Pub Date : 2025-12-12DOI: 10.1038/s41612-025-01275-7
Yuanyuan Ma, Xiaoxue Hu, Xianhong Meng, Di Ma
Tibetan Plateau (TP) is a sensitive region of climate change, with its precipitation change attracting considerable scientific attention. This study couples dynamical downscaling simulation with the storyline attribution approach to investigate the impact of regional climate change over East Asia (RCC) and TP (PCC) on the sub-daily precipitation over TP. RCC significantly reduces overall precipitation, mainly through decreased morning and stratiform precipitation, but enhances afternoon precipitation by increasing convective precipitation. Furthermore, RCC reduces the precipitation frequency and precipitation intensity, most substantially for morning stratiform precipitation. PCC exerts smaller and less statistically significant impact on precipitation than RCC. The opposing morning–afternoon effects of RCC stem from differing physical mechanisms: RCC stabilizes the atmosphere and reduces moisture in the morning, suppressing convection, while it enhances instability, moisture, and convective energy in the afternoon. Regional differences in RCC-induced precipitation changes are attributed to variations in moisture flux and atmospheric dynamics.
{"title":"Response and mechanisms of sub-daily precipitation over the Tibetan Plateau to regional climate change","authors":"Yuanyuan Ma, Xiaoxue Hu, Xianhong Meng, Di Ma","doi":"10.1038/s41612-025-01275-7","DOIUrl":"https://doi.org/10.1038/s41612-025-01275-7","url":null,"abstract":"Tibetan Plateau (TP) is a sensitive region of climate change, with its precipitation change attracting considerable scientific attention. This study couples dynamical downscaling simulation with the storyline attribution approach to investigate the impact of regional climate change over East Asia (RCC) and TP (PCC) on the sub-daily precipitation over TP. RCC significantly reduces overall precipitation, mainly through decreased morning and stratiform precipitation, but enhances afternoon precipitation by increasing convective precipitation. Furthermore, RCC reduces the precipitation frequency and precipitation intensity, most substantially for morning stratiform precipitation. PCC exerts smaller and less statistically significant impact on precipitation than RCC. The opposing morning–afternoon effects of RCC stem from differing physical mechanisms: RCC stabilizes the atmosphere and reduces moisture in the morning, suppressing convection, while it enhances instability, moisture, and convective energy in the afternoon. Regional differences in RCC-induced precipitation changes are attributed to variations in moisture flux and atmospheric dynamics.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"231 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145746843","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 : 2025-12-12DOI: 10.1038/s41612-025-01284-6
Manuel Dall´Osto, Mark F. Fitzsimons, James Brean, Preston Chebai Akenga, A. Jones, Tom Lachlan-Cope, Ana Sotomayor, Elisa Berdalet, Dolors Vaque, Roy M. Harrison, Karam Mansour, Matteo Rinaldi, Stefano Decesari, David Beddows, Marco Paglione
Measurements of pre-industrial conditions are of paramount importance for understanding historical climate change. The Southern Ocean and Antarctic continent are some of the least polluted environments on planet Earth. Alkylamines can rapidly partition into aerosols, increasing their mass, as well as form new particles altogether. We demonstrate the importance of pelagic “open ocean” (OO) and sympagic “sea ice” (SI) regions in supplying distinct organic nitrogen aerosol components. In the aerosol phase, dimethylamine (DMA) and trimethylamine (TMA) are both secondary, though DMA likely originates mainly from pelagic regions, while TMA is associated mainly with sympagic regions. Parallel measurements in ice and surface waters reveal that melting sea ice contains a factor of four more TMA than coastal Antarctic Peninsula waters; and seventeen times more TMA than OO regions - suggesting additional coastal Antarctic sources. To better interpret future climate change, we recommend employing regional atmospheric chemistry models to understand these diverse aerosol sources.
{"title":"Multiple oceanic sources of alkylamines in Southern Ocean atmospheres","authors":"Manuel Dall´Osto, Mark F. Fitzsimons, James Brean, Preston Chebai Akenga, A. Jones, Tom Lachlan-Cope, Ana Sotomayor, Elisa Berdalet, Dolors Vaque, Roy M. Harrison, Karam Mansour, Matteo Rinaldi, Stefano Decesari, David Beddows, Marco Paglione","doi":"10.1038/s41612-025-01284-6","DOIUrl":"https://doi.org/10.1038/s41612-025-01284-6","url":null,"abstract":"Measurements of pre-industrial conditions are of paramount importance for understanding historical climate change. The Southern Ocean and Antarctic continent are some of the least polluted environments on planet Earth. Alkylamines can rapidly partition into aerosols, increasing their mass, as well as form new particles altogether. We demonstrate the importance of pelagic “open ocean” (OO) and sympagic “sea ice” (SI) regions in supplying distinct organic nitrogen aerosol components. In the aerosol phase, dimethylamine (DMA) and trimethylamine (TMA) are both secondary, though DMA likely originates mainly from pelagic regions, while TMA is associated mainly with sympagic regions. Parallel measurements in ice and surface waters reveal that melting sea ice contains a factor of four more TMA than coastal Antarctic Peninsula waters; and seventeen times more TMA than OO regions - suggesting additional coastal Antarctic sources. To better interpret future climate change, we recommend employing regional atmospheric chemistry models to understand these diverse aerosol sources.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"9 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145746776","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 : 2025-12-12DOI: 10.1038/s41612-025-01265-9
Jorge Baño-Medina, Agniv Sengupta, Daniel Steinhoff, Patrick Mulrooney, Thomas Nipen, Mario Santa-Cruz, Yanbo Nie, Luca Delle Monache
Accurate precipitation forecasting often relies on high-resolution numerical weather prediction (NWP) models, which are essential for capturing fine-scale and nonlinear atmospheric dynamics. However, the computational demands of these models can be substantial. Leveraging recent advancements in artificial intelligence (AI), we present a stretched-grid AI-driven weather model with 6-km horizontal grid increments over the Western United States and ~31 km in other regions globally. The model employs an autoregressive framework to generate forecasts in minutes and is evaluated against global and regional NWP systems, as well as a lower-resolution AI model. Our results show that the regional AI model reduces 24-h accumulated precipitation errors, performs competitively with the regional NWP model, and effectively captures extreme precipitation events, particularly those linked to atmospheric rivers, which global coarser models often underestimate. This work underscores the potential of regional, high-resolution AI models for precipitation forecasting at km-scales, and discusses some of the challenges for future development.
{"title":"A regional high resolution AI weather model for the prediction of atmospheric rivers and extreme precipitation","authors":"Jorge Baño-Medina, Agniv Sengupta, Daniel Steinhoff, Patrick Mulrooney, Thomas Nipen, Mario Santa-Cruz, Yanbo Nie, Luca Delle Monache","doi":"10.1038/s41612-025-01265-9","DOIUrl":"https://doi.org/10.1038/s41612-025-01265-9","url":null,"abstract":"Accurate precipitation forecasting often relies on high-resolution numerical weather prediction (NWP) models, which are essential for capturing fine-scale and nonlinear atmospheric dynamics. However, the computational demands of these models can be substantial. Leveraging recent advancements in artificial intelligence (AI), we present a stretched-grid AI-driven weather model with 6-km horizontal grid increments over the Western United States and ~31 km in other regions globally. The model employs an autoregressive framework to generate forecasts in minutes and is evaluated against global and regional NWP systems, as well as a lower-resolution AI model. Our results show that the regional AI model reduces 24-h accumulated precipitation errors, performs competitively with the regional NWP model, and effectively captures extreme precipitation events, particularly those linked to atmospheric rivers, which global coarser models often underestimate. This work underscores the potential of regional, high-resolution AI models for precipitation forecasting at km-scales, and discusses some of the challenges for future development.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"68 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145746780","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 : 2025-12-12DOI: 10.1038/s41612-025-01282-8
Xin He, Chunsong Lu, Guang J. Zhang, Junjun Li, Lei Zhu, Hengqi Wang, Te Li, Xiaohao Guo, Sinan Gao, Yuhao Lin, Kai Yang, Wenhui Liu
Entrainment rate parameterization is important for convection schemes but uncertain in climate models. A new deep convective entrainment rate (λ) parameterization (HL parameterization) is developed from aircraft observations and implemented into the convection scheme (Song and Zhang, 2018, https://doi.org/10.1002/2017MS001191) in the Community Integrated Earth System Model version 1.1.0, replacing the previously used parameterization (Gregory parameterization). Compared with the Gregory parameterization, the HL parameterization simulates overall larger λ values and improves convective and large-scale precipitation simulations in the 30°S-30°N region, agreeing better with observations. The mechanism is that the HL parameterization suppresses deep convective cloud development macrophysically and microphysically compared with the Gregory parameterization. Indirectly, compared with the Gregory parameterization, the HL parameterization increases large-scale precipitation and reduces shallow convective precipitation, lowering total precipitation closer to observations. The HL parameterization enhances the model’s ability to simulate precipitation, providing a valuable reference for improving the deep convection scheme in climate models.
携射率参数化对对流方案很重要，但在气候模式中不确定。基于飞机观测发展了一种新的深层对流携流速率（λ）参数化（HL参数化），并将其应用于社区综合地球系统模型1.1.0版本的对流方案中（Song and Zhang, 2018, https://doi.org/10.1002/2017MS001191），取代了之前使用的参数化（Gregory参数化）。与Gregory参数化相比，HL参数化模拟的λ值总体上更大，并改善了30°S-30°N区域对流和大尺度降水的模拟，与观测结果吻合得更好。与Gregory参数化相比，HL参数化抑制了深层对流云的宏观物理和微观物理发展。间接地，与Gregory参数化相比，HL参数化增加了大尺度降水，减少了浅层对流降水，使总降水更接近观测值。HL参数化提高了模式对降水的模拟能力，为气候模式中对流方案的改进提供了有价值的参考。
{"title":"Improving precipitation simulations in CIESM through a new entrainment rate parameterization","authors":"Xin He, Chunsong Lu, Guang J. Zhang, Junjun Li, Lei Zhu, Hengqi Wang, Te Li, Xiaohao Guo, Sinan Gao, Yuhao Lin, Kai Yang, Wenhui Liu","doi":"10.1038/s41612-025-01282-8","DOIUrl":"https://doi.org/10.1038/s41612-025-01282-8","url":null,"abstract":"Entrainment rate parameterization is important for convection schemes but uncertain in climate models. A new deep convective entrainment rate (λ) parameterization (HL parameterization) is developed from aircraft observations and implemented into the convection scheme (Song and Zhang, 2018, https://doi.org/10.1002/2017MS001191) in the Community Integrated Earth System Model version 1.1.0, replacing the previously used parameterization (Gregory parameterization). Compared with the Gregory parameterization, the HL parameterization simulates overall larger λ values and improves convective and large-scale precipitation simulations in the 30°S-30°N region, agreeing better with observations. The mechanism is that the HL parameterization suppresses deep convective cloud development macrophysically and microphysically compared with the Gregory parameterization. Indirectly, compared with the Gregory parameterization, the HL parameterization increases large-scale precipitation and reduces shallow convective precipitation, lowering total precipitation closer to observations. The HL parameterization enhances the model’s ability to simulate precipitation, providing a valuable reference for improving the deep convection scheme in climate models.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"145 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145746790","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 : 2025-12-11DOI: 10.1038/s41612-025-01264-w
Changgui Lin, Kun Yang, Deliang Chen, Siyu Yue, Xu Zhou, Yonghui Lei, Jinmei Pan, Xi Cao, Yongkang Xue, Jiancheng Shi
The remote influences of springtime Third Pole (TP) snow cover (TPSC) on the Indian Summer Monsoon (ISM) and the East Asian Summer Monsoon (EASM) have been extensively studied. However, a clear mechanism explaining the cross-season links remains not well established. Before we confirm any remote effects, it is essential to first verify local influences. Here, we bear out the enduring local impact of the springtime TPSC according to a numerical experiment together with an observational investigation. By examining the evolution of underlying heat sources, we propose a self-sustaining mechanism elucidating the enduring local impact: considering the case of the springtime TPSC deficit, the excessive precipitation that initially responds to the enhanced surface heat and water fluxes releases extra atmospheric latent heat, which in turn drives an anomalous circulation favoring the next-coming precipitation. This finding adds credit to the cross-season influences of the springtime TPSC remotely on the ISM and the EASM. Furthermore, our work implicates that the TP may get more summer precipitation in a warmer future since there will be an inevitable decrease in springtime TPSC.
{"title":"Enduring local impact of springtime snow cover over the Third Pole","authors":"Changgui Lin, Kun Yang, Deliang Chen, Siyu Yue, Xu Zhou, Yonghui Lei, Jinmei Pan, Xi Cao, Yongkang Xue, Jiancheng Shi","doi":"10.1038/s41612-025-01264-w","DOIUrl":"https://doi.org/10.1038/s41612-025-01264-w","url":null,"abstract":"The remote influences of springtime Third Pole (TP) snow cover (TPSC) on the Indian Summer Monsoon (ISM) and the East Asian Summer Monsoon (EASM) have been extensively studied. However, a clear mechanism explaining the cross-season links remains not well established. Before we confirm any remote effects, it is essential to first verify local influences. Here, we bear out the enduring local impact of the springtime TPSC according to a numerical experiment together with an observational investigation. By examining the evolution of underlying heat sources, we propose a self-sustaining mechanism elucidating the enduring local impact: considering the case of the springtime TPSC deficit, the excessive precipitation that initially responds to the enhanced surface heat and water fluxes releases extra atmospheric latent heat, which in turn drives an anomalous circulation favoring the next-coming precipitation. This finding adds credit to the cross-season influences of the springtime TPSC remotely on the ISM and the EASM. Furthermore, our work implicates that the TP may get more summer precipitation in a warmer future since there will be an inevitable decrease in springtime TPSC.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"20 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145718533","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 : 2025-12-04DOI: 10.1038/s41612-025-01262-y
Michael Sigmond, Lantao Sun
Previous studies using an emergent constraint have suggested that climate models underestimate the winter jet stream response to sea ice loss, casting doubt on the quality of mid-latitude climate projections. However, the robustness of this emergent constraint has been questioned. Here, we propose a more robust emergent constraint based on lower stratospheric winds. Using coordinated sea ice loss experiments with bespoke versions of two state-of-the-art climate models along with a multi-model archive, we identify a strong relationship between these winds and the jet stream response. The new emergent constraint reduces the uncertainty in the response by 62% and indicates that the real-world response closely matches the multi-model mean—suggesting no systematic underestimation, in contrast to earlier studies. Our results underscore the importance of reducing lower stratospheric wind biases and increase confidence in climate model projections of a future poleward shift of the jet stream in response to global warming.
{"title":"Jet stream response to future Arctic sea ice loss not underestimated by climate models","authors":"Michael Sigmond, Lantao Sun","doi":"10.1038/s41612-025-01262-y","DOIUrl":"https://doi.org/10.1038/s41612-025-01262-y","url":null,"abstract":"Previous studies using an emergent constraint have suggested that climate models underestimate the winter jet stream response to sea ice loss, casting doubt on the quality of mid-latitude climate projections. However, the robustness of this emergent constraint has been questioned. Here, we propose a more robust emergent constraint based on lower stratospheric winds. Using coordinated sea ice loss experiments with bespoke versions of two state-of-the-art climate models along with a multi-model archive, we identify a strong relationship between these winds and the jet stream response. The new emergent constraint reduces the uncertainty in the response by 62% and indicates that the real-world response closely matches the multi-model mean—suggesting no systematic underestimation, in contrast to earlier studies. Our results underscore the importance of reducing lower stratospheric wind biases and increase confidence in climate model projections of a future poleward shift of the jet stream in response to global warming.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"11 Suppl 3 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145664437","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 : 2025-12-01DOI: 10.1038/s41612-025-01231-5
Idris Hayward, Nicholas A. Martin, Valerio Ferracci, Mohsen Kazemimanesh, Simon Jude, Christopher Walton, Zaheer Ahmad Nasir, Prashant Kumar
Low-cost air quality sensors have shown great promise as a complement to high-cost reference and equivalent methods. Though not currently as accurate, their low barrier of entry and smaller form factor allow them to be deployed in greater numbers, thus enabling air quality measurements to be made at a far higher spatial and temporal resolution than previously possible. However, their measurements require corrections as they suffer from both short-term biases (e.g., changes in environmental conditions such as temperature and humidity), and long-term measurement drift due to degradation. Many studies have focused on calibration and re-calibration of sensors, but fewer focus on correcting pre-calibrated sensor measurements. Correcting measurements is a likely scenario for people buying off-the-shelf devices, as they will not have access to the raw data that underpins the measurements, such as sensor voltages. Previous studies focused on a small range of correction techniques, without accounting for the variances that can occur between devices or locations. This work aimed to perform a comprehensive assessment of different correction techniques applied to air quality sensor systems. More than 470,000 unique measurement corrections were tested across two sites to determine best practices for correction campaigns going forward, resulting in a far more robust study than previous works. It highlights the large variances in results that occurred between sites, particularly for NO 2 , with results often more impacted by device type and location than the regression technique used. Simpler linear models were also found to perform just as well as, and sometimes better than, more complex non-parametric techniques. This study highlights that, though a strong focus is often put on comparing different regression methods, the choice of technique has less impact than the configuration of the device or the conditions of the co-location site. Therefore, future studies should focus less on small-scale comparisons of regression techniques and more on how to improve the transferability and applicability of results from a co-location campaign to another.
{"title":"Comprehensive comparison of correction techniques for low-cost air quality sensors: the impact of device type and deployment environment","authors":"Idris Hayward, Nicholas A. Martin, Valerio Ferracci, Mohsen Kazemimanesh, Simon Jude, Christopher Walton, Zaheer Ahmad Nasir, Prashant Kumar","doi":"10.1038/s41612-025-01231-5","DOIUrl":"https://doi.org/10.1038/s41612-025-01231-5","url":null,"abstract":"Low-cost air quality sensors have shown great promise as a complement to high-cost reference and equivalent methods. Though not currently as accurate, their low barrier of entry and smaller form factor allow them to be deployed in greater numbers, thus enabling air quality measurements to be made at a far higher spatial and temporal resolution than previously possible. However, their measurements require corrections as they suffer from both short-term biases (e.g., changes in environmental conditions such as temperature and humidity), and long-term measurement drift due to degradation. Many studies have focused on calibration and re-calibration of sensors, but fewer focus on correcting pre-calibrated sensor measurements. Correcting measurements is a likely scenario for people buying off-the-shelf devices, as they will not have access to the raw data that underpins the measurements, such as sensor voltages. Previous studies focused on a small range of correction techniques, without accounting for the variances that can occur between devices or locations. This work aimed to perform a comprehensive assessment of different correction techniques applied to air quality sensor systems. More than 470,000 unique measurement corrections were tested across two sites to determine best practices for correction campaigns going forward, resulting in a far more robust study than previous works. It highlights the large variances in results that occurred between sites, particularly for NO <jats:sub>2</jats:sub> , with results often more impacted by device type and location than the regression technique used. Simpler linear models were also found to perform just as well as, and sometimes better than, more complex non-parametric techniques. This study highlights that, though a strong focus is often put on comparing different regression methods, the choice of technique has less impact than the configuration of the device or the conditions of the co-location site. Therefore, future studies should focus less on small-scale comparisons of regression techniques and more on how to improve the transferability and applicability of results from a co-location campaign to another.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"32 1","pages":""},"PeriodicalIF":9.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145645136","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：