npj Climate and Atmospheric Science最新文献

{"title":"Predictability of tropical cyclone track density in S2S reforecast","authors":"Chi Lok Loi, Kai-Chih Tseng, Chun-Chieh Wu","doi":"10.1038/s41612-025-00909-0","DOIUrl":"https://doi.org/10.1038/s41612-025-00909-0","url":null,"abstract":"<p>In this study, we examine the predictability of tropical cyclone (TC) track density in the subseasonal-to-seasonal (S2S) reforecast ensembles of the European Centre for Medium-range Weather Forecasts (ECMWF) using the method of average predictability time (APT). Eleven of the retrieved APT modes (APTMs) of TC track density possess an APT longer than 1 week. The most predictable of them, APTM-1, has an APT of almost three weeks and is found to be closely linked to the Boreal Summer Intraseasonal Oscillation (BSISO) and monsoon variability. Another discovery is the strong relationship between APTM-7 and the activity of mixed Rossby-gravity (MRG) waves and tropical depression (TD) type disturbances despite its short APT of ~12 days. We further carry out a simple case analysis to see how the relatively high predictability of APTM-1 manifests in the S2S model. Our work provides a new possibility for improving medium-range TC forecast skill, and has revealed how underlying tropical variability can play a role in determining TC predictability.</p>","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"44 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142989113","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":"Effects of fine terrain complexity on cloud and precipitation changes over the Tibetan Plateau: a modeling study","authors":"Kai Yang, Jinghua Chen, Tianliang Zhao, Chunsong Lu, Xiangde Xu, Yuehan Luo, Qingjian Yang, Chenghao Tan, Weikang Fu, Ziyue Wang","doi":"10.1038/s41612-025-00907-2","DOIUrl":"https://doi.org/10.1038/s41612-025-00907-2","url":null,"abstract":"<p>Inaccurate characterization of complex topography leads to the wet bias in climate models, particularly affecting terrain effects in regions like the Tibetan Plateau (TP). This study utilizes the Weather Research and Forecasting (WRF) model with multiple terrain datasets and introduces the terrain complexity index (TCI) to quantify the degree of terrain changes, aiming to evaluate how terrain complexity affects the cloud and precipitation processes over the TP. The results indicate that fine terrain complexity primarily causes earlier cloud formation and precipitation, resulting in more heavy precipitation on the southern slope of the TP (SSTP) and more light precipitation on the TP platform. The structure of moisture transport and microphysical processes further reveals that this promotes the formation of more medium and high clouds, increasing the proportion of solid precipitation over the SSTP. Over the TP platform, the restriction of medium and high cloud development with enhancing the proportion of low clouds for more liquid precipitation. These findings deepen the understanding of the TP’s complex terrain effect on cloud and precipitation changes in the Asian water cycle.</p>","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"29 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142987637","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":"Comparative analysis of methods for seasonal particulate organic nitrate estimation in urban areas","authors":"Wenfei Zhu, Jialin Shi, Song Guo, Qinghong Wang, Jun Chen, Shengrong Lou, Min Hu","doi":"10.1038/s41612-025-00904-5","DOIUrl":"https://doi.org/10.1038/s41612-025-00904-5","url":null,"abstract":"<p>Accurately estimating particulate organic nitrate under high NO_x and oxidizing conditions is critical. This study compared the NO_x⁺ ratio, unconstrained Positive Matrix Factorization (PMF), and Multilinear Engine-2 (ME2) methods to estimate particulate organic nitrate in Shanghai across different seasons. The factors associated with organic nitrate, as identified through two receptor methods, exhibited consistent daily patterns in spring, summer, and autumn, although source contributions varied. The NO_x⁺ ratio method reported higher organic nitrate levels than the PMF and ME2 methods, likely due to the fixed R_ON/R_AN parameter. Seasonal R_ON/R_AN parameters were optimized based on precursor emissions in Shanghai, achieving values of 3.13 in spring, 2.25 in summer, and 1.88 in autumn. This optimization reduced discrepancies in organic nitrate using the NO_x⁺ ratio to 3.2–7.4%. The optimized parameters in this study support the rapid and accurate estimation of organic nitrate during different seasons in urban areas.</p>","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"39 14 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142987636","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":"Amplification of Northern Hemisphere winter stationary waves in a warming world","authors":"Jueun Lee, S.-Y. Simon Wang, Seok-Woo Son, Daehyun Kim, Jee-Hoon Jeong, Hyungjun Kim, Jin-Ho Yoon","doi":"10.1038/s41612-025-00898-0","DOIUrl":"https://doi.org/10.1038/s41612-025-00898-0","url":null,"abstract":"<p>This study leverages the Global/Regional Integrated Model system (GRIMs) version 4.0 climate model to examine the mechanisms behind the recent intensification of winter stationary waves over western North America. Prescribed sea surface temperature warming forces a strengthening of westerly winds, amplifying the ridge that characterizes the stationary waves in western North America. The streamfunction budget analysis reveals relative vorticity advection is mainly associated with this process. We further show that ocean warming is the primary driver of changes in westerly winds and stationary waves in the Northern Hemisphere. Sea ice losses exert a considerable effect through a different mechanism, complementing the dominant influence of ocean warming on these atmospheric changes. Our results thus reveal the crucial role tropical oceans play in modulating global warming’s effect on the stationary waves in the Northern Hemisphere and add a more quantitative perspective to the previously reported influence of Arctic amplification.</p>","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"30 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142987638","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":"Weak coupling of observed surface PM2.5 in Delhi-NCR with rice crop residue burning in Punjab and Haryana","authors":"Poonam Mangaraj, Yutaka Matsumi, Tomoki Nakayama, Akash Biswal, Kazuyo Yamaji, Hikaru Araki, Natsuko Yasutomi, Masayuki Takigawa, Prabir K. Patra, Sachiko Hayashida, Akanksha Sharma, A. P. Dimri, Surendra K. Dhaka, Manpreet S. Bhatti, Mizuo Kajino, Sahil Mor, Ravindra Khaiwal, Sanjeev Bhardwaj, Vimal J. Vazhathara, Ravi K. Kunchala, Tuhin K. Mandal, Prakhar Misra, Tanbir Singh, Kamal Vatta, Suman Mor","doi":"10.1038/s41612-025-00901-8","DOIUrl":"https://doi.org/10.1038/s41612-025-00901-8","url":null,"abstract":"<p>Air pollution impacts on human health are of serious concern in northern India, and over the Delhi National Capital Region (NCR) in particular. The Kharif crop residue burning (CRB) is often blamed for degradation of Delhi-NCR’s seasonal air quality. However, the concentration of fine particulate matter (PM_2.5) remained stable in Delhi, while the fire detection counts (FDCs) from satellites over Punjab and Haryana declined by 50% or more during 2015–2023. We measured PM_2.5, carbon monoxide (CO) and related parameters over Delhi-NCR, Haryana and Punjab from a network of 30 low-cost sensors (CUPI-Gs) in a selected period (September–November) of 2022 and 2023. Measured PM_2.5 showed lower concentration in 2023 compared to 2022 at Punjab and Haryana sites, in compliance with FDC reductions. Using the CUPI-G measurements, airmass trajectories, particle dispersion and chemical-transport model simulations, we show that the CRB emissions over Punjab contributed only a meagre ~14% to the overall PM_2.5 over Delhi-NCR during October-November 2022. This indicates that there exists only a very weak coupling between PM_2.5 mass over Delhi-NCR and the CRB over Punjab, highlighting the effectiveness of the Graded Response Action Plan (GRAP) in controlling air pollution in the region.</p>","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"16 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142981855","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":"Climate change aggravated wildfire behaviour in the Iberian Peninsula in recent years","authors":"Martín Senande-Rivera, Damián Insua-Costa, Gonzalo Miguez-Macho","doi":"10.1038/s41612-025-00906-3","DOIUrl":"https://doi.org/10.1038/s41612-025-00906-3","url":null,"abstract":"<p>Climate change is considered to affect wildfire spread both by increasing fuel dryness and by altering vegetation mass and structure. However, the direct effect of global warming on wildfires is hard to quantify due to the multiple non-climatic factors involved in their ignition and spread. By combining wildfire observations with the latest generation of climate models, here we show that more than half of the large wildfires (area&gt;500 ha) occurring in the Iberian Peninsula between 2001 and 2021 present a significant increase in the rate of spread with respect to what it would have been in the pre-industrial period, attributable to global warming. The average acceleration of the rate of spread due to increased fuel dryness is between 2.0% and 8.3%, whereas the influence of enhanced vegetation growth since the pre-industrial period could potentially be even higher than the direct impact of temperature increase in fuel conditions.</p>","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"45 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142981858","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":"Substantial increases in compound climate extremes and associated socio-economic exposure across China under future climate change","authors":"Pei Fang, Taihua Wang, Dawen Yang, Lihua Tang, Yuting Yang","doi":"10.1038/s41612-025-00910-7","DOIUrl":"https://doi.org/10.1038/s41612-025-00910-7","url":null,"abstract":"<p>Under climate change, China faces intensifying compound extreme events with serious socio-economic ramifications, yet their future variations remain poorly understood. Here, we estimate historical hotspots and future changes of two typical compound events, i.e., sequential heatwave and precipitation (SHP) and concurrent drought and heatwave (CDH) across China, leveraging a bivariate bias correction method to adjust projections from global climate models. Results show substantial future increases in frequency, duration, and magnitude for both events, with the durations projected to double nationwide. The increases are more evident under higher emission scenarios, and could be largely underestimated if neglecting variable dependence during bias correction process. The projected changes will escalate socio-economic exposure across China’s major urban clusters, among which Guangdong-Hong Kong-Macao will face the highest risk. Our findings underscore the necessity of carbon emission controls, and call for adaptive measures to mitigate the threats induced by rising compound hazards in a changing climate.</p>","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"17 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142974848","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":"Skillful subseasonal ensemble predictions of heat wave onsets through better representation of land surface uncertainties","authors":"Qiyu Zhang, Mu Mu, Guodong Sun","doi":"10.1038/s41612-024-00876-y","DOIUrl":"https://doi.org/10.1038/s41612-024-00876-y","url":null,"abstract":"<p>Uncertainties in land surface processes notably limit subseasonal heat wave (HW) onset predictions. A better representation of the uncertainties in land surface processes using ensemble prediction methods may be an important way to improve HW onset predictions. However, generating ensemble members that adequately represent land surface process uncertainties, particularly those related to land surface parameters, remains challenging. In this study, a conditional nonlinear optimal perturbation related to parameters (CNOP-P) approach was employed to generate ensemble members for representing the uncertainties in land surface processes resulting from parameters. Via six strong and long-lasting HW events over the middle and lower reaches of the Yangtze River (MLYR), HW onset ensemble forecast experiments were conducted with the Weather Research and Forecasting (WRF) model. The performance of the CNOP-P approach and the traditional random parameter perturbation ensemble prediction method was evaluated. The results demonstrate that the deterministic and probabilistic skills of HW onset predictions show greater excellence using the CNOP-P approach, leading to much better predictions of extreme air temperatures than those using the traditional method. This occurred because the ensemble members generated by the CNOP-P method better represented the uncertainties in important land physical processes determining HW onsets over the MLYR, notably vegetation process uncertainties, whereas the ensemble members generated by the random parameter perturbation method could not. This finding suggests that the CNOP-P method is suitable for producing ensemble members that more appropriately represent model uncertainties through more reasonable parameter error characterization.</p>","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"75 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142974845","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":"Soil moisture controls over carbon sequestration and greenhouse gas emissions: a review","authors":"Yuefeng Hao, Jiafu Mao, Charles M. Bachmann, Forrest M. Hoffman, Gerbrand Koren, Haishan Chen, Hanqin Tian, Jiangong Liu, Jing Tao, Jinyun Tang, Lingcheng Li, Laibao Liu, Martha Apple, Mingjie Shi, Mingzhou Jin, Qing Zhu, Steve Kannenberg, Xiaoying Shi, Xi Zhang, Yaoping Wang, Yilin Fang, Yongjiu Dai","doi":"10.1038/s41612-024-00888-8","DOIUrl":"https://doi.org/10.1038/s41612-024-00888-8","url":null,"abstract":"<p>This literature review synthesizes the role of soil moisture in regulating carbon sequestration and greenhouse gas emissions (CS-GHG). Soil moisture directly affects photosynthesis, respiration, microbial activity, and soil organic matter dynamics, with optimal levels enhancing carbon storage while extremes, such as drought and flooding, disrupt these processes. A quantitative analysis is provided on the effects of soil moisture on CS-GHG across various ecosystems and climatic conditions, highlighting a “Peak and Decline” pattern for CO₂ emissions at 40% water-filled pore space (WFPS), while CH₄ and N₂O emissions peak at higher levels (60–80% and around 80% WFPS, respectively). The review also examines ecosystem models, discussing how soil moisture dynamics are incorporated to simulate photosynthesis, microbial activity, and nutrient cycling. Sustainable soil moisture management practices, including conservation agriculture, agroforestry, and optimized water management, prove effective in enhancing carbon sequestration and mitigating GHG emissions by maintaining ideal soil moisture levels. The review further emphasizes the importance of advancing multiscale observations and feedback modeling through high-resolution remote sensing and ground-based data integration, as well as hybrid modeling frameworks. The interactive model-experiment framework emerges as a promising approach for linking experimental data with model refinement, enabling continuous improvement of CS-GHG predictions. From a policy perspective, shifting focus from short-term agricultural productivity to long-term carbon sequestration is crucial. Achieving this shift will require financial incentives, robust monitoring systems, and collaboration among stakeholders to ensure sustainable practices effectively contribute to climate mitigation goals.</p>","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"29 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142974846","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":"Attribution of a record-breaking cold event in the historically warmest year of 2023 and assessing future risks","authors":"Yangbo Ye, Cheng Qian, Aiguo Dai, Yuting Zhang, Jiacheng Jiang, Xiaoye Zhang","doi":"10.1038/s41612-024-00886-w","DOIUrl":"https://doi.org/10.1038/s41612-024-00886-w","url":null,"abstract":"<p>An unexpected record-breaking cold event struck eastern China in December 2023, causing widespread transportation shutdowns, power supply shortages, and agricultural crop damage. The manner in which such an extraordinary cold event was formed under global warming is unclear, as is the way in which anthropogenic climate change may affect the present and future frequency and intensity of similar cold events. Here, we show that the large-scale atmospheric circulation associated with the warm Arctic was the main event driver, explaining 83 ± 2% of the intensity of the 2023 cold event, whereas the thermodynamic effect of climate change suppressed the event intensity by −6 ± 3% in ERA5 and −22 ± 2% in HadGEM3-A-N216. An attribution analysis based on coupled model simulations shows that, due to anthropogenic climate change, the frequency and intensity of 2023-like events decrease by 92.5 ± 2.5% and 1.9 ± 0.2 °C, respectively, under the 2023 climate state. The thermodynamic effect of anthropogenic climate change outweighs its dynamic effect. Future projections indicate that the frequency and intensity of these 2023-like events will further decrease by 95 ± 3% and 2.05 ± 0.25 °C by the end of this century under an intermediate-emissions scenario compared with estimates made under the present climate. In contrast, 2023-like events will be similar to present events when the 1.5 °C target of the Paris Agreement is achieved. These findings highlight the dampening effect of anthropogenic climate change on cold events, but adaptation measures for future risks of 2023-like cold events will be needed by the end of the century if carbon neutrality is achieved.</p>","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"40 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142968280","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}