npj Climate and Atmospheric Science最新文献_第9页

Global atmospheric distribution of microplastics with evidence of low oceanic emissions 微塑料在全球大气中的分布以及海洋排放低的证据

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2025-02-28 DOI: 10.1038/s41612-025-00914-3

Shanye Yang, Guy Brasseur, Stacy Walters, Pablo Lichtig, Cathy W. Y. Li

引用次数: 0

A source-weighted Benthic minus Planktonic radiocarbon method for estimating pure ocean water age 估算纯海水年龄的源加权底栖生物减去浮游生物放射性碳方法

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2025-02-27 DOI: 10.1038/s41612-025-00952-x

Jinbo Du, Sifan Gu, Zhengyu Liu, Lingwei Li, Ning Zhao

引用次数: 0

ENSO’s impact on linear and nonlinear predictability of Antarctic sea ice ENSO对南极海冰线性和非线性可预测性的影响

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2025-02-27 DOI: 10.1038/s41612-025-00962-9

Yunhe Wang, Xiaojun Yuan, Yibin Ren, Xiaofeng Li, Arnold L. Gordon

{"title":"ENSO’s impact on linear and nonlinear predictability of Antarctic sea ice","authors":"Yunhe Wang, Xiaojun Yuan, Yibin Ren, Xiaofeng Li, Arnold L. Gordon","doi":"10.1038/s41612-025-00962-9","DOIUrl":"https://doi.org/10.1038/s41612-025-00962-9","url":null,"abstract":"While the influence of ENSO on Antarctic sea ice variability is well-known, its role in sea ice predictability, both linear and nonlinear, remains unexplored. This study utilizes deep learning models to quantify ENSO’s impact on Antarctic sea ice predictability. We find that ENSO events exert cross-timescale influences on sea ice’s subseasonal linear and nonlinear predictability. Within a 3-week lead time, ice persistence is the primary source of predictability. Beyond this period, ENSO becomes a key source of Antarctic sea ice predictability, with El Niño enhancing ice linear predictability more than La Niña. Specifically, El Niño improves ice linear predictability by 25.6%, 19.6%, and 30.4% in the A-B Sea, Ross Sea, and Indian Ocean, respectively, at an 8-week lead time. La Niña mainly enhances ice nonlinear predictability, particularly in the Ross Sea. We demonstrate that ENSO provides additional sources for Antarctic sea ice predictability primarily through generating more extensive ice anomalies. These insights deepen our understanding of sea ice predictability and are crucial for advancing forecasting models.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"32 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143507333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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

Intensified exposure to compound extreme heat and ozone pollution in summer across Chinese cities 中国城市夏季极端高温和臭氧复合污染加剧

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2025-02-27 DOI: 10.1038/s41612-025-00966-5

Jingling Su, Limin Jiao, Gang Xu

引用次数: 0

Dynamic configuration before quasi-biennial oscillation disruptions revealed from the perspective of planetary waves 从行星波的角度揭示准两年振荡中断前的动态结构

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2025-02-27 DOI: 10.1038/s41612-024-00874-0

Yang He, Xiaoqian Zhu, Zheng Sheng

引用次数: 0

Incomplete mass closure in atmospheric nanoparticle growth 大气纳米颗粒生长中的不完全质量闭合

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2025-02-26 DOI: 10.1038/s41612-025-00893-5

Dominik Stolzenburg, Nina Sarnela, Federico Bianchi, Jing Cai, Runlong Cai, Yafang Cheng, Lubna Dada, Neil M. Donahue, Hinrich Grothe, Sebastian Holm, Veli-Matti Kerminen, Katrianne Lehtipalo, Tuukka Petäjä, Juha Sulo, Paul M. Winkler, Chao Yan, Juha Kangasluoma, Markku Kulmala

{"title":"Incomplete mass closure in atmospheric nanoparticle growth","authors":"Dominik Stolzenburg, Nina Sarnela, Federico Bianchi, Jing Cai, Runlong Cai, Yafang Cheng, Lubna Dada, Neil M. Donahue, Hinrich Grothe, Sebastian Holm, Veli-Matti Kerminen, Katrianne Lehtipalo, Tuukka Petäjä, Juha Sulo, Paul M. Winkler, Chao Yan, Juha Kangasluoma, Markku Kulmala","doi":"10.1038/s41612-025-00893-5","DOIUrl":"https://doi.org/10.1038/s41612-025-00893-5","url":null,"abstract":"Nucleation and subsequent growth of new aerosol particles in the atmosphere is a major source of cloud condensation nuclei and persistent large uncertainty in climate models. Newly formed particles need to grow rapidly to avoid scavenging by pre-existing aerosols and become relevant for the climate and air quality. In the continental atmosphere, condensation of oxygenated organic molecules is often the dominant mechanism for rapid growth. However, the huge variety of different organics present in the continental boundary layer makes it challenging to predict nanoparticle growth rates from gas-phase measurements. Moreover, recent studies have shown that growth rates of nanoparticles derived from particle size distribution measurements show surprisingly little dependency on potentially condensable vapors observed in the gas phase. Here, we show that the observed nanoparticle growth rates in the sub-10 nm size range can be predicted in the boreal forest only for springtime conditions, even with state-of-the-art mass spectrometers and particle sizing instruments. We find that, especially under warmer conditions, observed growth is slower than predicted from gas-phase condensation. We show that only a combination of simple particle-phase reaction schemes, phase separation due to non-ideal solution behavior, or particle-phase diffusion limitations can explain the observed lower growth rates. Our analysis provides first insights as to why atmospheric nanoparticle growth rates above 10 nm h−1 are rarely observed. Ultimately, a reduction of experimental uncertainties and improved sub-10 nm particle hygroscopicity and chemical composition measurements are needed to further investigate the occurrence of such a growth rate-limiting process.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"185 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143495528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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

Importance of the vertical mixing process in the development of El Niño Modoki 垂直混合过程在El Niño Modoki发展中的重要性

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2025-02-26 DOI: 10.1038/s41612-025-00973-6

Tomoki Tozuka

引用次数: 0

How different is tropical cyclone precipitation over land and ocean? 热带气旋在陆地和海洋上的降水有何不同？

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2025-02-25 DOI: 10.1038/s41612-025-00970-9

Lihao Chen, Zhanhong Ma, Jianfang Fei

引用次数: 0

Rapid evolution of energetic lightning strokes in Mediterranean winter storms 地中海冬季风暴中高能雷击的快速演变

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2025-02-25 DOI: 10.1038/s41612-025-00965-6

I. Kolmašová, O. Santolík, A. Kolínská, S. Pédeboy, R. Lán, L. Uhlíř

引用次数: 0

Climate warming and influenza dynamics: the modulating effects of seasonal temperature increases on epidemic patterns 气候变暖和流感动态：季节性温度升高对流行病模式的调节作用

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2025-02-25 DOI: 10.1038/s41612-025-00968-3

Wenxi Ruan, Yinglin Liang, Zhaobin Sun, Xingqin An

{"title":"Climate warming and influenza dynamics: the modulating effects of seasonal temperature increases on epidemic patterns","authors":"Wenxi Ruan, Yinglin Liang, Zhaobin Sun, Xingqin An","doi":"10.1038/s41612-025-00968-3","DOIUrl":"https://doi.org/10.1038/s41612-025-00968-3","url":null,"abstract":"The underexplored impact of climate change on influenza outbreak severity and duration hampers our understanding of how climate-driven changes affect transmission dynamics. Our study employs the SIRS (Susceptible-Infectious-Recovered-Susceptible) model to simulate incremental temperature rises (2.5 °C, 5 °C, 7.5 °C, and 10 °C) in winter and summer. Results show warming significantly influences infections across seasonal, interannual, and decadal scales. Higher temperatures significantly impact infection rates, especially in autumn and winter, with long-lasting effects extending 5-6 years. Sustained warming lowers the total infection numbers compared to pre-warming levels. When winter and summer experience simultaneous warming, infection fluctuations during the warming period are mainly driven by winter warming. Winter warming also lowers the peak-to-trough infection ratio, reducing epidemic intensity fluctuations. Additionally, parameter choices can significantly affect the impact of warming on infection rates. Warming of varying intensity and duration can significantly impact influenza outbreaks, potentially altering their seasonal patterns in a global warming context.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"141 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143495523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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