ppm h-¹。温度升高还提升了大气氧化能力(AOC)水平, 在中国南部较高的 AOC 由羟基自由基贡献, 而在中国北部则由硝基自由基贡献。由温度升高引起的反应速率变化对 o₃暴露和 aoc 的影响比 bvoc 排放增加带来的贡献更大。
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Atmospheric and Oceanic Science Letters
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