Pub Date : 2026-02-03DOI: 10.1038/s41612-026-01345-4
Mingyang Li, Wei Jia, Yan Yang, Hai Cheng, Jingyao Zhao, Shaoneng He, Guangxin Liu, Haowen Fan, Ting-Yong Li, Lidan Lei, Xiaofeng Ren, Na Zhang, Yinhuan Zhang, Jingfeng Lin, R. Lawrence Edwards
Despite numerous proxy-based reconstructions of climate since the Last Glacial Maximum, spatial hydroclimate variability in the Chinese monsoon region remains enigmatic. Here, we examine four stalagmites from northern China that collectively provide a continuous, highly resolved multi-proxy record over the past 25.5 ka. δ18O records capture large-scale variations in Asian summer monsoon (ASM) circulation, whereas trace element ratios and δ13C reflect regional precipitation variability; both follow precessional rhythms. Chinese stalagmite δ18O exhibits a zonal tripolar pattern, reflecting moisture sources and transport pathways. During Termination I, a meridional tripolar spatial precipitation pattern emerged, driven by El Niño–Southern Oscillation (ENSO) and mid-latitude westerlies dynamics. While precipitation peaked during the Middle Holocene, ASM circulation was strongest in the Early Holocene, a dipole hydrological pattern linked to residual Northern Hemisphere ice volume. A similar tripolar pattern re-emerged during the 4.2 ka event, suggesting a dominant role of ENSO in shaping this anomaly.
{"title":"Spatial patterns of Asian summer monsoon precipitation in the Chinese monsoon region since the LGM","authors":"Mingyang Li, Wei Jia, Yan Yang, Hai Cheng, Jingyao Zhao, Shaoneng He, Guangxin Liu, Haowen Fan, Ting-Yong Li, Lidan Lei, Xiaofeng Ren, Na Zhang, Yinhuan Zhang, Jingfeng Lin, R. Lawrence Edwards","doi":"10.1038/s41612-026-01345-4","DOIUrl":"https://doi.org/10.1038/s41612-026-01345-4","url":null,"abstract":"Despite numerous proxy-based reconstructions of climate since the Last Glacial Maximum, spatial hydroclimate variability in the Chinese monsoon region remains enigmatic. Here, we examine four stalagmites from northern China that collectively provide a continuous, highly resolved multi-proxy record over the past 25.5 ka. δ18O records capture large-scale variations in Asian summer monsoon (ASM) circulation, whereas trace element ratios and δ13C reflect regional precipitation variability; both follow precessional rhythms. Chinese stalagmite δ18O exhibits a zonal tripolar pattern, reflecting moisture sources and transport pathways. During Termination I, a meridional tripolar spatial precipitation pattern emerged, driven by El Niño–Southern Oscillation (ENSO) and mid-latitude westerlies dynamics. While precipitation peaked during the Middle Holocene, ASM circulation was strongest in the Early Holocene, a dipole hydrological pattern linked to residual Northern Hemisphere ice volume. A similar tripolar pattern re-emerged during the 4.2 ka event, suggesting a dominant role of ENSO in shaping this anomaly.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"5 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2026-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146102136","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}
Pub Date : 2026-02-02DOI: 10.1038/s41612-025-01311-6
Dongjin Cho, Yoo-Geun Ham, Suyeon Jeong, Seon-Yu Kang
Extreme heatwaves are intensifying under climate change, yet their prediction remains limited by inadequate representation of land–atmosphere (L–A) interactions. Most deep learning–based weather models rely solely on atmospheric variables, overlooking the influence of land surface conditions on heat extremes. Here, we present an L–A coupled prediction framework for Northern Hemisphere summer that incorporates multi-layer soil moisture (SM) and temperature into atmospheric forecasting. To better capture delayed land surface feedbacks, the model is trained with a multi-step loss. This approach improved the representation of L–A interactions across 1–7 day lead times. Using multi-step loss, the L–A coupled model achieved a 5.9–11.2% improvement in heatwave forecast accuracy relative to the atmosphere-only model, as measured by root mean squared error, whereas single-step loss achieved only 0.4–2.4% improvement. Skill gain was strongest at short leads (~ 3 day) when both SM and circulation predictability were high, and sustained through 7 days by L–A coupling driven by SM predictability. Case studies of recent heatwaves further demonstrated its ability to capture land surface drying and associated temperature extremes. These findings underscore the importance of incorporating L–A coupling with multi-step optimization for advancing data-driven heatwave prediction.
{"title":"A deep learning-based land-atmosphere coupled model for heatwave prediction","authors":"Dongjin Cho, Yoo-Geun Ham, Suyeon Jeong, Seon-Yu Kang","doi":"10.1038/s41612-025-01311-6","DOIUrl":"https://doi.org/10.1038/s41612-025-01311-6","url":null,"abstract":"Extreme heatwaves are intensifying under climate change, yet their prediction remains limited by inadequate representation of land–atmosphere (L–A) interactions. Most deep learning–based weather models rely solely on atmospheric variables, overlooking the influence of land surface conditions on heat extremes. Here, we present an L–A coupled prediction framework for Northern Hemisphere summer that incorporates multi-layer soil moisture (SM) and temperature into atmospheric forecasting. To better capture delayed land surface feedbacks, the model is trained with a multi-step loss. This approach improved the representation of L–A interactions across 1–7 day lead times. Using multi-step loss, the L–A coupled model achieved a 5.9–11.2% improvement in heatwave forecast accuracy relative to the atmosphere-only model, as measured by root mean squared error, whereas single-step loss achieved only 0.4–2.4% improvement. Skill gain was strongest at short leads (~ 3 day) when both SM and circulation predictability were high, and sustained through 7 days by L–A coupling driven by SM predictability. Case studies of recent heatwaves further demonstrated its ability to capture land surface drying and associated temperature extremes. These findings underscore the importance of incorporating L–A coupling with multi-step optimization for advancing data-driven heatwave prediction.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"44 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146102138","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}
Pub Date : 2026-02-02DOI: 10.1038/s41612-026-01339-2
Jian Ma, Jing Feng, Hui Su, Matthew Collins, Jing Su, In-Sik Kang, Masahiro Watanabe, Jianping Li, Yinding Zhang
Clouds significantly influence Earth’s radiative balance with complex changes in response to surface warming. The key drivers of the changes are the sea surface temperature (SST) pattern effect that reshapes cloud distributions, and the beta feedback that scales low-level fraction change to climatological amounts. Cloud radiative feedback remains the largest source of uncertainty in future climate projections, but current constraints are insufficient. Here, we demonstrate that the percentage change in tropical cloud fraction, driven by spatial patterns in SST increase, is linked to cloud height variations. We introduce a proportional warmer-get-higher paradigm and develop a pattern-based analytical framework, identifying three key factors governing cloud feedback: percentage cloud sensitivity to SST, climatological cloud cover, and SST warming patterns relative to the tropical mean. By leveraging recent observations to constrain these factors in two stages, we establish a process-oriented emergent constraint on projected cloud feedback in the 21st century. The first stage substitutes simulated cloud sensitivity and mean cloud cover to correct biases and reduce the spread by half. Then, the second stage attempts to further constrain the SST pattern effect, which explains 79% of the remaining spread in an attribution procedure. This percentage framework yields total, low, middle, and high cloud feedback of 0.49 ± 0.27, 0.33 ± 0.21, 0.09 ± 0.09, and 0.07 ± 0.06 W m-2 K-1 (90% confidence), respectively. It reduces intermodel uncertainty by 59% for cloud feedback and 33% for surface warming, resulting in a climate sensitivity of 4.08 ± 0.97 K.
云显著影响地球的辐射平衡，对地表变暖作出复杂的反应。这些变化的关键驱动因素是重塑云分布的海表温度（SST）模式效应，以及将低层部分变化缩放为气候量的β反馈。云辐射反馈仍然是未来气候预估中最大的不确定性来源，但目前的限制是不够的。在这里，我们证明了由海温增加的空间格局驱动的热带云分数的百分比变化与云高度变化有关。我们引入了一个比例变暖越高的范式，并开发了一个基于模式的分析框架，确定了控制云反馈的三个关键因素：云对海温的百分比敏感性、气候云量和相对于热带平均值的海温变暖模式。通过利用最近的观测结果将这些因素分为两个阶段，我们建立了一个面向过程的21世纪预计云反馈的紧急约束。第一阶段用模拟的云敏感性和平均云量代替，以纠正偏差并将传播减少一半。然后，第二阶段试图进一步约束海温模式效应，这解释了归因过程中剩余传播的79%。该百分比框架产生的总、低、中、高云反馈分别为0.49±0.27、0.33±0.21、0.09±0.09和0.07±0.06 W m-2 K-1（90%置信度）。它将云反馈的模式间不确定性降低了59%，将地表变暖的模式间不确定性降低了33%，导致气候敏感性为4.08±0.97 K。
{"title":"An analytical framework reduces cloud feedback uncertainty by linking percentage cloud change to surface ocean warming patterns","authors":"Jian Ma, Jing Feng, Hui Su, Matthew Collins, Jing Su, In-Sik Kang, Masahiro Watanabe, Jianping Li, Yinding Zhang","doi":"10.1038/s41612-026-01339-2","DOIUrl":"https://doi.org/10.1038/s41612-026-01339-2","url":null,"abstract":"Clouds significantly influence Earth’s radiative balance with complex changes in response to surface warming. The key drivers of the changes are the sea surface temperature (SST) pattern effect that reshapes cloud distributions, and the beta feedback that scales low-level fraction change to climatological amounts. Cloud radiative feedback remains the largest source of uncertainty in future climate projections, but current constraints are insufficient. Here, we demonstrate that the percentage change in tropical cloud fraction, driven by spatial patterns in SST increase, is linked to cloud height variations. We introduce a proportional warmer-get-higher paradigm and develop a pattern-based analytical framework, identifying three key factors governing cloud feedback: percentage cloud sensitivity to SST, climatological cloud cover, and SST warming patterns relative to the tropical mean. By leveraging recent observations to constrain these factors in two stages, we establish a process-oriented emergent constraint on projected cloud feedback in the 21st century. The first stage substitutes simulated cloud sensitivity and mean cloud cover to correct biases and reduce the spread by half. Then, the second stage attempts to further constrain the SST pattern effect, which explains 79% of the remaining spread in an attribution procedure. This percentage framework yields total, low, middle, and high cloud feedback of 0.49 ± 0.27, 0.33 ± 0.21, 0.09 ± 0.09, and 0.07 ± 0.06 W m-2 K-1 (90% confidence), respectively. It reduces intermodel uncertainty by 59% for cloud feedback and 33% for surface warming, resulting in a climate sensitivity of 4.08 ± 0.97 K.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"39 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146102137","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}
Pub Date : 2026-01-30DOI: 10.1038/s41612-026-01334-7
Pouria Behnoudfar, Charlotte Moser, Marc Bocquet, Sibo Cheng, Nan Chen
Computer models are indispensable tools for understanding the Earth system. While high-resolution operational models have achieved many successes, they exhibit persistent biases, particularly in simulating extreme events and statistical distributions. In contrast, coarse-grained idealized models isolate fundamental processes and can be precisely calibrated to excel in characterizing specific dynamical and statistical features. However, different models remain siloed by disciplinary boundaries. By leveraging the complementary strengths of models of varying complexity, we develop an explainable AI framework for Earth system emulators. It bridges the model hierarchy through a reconfigured latent data assimilation technique, uniquely suited to exploit the sparse output from the idealized models. The resulting bridging model inherits the high resolution and comprehensive variables of operational models while achieving global accuracy enhancements through targeted improvements from idealized models. Crucially, the mechanism of AI provides a clear rationale for these advancements, moving beyond black-box correction to physically insightful understanding in a computationally efficient framework that enables effective physics-assisted digital twins and uncertainty quantification. We demonstrate its power by significantly correcting biases in CMIP6 simulations of El Niño spatiotemporal patterns, leveraging statistically accurate idealized models. This work also highlights the importance of pushing idealized model development and advancing communication between modeling communities.
{"title":"Bridging idealized and operational models: an explainable AI framework for Earth system emulators","authors":"Pouria Behnoudfar, Charlotte Moser, Marc Bocquet, Sibo Cheng, Nan Chen","doi":"10.1038/s41612-026-01334-7","DOIUrl":"https://doi.org/10.1038/s41612-026-01334-7","url":null,"abstract":"Computer models are indispensable tools for understanding the Earth system. While high-resolution operational models have achieved many successes, they exhibit persistent biases, particularly in simulating extreme events and statistical distributions. In contrast, coarse-grained idealized models isolate fundamental processes and can be precisely calibrated to excel in characterizing specific dynamical and statistical features. However, different models remain siloed by disciplinary boundaries. By leveraging the complementary strengths of models of varying complexity, we develop an explainable AI framework for Earth system emulators. It bridges the model hierarchy through a reconfigured latent data assimilation technique, uniquely suited to exploit the sparse output from the idealized models. The resulting bridging model inherits the high resolution and comprehensive variables of operational models while achieving global accuracy enhancements through targeted improvements from idealized models. Crucially, the mechanism of AI provides a clear rationale for these advancements, moving beyond black-box correction to physically insightful understanding in a computationally efficient framework that enables effective physics-assisted digital twins and uncertainty quantification. We demonstrate its power by significantly correcting biases in CMIP6 simulations of El Niño spatiotemporal patterns, leveraging statistically accurate idealized models. This work also highlights the importance of pushing idealized model development and advancing communication between modeling communities.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"104 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146089762","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}
{"title":"ENSO modulated upstream convection as the primary control on interannual δ¹⁸O variability in East Asia","authors":"Ashish Sinha, Jingya Cheng, Hanying Li, Masahiro Tanoue, Hayoung Bong, Haiwei Zhang, Liangcheng Tan, Hai Cheng, Kei Yoshimura","doi":"10.1038/s41612-026-01333-8","DOIUrl":"https://doi.org/10.1038/s41612-026-01333-8","url":null,"abstract":"","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"21 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2026-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146089733","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}
Pub Date : 2026-01-28DOI: 10.1038/s41612-026-01338-3
Peter B. Gibson, Neelesh Rampal, Felix W. Goddard, Bin Guan, Michael J. DeFlorio, Hamish D. Prince
Global climate models project that the South Pacific will be a hotspot for some of the largest atmospheric river (AR) changes. Thus, there is an urgent need to review both historical trends and updated high-resolution climate projections tailored to this region. Here we show that significant trends in AR frequency from reanalysis are mostly still constrained to the ocean (~45–60°S). For landfalling ARs, trends in synoptic-scale features are not yet considered robust, whereas percentile-based moisture transports show stronger increases over parts of southern New Zealand and Tasmania. Furthermore, high-resolution downscaled climate projections indicate that landfalling AR trends should become much more widespread and robustly detectable (5 of 6 models) in the next 10–20 years, first appearing across regions of southern New Zealand during spring and winter. Even under a moderate emissions scenario, projections indicate that the frequency of extreme landfalling ARs could double before mid-century, carrying significant societal impacts.
{"title":"Emerging trends in landfalling atmospheric rivers over the South Pacific","authors":"Peter B. Gibson, Neelesh Rampal, Felix W. Goddard, Bin Guan, Michael J. DeFlorio, Hamish D. Prince","doi":"10.1038/s41612-026-01338-3","DOIUrl":"https://doi.org/10.1038/s41612-026-01338-3","url":null,"abstract":"Global climate models project that the South Pacific will be a hotspot for some of the largest atmospheric river (AR) changes. Thus, there is an urgent need to review both historical trends and updated high-resolution climate projections tailored to this region. Here we show that significant trends in AR frequency from reanalysis are mostly still constrained to the ocean (~45–60°S). For landfalling ARs, trends in synoptic-scale features are not yet considered robust, whereas percentile-based moisture transports show stronger increases over parts of southern New Zealand and Tasmania. Furthermore, high-resolution downscaled climate projections indicate that landfalling AR trends should become much more widespread and robustly detectable (5 of 6 models) in the next 10–20 years, first appearing across regions of southern New Zealand during spring and winter. Even under a moderate emissions scenario, projections indicate that the frequency of extreme landfalling ARs could double before mid-century, carrying significant societal impacts.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"21 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2026-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146057255","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}
Pub Date : 2026-01-28DOI: 10.1038/s41612-026-01336-5
Rong Li, Zhongyin Cai, Xinyi Yu, Cheng Wang, Lide Tian
It remains uncertain whether precipitation oxygen isotopes (δ18O) reliably capture East Asian Meiyu monsoon variability. Analyzing daily δ18O across the Yangtze-Huai River Basin from 28-34°N, we reveal a distinct spatial dichotomy. In the middle and northern Meiyu regions, δ18O robustly tracks Meiyu precipitation. Conversely, the southern Meiyu margin is decoupled from Meiyu variability, primarily reflecting upstream convection processes further south. We identify the western Pacific subtropical high (WPSH) as the central driver, creating a dynamic dipole: its northwestward extension enhances moisture transport and deep convection along its northwestern flank (driving isotopic depletion in the northern Meiyu region), while imposing subsidence and convective inhibition under its body (suppressing isotopic depletion in the southern Meiyu region). Importantly, these mechanisms persist on interannual timescales. Consequently, while northern δ18O records effectively capture Meiyu variability, southern records reflect distinct vertical constraints, necessitating spatially differentiated paleoclimate interpretations.
{"title":"East Asian Meiyu variability reflected in precipitation oxygen isotopes via western Pacific subtropical high","authors":"Rong Li, Zhongyin Cai, Xinyi Yu, Cheng Wang, Lide Tian","doi":"10.1038/s41612-026-01336-5","DOIUrl":"https://doi.org/10.1038/s41612-026-01336-5","url":null,"abstract":"It remains uncertain whether precipitation oxygen isotopes (δ18O) reliably capture East Asian Meiyu monsoon variability. Analyzing daily δ18O across the Yangtze-Huai River Basin from 28-34°N, we reveal a distinct spatial dichotomy. In the middle and northern Meiyu regions, δ18O robustly tracks Meiyu precipitation. Conversely, the southern Meiyu margin is decoupled from Meiyu variability, primarily reflecting upstream convection processes further south. We identify the western Pacific subtropical high (WPSH) as the central driver, creating a dynamic dipole: its northwestward extension enhances moisture transport and deep convection along its northwestern flank (driving isotopic depletion in the northern Meiyu region), while imposing subsidence and convective inhibition under its body (suppressing isotopic depletion in the southern Meiyu region). Importantly, these mechanisms persist on interannual timescales. Consequently, while northern δ18O records effectively capture Meiyu variability, southern records reflect distinct vertical constraints, necessitating spatially differentiated paleoclimate interpretations.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"55 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2026-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146057254","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}
Pub Date : 2026-01-28DOI: 10.1038/s41612-025-01297-1
Nick J. Dunstone, Chaofan Li, Doug M. Smith, Steven C. Hardiman, Leon Hermanson, Zu Luo, Adam A. Scaife, Rhidian Thomas, Lin Wang, Tim Woollings
In contrast to global warming trends, much of Eurasia experienced a winter cooling trend over 1990–2014. Some studies have proposed a causal link between this regional cooling, particularly strong over Siberia, to coincident reductions in Arctic sea-ice extent. However, free-running historical climate models overwhelmingly simulate a forced Eurasian warming signal, leading other studies to suggest that internal variability explains the observed cooling. Here, we use retrospective seasonal climate predictions to highlight a robust dynamical link between Siberian cooling and upstream north-east Atlantic atmospheric circulation changes. Examining the interannual predictability of these circulation patterns, we find spuriously weak but skilful model signals. When these weak dynamical signals are corrected, stronger low-frequency variability in downstream Siberian temperature also emerges, with half of the observed 1990–2014 cooling simulated. Our results suggest that Eurasian decadal climate variability is at least partly driven by a predictable atmospheric circulation response to slowly evolving boundary conditions.
{"title":"Predictable atmospheric circulation driver of Eurasian winter temperatures","authors":"Nick J. Dunstone, Chaofan Li, Doug M. Smith, Steven C. Hardiman, Leon Hermanson, Zu Luo, Adam A. Scaife, Rhidian Thomas, Lin Wang, Tim Woollings","doi":"10.1038/s41612-025-01297-1","DOIUrl":"https://doi.org/10.1038/s41612-025-01297-1","url":null,"abstract":"In contrast to global warming trends, much of Eurasia experienced a winter cooling trend over 1990–2014. Some studies have proposed a causal link between this regional cooling, particularly strong over Siberia, to coincident reductions in Arctic sea-ice extent. However, free-running historical climate models overwhelmingly simulate a forced Eurasian warming signal, leading other studies to suggest that internal variability explains the observed cooling. Here, we use retrospective seasonal climate predictions to highlight a robust dynamical link between Siberian cooling and upstream north-east Atlantic atmospheric circulation changes. Examining the interannual predictability of these circulation patterns, we find spuriously weak but skilful model signals. When these weak dynamical signals are corrected, stronger low-frequency variability in downstream Siberian temperature also emerges, with half of the observed 1990–2014 cooling simulated. Our results suggest that Eurasian decadal climate variability is at least partly driven by a predictable atmospheric circulation response to slowly evolving boundary conditions.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"86 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2026-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146057256","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}
Pub Date : 2026-01-27DOI: 10.1038/s41612-026-01335-6
Run Yuan, Rui Zhang, Li Jiang, Tiegang Li, James Russell, Fan Zhang, Minglei Guan, Xiaoxiao Yu, Yuhang Wan, Zhiyong Liu, Shiyang Xu
The Western Pacific Warm Pool (WPWP) acts as Earth’s largest tropical heat reservoir; however, the mechanisms that drive orbital-scale sea surface salinity (SSS) variability remain unresolved, as traditional δ¹⁸O-based proxies conflate regional salinity with global ice-volume effects. Here, we present a 450 kyr SSS record from the WPWP using hydrogen isotope composition of alkenones (δDAlk)—a proxy isolating evaporation-precipitation balance—paired with isotope-enabled climate modeling. Our results reveal dominant precessional SSS variability, with maxima during boreal precession minima (Pmin) when intensified meridional insolation gradients strengthen Walker Circulation, enhance evaporation, and sustain La Niña-like conditions. The δDAlk record demonstrates that precession-driven ocean-atmosphere feedbacks govern 78% of SSS variability, and reconcile discrepancies in previous δ¹⁸O-based studies showing the significant influence of obliquity. Integration with climate simulations shows that precession-induced trade winds amplify saline water advection and evaporation, establishing a “salinification triad” that dominates WPWP hydroclimate. These findings redefine the WPWP as a precession-paced engine of tropical hydrology, suggesting that the low-latitude tropical hydrology is highly sensitive to insolation intensity and then regulates ENSO-monsoon interactions. By isolating orbital controls on salinity extremes, this work advances frameworks for projecting hydrological responses to anthropogenic warming, critical for regions reliant on monsoon rainfall, emphasizing the vulnerability of tropical hydrological extremes to orbital forcing.
{"title":"Precession-driven salinity feedback in the western Pacific warm pool: insights from alkenone hydrogen isotopes over the past 450 kyr","authors":"Run Yuan, Rui Zhang, Li Jiang, Tiegang Li, James Russell, Fan Zhang, Minglei Guan, Xiaoxiao Yu, Yuhang Wan, Zhiyong Liu, Shiyang Xu","doi":"10.1038/s41612-026-01335-6","DOIUrl":"https://doi.org/10.1038/s41612-026-01335-6","url":null,"abstract":"The Western Pacific Warm Pool (WPWP) acts as Earth’s largest tropical heat reservoir; however, the mechanisms that drive orbital-scale sea surface salinity (SSS) variability remain unresolved, as traditional δ¹⁸O-based proxies conflate regional salinity with global ice-volume effects. Here, we present a 450 kyr SSS record from the WPWP using hydrogen isotope composition of alkenones (δDAlk)—a proxy isolating evaporation-precipitation balance—paired with isotope-enabled climate modeling. Our results reveal dominant precessional SSS variability, with maxima during boreal precession minima (Pmin) when intensified meridional insolation gradients strengthen Walker Circulation, enhance evaporation, and sustain La Niña-like conditions. The δDAlk record demonstrates that precession-driven ocean-atmosphere feedbacks govern 78% of SSS variability, and reconcile discrepancies in previous δ¹⁸O-based studies showing the significant influence of obliquity. Integration with climate simulations shows that precession-induced trade winds amplify saline water advection and evaporation, establishing a “salinification triad” that dominates WPWP hydroclimate. These findings redefine the WPWP as a precession-paced engine of tropical hydrology, suggesting that the low-latitude tropical hydrology is highly sensitive to insolation intensity and then regulates ENSO-monsoon interactions. By isolating orbital controls on salinity extremes, this work advances frameworks for projecting hydrological responses to anthropogenic warming, critical for regions reliant on monsoon rainfall, emphasizing the vulnerability of tropical hydrological extremes to orbital forcing.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"7 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2026-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146057257","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}
Pub Date : 2026-01-27DOI: 10.1038/s41612-025-01283-7
Steven C. Hardiman, Adam A. Scaife, Nick J. Dunstone, Philip E. Bett-Williams, Chaofan Li, Lin Wang
Due to its potentially life—threatening and devastating economic impacts, variability in the East Asian Summer Monsoon needs better understanding, more accurate simulation and improved prediction. Much of the current ability of long-range summer monsoon forecasts stems from the link to the preceding winter El Niño Southern Oscillation, but the mechanisms behind this lagged impact are not fully understood. In this study, a simple new mechanism is proposed, based on migrating Atmospheric Angular Momentum anomalies. The polewards migration of atmospheric angular momentum associated with winter El Niño is shown to impact the northwest Pacific anticyclone responsible for much of the year-to-year variability in the monsoon. Model forecasts of the summer monsoon are shown to have increased accuracy when this new mechanism is active, with the increase in the success rate of forecasts due to migrating angular momentum anomalies shown to be as large as the effect of El Niño itself.
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