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.
{"title":"New mechanism for delayed ENSO impact on the East Asian Summer Monsoon","authors":"Steven C. Hardiman, Adam A. Scaife, Nick J. Dunstone, Philip E. Bett-Williams, Chaofan Li, Lin Wang","doi":"10.1038/s41612-025-01283-7","DOIUrl":"https://doi.org/10.1038/s41612-025-01283-7","url":null,"abstract":"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.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"17 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2026-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146057260","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 : 2026-01-26DOI: 10.1038/s41612-026-01328-5
Hyebin Park, Seonyoung Park, Daehyun Kang, Jeong-Hwan Kim
Artificial intelligence has improved the accuracy and efficiency of weather forecasting, surpassing traditional numerical weather prediction models. However, the coarse spatial resolution of global weather forecasting systems limits their ability to capture fine-scale surface heterogeneity and localized extremes, particularly in regions with complex terrain or urban heat island effects. Here, we introduce SR-Weather, a deep learning-based super-resolution framework that converts coarse 0.25° forecasts into 1-km surface air temperature fields using MODIS-derived temperature targets and high-resolution auxiliary inputs. SR-Weather outperforms existing super-resolution methods by explicitly incorporating spatial context, such as topography, impervious surface fraction, and seasonal climatology maps of air temperature. When SR-Weather was applied to the FuXi global weather forecast, the 7-day forecast error in South Korea decreased by more than 20%, which was comparable to the 1-day forecast error from low-resolution prediction using simple spatial interpolation. In addition, SR-Weather effectively reconstructs missing pixels in MODIS-derived air temperature maps under heavy cloud contamination by leveraging auxiliary variables and climatologically smoothed fields. Although validated over South Korea, the framework relies on globally available MODIS products and minimal auxiliary inputs, making it feasible to retrain for other regions. These results indicate that SR-Weather is a scalable and high-fidelity tool for enhancing machine learning-based weather forecasts at fine spatial scales.
{"title":"A super-resolution framework for downscaling machine learning weather prediction toward 1-km air temperature","authors":"Hyebin Park, Seonyoung Park, Daehyun Kang, Jeong-Hwan Kim","doi":"10.1038/s41612-026-01328-5","DOIUrl":"https://doi.org/10.1038/s41612-026-01328-5","url":null,"abstract":"Artificial intelligence has improved the accuracy and efficiency of weather forecasting, surpassing traditional numerical weather prediction models. However, the coarse spatial resolution of global weather forecasting systems limits their ability to capture fine-scale surface heterogeneity and localized extremes, particularly in regions with complex terrain or urban heat island effects. Here, we introduce SR-Weather, a deep learning-based super-resolution framework that converts coarse 0.25° forecasts into 1-km surface air temperature fields using MODIS-derived temperature targets and high-resolution auxiliary inputs. SR-Weather outperforms existing super-resolution methods by explicitly incorporating spatial context, such as topography, impervious surface fraction, and seasonal climatology maps of air temperature. When SR-Weather was applied to the FuXi global weather forecast, the 7-day forecast error in South Korea decreased by more than 20%, which was comparable to the 1-day forecast error from low-resolution prediction using simple spatial interpolation. In addition, SR-Weather effectively reconstructs missing pixels in MODIS-derived air temperature maps under heavy cloud contamination by leveraging auxiliary variables and climatologically smoothed fields. Although validated over South Korea, the framework relies on globally available MODIS products and minimal auxiliary inputs, making it feasible to retrain for other regions. These results indicate that SR-Weather is a scalable and high-fidelity tool for enhancing machine learning-based weather forecasts at fine spatial scales.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"1 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2026-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146048260","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 : 2026-01-23DOI: 10.1038/s41612-025-01302-7
Michael O’Sullivan, Pierre Friedlingstein, Stephen Sitch, Julia Pongratz, Clemens Schwingshackl, Thomas Gasser, Philippe Ciais, Vivek Arora, Etsushi Kato, Jürgen Knauer, Erwan Monier, Tobias Nützel, Qing Sun, Wenping Yuan, Xu Yue, Sönke Zaehle
The natural land carbon sink (SLAND) absorbs roughly 25–30% of anthropogenic CO2 emissions, thus playing a critical role in offsetting climate warming. In the Global Carbon Budget (GCB), SLAND is estimated using model simulations that isolate the carbon response of land to environmental changes (i.e. rising atmospheric CO2, nitrogen deposition, and changes in climate). However, these simulations assume fixed pre-industrial land cover, failing to represent today’s human-altered landscapes. This leads to a systematic overestimation of forest area, and thus CO2 sink strength, in regions heavily altered by human activity. We present a new process-based approach to estimate SLAND using Dynamic Global Vegetation Models. Our corrected estimate reduces SLAND by ~20% (0.6 PgC yr-1) over 2015–2024, from 3.00 ± 0.94 to 2.42 ± 0.77 PgC yr-1. We incorporate this new SLAND estimate with emissions from land-use change from bookkeeping models, to estimate a net land sink of 1.19 ± 1.04 PgC yr-1, which aligns closely with atmospheric inversion constraints. This downward revision of SLAND reduces the magnitude of the budget imbalance for 2015–2024, indicating a more consistent partitioning of the global carbon budget.
自然土地碳汇（SLAND）吸收了大约25-30%的人为二氧化碳排放，因此在抵消气候变暖方面发挥着关键作用。在全球碳预算（GCB）中，SLAND是通过模式模拟来估算的，该模式模拟分离了土地对环境变化（即大气二氧化碳上升、氮沉降和气候变化）的碳响应。然而，这些模拟假设工业化前的土地覆盖是固定的，无法代表今天人为改变的景观。这导致系统地高估了受人类活动严重影响地区的森林面积，从而高估了二氧化碳汇强度。我们提出了一种新的基于过程的方法，利用动态全球植被模型来估计SLAND。我们的修正估计在2015-2024年期间将SLAND减少了约20% (0.6 PgC -1)，从3.00±0.94降至2.42±0.77 PgC -1。我们将这一新的SLAND估计值与簿记模式中土地利用变化产生的排放结合起来，估计净陆地汇为1.19±1.04 PgC年-1，这与大气反演约束非常吻合。SLAND的向下修正降低了2015-2024年预算失衡的程度，表明全球碳预算的分配更加一致。
{"title":"An improved approach to estimate the natural land carbon sink","authors":"Michael O’Sullivan, Pierre Friedlingstein, Stephen Sitch, Julia Pongratz, Clemens Schwingshackl, Thomas Gasser, Philippe Ciais, Vivek Arora, Etsushi Kato, Jürgen Knauer, Erwan Monier, Tobias Nützel, Qing Sun, Wenping Yuan, Xu Yue, Sönke Zaehle","doi":"10.1038/s41612-025-01302-7","DOIUrl":"https://doi.org/10.1038/s41612-025-01302-7","url":null,"abstract":"The natural land carbon sink (SLAND) absorbs roughly 25–30% of anthropogenic CO2 emissions, thus playing a critical role in offsetting climate warming. In the Global Carbon Budget (GCB), SLAND is estimated using model simulations that isolate the carbon response of land to environmental changes (i.e. rising atmospheric CO2, nitrogen deposition, and changes in climate). However, these simulations assume fixed pre-industrial land cover, failing to represent today’s human-altered landscapes. This leads to a systematic overestimation of forest area, and thus CO2 sink strength, in regions heavily altered by human activity. We present a new process-based approach to estimate SLAND using Dynamic Global Vegetation Models. Our corrected estimate reduces SLAND by ~20% (0.6 PgC yr-1) over 2015–2024, from 3.00 ± 0.94 to 2.42 ± 0.77 PgC yr-1. We incorporate this new SLAND estimate with emissions from land-use change from bookkeeping models, to estimate a net land sink of 1.19 ± 1.04 PgC yr-1, which aligns closely with atmospheric inversion constraints. This downward revision of SLAND reduces the magnitude of the budget imbalance for 2015–2024, indicating a more consistent partitioning of the global carbon budget.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"51 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2026-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146033638","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 : 2026-01-21DOI: 10.1038/s41612-026-01329-4
John L. McBride, Lichun Tang, Zifeng Yu, Klaus Fraedrich
Rapid intensification (RI) of tropical cyclones (TCs) poses a major challenge in intensity forecasting and is a key contributor to the observed bimodal distribution of cyclone peak intensities. However, it remains unclear whether RI represents a distinct dynamical process. Here, we use lag plot (phase space) analysis from nonlinear dynamical systems theory to examine the underlying dynamics of RI and non-RI cyclones. Case studies of Typhoon Yagi (RI) and Typhoon Bebinca (non-RI) that made landfall in southern China in September 2024, combined with statistical analyses of a global cyclone dataset (1990–2021), reveal systematic differences in phase trajectories and correlations between lifetime maximum intensity (LMI) and intensification time. Our findings suggest that RI is not merely an amplification of normal intensification but represents a distinct dynamical regime, characterised by a transient intensification process, rather than the approximately steady intensity growth of the non-RI cyclones. A simple trend-persistence model is used as a dynamical diagnostic to examine error growth in the two regimes.
{"title":"Do rapidly and non-rapidly intensifying tropical cyclones represent two different dynamical regimes","authors":"John L. McBride, Lichun Tang, Zifeng Yu, Klaus Fraedrich","doi":"10.1038/s41612-026-01329-4","DOIUrl":"https://doi.org/10.1038/s41612-026-01329-4","url":null,"abstract":"Rapid intensification (RI) of tropical cyclones (TCs) poses a major challenge in intensity forecasting and is a key contributor to the observed bimodal distribution of cyclone peak intensities. However, it remains unclear whether RI represents a distinct dynamical process. Here, we use lag plot (phase space) analysis from nonlinear dynamical systems theory to examine the underlying dynamics of RI and non-RI cyclones. Case studies of Typhoon Yagi (RI) and Typhoon Bebinca (non-RI) that made landfall in southern China in September 2024, combined with statistical analyses of a global cyclone dataset (1990–2021), reveal systematic differences in phase trajectories and correlations between lifetime maximum intensity (LMI) and intensification time. Our findings suggest that RI is not merely an amplification of normal intensification but represents a distinct dynamical regime, characterised by a transient intensification process, rather than the approximately steady intensity growth of the non-RI cyclones. A simple trend-persistence model is used as a dynamical diagnostic to examine error growth in the two regimes.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"6 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2026-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146006140","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 : 2026-01-20DOI: 10.1038/s41612-026-01330-x
Kai Zhao, Haikun Zhao, Philip J. Klotzbach, Liguang Wu, Chao Wang, Jian Cao
Changes in tropical cyclone (TC) frequency in a warming climate remain highly uncertain, with model simulations often yielding conflicting results. Here, through an analysis of 26 CMIP6 models under the SSP5-8.5 scenario, we project a decline in global TC frequency of 2–10% by the late 21st century. This decline is driven by an El Niño-like warming pattern, marked by amplified warming in the equatorial central-eastern Pacific, equatorial Atlantic, and North Indian Ocean. These non-uniform sea surface temperature (SST) trends weaken zonal SST gradients, suppressing the Walker circulation, and inducing Gill-type atmospheric responses to localized heating, in addition to an equatorward shift in the Intertropical Convergence Zone. These changes reduce upward motion across most basins, suppressing TC genesis. Additionally, radiative forcing reduces interhemispheric temperature contrasts, dampening the cross-equatorial Hadley circulation and further decreasing TC frequency, most notably in the South Indian Ocean. Our findings highlight the critical role of spatially heterogeneous SST warming in modulating TC activity and stress the need to reduce uncertainties in future SST projections. These insights advance the physical understanding of climate-driven TC projections and provide essential guidance for adaptation planning in vulnerable regions.
{"title":"Anthropogenic warming projected to drive a decline in global tropical cyclone frequency in CMIP6 simulations","authors":"Kai Zhao, Haikun Zhao, Philip J. Klotzbach, Liguang Wu, Chao Wang, Jian Cao","doi":"10.1038/s41612-026-01330-x","DOIUrl":"https://doi.org/10.1038/s41612-026-01330-x","url":null,"abstract":"Changes in tropical cyclone (TC) frequency in a warming climate remain highly uncertain, with model simulations often yielding conflicting results. Here, through an analysis of 26 CMIP6 models under the SSP5-8.5 scenario, we project a decline in global TC frequency of 2–10% by the late 21st century. This decline is driven by an El Niño-like warming pattern, marked by amplified warming in the equatorial central-eastern Pacific, equatorial Atlantic, and North Indian Ocean. These non-uniform sea surface temperature (SST) trends weaken zonal SST gradients, suppressing the Walker circulation, and inducing Gill-type atmospheric responses to localized heating, in addition to an equatorward shift in the Intertropical Convergence Zone. These changes reduce upward motion across most basins, suppressing TC genesis. Additionally, radiative forcing reduces interhemispheric temperature contrasts, dampening the cross-equatorial Hadley circulation and further decreasing TC frequency, most notably in the South Indian Ocean. Our findings highlight the critical role of spatially heterogeneous SST warming in modulating TC activity and stress the need to reduce uncertainties in future SST projections. These insights advance the physical understanding of climate-driven TC projections and provide essential guidance for adaptation planning in vulnerable regions.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"63 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2026-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146006103","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 : 2026-01-19DOI: 10.1038/s41612-026-01325-8
Leonardo A. Clarke, Jhordanne J. Jones, Michael A. Taylor, Matthew St. Michael Williams, Tajay Edwards, Tannecia S. Stephenson
Sea surface temperatures (SSTs) in the tropical North Atlantic have historically served as reliable predictors of early-season rainfall across the Caribbean. In particular, rainfall onset has been linked to SSTs exceeding the convective threshold necessary to support deep convection. However, recent warming trends appear to have altered this relationship. Here, we show that although SSTs routinely exceed the convective threshold earlier in the season, early rainfall has not increased. This decoupling reflects a shift in the atmospheric state, with enhanced stability, evidenced by reduced convective available potential energy and increased convective inhibition, increasingly suppressing convection. Reduced rainfall results in a more persistent Caribbean Low-Level Jet (CLLJ), further inhibiting rainfall by promoting subsidence and dry air advection. Correlations indicate that dynamic atmospheric variables now explain a larger share of rainfall variability than absolute SSTs. These findings signal a regime shift in Caribbean rainfall dynamics and raise concerns about the declining utility of SST-based predictors under continued climate warming. These results have significant implications for seasonal forecasting and adaptation planning across Caribbean Small Island Developing States.
{"title":"Breaking the link: warming disrupts early-season rainfall predictability in the Caribbean","authors":"Leonardo A. Clarke, Jhordanne J. Jones, Michael A. Taylor, Matthew St. Michael Williams, Tajay Edwards, Tannecia S. Stephenson","doi":"10.1038/s41612-026-01325-8","DOIUrl":"https://doi.org/10.1038/s41612-026-01325-8","url":null,"abstract":"Sea surface temperatures (SSTs) in the tropical North Atlantic have historically served as reliable predictors of early-season rainfall across the Caribbean. In particular, rainfall onset has been linked to SSTs exceeding the convective threshold necessary to support deep convection. However, recent warming trends appear to have altered this relationship. Here, we show that although SSTs routinely exceed the convective threshold earlier in the season, early rainfall has not increased. This decoupling reflects a shift in the atmospheric state, with enhanced stability, evidenced by reduced convective available potential energy and increased convective inhibition, increasingly suppressing convection. Reduced rainfall results in a more persistent Caribbean Low-Level Jet (CLLJ), further inhibiting rainfall by promoting subsidence and dry air advection. Correlations indicate that dynamic atmospheric variables now explain a larger share of rainfall variability than absolute SSTs. These findings signal a regime shift in Caribbean rainfall dynamics and raise concerns about the declining utility of SST-based predictors under continued climate warming. These results have significant implications for seasonal forecasting and adaptation planning across Caribbean Small Island Developing States.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"53 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2026-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146006138","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 : 2026-01-19DOI: 10.1038/s41612-026-01331-w
S. Abhik, Fabio A. Capitanio, B. N. Goswami, Alexander Farnsworth, Peter D. Clift, Dietmar Dommenget
{"title":"Author Correction: A brief history of Asian summer monsoon evolution in the Cenozoic era","authors":"S. Abhik, Fabio A. Capitanio, B. N. Goswami, Alexander Farnsworth, Peter D. Clift, Dietmar Dommenget","doi":"10.1038/s41612-026-01331-w","DOIUrl":"https://doi.org/10.1038/s41612-026-01331-w","url":null,"abstract":"","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"1 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2026-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146033642","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}
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