npj Climate and Atmospheric Science最新文献

{"title":"CO2-induced climate change assessment for the extreme 2022 Pakistan rainfall using seasonal forecasts","authors":"Antje Weisheimer, Tim N. Palmer, Nicholas J. Leach, Myles R. Allen, Christopher D. Roberts, Muhammad Adnan Abid","doi":"10.1038/s41612-025-01136-3","DOIUrl":"https://doi.org/10.1038/s41612-025-01136-3","url":null,"abstract":"<p>While it is widely believed that the intense rainfall in summer 2022 over Pakistan was substantially exacerbated by anthropogenic climate change^1,2, climate models struggled to confirm this^3,4. Using a high-resolution operational seasonal forecasting system that successfully predicted the extreme wet conditions, we perform counterfactual experiments simulating pre-industrial and future conditions. Both experiments also exhibit strong anomalous rainfall, indicating a limited role of CO₂-induced forcing. We attribute 10% of the total rainfall to historical increases in CO₂ and ocean temperature. However, further increases in the future suggest a weak mean precipitation reduction but with increased variability. By decomposing rainfall and large-scale circulation into CO₂ and SST-related signals, we illustrate a tendency for these signals to compensate each other in future scenarios. This suggests that historical CO₂ impacts may not reliably predict future responses. Accurately capturing local dynamics is therefore essential for regional climate adaptation planning and for informing loss and damage discussions.</p>","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"22 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144594805","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":"Toward long-range ENSO prediction with an explainable deep learning model","authors":"Qi Chen, Yinghao Cui, Guobin Hong, Karumuri Ashok, Yuchun Pu, Xiaogu Zheng, Xuanze Zhang, Wei Zhong, Peng Zhan, Zhonglei Wang","doi":"10.1038/s41612-025-01159-w","DOIUrl":"https://doi.org/10.1038/s41612-025-01159-w","url":null,"abstract":"<p>El Niño-Southern Oscillation (ENSO) is a prominent mode of interannual climate variability with far-reaching global impacts. Its evolution is governed by intricate air-sea interactions, posing significant challenges for long-term prediction. In this study, we introduce CTEFNet, a multivariate deep learning model that synergizes convolutional neural networks and transformers to enhance ENSO forecasting. By integrating multiple oceanic and atmospheric predictors, CTEFNet extends the effective forecast lead time to 20 months while mitigating the impact of the spring predictability barrier, outperforming both dynamical models and state-of-the-art deep learning approaches. Furthermore, CTEFNet offers physically meaningful and statistically significant insights through gradient-based sensitivity analysis, revealing the key precursor signals that govern ENSO dynamics, which align with well-established theories and reveal new insights about inter-basin interactions among the Pacific, Atlantic, and Indian Oceans. The CTEFNet’s superior predictive skill and interpretable sensitivity assessments underscore its potential for advancing climate prediction. Our findings highlight the importance of multivariate coupling in ENSO evolution and demonstrate the promise of deep learning in capturing complex climate dynamics with enhanced interpretability.</p>","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"8 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144587029","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":"Unravelling drivers of the future Mediterranean precipitation paradox during cyclones","authors":"Marco Chericoni, Giorgia Fosser, Emmanouil Flaounas, Marco Gaetani, Alessandro Anav","doi":"10.1038/s41612-025-01121-w","DOIUrl":"https://doi.org/10.1038/s41612-025-01121-w","url":null,"abstract":"<p>Both global climate models and a high-resolution atmosphere-ocean coupled regional climate model project a drying trend across the Mediterranean region, alongside an increase in cyclone-related precipitation. However, only the high-resolution model captures the physical mechanisms driving these changes across three emission scenarios, namely, enhanced moisture transport processes fuelling cyclone activity. These results highlight the added value of fine-scale modelling for understanding future Mediterranean hydroclimatic extremes.</p>","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"11 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144594909","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":"Types of regional and localised new aerosol particle formation and growth processes: Atmospheric Banana Atlas","authors":"Imre Salma, Tamás Weidinger, János Rohonczy, Máté Vörösmarty","doi":"10.1038/s41612-025-01149-y","DOIUrl":"https://doi.org/10.1038/s41612-025-01149-y","url":null,"abstract":"<p>The structure and variability of atmospheric new particle formation and particle diameter growth (NPF&amp;G) processes provide valuable insights into the underlying chemical, physical and meteorological mechanisms including atmospheric mixing and transport-related effects. Therefore, we systematically categorised and characterised the NPF&amp;G events observed over 13 years in an urban environment. Six regional-scale banana plot types with narrow onset, broad onset, arch shape, double onset, tandem growth and nocturnal occurrence were identified. Additionally, two localised types were defined: one exhibiting multiple, but underdeveloped banana shapes, and another with diverse angulate structures, both being limited in time. The localised processes typically occurred on 7% of days, and produced high (up to 60 × 10³ cm⁻³) ultrafine particle number concentrations. Regional and localised processes can also happen on the same day. Our findings highlight the need to extend current NPF&amp;G identification and classification frameworks by incorporating an additional step to distinguish localised events from regional processes.</p>","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"7 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144594786","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":"How key features of early development shape deep convective systems","authors":"Sophie Abramian, Caroline Muller, Camille Risi, Thomas Fiolleau, Rémy Roca","doi":"10.1038/s41612-025-01154-1","DOIUrl":"https://doi.org/10.1038/s41612-025-01154-1","url":null,"abstract":"<p>Deep Convective Systems (DCSs) reaching scales of 100–1000 km play a pivotal role as the primary precipitation source in the tropics. Those systems can have large cloud shields, and thus not only affect severe precipitation patterns but also play a crucial part in modulating the tropical radiation budget. Understanding the complex factors that control how these systems grow and how they will behave in a warming climate remain fundamental challenges. Research efforts have been directed, on one hand, towards understanding the environmental control on these systems, and on the other hand, towards exploring the internal potential of systems to develop and self-aggregate in idealized simulations. However, we still lack understanding on the relative role of the environment and internal feedbacks on DCS mature size and why. The novel high-resolution global SAM simulation from the DYAMOND project, combined with the TOOCAN Lagrangian tracking of DCSs and machine learning tools, offers an unprecedented opportunity to explore this question. We find that a system’s growth rate during the first 2 h of development predicts its final size with a Pearson correlation coefficient of 0.65. Beyond this period, growth rate emerges as the strongest predictor. However, in the early stages, additional factors–such as ice water path heterogeneity, migration distance, interactions with neighboring systems, and deep shear–play a more significant role. Our study quantitatively assesses the relative influence of internal versus external factors on the mature cloud shield size. Our results show that system-intrinsic properties exert a stronger influence than environmental conditions, suggesting that the initial environment does not strictly constrain final system size, particularly for larger systems where internal dynamics dominate.</p>","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"150 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144578275","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":"Source apportionment of PM10 based on offline chemical speciation data at 24 European sites","authors":"Xiansheng Liu, Xun Zhang, Bowen Jin, Tao Wang, Siyuan Qian, Jin Zou, Vy Ngoc Thuy Dinh, Jean-Luc Jaffrezo, Gaëlle Uzu, Pamela Dominutti, Sophie Darfeuil, Olivier Favez, Sébastien Conil, Nicolas Marchand, Sonia Castillo, Jesús D. de la Rosa, Stuart Grange, Christoph Hueglin, Konstantinos Eleftheriadis, Evangelia Diapouli, Manousos-Ioannis Manousakas, Maria Gini, Silvia Nava, Giulia Calzolai, Célia Alves, Marta Monge, Cristina Reche, Roy M. Harrison, Philip K. Hopke, Andrés Alastuey, Xavier Querol","doi":"10.1038/s41612-025-01097-7","DOIUrl":"https://doi.org/10.1038/s41612-025-01097-7","url":null,"abstract":"<p>This study applied Positive Matrix Factorization (PMF) to PM₁₀ speciation datasets from 24 urban sites across six European countries (France, Greece, Italy, Portugal, Spain, and Switzerland) to perform a detailed source apportionment (SA) analysis. By using a consistent source apportionment tool for all datasets, the study enhances the comparability of PM₁₀ SA results across urban Europe. The results identified seven major PM₁₀ sources including road traffic, biomass burning, crustal/mineral sources, secondary aerosols, industrial emissions, sea salt, and heavy oil combustion (HOC). Road traffic emerged as the predominant source of PM₁₀ in urban areas, with contributions varying by location, but representing as much as 41% in high-traffic zones. Biomass burning was detected at 23 sites, contributing 8% to 41% on yearly averages, with substantial increase in winter. Crustal sources were present at all sites (3–33%). Industrial sources contributed relatively less PM₁₀ mass, which was identified at 10 sites with contributions ranging from 2% to 14%. Secondary inorganic and organic aerosol, consisting primarily of ammonium nitrates and sulfates, and organic matter, formed a portion of the PM₁₀ mass (5–41%). These secondary factors are primarily influenced by anthropogenic emissions, including the various combustion processes. Sea salt, predominantly found in coastal areas, contributed between 4% and 21%, reflecting the impact of the marine environments on air quality. This source was very often ‘aged’ (mixed with anthropogenic pollutants from different origins). Additionally, HOC, especially emits from shipping activities, and traced by V and Ni, was also a frequent contributing source (2–15% for 9 sites), indicating a need for more stringent emission controls. The chemical comparison is performed which indicates road traffic and secondary aerosols, showed consistent chemical profiles across sites, while industrial, HOC, and crustal sources displayed significant site-specific variability. These findings underscore the need for tailored air quality strategies according to local sources of emissions and the importance of long-term PM speciation monitoring for effective pollution control.</p>","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"27 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144566379","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":"Largely underestimated production of isoprene epoxydiols (IEPOX) through high-NO oxidation pathways in urban areas","authors":"Sainan Wang, Mike J. Newland, Andrew R. Rickard, Jacqueline F. Hamilton, Thomas J. Bannan, Archit Mehra, Carl J. Percival, Freya A. Squires, Weiwei Hu, Wei Song, Yang Chen, Xiaoling Zhang, Liming Wang, Xinming Wang","doi":"10.1038/s41612-025-01151-4","DOIUrl":"https://doi.org/10.1038/s41612-025-01151-4","url":null,"abstract":"<p>Isoprene is the dominant nonmethane volatile organic compound (VOC) emitted into the atmosphere globally, with important atmospheric chemistry impacts on air quality and climate. One crucial intermediate in its gas-phase oxidation is isoprene epoxydiol (IEPOX), which contributes significantly to the formation of secondary organic aerosols (SOA). It is generally accepted that IEPOX is efficiently formed in remote forested regions with a sufficiently low NO/HO₂ ratio. Here, we show that the oxidation of isoprene hydroxynitrates (IHN) can be an alternative, efficient, NO-driven pathway leading to the formation of IEPOX in urban areas where moderate to high NO concentrations exist. Field measurements from the megacity of Beijing show that this pathway contributes to more than 50% of IEPOX production during the morning and early afternoon. The results improve our understanding of the NO_x dependence of SOA formation in polluted areas, where anthropogenic emissions can significantly enhance biogenic SOA formation.</p>","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"4 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144566378","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":"Dynamic calibration of low-cost PM2.5 sensors using trust-based consensus mechanisms","authors":"Sachit Mahajan, Dirk Helbing","doi":"10.1038/s41612-025-01145-2","DOIUrl":"https://doi.org/10.1038/s41612-025-01145-2","url":null,"abstract":"<p>Low-cost particulate matter (PM) sensors enable high-resolution urban air quality monitoring but face challenges from offsets, scaling mismatches, and drift. We propose an <i>adaptive</i> trust-based calibration framework that first corrects systematic errors and then dynamically adjusts model complexity based on sensor reliability. Extensive simulations and real-world deployment in Zurich, Switzerland validate the approach. Each sensor’s trust score integrates four indicators: accuracy, stability, responsiveness, and consensus alignment. High-trust sensors receive minimal correction, preserving baseline accuracy, while low-trust sensors leverage expanded wavelet-based features and deeper models. Results show mean absolute error (MAE) reductions of up to 68% for poorly performing sensors and 35–38% for reliable ones, outperforming conventional calibration methods. By using trust-weighted consensus, the framework reduces dependence on large training datasets and frequent re-calibrations, ensuring scalability. These findings demonstrate that dynamic, trust-driven calibration can substantially enhance low-cost sensor network accuracy across both controlled scenarios and complex real-world environments.</p>","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"1 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144566239","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":"Evaluating predictability limits of North American winter precipitation","authors":"Joseph P. Clark, Nathaniel C. Johnson","doi":"10.1038/s41612-025-01132-7","DOIUrl":"https://doi.org/10.1038/s41612-025-01132-7","url":null,"abstract":"<p>Given that seasonal precipitation predictions over North America are not particularly skillful, assessing whether forecast system refinements can enhance skill and societal usefulness of seasonal forecasts is important. We investigate by using average predictability time (APT) analysis to filter wintertime, seasonal precipitation hindcasts provided by the Seamless System for Prediction and Earth System Research. Using this method, which decomposes forecasts into predictable modes, we find limited potential to improve seasonal precipitation forecasts over North America owing to the subseasonal predictability timescales of most APT modes. Nevertheless, more skillful forecasts of APT mode 2, which is tied to equatorial Pacific convection and has a predictability timescale of about 220 days, may improve seasonal precipitation forecasts over North America. We demonstrate that predictions for the winters of 2015–2016 and 2021–2022, which featured notable forecast errors over western North America, may have been improved with better predictions of this second APT mode.</p>","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"9 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144547352","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":"Emergence of anthropogenic precipitation changes in a future warmer climate","authors":"Shoji Kusunoki, Ryo Mizuta, Masahiro Hosaka","doi":"10.1038/s41612-025-01128-3","DOIUrl":"https://doi.org/10.1038/s41612-025-01128-3","url":null,"abstract":"<p>The ‘emergence year’ <i>Ye</i> is defined as the start of a future period during which precipitation consistently exceeds the maximum value of the past historical period. Emergence years of future anthropogenic changes in annual average precipitation (<i>Pav</i>) and annual maximum 1-day precipitation (<i>P1d</i>) were projected using high-resolution global atmospheric models with 20-km and 60-km grid-size for the period 1950-2099. A total of 10,000 randomized time series representing the time evolution of decadal natural variability enabled us to directly evaluate estimated frequency distributions (EDFs) on a grid point basis. <i>Ye</i> for both <i>Pav</i> and <i>P1d</i> generally occur earlier at high latitudes than they are elsewhere, and <i>Ye</i>(<i>P1d</i>) is generally later than <i>Ye</i>(<i>Pav</i>). <i>Ye</i>(<i>P1d</i>) covers a larger area than <i>Ye</i>(<i>Pav</i>) does and <i>Ye</i>(<i>P1d</i>) may occur earlier in the tropics and mid-latitudes than <i>Ye</i>(<i>Pav</i>). <i>Ye</i> occurs earlier in scenarios with higher anthropogenic emissions than in scenarios with lower emissions.</p>","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"148 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144547389","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}