npj Climate and Atmospheric Science最新文献_第4页

Methane emissions from penguin colonies reshape the natural greenhouse gas budget 企鹅聚居地的甲烷排放重塑了自然温室气体收支

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2026-09-23 DOI: 10.1038/s41612-026-01556-9

Alejandro Román,Silvia Amaya-Vías,Manuel Díez-Minguito,Antonio Tovar-Sánchez,Gabriel Navarro,Susana Flecha,I. Emma Huertas

引用次数: 0

Physically constrained machine learning improves radiation, clouds, and albedo forecasts globally 物理约束的机器学习可以改善全球的辐射、云和反照率预测

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2026-09-21 DOI: 10.1038/s41612-026-01550-1

Huang Qiusheng, Xiaohui Zhong, Junyu Cai, Linfan Zhou, Zijian Zhu, Wenxu Qian, Lei Chen, Libo Wu, Dazhi Yang, Hao Li

{"title":"Physically constrained machine learning improves radiation, clouds, and albedo forecasts globally","authors":"Huang Qiusheng, Xiaohui Zhong, Junyu Cai, Linfan Zhou, Zijian Zhu, Wenxu Qian, Lei Chen, Libo Wu, Dazhi Yang, Hao Li","doi":"10.1038/s41612-026-01550-1","DOIUrl":"https://doi.org/10.1038/s41612-026-01550-1","url":null,"abstract":"Clouds, radiation, and surface albedo are essential to Earth’s energy balance and have a significant impact on applications such as solar energy, yet they remain challenging to represent accurately in global forecast systems. Recent machine learning-based weather forecasting models have matched or outperformed conventional numerical models for large-scale dynamical variables, but most do not explicitly predict clouds, radiation, or albedo, limiting their physical fidelity. Here, we present FuXi-RTM, a hybrid machine learning model that integrates a differentiable machine learning surrogate of a widely used radiative transfer model (MLRTM) directly within global weather forecasts. By jointly predicting clouds, surface albedo, and radiative fluxes, and by allowing radiative transfer gradients to constrain the forecast state, FuXi-RTM improves radiative consistency while maintaining computational efficiency. Against reanalysis data, independent ground-based station observations, and satellite-derived radiation products, FuXi-RTM improves forecasts of shortwave radiation and cloud-related variables relative to unconstrained variants and state-of-the-art physics-based models. These results suggest that differentiable physical constraints can improve machine learning-based weather forecasts for both Earth system prediction and solar energy applications.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"1 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2026-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149010569","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

Reduced trapping efficiency of mesoscale eddies under eddy-eddy interactions 涡旋-涡旋相互作用下中尺度涡旋捕获效率降低

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2026-09-19 DOI: 10.1038/s41612-026-01551-0

Tongya Liu, Xiaoming Zhai, Weijie Sun, Dake Chen

{"title":"Reduced trapping efficiency of mesoscale eddies under eddy-eddy interactions","authors":"Tongya Liu, Xiaoming Zhai, Weijie Sun, Dake Chen","doi":"10.1038/s41612-026-01551-0","DOIUrl":"https://doi.org/10.1038/s41612-026-01551-0","url":null,"abstract":"Oceanic mesoscale eddies are commonly assumed to act as coherent structures that trap and transport water masses over long distances. However, recent Lagrangian studies suggest that long-lived coherent structures in the ocean are much more limited than implied by Eulerian eddy boundaries. In this study, surface drifters are used to examine the material transport capabilities of mesoscale eddies, and it is found that drifters initially enclosed by eddies tend to rapidly leak out after only a few days on average, indicating that these drifters are not effectively trapped and coherently transported by mesoscale eddies. Furthermore, a series of numerical experiments suggests that while an isolated eddy can effectively transport initially enclosed water parcels, significant water leakage occurs in the presence of multiple eddies, which may be associated with eddy–eddy interactions. And the degree of this leakage is found to be positively correlated with the intensity of the background strain field. Our results suggest that, in realistic multi-eddy environments, eddy stirring may contribute more significantly to material transport than eddy trapping, with broad implications for heat and biogeochemical tracer redistribution and for the representation of eddy transport in climate models.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"47 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2026-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149010570","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

Is the AMV teleconnection to the tropical Pacific robust? A multi-model large ensemble study AMV与热带太平洋的远程连接是否可靠？多模型大系综研究

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2026-09-18 DOI: 10.1038/s41612-026-01548-9

Arundhati Kalyan, Amanda C. Maycock, Jeff R. Knight, Yohan Ruprich-Robert

引用次数: 0

Deep learning trained on high-fidelity climate model simulations extends the skillful prediction of Northern Tropical Atlantic SST anomalies 在高保真气候模式模拟上训练的深度学习扩展了对北热带大西洋海温异常的熟练预测

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2026-09-16 DOI: 10.1038/s41612-026-01546-x

Ao Liu, Jinqing Zuo, Hui Gao, Steven C. Hardiman, Lijuan Chen, Junhu Zhao, Jiacan Yuan

{"title":"Deep learning trained on high-fidelity climate model simulations extends the skillful prediction of Northern Tropical Atlantic SST anomalies","authors":"Ao Liu, Jinqing Zuo, Hui Gao, Steven C. Hardiman, Lijuan Chen, Junhu Zhao, Jiacan Yuan","doi":"10.1038/s41612-026-01546-x","DOIUrl":"https://doi.org/10.1038/s41612-026-01546-x","url":null,"abstract":"Boreal spring sea surface temperature (SST) anomalies in the northern tropical Atlantic (NTA) are key drivers of global climate extremes, yet their prediction remains challenging for state-of-the-art dynamical models. Deep learning offers promise for seasonal SST prediction but is limited by data scarcity and weak physical interpretability. Here, we develop a convolutional neural network (CNN) framework for NTA prediction and demonstrate that physics-informed training data selection improves performance. Specifically, selecting CMIP6 models that realistically capture the ENSO–NTA teleconnection, rather than using all the CMIP6 models, significantly enhances predictive skill. The CNN trained on these selected models extends effective predictions to 8 lead months, compared to 7 months in a multi-model ensemble of dynamic models, with notable improvements in boreal winter and spring. It also slightly outperforms dynamical models in predicting extreme spring NTA events. Further analysis shows that the model captures physically consistent precursors, with predictability governed by the interplay between ENSO forcing and local ocean–atmosphere variability. These results highlight the value of physics-informed data selection in deep learning and its potential to improve prediction of NTA SST anomalies.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"19 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2026-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149010572","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 new event-scale evaluation framework suggests underestimated skill of WRF-HAILCAST model in climatological hail simulations 一个新的事件尺度评价框架表明WRF-HAILCAST模式在气候冰雹模拟中的技能被低估

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2026-09-16 DOI: 10.1038/s41612-026-01538-x

Gaojie Xu, Tingfeng Dou, Shuting Guan, Yifan Yang

{"title":"A new event-scale evaluation framework suggests underestimated skill of WRF-HAILCAST model in climatological hail simulations","authors":"Gaojie Xu, Tingfeng Dou, Shuting Guan, Yifan Yang","doi":"10.1038/s41612-026-01538-x","DOIUrl":"https://doi.org/10.1038/s41612-026-01538-x","url":null,"abstract":"Hail simulation remains challenging in convection-permitting models, and diagnosing bias pathways is essential for targeted improvement. We developed a framework for evaluating the performance of WRF–HAILCAST in hail simulations from the perspective of mesoscale convection. Across 1,502 hail events in China, the model reproduced hail-swath morphology in 50.87% of cases. Among these cases, 53.4% also showed hail-size distributions consistent with observations. Biases emerged at distinct stages of the simulation chain. In 30.36% of events, displacement of the simulated convective system shifted the entire hail footprint, indicating an upstream positional error. Extent biases were not primarily caused by a prolonged hail lifecycle. Instead, both overestimation and underestimation of hail extent were tied more closely to storm realization and hail diagnosis than to CAPE and shear backgrounds, as they depended on where WRF generated mature precipitating cores and where HAILCAST initiated and grew hail. This event-scale framework offers a new perspective on WRF–HAILCAST evaluation and reveals bias pathways often obscured in cell-based verification, tracing large-sample biases across the hail-simulation chain, from large-scale forcing and the mesoscale convective environment to storm organization, hail initiation, and growth.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"17 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2026-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149010573","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

Combining AI and numerical models for improving short-medium range precipitation prediction 结合人工智能与数值模式改进中短期降水预报

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2026-09-15 DOI: 10.1038/s41612-026-01547-w

Hanbing Kong, Guoxing Chen, Ziyin Zhang, Wei-Chyung Wang, Jie Feng, Guihua Wang, Yijun Zhang, Yuejian Zhu

{"title":"Combining AI and numerical models for improving short-medium range precipitation prediction","authors":"Hanbing Kong, Guoxing Chen, Ziyin Zhang, Wei-Chyung Wang, Jie Feng, Guihua Wang, Yijun Zhang, Yuejian Zhu","doi":"10.1038/s41612-026-01547-w","DOIUrl":"https://doi.org/10.1038/s41612-026-01547-w","url":null,"abstract":"Short-to-medium-range precipitation forecasts, critical for water resource management and flood risk mitigation, remain challenging for both conventional numerical weather models (NWMs) and rapidly-advancing artificial intelligence (AI)-based models. We present an AI-NWM hybrid approach to improve this task over the Chinese mainland. The approach develops an AI-based model that predicts 24-hour total precipitation using meteorological fields, bypassing uncertainties in NWM cloud parameterizations, and then drives it with NWM-predicted meteorological fields to produce multi-lead daily precipitation forecasts, leveraging the physical consistency of NWM forecasts. Using meteorological forecasts from the National Centers for Environmental Prediction Global Forecast System (GFS), the approach significantly enhances GFS precipitation prediction accuracy. For forecasts with leads of 1–16 days, the root-mean-square error drops by 16.8%, and the pattern correlation coefficient rises by 22.1%, extending the reliable horizon by nearly 2 days. Higher or comparable equitable threat scores across 1–100 mm day−1 thresholds confirm its reliability.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"31 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2026-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149010574","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

Eurasian Summertime Intraseasonal Oscillation and its impact on compound hot-dry extremes 欧亚大陆夏季季内振荡及其对复合干热极端天气的影响

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2026-09-15 DOI: 10.1038/s41612-026-01549-8

Jeong-Hun Kim, Yu Kosaka, Joowan Kim

{"title":"Eurasian Summertime Intraseasonal Oscillation and its impact on compound hot-dry extremes","authors":"Jeong-Hun Kim, Yu Kosaka, Joowan Kim","doi":"10.1038/s41612-026-01549-8","DOIUrl":"https://doi.org/10.1038/s41612-026-01549-8","url":null,"abstract":"Mid- to high-latitude intraseasonal dynamics remain an underappreciated driver of summertime compound extremes over the Eurasian continent. Here, we identify the Eurasian Summertime Intraseasonal Oscillation (ESISO), a coherent propagating intraseasonal mode defined by the leading EOF pair of Eurasian summertime surface air temperature variability, using JRA-3Q reanalysis, and examine its future changes through large-ensemble climate simulations (d4PDF). The ESISO propagates southeastward from the Western Siberian Plain toward East Asia via Rossby wave energy dispersion, maintaining a predominantly equivalent barotropic structure. This propagation exerts striking phase-dependent control on compound hot-dry extremes across the Eurasian continent: the probability of simultaneously exceeding the 90th percentile thresholds of daily maximum temperature (TMX) and vapor pressure deficit (VPD) increases approximately 20-fold over East Asia during warm phases compared to cold phases (15.8% vs 0.8%). Under +4 K warming, the fundamental spatial structure of the ESISO remains robust, while the frequency of intense events (amplitude > 2σ) increases significantly in most phases and the associated anomalies strengthen modestly, amplifying compound hot-dry extreme risk along the propagation pathway. These results establish the ESISO as a distinct mid- to high-latitude contributor to Eurasian compound extremes that complements existing tropical and subtropical forcing frameworks, and as a key dynamical contributor with implications for subseasonal prediction of heat-drought co-occurrences and climate risk management across the Eurasian continent.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"20 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2026-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149010575","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

Warming of the subpolar North Pacific accelerated by sea ice retreat and wind changes 由于海冰退缩和风的变化，北太平洋亚极地的变暖加速了

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2026-09-14 DOI: 10.1038/s41612-026-01541-2

Kai Ge, Yuanlong Li, Jing Duan, Pengfei Lin, Lijing Cheng, Haibo Bi, Fan Wang

{"title":"Warming of the subpolar North Pacific accelerated by sea ice retreat and wind changes","authors":"Kai Ge, Yuanlong Li, Jing Duan, Pengfei Lin, Lijing Cheng, Haibo Bi, Fan Wang","doi":"10.1038/s41612-026-01541-2","DOIUrl":"https://doi.org/10.1038/s41612-026-01541-2","url":null,"abstract":"Climate models predict that the Pacific will become the foremost reservoir of human-induced heat in the 21st century among all oceans, with the subpolar North Pacific (SPNP) emerging as the critical region for heat uptake. Recent observations detect alarming warming rates across the Sea of Okhotsk, the Bering Sea, and the Gulf of Alaska. Yet, processes by which these seas absorb and store the heat remain unclear. Here, by combining observational datasets and model experiments, we reveal that the heat uptake in these SPNP seas has accelerated since the 1970s due to sea-ice retreat and shifts in large-scale winds. Specifically, a decline in winter sea ice growth in shelf regions of the SPNP amplifies surface atmospheric warming. The warming in surface air temperature suppresses sensible heat release in the SPNP interior, resulting in increased heat uptake. Furthermore, altered North Pacific winds spin up the subpolar circulation gyre, propelling increased heat transport from lower latitudes into the SPNP seas. The surface-intensified warming in the SPNP enhances stratification and shoals the mixed layer, triggering more marine heatwaves and disrupting biogeochemical cycles.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"155 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2026-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149010576","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

Seasonal shifts in regional and local controls on ambient isoprene in a semi-arid African savanna 半干旱非洲稀树草原区域和地方环境异戊二烯控制的季节变化

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2026-09-08 DOI: 10.1038/s41612-026-01540-3

Yang Liu,Toni Tykkä,Arnaud P. Praplan,Simon Schallhart,Kelebogile B. Mfundisi,Baagi T. Mmereki,Ville Vakkari,Heidi Hellén

引用次数: 0