Pub Date : 2024-08-07DOI: 10.1038/s41612-024-00723-0
Liwei Jia, Thomas L. Delworth, Xiaosong Yang, William Cooke, Nathaniel C. Johnson, Liping Zhang, Youngji Joh, Feiyu Lu, Colleen McHugh
Humid heat extreme (HHE) is a type of compound extreme weather event that poses severe risks to human health. Skillful forecasts of HHE months in advance are crucial for developing strategies to enhance community resilience to extreme events1,2. This study demonstrates that the frequency of summertime HHE in the southeastern United States (SEUS) can be skillfully predicted 0–1 months in advance using the SPEAR (Seamless system for Prediction and EArth system Research) seasonal forecast system. Sea surface temperatures (SSTs) in the tropical North Atlantic (TNA) basin are identified as the primary driver of this prediction skill. The responses of large-scale atmospheric circulation and winds to anomalous warm SSTs in the TNA favor the transport of heat and moisture from the Gulf of Mexico to the SEUS. This research underscores the role of slowly varying sea surface conditions in modifying large-scale environments, thereby contributing to the skillful prediction of HHE in the SEUS. The results of this study have potential applications in the development of early warning systems for HHE.
{"title":"Seasonal predictions of summer compound humid heat extremes in the southeastern United States driven by sea surface temperatures","authors":"Liwei Jia, Thomas L. Delworth, Xiaosong Yang, William Cooke, Nathaniel C. Johnson, Liping Zhang, Youngji Joh, Feiyu Lu, Colleen McHugh","doi":"10.1038/s41612-024-00723-0","DOIUrl":"10.1038/s41612-024-00723-0","url":null,"abstract":"Humid heat extreme (HHE) is a type of compound extreme weather event that poses severe risks to human health. Skillful forecasts of HHE months in advance are crucial for developing strategies to enhance community resilience to extreme events1,2. This study demonstrates that the frequency of summertime HHE in the southeastern United States (SEUS) can be skillfully predicted 0–1 months in advance using the SPEAR (Seamless system for Prediction and EArth system Research) seasonal forecast system. Sea surface temperatures (SSTs) in the tropical North Atlantic (TNA) basin are identified as the primary driver of this prediction skill. The responses of large-scale atmospheric circulation and winds to anomalous warm SSTs in the TNA favor the transport of heat and moisture from the Gulf of Mexico to the SEUS. This research underscores the role of slowly varying sea surface conditions in modifying large-scale environments, thereby contributing to the skillful prediction of HHE in the SEUS. The results of this study have potential applications in the development of early warning systems for HHE.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":null,"pages":null},"PeriodicalIF":8.5,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00723-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141904578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-04DOI: 10.1038/s41612-024-00726-x
Yangzhou Wu, Quan Liu, Dantong Liu, Ping Tian, Weiqi Xu, Junfeng Wang, Kang Hu, Siyuan Li, Xiaotong Jiang, Fei Wang, Mengyu Huang, Deping Ding, Chenjie Yu, Dawei Hu
Particulate organic nitrates (pON) significantly contribute to the mass of organic aerosol and influence the nitrogen oxides cycle in the atmosphere, but their evolution and lifetime remain uncertain. This study performed simultaneous measurements on the anthropogenically affected surface site and the mountain site on top of the polluted planetary boundary layer (PBL). After aging in the PBL, organic nitrate was converted from primary sources (decreased from 8.7% to 4.3%) to secondary sources (increased from 6.3% to 36.1%), spanning from the surface to the mountain. The evaporation of more volatile inorganic nitrate and the production of secondary organic nitrate during aging in the PBL contributed to the enhanced pON fraction over the top of PBL. The contribution of light absorption by brown carbon increased by 57% at the top of PBL compared to the surface, consistent with the higher fraction of nitrogenous organic aerosols over the mountain. The results provide field evidence that the nitrogenous organic aerosols (OA) may be preserved by adding into secondary OA and significantly contribute to the enhanced importance of brown carbon after aging the vertical transport in the PBL.
{"title":"Enhanced formation of nitrogenous organic aerosols and brown carbon after aging in the planetary boundary layer","authors":"Yangzhou Wu, Quan Liu, Dantong Liu, Ping Tian, Weiqi Xu, Junfeng Wang, Kang Hu, Siyuan Li, Xiaotong Jiang, Fei Wang, Mengyu Huang, Deping Ding, Chenjie Yu, Dawei Hu","doi":"10.1038/s41612-024-00726-x","DOIUrl":"10.1038/s41612-024-00726-x","url":null,"abstract":"Particulate organic nitrates (pON) significantly contribute to the mass of organic aerosol and influence the nitrogen oxides cycle in the atmosphere, but their evolution and lifetime remain uncertain. This study performed simultaneous measurements on the anthropogenically affected surface site and the mountain site on top of the polluted planetary boundary layer (PBL). After aging in the PBL, organic nitrate was converted from primary sources (decreased from 8.7% to 4.3%) to secondary sources (increased from 6.3% to 36.1%), spanning from the surface to the mountain. The evaporation of more volatile inorganic nitrate and the production of secondary organic nitrate during aging in the PBL contributed to the enhanced pON fraction over the top of PBL. The contribution of light absorption by brown carbon increased by 57% at the top of PBL compared to the surface, consistent with the higher fraction of nitrogenous organic aerosols over the mountain. The results provide field evidence that the nitrogenous organic aerosols (OA) may be preserved by adding into secondary OA and significantly contribute to the enhanced importance of brown carbon after aging the vertical transport in the PBL.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":null,"pages":null},"PeriodicalIF":8.5,"publicationDate":"2024-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00726-x.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141887444","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-03DOI: 10.1038/s41612-024-00722-1
Yeonsu Lee, Dongjin Cho, Jungho Im, Cheolhee Yoo, Joonlee Lee, Yoo-Geun Ham, Myong-In Lee
Increasing heatwave intensity and mortality demand timely and accurate heatwave prediction. The present study focused on teleconnection, the influence of distant land and ocean variability on local weather events, to drive long-term heatwave predictions. The complexity of teleconnection poses challenges for physical-based prediction models. In this study, we employed a machine learning model and explainable artificial intelligence to identify the teleconnection drivers for heatwaves in South Korea. Drivers were selected based on their statistical significance with annual heatwave frequency ( | R | > 0.3, p < 0.05). Our analysis revealed that two snow depth (SD) variabilities—a decrease in the Gobi Desert and increase in the Tianshan Mountains—are the most important and predictive teleconnection drivers. These drivers exhibit a high correlation with summer climate conditions conducive to heatwaves. Our study lays the groundwork for further research into understanding land–atmosphere interactions over these two SD regions and their significant impact on heatwave patterns in South Korea.
热浪强度和死亡率的增加要求及时准确地预测热浪。本研究侧重于远距离联系，即远距离陆地和海洋变率对本地天气事件的影响，以推动长期热浪预测。远距离联系的复杂性给基于物理的预测模型带来了挑战。在本研究中，我们采用了机器学习模型和可解释人工智能来识别韩国热浪的远距离联系驱动因素。选择驱动因素的依据是它们与年度热浪频率的统计显著性 ( | R | > 0.3, p < 0.05)。我们的分析表明，戈壁滩积雪深度（SD）的减少和天山山脉积雪深度的增加是最重要和最具预测性的远缘驱动因素。这些驱动因素与有利于热浪的夏季气候条件具有高度相关性。我们的研究为进一步了解这两个 SD 区域的陆地-大气相互作用及其对韩国热浪模式的重大影响奠定了基础。
{"title":"Unveiling teleconnection drivers for heatwave prediction in South Korea using explainable artificial intelligence","authors":"Yeonsu Lee, Dongjin Cho, Jungho Im, Cheolhee Yoo, Joonlee Lee, Yoo-Geun Ham, Myong-In Lee","doi":"10.1038/s41612-024-00722-1","DOIUrl":"10.1038/s41612-024-00722-1","url":null,"abstract":"Increasing heatwave intensity and mortality demand timely and accurate heatwave prediction. The present study focused on teleconnection, the influence of distant land and ocean variability on local weather events, to drive long-term heatwave predictions. The complexity of teleconnection poses challenges for physical-based prediction models. In this study, we employed a machine learning model and explainable artificial intelligence to identify the teleconnection drivers for heatwaves in South Korea. Drivers were selected based on their statistical significance with annual heatwave frequency ( | R | > 0.3, p < 0.05). Our analysis revealed that two snow depth (SD) variabilities—a decrease in the Gobi Desert and increase in the Tianshan Mountains—are the most important and predictive teleconnection drivers. These drivers exhibit a high correlation with summer climate conditions conducive to heatwaves. Our study lays the groundwork for further research into understanding land–atmosphere interactions over these two SD regions and their significant impact on heatwave patterns in South Korea.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":null,"pages":null},"PeriodicalIF":8.5,"publicationDate":"2024-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00722-1.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141880213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Unprecedentedly extreme precipitation occurred in Pakistan (PAK), and mega heat waves persisted along the Yangtze River Valley (YRV) from July to August 2022. Using the advanced multiscale window transform-based canonical transfer attribution framework, we quantitatively delineated intra-scale and inter-scale interactions leading to record-breaking spatially concurrent extremes in 2022 and comprehensively revealed differences in dynamic processes affecting extreme events in July and August. The basic flow scale window lost the available potential energy (APE), and through APE canonical transfers to the intraseasonal-scale and synoptic-scale windows, the inter-scale dynamic processes and barotropic instability of the basic flow scale preserved the concurrent extreme in July. In August, the eruptive synoptic-scale kinetic energy convergence provided dynamic conditions for the sinking motion of the YRV and its advection to PAK from the Indian Ocean. Consequently, the interaction between high- and low-frequency processes drove atmospheric circulation in summer, but the high-frequency process in August played a vital role in extreme events. Additionally, the heat source in the tropical western-central Pacific is considered one of the key drivers for localized repetitive bursts of energy. This study emphasizes both the interactions between multiple scales of atmospheric dynamics and reveals the driving mechanisms behind the impacts of warming on extreme events, linking the external forcing issue with the free problem of atmospheric internal instability.
{"title":"Multiscale interaction underlying 2022 concurrent extreme precipitation in Pakistan and heatwave in Yangtze River Valley","authors":"Qianrong Ma, Yingxiao Sun, Rui Hu, Zhiwei Zhu, Kaiguo Xiong, Hao Wu, Pengcheng Yan, Guolin Feng","doi":"10.1038/s41612-024-00725-y","DOIUrl":"10.1038/s41612-024-00725-y","url":null,"abstract":"Unprecedentedly extreme precipitation occurred in Pakistan (PAK), and mega heat waves persisted along the Yangtze River Valley (YRV) from July to August 2022. Using the advanced multiscale window transform-based canonical transfer attribution framework, we quantitatively delineated intra-scale and inter-scale interactions leading to record-breaking spatially concurrent extremes in 2022 and comprehensively revealed differences in dynamic processes affecting extreme events in July and August. The basic flow scale window lost the available potential energy (APE), and through APE canonical transfers to the intraseasonal-scale and synoptic-scale windows, the inter-scale dynamic processes and barotropic instability of the basic flow scale preserved the concurrent extreme in July. In August, the eruptive synoptic-scale kinetic energy convergence provided dynamic conditions for the sinking motion of the YRV and its advection to PAK from the Indian Ocean. Consequently, the interaction between high- and low-frequency processes drove atmospheric circulation in summer, but the high-frequency process in August played a vital role in extreme events. Additionally, the heat source in the tropical western-central Pacific is considered one of the key drivers for localized repetitive bursts of energy. This study emphasizes both the interactions between multiple scales of atmospheric dynamics and reveals the driving mechanisms behind the impacts of warming on extreme events, linking the external forcing issue with the free problem of atmospheric internal instability.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":null,"pages":null},"PeriodicalIF":8.5,"publicationDate":"2024-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00725-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141887447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The arid region of Northwest China (ARNC) has experienced a significantly higher warming rate than the global average and exhibits pronounced seasonal asymmetry, which has important implications for the region’s water-dependent systems. To understand the spatiotemporal patterns and driving mechanisms of seasonal asymmetric warming in the ARNC, we investigated seasonal changes in temperature rise and their underlying causes based on station and reanalysis data. We found that the dominant season of temperature increase shifted from winter to spring. The contribution of spring warming to the total temperature increase rose from −5%–7% to 58%–59%, while the contribution of winter warming decreased from 60%–75% to −4%–9%. However, the mechanisms underlying spring warming and winter cooling differ. An increase in solar radiation caused by a decrease in cloud cover (R = −0.64) was the main reason for spring warming, while a strengthening Siberian High primarily drove winter cooling.
{"title":"The dominant warming season shifted from winter to spring in the arid region of Northwest China","authors":"Fan Sun, Yupeng Li, Yaning Chen, Gonghuan Fang, Weili Duan, Baofu Li, Zhi Li, Xingming Hao, Yuhai Yang, Xueqi Zhang","doi":"10.1038/s41612-024-00724-z","DOIUrl":"10.1038/s41612-024-00724-z","url":null,"abstract":"The arid region of Northwest China (ARNC) has experienced a significantly higher warming rate than the global average and exhibits pronounced seasonal asymmetry, which has important implications for the region’s water-dependent systems. To understand the spatiotemporal patterns and driving mechanisms of seasonal asymmetric warming in the ARNC, we investigated seasonal changes in temperature rise and their underlying causes based on station and reanalysis data. We found that the dominant season of temperature increase shifted from winter to spring. The contribution of spring warming to the total temperature increase rose from −5%–7% to 58%–59%, while the contribution of winter warming decreased from 60%–75% to −4%–9%. However, the mechanisms underlying spring warming and winter cooling differ. An increase in solar radiation caused by a decrease in cloud cover (R = −0.64) was the main reason for spring warming, while a strengthening Siberian High primarily drove winter cooling.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":null,"pages":null},"PeriodicalIF":8.5,"publicationDate":"2024-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00724-z.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141887446","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-26DOI: 10.1038/s41612-024-00719-w
Fei Huo, Li Xu, Zhenhua Li, Yanping Li, James S. Famiglietti, Hrishi A. Chandanpurkar
{"title":"Author Correction: Can climate change signals be detected from the terrestrial water storage at daily timescale?","authors":"Fei Huo, Li Xu, Zhenhua Li, Yanping Li, James S. Famiglietti, Hrishi A. Chandanpurkar","doi":"10.1038/s41612-024-00719-w","DOIUrl":"10.1038/s41612-024-00719-w","url":null,"abstract":"","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":null,"pages":null},"PeriodicalIF":8.5,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00719-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141968495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-24DOI: 10.1038/s41612-024-00713-2
Eui-Seok Chung, Seong-Joong Kim, Sang-Ki Lee, Kyung-Ja Ha, Sang-Wook Yeh, Yong Sun Kim, Sang-Yoon Jun, Joo-Hong Kim, Dongmin Kim
It remains unresolved whether the La Niña-like sea surface temperature (SST) trend pattern during the satellite era, featuring a distinct warming in the northwest/southwest Pacific but cooling in the tropical eastern Pacific, is driven by either external forcing or internal variability. Here, by conducting a comprehensive analysis of observations and a series of climate model simulations for the historical period, we show that a combination of internal variability and human activity may have shaped the observed La Niña-like SST trend pattern. As in observations, SSTs in each model ensemble member show a distinct multi-decadal swing between El Niño-like and La Niña-like trend patterns due to internal variability. The ensemble-mean trends for some models are, however, found to exhibit an enhanced zonal SST gradient along the equatorial Pacific over periods such as 1979–2010, suggesting a role of external forcing. In line with this hypothesis, single-forcing large ensemble model simulations show that human-induced stratospheric ozone depletion and/or aerosol changes have acted to enhance the zonal SST gradient via strengthening of Pacific trade winds, although the effect is model dependent. Our finding suggests that the La Niña-like SST trend is unlikely to persist under sustained global warming because both the ozone and aerosol impacts will eventually weaken.
{"title":"Tropical eastern Pacific cooling trend reinforced by human activity","authors":"Eui-Seok Chung, Seong-Joong Kim, Sang-Ki Lee, Kyung-Ja Ha, Sang-Wook Yeh, Yong Sun Kim, Sang-Yoon Jun, Joo-Hong Kim, Dongmin Kim","doi":"10.1038/s41612-024-00713-2","DOIUrl":"10.1038/s41612-024-00713-2","url":null,"abstract":"It remains unresolved whether the La Niña-like sea surface temperature (SST) trend pattern during the satellite era, featuring a distinct warming in the northwest/southwest Pacific but cooling in the tropical eastern Pacific, is driven by either external forcing or internal variability. Here, by conducting a comprehensive analysis of observations and a series of climate model simulations for the historical period, we show that a combination of internal variability and human activity may have shaped the observed La Niña-like SST trend pattern. As in observations, SSTs in each model ensemble member show a distinct multi-decadal swing between El Niño-like and La Niña-like trend patterns due to internal variability. The ensemble-mean trends for some models are, however, found to exhibit an enhanced zonal SST gradient along the equatorial Pacific over periods such as 1979–2010, suggesting a role of external forcing. In line with this hypothesis, single-forcing large ensemble model simulations show that human-induced stratospheric ozone depletion and/or aerosol changes have acted to enhance the zonal SST gradient via strengthening of Pacific trade winds, although the effect is model dependent. Our finding suggests that the La Niña-like SST trend is unlikely to persist under sustained global warming because both the ozone and aerosol impacts will eventually weaken.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":null,"pages":null},"PeriodicalIF":8.5,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00713-2.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141755115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The East Asian summer monsoon precipitation has exhibited a well-known “southern China flood and northern China drought” pattern in recent decades. The increase in aerosols and warming oceans are recognized as two important forcings that control of the precipitation trends over East Asian land. However, in this study, by using large ensemble simulations from the CMIP6 Polar Amplification Model Intercomparison Project (PAMIP), the influence of Arctic amplification, serving as the prominent feature of global warming, is very important in modulating the East Asian summer precipitation pattern, which is comparable to the influence of sea surface temperature (SST). Additionally, the observed “southern China flood and northern China drought” pattern only exists in July and August, whereas a triple pattern with the precipitation positive anomaly center over Middle China occurs in June. These patterns are closely connected with the regional differences in Arctic sea ice loss from June to July, affected through both the Rossby waves propagating in a weaker westerly jet and the decrease in the large-scale meridional thermal contrast in a warming climate.
{"title":"The role of Arctic sea ice loss in the interdecadal trends of the East Asian summer monsoon in a warming climate","authors":"Xiaoqi Zhang, Bian He, Qing Bao, Yimin Liu, Guoxiong Wu, Anmin Duan, Wenting Hu, Chen Sheng, Jian Rao","doi":"10.1038/s41612-024-00717-y","DOIUrl":"10.1038/s41612-024-00717-y","url":null,"abstract":"The East Asian summer monsoon precipitation has exhibited a well-known “southern China flood and northern China drought” pattern in recent decades. The increase in aerosols and warming oceans are recognized as two important forcings that control of the precipitation trends over East Asian land. However, in this study, by using large ensemble simulations from the CMIP6 Polar Amplification Model Intercomparison Project (PAMIP), the influence of Arctic amplification, serving as the prominent feature of global warming, is very important in modulating the East Asian summer precipitation pattern, which is comparable to the influence of sea surface temperature (SST). Additionally, the observed “southern China flood and northern China drought” pattern only exists in July and August, whereas a triple pattern with the precipitation positive anomaly center over Middle China occurs in June. These patterns are closely connected with the regional differences in Arctic sea ice loss from June to July, affected through both the Rossby waves propagating in a weaker westerly jet and the decrease in the large-scale meridional thermal contrast in a warming climate.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":null,"pages":null},"PeriodicalIF":8.5,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00717-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141764077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-23DOI: 10.1038/s41612-024-00721-2
Shuai Wang, Hiroyuki Murakami, William Cooke
There is less consensus on whether human activities have significantly altered tropical cyclone (TC) statistics, given the relatively short duration of reliable observed records. Understanding and projecting TC frequency change is more challenging in certain coastal regions with lower TC activity yet high exposure, such as Western Europe. Here, we show, with large-ensemble simulations, that the observed increase in TC frequency near Western Europe from 1966 to 2020 is likely linked to the anthropogenic aerosol effect. Under a future scenario featuring regionally controlled aerosol emissions and substantially increased greenhouse gas concentrations (Shared Socioeconomic Pathway 5-85), our simulations show a potential decrease in TC frequency near Western Europe by the end of the 21st century. These contrasting trends in historical and future TC frequencies are primarily due to the rise for 1966–2020 and potentially subsequent fall for 2030–2100 in TC genesis frequency in the North Atlantic. The response of large-scale environmental conditions to anthropogenic forcing is found to be crucial in explaining the historical and future changes in TC frequency near Western Europe.
{"title":"Anthropogenic effects on tropical cyclones near Western Europe","authors":"Shuai Wang, Hiroyuki Murakami, William Cooke","doi":"10.1038/s41612-024-00721-2","DOIUrl":"10.1038/s41612-024-00721-2","url":null,"abstract":"There is less consensus on whether human activities have significantly altered tropical cyclone (TC) statistics, given the relatively short duration of reliable observed records. Understanding and projecting TC frequency change is more challenging in certain coastal regions with lower TC activity yet high exposure, such as Western Europe. Here, we show, with large-ensemble simulations, that the observed increase in TC frequency near Western Europe from 1966 to 2020 is likely linked to the anthropogenic aerosol effect. Under a future scenario featuring regionally controlled aerosol emissions and substantially increased greenhouse gas concentrations (Shared Socioeconomic Pathway 5-85), our simulations show a potential decrease in TC frequency near Western Europe by the end of the 21st century. These contrasting trends in historical and future TC frequencies are primarily due to the rise for 1966–2020 and potentially subsequent fall for 2030–2100 in TC genesis frequency in the North Atlantic. The response of large-scale environmental conditions to anthropogenic forcing is found to be crucial in explaining the historical and future changes in TC frequency near Western Europe.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":null,"pages":null},"PeriodicalIF":8.5,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00721-2.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141754732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In August 2022, an unprecedented compound heatwave and drought event (CHDE) lasting 24 days occurred in the Yangtze River valley (YRV), leading to a severe reduction of the crop, fresh water, and power supply. We constructed a joint cumulative probability distribution of heatwave and drought intensity, and found that the lowest probability-based index (PI) of 0.06 in 2022 was estimated as a 1-in-662-year event over the 1961–2022 climate. We then detected the fingerprint of greenhouse gas forcing to the observed PI in a generalized extreme value framework, but not the aerosol forcing, suggesting the leading contribution of greenhouse gas forcing on such extreme CHDE. Furthermore, anthropogenic influence had increased the probability of such CHDE by more than 10 times compared to the counterfactual climate. Also, the PI decreased from about 0.30 at the present climate to about 0.14 at the 3 °C global warming level, indicating that CHDE will become more extreme over YRV.
{"title":"Contribution of anthropogenic influence to the 2022-like Yangtze River valley compound heatwave and drought event","authors":"Dong Chen, Shaobo Qiao, Jie Yang, Shankai Tang, Dongdong Zuo, Guolin Feng","doi":"10.1038/s41612-024-00720-3","DOIUrl":"10.1038/s41612-024-00720-3","url":null,"abstract":"In August 2022, an unprecedented compound heatwave and drought event (CHDE) lasting 24 days occurred in the Yangtze River valley (YRV), leading to a severe reduction of the crop, fresh water, and power supply. We constructed a joint cumulative probability distribution of heatwave and drought intensity, and found that the lowest probability-based index (PI) of 0.06 in 2022 was estimated as a 1-in-662-year event over the 1961–2022 climate. We then detected the fingerprint of greenhouse gas forcing to the observed PI in a generalized extreme value framework, but not the aerosol forcing, suggesting the leading contribution of greenhouse gas forcing on such extreme CHDE. Furthermore, anthropogenic influence had increased the probability of such CHDE by more than 10 times compared to the counterfactual climate. Also, the PI decreased from about 0.30 at the present climate to about 0.14 at the 3 °C global warming level, indicating that CHDE will become more extreme over YRV.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":null,"pages":null},"PeriodicalIF":8.5,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00720-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141755346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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