npj Climate and Atmospheric Science最新文献

Uncovering missing Eurasian blocking events and their robust role in East Asian winter extremes: a region-dependent detection approach 揭示欧亚大陆缺失的阻断事件及其在东亚冬季极端事件中的强大作用：一种依赖区域的检测方法

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2026-04-27 DOI: 10.1038/s41612-026-01415-7

Hayeon Noh, Ho-Young Ku, Mi-Kyung Sung, Baek-Min Kim

引用次数: 0

Generative machine learning for skilful 3D radar nowcasting 生成机器学习技术的三维雷达临近预报

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2026-04-27 DOI: 10.1038/s41612-026-01407-7

Jiaquan Wan, Tao Yang, Qianhua Yu, Ranyu Liu, Weidong Li, Hao Song, Xing Wang, Junchao Wang, Fengchang Xue, Ziniu Xiao, Chunxiang Shi, Quan J. Wang, Jingyu Wang, Baoxiang Pan

{"title":"Generative machine learning for skilful 3D radar nowcasting","authors":"Jiaquan Wan, Tao Yang, Qianhua Yu, Ranyu Liu, Weidong Li, Hao Song, Xing Wang, Junchao Wang, Fengchang Xue, Ziniu Xiao, Chunxiang Shi, Quan J. Wang, Jingyu Wang, Baoxiang Pan","doi":"10.1038/s41612-026-01407-7","DOIUrl":"https://doi.org/10.1038/s41612-026-01407-7","url":null,"abstract":"Timely, reliable, and robust radar nowcasting is an essential tool for extreme precipitation predictions and weather-dependent decision-making, yet existing methods still face two limitations: effective utilization of 3D radar data and robust prediction with occlusions or missing observations. We propose EchoCast-3D, a generative AI-based 3D ensemble probabilistic nowcasting model. Based on a Mask Diffusion Transformer backbone and trained using 3D radar echo data, EchoCast-3D delivers spatiotemporally consistent 3D forecasts, and generates reliable and complete predictions even when observations contain missing areas, a situation common in operational practice. In multiple real-world rainstorm case studies, EchoCast-3D precisely predicts the 3D evolution of severe convective systems and precipitation processes. Quantitative verification indicates that compared to existing powerful 2D nowcasting systems, EchoCast-3D achieves remarkable improvements of 34.5% in Continuous Ranked Probability Score, 14.5% in Mean Absolute Error, and 17.6% in Critical Success Index at echo intensity exceeding 40 dBZ. Even with 15% data missing, EchoCast-3D still can deliver stable and reasonable predictions, reaching the current state-of-the-art. Our research demonstrates practical application value in extreme weather preparation, and provides accurate, robust radar nowcasting in operations. We anticipate this work will serve as a foundation for new insights in nowcasting research.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"4 7 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2026-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147751775","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

TopoFlow: topography-aware pollutant Flow learning for high-resolution air quality prediction TopoFlow：用于高分辨率空气质量预测的地形感知污染物流量学习

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2026-04-24 DOI: 10.1038/s41612-026-01417-5

Ammar Kheder, Helmi Toropainen, Wenqing Peng, Samuel Antão, Jia Chen, Michael Boy, Zhi-Song Liu

{"title":"TopoFlow: topography-aware pollutant Flow learning for high-resolution air quality prediction","authors":"Ammar Kheder, Helmi Toropainen, Wenqing Peng, Samuel Antão, Jia Chen, Michael Boy, Zhi-Song Liu","doi":"10.1038/s41612-026-01417-5","DOIUrl":"https://doi.org/10.1038/s41612-026-01417-5","url":null,"abstract":"We propose TopoFlow (Topography-aware pollutant Flow learning), a physics-guided neural network for efficient, high-resolution air quality prediction. To explicitly embed physical processes into the learning framework, we identify two critical factors governing pollutant dynamics: topography and wind direction. Complex terrain can channel, block and trap pollutants, while wind acts as a primary driver of their transport and dispersion. Building on these insights, TopoFlow leverages a vision transformer architecture with two novel mechanisms: topography-aware attention, which explicitly models terrain-induced flow patterns and wind-guided patch reordering, which aligns spatial representations with prevailing wind directions. Trained on 6 years of high-resolution reanalysis data assimilating observations from over 1400 surface monitoring stations across China, TopoFlow achieves a PM2.5 RMSE of 9.71 μg/m3, representing a 71–80% improvement over operational forecasting systems and a 13% improvement over state-of-the-art AI baselines. Forecast errors remain well below China’s 24-hour air quality threshold of 75 μg/m3 (GB 3095-2012), enabling reliable discrimination between clean and polluted conditions. These performance gains are consistent across all four major pollutants and forecast lead times from 12 to 96 hours, demonstrating that principled integration of physical knowledge into neural networks can fundamentally advance air quality prediction.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"6 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2026-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147751798","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

Regional structure of the polar vortex via planetary wave phase diagnostics and its link to cold air outbreaks 通过行星波相位诊断极地涡旋的区域结构及其与冷空气爆发的联系

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2026-04-24 DOI: 10.1038/s41612-026-01418-4

Varunesh Chandra, Muyin Wang, James E. Overland

{"title":"Regional structure of the polar vortex via planetary wave phase diagnostics and its link to cold air outbreaks","authors":"Varunesh Chandra, Muyin Wang, James E. Overland","doi":"10.1038/s41612-026-01418-4","DOIUrl":"https://doi.org/10.1038/s41612-026-01418-4","url":null,"abstract":"Extreme winter cold-air outbreaks (CAOs) impose substantial societal and economic impacts across the Northern Hemisphere, yet the stratospheric processes that modulate these events—and shape their regional expression—remain incompletely understood. Previous studies relied on cluster-based classifications of polar vortex states, which discretize continuous variability and often emphasize North American impacts. Here, we introduce a, phase-based diagnostic framework that characterizes the evolving geometry of the lower stratospheric polar vortex (LSPV) using amplitude, percentage of longitudinal spatial variance explained by wave-1 and wave-2 components, and their longitudinal phase in 100 hPa geopotential height anomalies. This approach distinguishes displacement (wave-1) and stretching (wave-2) configurations and identifies four recurrent trough orientations over North America, Atlantic, Asia, and Far East. Composite analysis for January–February 1979–2024 shows that these phase-locked configurations are frequently associated with vertically coherent anomaly patterns between 100 hPa and 500 hPa and with distinct surface temperature anomalies. A transition-probability matrix indicates that LSPV trough configurations often reorganize between preferred longitudinal sectors than propagate gradually in longitude. These results show that wave-1 (displacement) and wave-2 (stretching) geometries represent recurrent modes of LSPV variability during January–February, with sector-dependent surface temperature anomalies, providing a framework for understanding the regional structure of CAO-related midlatitude winter circulation patterns.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"26 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2026-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147751777","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

Model-observation discrepancies in Arctic moisture intrusions: causes and pathways for improved simulation 北极水汽侵入的模式观测差异：改进模拟的原因和途径

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2026-04-24 DOI: 10.1038/s41612-026-01400-0

Weiming Ma, Nicole Feldl, Hailong Wang, Gang Chen, Sandro W. Lubis, Yun Qian, Bryce E. Harrop

{"title":"Model-observation discrepancies in Arctic moisture intrusions: causes and pathways for improved simulation","authors":"Weiming Ma, Nicole Feldl, Hailong Wang, Gang Chen, Sandro W. Lubis, Yun Qian, Bryce E. Harrop","doi":"10.1038/s41612-026-01400-0","DOIUrl":"https://doi.org/10.1038/s41612-026-01400-0","url":null,"abstract":"Arctic moisture intrusions (MIs), narrow filaments of strong moisture transport, are key drivers of poleward moisture flux and Arctic weather extremes, yet their representation in climate models is poorly understood. Using a new Arctic MI detection algorithm, we document persistent biases across three CMIP generations (CMIP3–CMIP6): models overestimate MI occurrence over the Pacific sector and underestimate it over the Atlantic sector. These errors stem from misrepresented midlatitude westerly jets, with an equatorward North Atlantic jet associated with too few Atlantic MIs, and a poleward, weakened North Pacific jet linked to too many Pacific MIs. Experiments that correct sea surface temperature and sea ice concentration biases and increase atmospheric resolution improve jet structure and MI statistics, while a cloud-locking simulation indicates that better high-frequency cloud–radiation–circulation interactions can yield further gains. Our results clarify pathways to reducing long-standing MI and jet biases, providing guidance for improving simulations of Arctic and midlatitude climate.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"21 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2026-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147751779","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

Differences in microphysical structures between continental and oceanic thunderstorms: a GPM/DPR-based comparison 大陆和海洋雷暴的微物理结构差异：基于GPM/ pr的比较

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2026-04-22 DOI: 10.1038/s41612-026-01416-6

Xiaojie Liu, Dong Zheng, Wen Yao, Yijun Zhang, Yanan Zhu

{"title":"Differences in microphysical structures between continental and oceanic thunderstorms: a GPM/DPR-based comparison","authors":"Xiaojie Liu, Dong Zheng, Wen Yao, Yijun Zhang, Yanan Zhu","doi":"10.1038/s41612-026-01416-6","DOIUrl":"https://doi.org/10.1038/s41612-026-01416-6","url":null,"abstract":"Although the disparities in lightning activity between continental and oceanic thunderstorms have been widely investigated from thermodynamic, dynamic, and aerosol perspectives, their hydrometeor characteristics remain inadequately understood. This study compares microphysical properties of total thunderstorms and lightning-bearing cloud columns (lightning columns) over continental South China (SC) and oceanic South China Sea (SCS) using the observations from the Dual-frequency Precipitation Radar onboard the Global Precipitation Measurement satellite and lightning data from the Earth Networks Total Lightning Network and World Wide Lightning Location Network. Results show that SC thunderstorms feature higher echo tops of strong echoes (≥40 dBZ) than SCS thunderstorms, while SCS thunderstorms are spatially about three times as large as SC thunderstorms. SC thunderstorms have higher volume fractions of low-density ice particles across all sizes and of larger-sized dense ice and mixed-phase particles, whereas SCS thunderstorms exhibit higher fractions of small-to-medium-sized dense ice/mixed-phase particles and liquid water. Lightning columns in both regions contain more abundant and larger hydrometeors than overall thunderstorms, and the regional differences in hydrometeor properties between lightning columns are broadly consistent with those between the thunderstorms. Differences in volume-weighted mean diameter are most pronounced within the mixed-phase zone (0 to −20 °C).","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"25 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2026-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147734072","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

Deep learning-based adjoint modeling for daily CO estimations 基于深度学习的CO日估算伴随建模

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2026-04-22 DOI: 10.1038/s41612-026-01410-y

Hyun-Jeong Lee, Dongjin Cho, Yoo-Geun Ham

{"title":"Deep learning-based adjoint modeling for daily CO estimations","authors":"Hyun-Jeong Lee, Dongjin Cho, Yoo-Geun Ham","doi":"10.1038/s41612-026-01410-y","DOIUrl":"https://doi.org/10.1038/s41612-026-01410-y","url":null,"abstract":"In this study, we develop a four-dimensional variational data assimilation (4DVAR)-based adjoint modeling framework using deep learning (DL) for estimating daily carbon monoxide (CO) concentrations over east Asia. The forward model is built on a U-Net architecture, and its adjoint version is formulated by explicitly calculating the gradients of the cost function with respect to the initial condition by leveraging the backpropagation algorithm. The DL-based adjoint model (ADM) was first validated through the adjoint test, the finite-difference gradient test. The idealized experiments using synthetic CO increments at a single grid point over the Korean Peninsula showed that the adjoint sensitivities spread horizontally and vertically to the upstream region along the climatological flows with diffusive features. In addition, the idealized 4DVAR experiments using in-situ CO observations over Korea and Japan during 2020–2022 demonstrated substantial error reduction across the Korean Peninsula, Japan, and northeastern China. This confirms that the DL-based ADM exhibits physically reasonable propagation of the observational information over time and space, offering a promising and efficient alternative to dynamic model-dependent adjoint frameworks constrained by the high computational costs.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"18 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2026-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147734070","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

Complementary error structures of AI and numerical models in forecasting boundary-layer jets over the South China Sea 人工智能与数值模式在南海边界层急流预报中的互补误差结构

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2026-04-22 DOI: 10.1038/s41612-026-01419-3

Haimin Li, Yu Du

{"title":"Complementary error structures of AI and numerical models in forecasting boundary-layer jets over the South China Sea","authors":"Haimin Li, Yu Du","doi":"10.1038/s41612-026-01419-3","DOIUrl":"https://doi.org/10.1038/s41612-026-01419-3","url":null,"abstract":"The boundary-layer jet (BLJ) over the northern South China Sea exerts a strong influence on heavy rainfall along the South China coast, yet its predictability across different modeling frameworks remains insufficiently understood. This study presents a systematic comparison of BLJ forecasts from a conventional numerical weather prediction (NWP) model (the European Centre for Medium-Range Weather Forecasts, ECMWF) and a data-driven artificial intelligence (AI) model (Pangu). The AI model outperforms the NWP model in overall accuracy, with reduced root-mean-square errors and improved representation of wind direction. However, the two models exhibit distinct and opposite systematic error structures. ECMWF consistently overestimates BLJ intensity and spatial extent, accompanied by a northwestward displacement of the jet core and a clockwise wind-direction bias. Conversely, Pangu underestimates BLJ intensity, with a northeastward core shift and a counterclockwise wind-direction bias. Motivated by these complementary errors, we develop a U-Net–based blending framework with a composite loss function integrating mean absolute error, miss rate, and false alarm rate. The blended forecasts significantly outperform both individual models across multiple BLJ metrics. These results demonstrate that combining physics-based and AI-based forecasts can mitigate systematic biases to improve BLJ prediction, highlighting a promising pathway toward hybrid forecasting systems for weather extremes.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"23 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2026-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147734071","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

Interlinks between sea-ice melting and continental wetting under a changing Arctic moisture transport 北极水汽输送变化下海冰融化与大陆湿润之间的联系

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2026-04-21 DOI: 10.1038/s41612-026-01389-6

Tetsu Nakamura, Tomonori Sato, Yoshiki Fukutomi, Tetsuya Hiyama

{"title":"Interlinks between sea-ice melting and continental wetting under a changing Arctic moisture transport","authors":"Tetsu Nakamura, Tomonori Sato, Yoshiki Fukutomi, Tetsuya Hiyama","doi":"10.1038/s41612-026-01389-6","DOIUrl":"https://doi.org/10.1038/s41612-026-01389-6","url":null,"abstract":"Abrupt Arctic warming has profound implications for both polar and mid-latitude climates, with moisture transport playing a central role in Arctic amplification. Using a tagged water vapor transport model driven by three reanalysis datasets, we quantify seasonal Arctic moisture transport during 1980–2024 and evaluate the inter-dataset spread. Robust features across all datasets indicate that summer moistening is primarily caused by increased inflow of continental moisture, while autumn moistening is dominated by local evaporation over the Arctic Ocean. Although evaporation trends exhibit substantial inter-reanalysis discrepancies, the associated summer moisture transport into the Arctic is remarkably consistent across datasets, underscoring the dominant role of circulation changes. Simulations further show that sea ice retreat induces the Arctic Dipole pattern that reinforces moisture transport and radiative feedbacks, suggesting a previously unrecognized feedback loop. Our findings highlight both the robust and uncertain components of the Arctic moisture cycle and emphasize the need to better constrain surface evaporation in Arctic climate modeling.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"5 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2026-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147734073","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

Beyond global mean temperature: increasing asymmetry of global warming in past and future climate change 超越全球平均温度：全球变暖在过去和未来气候变化中的不对称性增加

IF 9 1区地球科学

npj Climate and Atmospheric Science Pub Date : 2026-04-17 DOI: 10.1038/s41612-026-01411-x

Qiuying Gan, Jeremy Cheuk-Hin Leung, Wenjie Dong, Yazhu Yang, Dingchi Zhao, Yi Li, Renhe Zhang, Banglin Zhang

{"title":"Beyond global mean temperature: increasing asymmetry of global warming in past and future climate change","authors":"Qiuying Gan, Jeremy Cheuk-Hin Leung, Wenjie Dong, Yazhu Yang, Dingchi Zhao, Yi Li, Renhe Zhang, Banglin Zhang","doi":"10.1038/s41612-026-01411-x","DOIUrl":"https://doi.org/10.1038/s41612-026-01411-x","url":null,"abstract":"Global surface warming is recognized for its spatial asymmetry, which drives the complexity of climate change impacts. However, solely relying on average surface temperature change (({Delta T}_{{mean}})) as an indicator of climate change may obscure this asymmetry. Here, going beyond ({Delta T}_{{mean}}), we quantify the long-term change in global warming asymmetry and its implications for climate mitigation. Results reveal a significant increase in warming asymmetry (0.18–0.29 °C3/decade) since 1900. Among 58 IPCC reference regions, the Arctic Ocean, Northwest North America, and Russian Regions contribute only 48% of this trend, with other Northern Hemisphere mid-high latitudes accounting for an additional 35%. Climate models project an emission-dependent nonlinear acceleration of warming asymmetry, with trends under SSP 5-8.5 being approximately 3–8 times greater than those under SSP2-4.5 and SSP1-2.6. Consequently, the global surface temperature change deviates from its original Gaussian distribution toward a highly skewed bimodal distribution. This increasing asymmetry implies a widening “divergence” within the climate system that is dependent on emission levels, including the gap between the ({Delta T}_{{mean}}) and those observed across the majority of regions. Without rigorous emission reductions, this gap could foster cognitive biases in public awareness toward climate change, undermining public acceptance of climate mitigation policies.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"197 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2026-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147709300","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