npj Climate and Atmospheric Science最新文献

A low-dimensional recursive deep learning model for El Niño-Southern Oscillation simulation El Niño-Southern振荡模拟的低维递归深度学习模型

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2025-04-27 DOI: 10.1038/s41612-025-01053-5

Jiho Ko, Na-Yeon Shin, Jonghun Kam, Yoo-Geun Ham, Jong-Seong Kug

{"title":"A low-dimensional recursive deep learning model for El Niño-Southern Oscillation simulation","authors":"Jiho Ko, Na-Yeon Shin, Jonghun Kam, Yoo-Geun Ham, Jong-Seong Kug","doi":"10.1038/s41612-025-01053-5","DOIUrl":"https://doi.org/10.1038/s41612-025-01053-5","url":null,"abstract":"In this study, we develop a low-dimensional recursive model using deep learning (DL) to understand the dynamics of the El Niño-Southern Oscillation (ENSO). Unlike most existing research that relies on Coupled General Circulation Models (CGCMs), we explore a DL technique as an alternative approach to simulate ENSO characteristics. To replicate the observed stochastically excited oscillations, we incorporate stochastic noise into the recursive process of the DL model. Our long-term simulations demonstrate that the DL model effectively reproduces ENSO characteristics comparable to those captured by CGCMs. Additionally, we conduct experiments to analyze the interactions between ENSO and the Indian and Atlantic Oceans, evaluating their impacts on ENSO dynamics. Beyond capturing ENSO characteristics, the DL model exhibits skillful ENSO prediction capabilities. Using eXplainable AI (XAI) methods, we identify the contributions of each variable to ENSO predictability. Our findings suggest that this DL model serves as a valuable tool for understanding climate dynamics at a relatively low computational cost, providing an alternative to complex physically-based models.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"16 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143877857","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

Summer 2024 in northern Fennoscandia was very likely the warmest in 2000 years 芬诺斯坎迪亚北部2024年的夏天很可能是2000年来最温暖的

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2025-04-26 DOI: 10.1038/s41612-025-01046-4

Mika Rantanen, Samuli Helama, Jouni Räisänen, Hilppa Gregow

{"title":"Summer 2024 in northern Fennoscandia was very likely the warmest in 2000 years","authors":"Mika Rantanen, Samuli Helama, Jouni Räisänen, Hilppa Gregow","doi":"10.1038/s41612-025-01046-4","DOIUrl":"https://doi.org/10.1038/s41612-025-01046-4","url":null,"abstract":"Summer 2024 was exceptionally warm in northern Fennoscandia, with June-August mean temperatures at several long-term weather stations surpassing the long-standing record set in 1937. In this region, summer mean temperatures have been reconstructed from tree-ring proxies, which provide annually resolved and millennium-long records of past climate. Here we show, using in-situ observations and two different tree-ring reconstructions, that summer 2024 was the warmest summer in 2000 years in northern Fennoscandia. Employing an attribution method based on Coupled Model Intercomparison Project Phase 6 climate models, we further estimate that climate change increased the likelihood of this extreme season by a factor of 93 (5–95% uncertainty range 19–881) and increased the temperature an additional 2.1 °C (1.4–2.8 °C). Atmospheric circulation patterns influencing both summers 1937 and 2024 were largely similar, suggesting a comparable large-scale circulation influence. Our findings highlight the impact of climate change for the contemporary heat extremes in Fennoscandia, indicating that the warming of summer climate is emerging from its range of natural climate variability over the last two millennia.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"34 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143877903","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

Disentangling anthropogenic and dynamic contributions to recent ocean warming 解开人为和动力因素对近期海洋变暖的影响

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2025-04-26 DOI: 10.1038/s41612-025-01043-7

Jiheun Lee, Rémi Tailleux, Till Kuhlbrodt

{"title":"Disentangling anthropogenic and dynamic contributions to recent ocean warming","authors":"Jiheun Lee, Rémi Tailleux, Till Kuhlbrodt","doi":"10.1038/s41612-025-01043-7","DOIUrl":"https://doi.org/10.1038/s41612-025-01043-7","url":null,"abstract":"As the ocean absorbs over 90% of excess radiative heat, recent ocean warming is shaped by a combination of anthropogenic surface heat gain and dynamical processes redistributing heat. To distinguish these contributions, we introduce a novel framework that decomposes temperature changes into three components: ‘spice’ (density-compensated variability) and ‘heave’ (density-contributing variability), with heave further divided into ‘passive’ (net warming) and ‘dynamic’ (redistribution) contributions. Passive heave captures anthropogenic warming subducted along isopycnals, while spice and dynamic heave, which globally sum to zero, represent heat redistribution. Observations and climate models demonstrate general agreement on passive heave, establishing it as a key oceanic fingerprint of anthropogenic climate change. In contrast, dynamic heave, driven by interannual-to-decadal variability, exhibits significant spatial heterogeneity, with notable discrepancies between models and observations. This framework links ocean heat uptake to sea-level change, with passive heave driving global thermosteric rise and dynamic heave contributing to regional dynamic sea level changes.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"6 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143877858","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

FuXi-DA: a generalized deep learning data assimilation framework for assimilating satellite observations FuXi-DA：用于同化卫星观测数据的广义深度学习数据同化框架

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2025-04-26 DOI: 10.1038/s41612-025-01039-3

Xiaoze Xu, Xiuyu Sun, Wei Han, Xiaohui Zhong, Lei Chen, Zhiqiu Gao, Hao Li

{"title":"FuXi-DA: a generalized deep learning data assimilation framework for assimilating satellite observations","authors":"Xiaoze Xu, Xiuyu Sun, Wei Han, Xiaohui Zhong, Lei Chen, Zhiqiu Gao, Hao Li","doi":"10.1038/s41612-025-01039-3","DOIUrl":"https://doi.org/10.1038/s41612-025-01039-3","url":null,"abstract":"Data assimilation (DA), as an indispensable component within contemporary Numerical Weather Prediction (NWP) systems, plays a crucial role in generating the analysis that significantly impacts forecast performance. Nevertheless, developing an efficient DA system poses significant challenges, particularly in establishing intricate relationships between the background field and the vast amount of multi-source observation data within limited operational time windows. Recently, Deep learning-based (DL-based) weather forecast models have shown promise in matching, even surpassing, the leading operational NWP models worldwide. This success motivates the exploration of establishing DL-based DA frameworks. DL models possess multi-modal modeling capabilities, enabling the fusion of multi-source data in the feature space, which is very similar to the process of assimilating multi-source observational data in DA systems. In this study, we introduce FuXi-DA, a generalized DL-based DA framework for assimilating satellite observations. By assimilating data from Advanced Geosynchronous Radiation Imager aboard Fengyun-4B, FuXi-DA consistently mitigates analysis errors and significantly improves forecast performance. Furthermore, FuXi-DA has been validated against established atmospheric physics, demonstrating its consistency and reliability.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"31 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143877902","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

Aerosol inhibition on photochemical surface ozone formation under future climate and air quality scenarios 未来气候和空气质量情景下气溶胶对光化学表面臭氧形成的抑制作用

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2025-04-25 DOI: 10.1038/s41612-025-01048-2

G. S. Gopikrishnan, D. M. Westervelt, J. Kuttippurath

引用次数: 0

Glacier meltwater has limited contributions to the total runoff in the major rivers draining the Tibetan Plateau 冰川融水对青藏高原主要河流径流量的贡献有限

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2025-04-25 DOI: 10.1038/s41612-025-01060-6

Yi Nan, Fuqiang Tian, Jeffrey McDonnell, Guangheng Ni, Lide Tian, Zongxing Li, Denghua Yan, Xinghui Xia, Ting Wang, Songjun Han, Kunbiao Li

引用次数: 0

Oxygen-rich anionic metal silicate clusters as nucleation seeds for noctilucent clouds 富氧阴离子金属硅酸盐团簇作为夜光云的成核种子

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2025-04-23 DOI: 10.1038/s41612-025-01019-7

Joan Mariñoso Guiu, Joost M. Bakker, Thorsten M. Bernhardt, John M. C. Plane, Stefan T. Bromley, Sandra M. Lang

{"title":"Oxygen-rich anionic metal silicate clusters as nucleation seeds for noctilucent clouds","authors":"Joan Mariñoso Guiu, Joost M. Bakker, Thorsten M. Bernhardt, John M. C. Plane, Stefan T. Bromley, Sandra M. Lang","doi":"10.1038/s41612-025-01019-7","DOIUrl":"https://doi.org/10.1038/s41612-025-01019-7","url":null,"abstract":"Silicate-based meteoric smoke particles (MSPs) resulting from extraterrestrial dust impacting on the upper atmosphere are likely involved in seeding the formation of mesospheric ice-based noctilucent clouds (NLCs). However, the detailed physicochemical properties of MSP seeds remain elusive. Considering that ice formation is sensitive to MSP charging efficiency, here we focus on species which can efficiently capture charge. As in situ MSP characterisation is highly challenging, we mimic atmospheric MSP formation using laser ablation and collisional cooling to produce small anionic magnesium silicate clusters. Our detailed experimental and theoretical characterisation shows that these clusters have unusual oxygen-rich structures. Moreover, the corresponding neutral clusters have extraordinarily high adiabatic electron affinities and 3-18% charging efficiencies, which is remarkably consistent with estimates required by models to simulate atmospheric measurements. Overall, our highly oxidised anionic silicate clusters exhibit all necessary chemical, electronic and optical properties to be highly credible MSP-based seed candidates for NLC nucleation.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"69 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143862915","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

Growing human-induced climate change fingerprint in regional weekly fire extremes 越来越多的人为气候变化在区域性每周极端火灾中留下了印记

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2025-04-23 DOI: 10.1038/s41612-025-01021-z

Sifang Feng, Jakob Zscheischler, Zengchao Hao, Emanuele Bevacqua

{"title":"Growing human-induced climate change fingerprint in regional weekly fire extremes","authors":"Sifang Feng, Jakob Zscheischler, Zengchao Hao, Emanuele Bevacqua","doi":"10.1038/s41612-025-01021-z","DOIUrl":"https://doi.org/10.1038/s41612-025-01021-z","url":null,"abstract":"Wildfires cause large damage to natural and human systems. Despite the clear connection between human-induced climate change and increased fire weather risk, a global, systematic attribution of observed extreme fires to human-induced climate change is lacking. Here, we address this gap by first linking observed regional weekly burned area extremes (>85th percentile) to the fire weather index (FWI) during the fire seasons of 2002–2015 via a logistic regression model, and then using simulations from climate models to quantify the impact of human-induced climate change. Focusing on regions with good predictability of the statistical model, we find that human-induced climate change was responsible for a fraction equal to 8% (±4%, standard deviation across climate models) of the predicted probability of more than 700 regional fire extremes on average, thereby increasing the probability of experiencing a fire extreme across 15 out of 19 analysed regions. While higher temperature is the main driver of the increased fire extreme probability, shifts in precipitation, relative humidity, and/or wind speed substantially modulated fire changes across many regions. Mainly because of warming, the probability of extreme fires attributable to human-induced climate change increased by 5.2%/decade globally over 2002–2015, in line with an acceleration of the climate-driven enhancement of fire extremes over the last decades that may continue in the near future. These findings highlight the urgent need for sustainable fire management strategies.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"47 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143862916","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

Stratospheric ozone depletion has contributed to the recent tropical La Niña-like cooling pattern 平流层臭氧消耗促成了近期热带地区类似拉尼娜现象的降温模式

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2025-04-22 DOI: 10.1038/s41612-025-01020-0

Yue Dong, Lorenzo M. Polvani, Yen-Ting Hwang, Mark R. England

引用次数: 0

Predictable equatorial Atlantic variability from atmospheric convection-ocean coupling 大气对流-海洋耦合带来的可预测赤道大西洋变率

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2025-04-22 DOI: 10.1038/s41612-025-01041-9

Hyacinth C. Nnamchi, Mojib Latif

引用次数: 0