npj Climate and Atmospheric Science最新文献_第6页

Toward skillful forecasting of super El Niño events using a diffusion-based westerly wind burst parameterization 利用基于扩散的西风爆发参数化技术预测超级El Niño事件

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2025-07-19 DOI: 10.1038/s41612-025-01158-x

Chaopeng Ji, Mu Mu, Bo Qin, Tao Lian, Shijin Yuan, Jie Feng, Xunshu Song, Yuntao Wei, Guokun Dai, Jinyu Wang, Xianghui Fang

{"title":"Toward skillful forecasting of super El Niño events using a diffusion-based westerly wind burst parameterization","authors":"Chaopeng Ji, Mu Mu, Bo Qin, Tao Lian, Shijin Yuan, Jie Feng, Xunshu Song, Yuntao Wei, Guokun Dai, Jinyu Wang, Xianghui Fang","doi":"10.1038/s41612-025-01158-x","DOIUrl":"https://doi.org/10.1038/s41612-025-01158-x","url":null,"abstract":"Forecasting super El Niño remains challenging, partly due to poor representation of westerly wind bursts (WWBs). We developed an artificial intelligence-based denoising diffusion probabilistic model (DDPM) to skillfully parameterize WWBs, capturing their joint modulation by oceanic and atmospheric processes. The DDPM-based scheme effectively captures observed WWBs’ characteristics (e.g., frequency, intensity, and spatial center). When implemented in the Community Earth System Model, it outperforms both the control (CTRL, without WWBs parameterization) and conventional warm pool eastern edge (WPEE)-dependent parameterization in predicting intensity and seasonal phase-locking for super El Niños (1982/83, 1997/98, 2015/16). This improvement stems from DDPM’s realistic WWBs representation, correcting CTRL and WPEE’s biases of overly weak and westward-shifted winds during El Niño growth. Consequently, DDPM produces more realistic eastern Pacific sea surface temperature anomaly warming patterns. These findings underscore WWB's accuracy as key to super El Niño prediction and demonstrate machine learning’s potential for WWB's parameterization.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"210 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144664568","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

A Generative Framework for Probabilistic, Spatiotemporally Coherent Downscaling of Climate Simulation 气候模拟的概率、时空相干降尺度生成框架

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2025-07-18 DOI: 10.1038/s41612-025-01157-y

Jonathan Schmidt, Luca Schmidt, Felix M. Strnad, Nicole Ludwig, Philipp Hennig

{"title":"A Generative Framework for Probabilistic, Spatiotemporally Coherent Downscaling of Climate Simulation","authors":"Jonathan Schmidt, Luca Schmidt, Felix M. Strnad, Nicole Ludwig, Philipp Hennig","doi":"10.1038/s41612-025-01157-y","DOIUrl":"https://doi.org/10.1038/s41612-025-01157-y","url":null,"abstract":"Local climate information is crucial for impact assessment and decision-making, yet coarse global climate simulations cannot capture small-scale phenomena. Current statistical downscaling methods infer these phenomena as temporally decoupled spatial patches. However, to preserve physical properties, estimating spatio-temporally coherent high-resolution weather dynamics for multiple variables across long time horizons is crucial. We present a novel generative framework that uses a score-based diffusion model trained on high-resolution reanalysis data to capture the statistical properties of local weather dynamics. After training, we condition on coarse climate model data to generate weather patterns consistent with the aggregate information. As this predictive task is inherently uncertain, we leverage the probabilistic nature of diffusion models and sample multiple trajectories. We evaluate our approach with high-resolution reanalysis information before applying it to the climate model downscaling task. We then demonstrate that the model generates spatially and temporally coherent weather dynamics that align with global climate output.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"30 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144652371","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

Relative contribution of anthropogenic warming to the unprecedented heatwave in South America in 2023 人为变暖对2023年南美洲前所未有的热浪的相对贡献

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2025-07-18 DOI: 10.1038/s41612-025-01142-5

Congren Li, Xiaojing Yu, Jianghua Zheng, Mingjiang Deng, Wanqiang Han, Ping Ma

{"title":"Relative contribution of anthropogenic warming to the unprecedented heatwave in South America in 2023","authors":"Congren Li, Xiaojing Yu, Jianghua Zheng, Mingjiang Deng, Wanqiang Han, Ping Ma","doi":"10.1038/s41612-025-01142-5","DOIUrl":"https://doi.org/10.1038/s41612-025-01142-5","url":null,"abstract":"In 2023, South America experienced an unprecedented heatwave that threatened socioeconomic structures and ecosystems. This study uses attribution analysis to evaluate the contributions of atmospheric circulation patterns and human factors to the heatwave's probability and intensity. The 2023 heatwave is a 1-in-130-year event and a 1-in-65-year event, with and without considering the 2023 heatwave in the fitting, respectively. The large-scale meteorological analysis revealed that the heatwave was driven by an anomalously high-pressure system that formed a heat dome from dry, hot air columns. ALL (all-forcing scenario) and GHG (greenhouse gas scenario) simulations indicate the likelihood of future extreme heatwaves increases by 28.45% [27.60%, 29.30%] (90% confidence interval) and 30.42% [29.51%, 31.33%] (90% confidence interval), respectively, based on data from 1850 to 2014. Insights from Coupled Model Intercomparison Project Phase 6 (CMIP6) models emphasize that human-induced warming significantly contributes to heatwaves, which highlights the need for effective climate adaptation and mitigation strategies.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"29 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144652372","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

A dual-core model for ENSO diversity: unifying model hierarchies for realistic simulations ENSO多样性的双核模型：现实模拟的统一模型层次

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2025-07-14 DOI: 10.1038/s41612-025-01164-z

Jinyu Wang, Xianghui Fang, Nan Chen, Bo Qin, Mu Mu, Chaopeng Ji

{"title":"A dual-core model for ENSO diversity: unifying model hierarchies for realistic simulations","authors":"Jinyu Wang, Xianghui Fang, Nan Chen, Bo Qin, Mu Mu, Chaopeng Ji","doi":"10.1038/s41612-025-01164-z","DOIUrl":"https://doi.org/10.1038/s41612-025-01164-z","url":null,"abstract":"Despite advances in climate modeling, simulating the El Niño-Southern Oscillation (ENSO) remains challenging due to its spatiotemporal diversity and complexity. To address this, we build upon existing model hierarchies to develop a new unified modeling platform, which provides practical, scalable, and accurate tools for advancing ENSO research. Within this framework, we introduce a dual-core ENSO model (DCM) that integrates two widely used ENSO modeling approaches: a linear stochastic model confined to the equator and a nonlinear intermediate model extending off-equator. The stochastic model ensures computational efficiency and statistical accuracy. It captures essential ENSO characteristics and reproduces the observed non-Gaussian statistics. Meanwhile, the nonlinear model assimilates pseudo-observations from the stochastic model while resolving key air-sea interactions, such as oceanic feedback balances and spatial patterns of sea surface temperature anomalies during El Niño peaks. The DCM effectively captures the realistic dynamical and statistical features of the ENSO diversity and complexity. The computational efficiency of the DCM also facilitates a rapid generation of extended ENSO datasets, overcoming observational limitations.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"15 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144630220","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

Future increase in European compound events where droughts end in heavy precipitation 未来欧洲复合事件增加，干旱以强降水结束

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2025-07-12 DOI: 10.1038/s41612-025-01139-0

Birthe Marie Steensen, Gunnar Myhre, Øivind Hodnebrog, Erich Fischer

引用次数: 0

Linking North Pacific eastern subtropical mode water to ENSO: precursor signatures and subtropical cell pathways 连接北太平洋东部副热带模态水与ENSO：前体特征和副热带细胞通路

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2025-07-12 DOI: 10.1038/s41612-025-01147-0

LingLing Liu, Jin-Yi Yu, Fan Wang, Jianing Wang, YongFu Lin

引用次数: 0

Diversity of La Niña onset La Niña发病的多样性

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2025-07-11 DOI: 10.1038/s41612-025-01141-6

Xiao Pan, Tim Li

引用次数: 0

Potential tropical cyclone movement and intensification factors imaged by spaceborne SAR 星载SAR成像的潜在热带气旋运动和增强因素

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2025-07-11 DOI: 10.1038/s41612-025-01162-1

Guosheng Zhang, Xiaofeng Li, Pakwai Chan, Hui Su

引用次数: 0

Complex gas-particle partitioning of nitro-phenolic compounds: field-based insights and determination of apparent activity coefficient 硝基酚类化合物的复杂气粒分配：基于现场的见解和表观活度系数的测定

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2025-07-11 DOI: 10.1038/s41612-025-01156-z

Yi Chen, Men Xia, Penggang Zheng, Yumin Li, Zhouxing Zou, Shengrui Tong, Kun Li, Xin Feng, Lirong Hui, Qi Yuan, Jinjian Li, Jian Zhen Yu, Shuncheng Lee, Tao Wang, Zhe Wang

{"title":"Complex gas-particle partitioning of nitro-phenolic compounds: field-based insights and determination of apparent activity coefficient","authors":"Yi Chen, Men Xia, Penggang Zheng, Yumin Li, Zhouxing Zou, Shengrui Tong, Kun Li, Xin Feng, Lirong Hui, Qi Yuan, Jinjian Li, Jian Zhen Yu, Shuncheng Lee, Tao Wang, Zhe Wang","doi":"10.1038/s41612-025-01156-z","DOIUrl":"https://doi.org/10.1038/s41612-025-01156-z","url":null,"abstract":"Gas–particle partitioning (GPP) of oxygenated semi–volatile organic compounds (SVOCs) is crucial for atmospheric organic aerosol formation, yet large uncertainties persist in its simulation due to challenges in obtaining accurate parameters. This study focuses on nitro–phenolic species (NPs), representative oxygenated SVOCs impacting solar radiative balance and atmospheric chemistry. Concurrent measurements of gaseous and particulate NPs at a subtropical coastal site showed particulate fractions ranging from 8.6% to 53%, which deviated from traditional theoretical estimates by factors of 0.26 to 104. To address these discrepancies, a field-based activity coefficient (ζ) was derived by integrating measured parameters and theoretical considerations. Incorporating ζ into a box model significantly improved simulations for mono–NPs and uncovered a more complex GPP process for di–NPs than previously recognized. The successful application of ζ in a regional model highlights its broader applicability and calls for more quantitative studies for various SVOCs.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"149 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144611246","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

Continuous gap-filled atmospheric N2O record for the past 800,000 years using machine learning techniques 使用机器学习技术记录过去80万年的连续间隙填充大气N2O记录

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2025-07-10 DOI: 10.1038/s41612-025-01153-2

Nasrin Salehnia, Eunji Byun, Jinho Ahn, Kajal Kumari

{"title":"Continuous gap-filled atmospheric N2O record for the past 800,000 years using machine learning techniques","authors":"Nasrin Salehnia, Eunji Byun, Jinho Ahn, Kajal Kumari","doi":"10.1038/s41612-025-01153-2","DOIUrl":"https://doi.org/10.1038/s41612-025-01153-2","url":null,"abstract":"Ice cores are crucial archives of atmospheric greenhouse gas (GHG) concentrations. Despite the importance of nitrous oxide (N2O) as a GHG, existing ice core records contain gaps, particularly during glacial periods, due to the high dust content in ice samples that may cause in situ chemical or biological reactions, increasing N2O concentration. By developing an iterative process that applies machine learning (ML) models to existing data on CO2, CH4, and N2O from Antarctic ice cores, we simulated a continuous time series of atmospheric N2O concentrations for the past 800,000 years (kyr). The continuous N2O record allows us to investigate long-term variability and potential climate feedback that would otherwise remain obscured, as spectral analysis of this record has revealed significant N2O periodicities of ~100, 41, and 23 kyr. While ML-based simulations cannot fully replace real, artifact-free measurements, they provide a valuable complementary approach to interpreting past climate dynamics, especially when empirical data are limited or compromised.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"4 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144594907","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