Pub Date : 2024-11-27DOI: 10.1038/s41612-024-00828-6
Kangjie Ma, Hainan Gong, Lin Wang, Bo Liu, Yulan Li, Huanhuan Ran, Wen Chen
In August 2022, unprecedented and long-lasting extreme heatwaves attacked the Northern Hemisphere, with simultaneous record-breaking surface air temperature (SAT) in Eastern Europe (EE), Southern China (SC), and Western North America (WNA). However, the underlying physical mechanisms of these concurrent heatwaves, and the extent to which they are driven by anthropogenic forcing versus internal variability remain unclear. Our analysis using the HadGEM3-A-N216 large ensemble attribution model reveals that anthropogenic forcing is responsible for approximately 50% of the heatwaves in EE and SC, and over 80% in WNA. Furthermore, an internally-generated circumglobal atmospheric wave train is identified as a key circulation factor facilitating these simultaneous heatwaves. Observations and numerical simulations indicate that extreme warm sea surface temperature (SST) anomalies in the North Atlantic, North Pacific and Barents Sea, along with extreme cold SST anomalies in the tropical central Pacific, are critical in the formation and maintenance of this atmospheric teleconnection wave train. Under future high-emission scenarios, the influence of the internally-generated atmospheric teleconnection on concurrent heatwaves may be enhanced, particularly in WNA.
{"title":"Anthropogenic forcing intensified internally driven concurrent heatwaves in August 2022 across the Northern Hemisphere","authors":"Kangjie Ma, Hainan Gong, Lin Wang, Bo Liu, Yulan Li, Huanhuan Ran, Wen Chen","doi":"10.1038/s41612-024-00828-6","DOIUrl":"10.1038/s41612-024-00828-6","url":null,"abstract":"In August 2022, unprecedented and long-lasting extreme heatwaves attacked the Northern Hemisphere, with simultaneous record-breaking surface air temperature (SAT) in Eastern Europe (EE), Southern China (SC), and Western North America (WNA). However, the underlying physical mechanisms of these concurrent heatwaves, and the extent to which they are driven by anthropogenic forcing versus internal variability remain unclear. Our analysis using the HadGEM3-A-N216 large ensemble attribution model reveals that anthropogenic forcing is responsible for approximately 50% of the heatwaves in EE and SC, and over 80% in WNA. Furthermore, an internally-generated circumglobal atmospheric wave train is identified as a key circulation factor facilitating these simultaneous heatwaves. Observations and numerical simulations indicate that extreme warm sea surface temperature (SST) anomalies in the North Atlantic, North Pacific and Barents Sea, along with extreme cold SST anomalies in the tropical central Pacific, are critical in the formation and maintenance of this atmospheric teleconnection wave train. Under future high-emission scenarios, the influence of the internally-generated atmospheric teleconnection on concurrent heatwaves may be enhanced, particularly in WNA.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":" ","pages":"1-9"},"PeriodicalIF":8.5,"publicationDate":"2024-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00828-6.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142718957","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 : 2024-11-26DOI: 10.1038/s41612-024-00768-1
Parvathi Kooloth, Jian Lu, Craig Bakker, Derek DeSantis, Adam Rupe
Several Earth system components are at a high risk of undergoing rapid, irreversible qualitative changes or “tipping” with increasing climate warming. It is therefore necessary to investigate the feasibility of arresting or even reversing the crossing of tipping thresholds. Here, we study feedback control of an idealized energy balance model (EBM) for Earth’s climate, which exhibits a “small icecap” instability responsible for a rapid transition to an ice-free climate under increasing greenhouse gas forcing. We develop an optimal control strategy for the EBM under different forcing scenarios to reverse sea-ice loss while minimizing costs. Control is achievable for this system, but the cost nearly quadruples once the system tips. While thermal inertia may delay tipping, leading to an overshoot of the critical forcing threshold, this leeway comes with a steep rise in requisite control once tipping occurs. Additionally, we find that the optimal control is localized in the polar region.
{"title":"Optimal control of polar sea-ice near its tipping points","authors":"Parvathi Kooloth, Jian Lu, Craig Bakker, Derek DeSantis, Adam Rupe","doi":"10.1038/s41612-024-00768-1","DOIUrl":"10.1038/s41612-024-00768-1","url":null,"abstract":"Several Earth system components are at a high risk of undergoing rapid, irreversible qualitative changes or “tipping” with increasing climate warming. It is therefore necessary to investigate the feasibility of arresting or even reversing the crossing of tipping thresholds. Here, we study feedback control of an idealized energy balance model (EBM) for Earth’s climate, which exhibits a “small icecap” instability responsible for a rapid transition to an ice-free climate under increasing greenhouse gas forcing. We develop an optimal control strategy for the EBM under different forcing scenarios to reverse sea-ice loss while minimizing costs. Control is achievable for this system, but the cost nearly quadruples once the system tips. While thermal inertia may delay tipping, leading to an overshoot of the critical forcing threshold, this leeway comes with a steep rise in requisite control once tipping occurs. Additionally, we find that the optimal control is localized in the polar region.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":" ","pages":"1-10"},"PeriodicalIF":8.5,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00768-1.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142712559","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 : 2024-11-23DOI: 10.1038/s41612-024-00839-3
Sujuan Chen, Maigeng Zhou, De Li Liu, Shilu Tong, Zhiwei Xu, Mengmeng Li, Michael Tong, Qiyong Liu, Jun Yang
Climate change and diabetes pose the dual challenges to human health, yet there is a lack of evidence regarding future health burden of diabetes attributable to climate change. In this study, we used three-stage analytic strategy to project the heat-related and heatwave-related diabetes deaths by demographic characteristics and regions, during 2010–2100 in 32 major Chinese cities. Under SSP5-8.5 (high carbon emission scenario), heat-related attributable fraction of diabetes mortality is projected to rise from 2.3% (95% empirical confidence interval [eCI]: 1.1%, 3.6%) in the 2010s to 19.2% (95% eCI: 10.2%, 32.5%) in the 2090s, and estimated heatwave-related attributable fractions will increase from 0.8% (95% eCI: 0.6%, 1.0%) in the 2010s to 9.3% (95% eCI: 6.7%, 11.8%) in the 2090s. We projected that the number of heat- and heatwave-related diabetes deaths would increase from 1525 (95% eCI: 759, 2431) and 529 (95% eCI: 382, 668) in the 2010s, to 12,956 (95% eCI: 6861, 21,937) and 6312 (95% eCI: 4557, 7972) in the 2090s, respectively. Under SSP1-2.6, SSP2-4.5, and SSP3-7.0 (lower carbon emissions), we projected much lower future heat- and heatwave-related diabetes mortality burdens. Our findings might provide new insights for the development of protecting patients with diabetes from increasing temperature.
{"title":"Mortality burden of diabetes attributable to high temperature and heatwave under climate change scenarios in China","authors":"Sujuan Chen, Maigeng Zhou, De Li Liu, Shilu Tong, Zhiwei Xu, Mengmeng Li, Michael Tong, Qiyong Liu, Jun Yang","doi":"10.1038/s41612-024-00839-3","DOIUrl":"10.1038/s41612-024-00839-3","url":null,"abstract":"Climate change and diabetes pose the dual challenges to human health, yet there is a lack of evidence regarding future health burden of diabetes attributable to climate change. In this study, we used three-stage analytic strategy to project the heat-related and heatwave-related diabetes deaths by demographic characteristics and regions, during 2010–2100 in 32 major Chinese cities. Under SSP5-8.5 (high carbon emission scenario), heat-related attributable fraction of diabetes mortality is projected to rise from 2.3% (95% empirical confidence interval [eCI]: 1.1%, 3.6%) in the 2010s to 19.2% (95% eCI: 10.2%, 32.5%) in the 2090s, and estimated heatwave-related attributable fractions will increase from 0.8% (95% eCI: 0.6%, 1.0%) in the 2010s to 9.3% (95% eCI: 6.7%, 11.8%) in the 2090s. We projected that the number of heat- and heatwave-related diabetes deaths would increase from 1525 (95% eCI: 759, 2431) and 529 (95% eCI: 382, 668) in the 2010s, to 12,956 (95% eCI: 6861, 21,937) and 6312 (95% eCI: 4557, 7972) in the 2090s, respectively. Under SSP1-2.6, SSP2-4.5, and SSP3-7.0 (lower carbon emissions), we projected much lower future heat- and heatwave-related diabetes mortality burdens. Our findings might provide new insights for the development of protecting patients with diabetes from increasing temperature.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":" ","pages":"1-9"},"PeriodicalIF":8.5,"publicationDate":"2024-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00839-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142691027","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 : 2024-11-22DOI: 10.1038/s41612-024-00838-4
Martin Bauer, Hendryk Czech, Lukas Anders, Johannes Passig, Uwe Etzien, Jan Bendl, Thorsten Streibel, Thomas W. Adam, Bert Buchholz, Ralf Zimmermann
Ship traffic substantially contributes to air pollution, thus affecting climate and human health. Recently introduced regulations by the International Maritime Organization (IMO) on the fuel sulfur content (FSC) caused a shift in marine fuel onsumption from heavy fuel oils (HFO) to diesel-like distillate fuels, but also to alternative hybrid fuels and the operation of sulfur scrubbers. Using multi-wavelength thermal-optical carbon analysis (MW-TOCA), our study provides emission factors (EF) of carbonaceous aerosol particles and link the fuel composition to features observed in the soot microstructure, which may be exploited in online monitoring by single-particle mass spectrometry (SPMS). Particulate matter from distillate fuels absorbs stronger light of the visible UV and near-infrared range than HFO. However, Simple Forcing Efficiency (SFE) of absorption weighted by EF of total carbon compensated the effect, leading to a net reduction by >50% when changing form HFO to distillate fuels.
船舶交通严重加剧了空气污染，从而影响气候和人类健康。国际海事组织（IMO）最近出台了关于燃料硫含量（FSC）的规定，导致船舶燃料消费从重油（HFO）转向柴油类馏分燃料，同时也转向替代性混合燃料和硫洗涤器的运行。通过使用多波长热光学碳分析（MW-TOCA），我们的研究提供了碳质气溶胶颗粒的排放因子（EF），并将燃料成分与烟尘微观结构中观察到的特征联系起来，这些特征可在单颗粒质谱仪（SPMS）在线监测中加以利用。与氢氟烯烃相比，来自馏分燃料的颗粒物质吸收更强的可见紫外线和近红外光。然而，以总碳的 EF 加权的吸收简单强迫效率（SFE）弥补了这一影响，当从氢氟烯烃燃料转变为馏分燃料时，吸收简单强迫效率净减少了 50%。
{"title":"Impact of fuel sulfur regulations on carbonaceous particle emission from a marine engine","authors":"Martin Bauer, Hendryk Czech, Lukas Anders, Johannes Passig, Uwe Etzien, Jan Bendl, Thorsten Streibel, Thomas W. Adam, Bert Buchholz, Ralf Zimmermann","doi":"10.1038/s41612-024-00838-4","DOIUrl":"10.1038/s41612-024-00838-4","url":null,"abstract":"Ship traffic substantially contributes to air pollution, thus affecting climate and human health. Recently introduced regulations by the International Maritime Organization (IMO) on the fuel sulfur content (FSC) caused a shift in marine fuel onsumption from heavy fuel oils (HFO) to diesel-like distillate fuels, but also to alternative hybrid fuels and the operation of sulfur scrubbers. Using multi-wavelength thermal-optical carbon analysis (MW-TOCA), our study provides emission factors (EF) of carbonaceous aerosol particles and link the fuel composition to features observed in the soot microstructure, which may be exploited in online monitoring by single-particle mass spectrometry (SPMS). Particulate matter from distillate fuels absorbs stronger light of the visible UV and near-infrared range than HFO. However, Simple Forcing Efficiency (SFE) of absorption weighted by EF of total carbon compensated the effect, leading to a net reduction by >50% when changing form HFO to distillate fuels.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":" ","pages":"1-8"},"PeriodicalIF":8.5,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00838-4.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142684192","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 : 2024-11-21DOI: 10.1038/s41612-024-00824-w
Wu Su, Binghao Wang, Hanyue Chen, Lin Zhu, Xiaogu Zheng, Song Xi Chen
Accurate estimation of carbon removal by terrestrial ecosystems and oceans is crucial to the success of global carbon mitigation initiatives. The emergence of multi-source CO2 observations offers prospects for an improved assessment of carbon fluxes. However, the utility of these diverse observations has been limited by their heterogeneity, leading to much variation in estimated carbon fluxes. To harvest the diverse data types, this paper develops a multi-observation carbon assimilation system (MCAS), which simultaneously integrates both satellite and ground-based observations. MCAS modifies the ensemble Kalman filter to apply different inflation factors to different types of observation errors, addressing the heterogeneity between satellite and in situ data. In commonly used independent validation datasets, the carbon flux derived from MCAS outperformed those obtained from a single source, demonstrating a 20% reduction in error compared to existing carbon flux products. We use MCAS to conduct ecosystem and ocean carbon flux inversion for the period of 2016–2020, which reveals that the 5-year average global net terrestrial and ocean sink was 1.84 ± 0.60 and 2.74 ± 0.49 petagrams, absorbing approximately 47% of human-caused CO2 emissions together, which were consistent with the global carbon project estimates of 1.82 and 2.66 petagrams. All these facts suggest MCAS is a better methodology than those for assimilating single-source observation only.
{"title":"A new global carbon flux estimation methodology by assimilation of both in situ and satellite CO2 observations","authors":"Wu Su, Binghao Wang, Hanyue Chen, Lin Zhu, Xiaogu Zheng, Song Xi Chen","doi":"10.1038/s41612-024-00824-w","DOIUrl":"10.1038/s41612-024-00824-w","url":null,"abstract":"Accurate estimation of carbon removal by terrestrial ecosystems and oceans is crucial to the success of global carbon mitigation initiatives. The emergence of multi-source CO2 observations offers prospects for an improved assessment of carbon fluxes. However, the utility of these diverse observations has been limited by their heterogeneity, leading to much variation in estimated carbon fluxes. To harvest the diverse data types, this paper develops a multi-observation carbon assimilation system (MCAS), which simultaneously integrates both satellite and ground-based observations. MCAS modifies the ensemble Kalman filter to apply different inflation factors to different types of observation errors, addressing the heterogeneity between satellite and in situ data. In commonly used independent validation datasets, the carbon flux derived from MCAS outperformed those obtained from a single source, demonstrating a 20% reduction in error compared to existing carbon flux products. We use MCAS to conduct ecosystem and ocean carbon flux inversion for the period of 2016–2020, which reveals that the 5-year average global net terrestrial and ocean sink was 1.84 ± 0.60 and 2.74 ± 0.49 petagrams, absorbing approximately 47% of human-caused CO2 emissions together, which were consistent with the global carbon project estimates of 1.82 and 2.66 petagrams. All these facts suggest MCAS is a better methodology than those for assimilating single-source observation only.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":" ","pages":"1-10"},"PeriodicalIF":8.5,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00824-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142684193","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 : 2024-11-20DOI: 10.1038/s41612-024-00840-w
Longhuan Wang, Binghao Jia, Xing Yuan, Zhenghui Xie, Kun Yang, Jiancheng Shi
The change of groundwater storage (GWS) on the Tibetan Plateau (TP) is vital for water resources management and regional sustainability, but its estimation has large uncertainty due to insufficient hydrological measurements and diverse future climate scenarios. Here, we employ high-resolution land surface modeling, advanced satellite observations, global climate model data, and deep learning to estimate GWS changes in the past and future. We find a 3.51 ± 2.40 Gt yr−1 increase in GWS from 2002–2018, especially in exorheic basins, attributed to glacier melting. The GWS will persistently increase in the future, but the growth rate is slowing down (0.14 Gt yr−1 for 2079–2100 under a high emission scenario). Increasing GWS is projected over most endorheic basins, which is associated with increasing precipitation and decreasing shortwave radiation. In contrast, decreasing GWS is projected over the headwaters of Amu Darya, Yangtze, and Yellow river basins. These insights have implications for sustainable water resource management in a changing climate.
{"title":"The slowdown of increasing groundwater storage in response to climate warming in the Tibetan Plateau","authors":"Longhuan Wang, Binghao Jia, Xing Yuan, Zhenghui Xie, Kun Yang, Jiancheng Shi","doi":"10.1038/s41612-024-00840-w","DOIUrl":"10.1038/s41612-024-00840-w","url":null,"abstract":"The change of groundwater storage (GWS) on the Tibetan Plateau (TP) is vital for water resources management and regional sustainability, but its estimation has large uncertainty due to insufficient hydrological measurements and diverse future climate scenarios. Here, we employ high-resolution land surface modeling, advanced satellite observations, global climate model data, and deep learning to estimate GWS changes in the past and future. We find a 3.51 ± 2.40 Gt yr−1 increase in GWS from 2002–2018, especially in exorheic basins, attributed to glacier melting. The GWS will persistently increase in the future, but the growth rate is slowing down (0.14 Gt yr−1 for 2079–2100 under a high emission scenario). Increasing GWS is projected over most endorheic basins, which is associated with increasing precipitation and decreasing shortwave radiation. In contrast, decreasing GWS is projected over the headwaters of Amu Darya, Yangtze, and Yellow river basins. These insights have implications for sustainable water resource management in a changing climate.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":" ","pages":"1-10"},"PeriodicalIF":8.5,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00840-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142678658","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 : 2024-11-20DOI: 10.1038/s41612-024-00836-6
Iravati Ray, Shoumick Mitra, Jariya Kayee, Shufang Yuan, S. M. Shiva Nagendra, Xianfeng Wang, Reshmi Das
India, heavily reliant on coal for power generation, has been a significant emitter of particulate matter (PM) bound lead (Pb) and other heavy metals. It is crucial to understand whether implementation of stricter norms in recent years have effectively reduced emissions from coal combustion. This study aims to investigate and quantify the primary sources of PM2.5 in an area housing a major lignite-fired power plant in South India using Pb isotopic compositions and elemental concentrations. Characteristic ratios such as V/Pb and Cu/Pb demonstrate negligible influence from coal combustion, and indicate that summer aerosols are influenced by open burning. In Pb triple-isotope space the PM2.5 aerosols plot away from coal, overlapping with open burning signatures. These indicate that the atmosphere is predominantly influenced by open burning of solid waste and biomass rather than coal combustion, suggesting a promising decrease in coal emissions. Bayesian mixing model demonstrates that solid waste & biomass burning is the largest anthropogenic contributor towards atmospheric Pb (up to 26%), even in a region of coal combustion and presence of medium and small-scale industries. The dominance of open burning as a pollution source in the vicinity of a lignite fired power plant highlights the necessity for better waste management strategies.
{"title":"Dominance of open burning signatures in PM2.5 near coal plant should redefine pollutant priorities of India","authors":"Iravati Ray, Shoumick Mitra, Jariya Kayee, Shufang Yuan, S. M. Shiva Nagendra, Xianfeng Wang, Reshmi Das","doi":"10.1038/s41612-024-00836-6","DOIUrl":"10.1038/s41612-024-00836-6","url":null,"abstract":"India, heavily reliant on coal for power generation, has been a significant emitter of particulate matter (PM) bound lead (Pb) and other heavy metals. It is crucial to understand whether implementation of stricter norms in recent years have effectively reduced emissions from coal combustion. This study aims to investigate and quantify the primary sources of PM2.5 in an area housing a major lignite-fired power plant in South India using Pb isotopic compositions and elemental concentrations. Characteristic ratios such as V/Pb and Cu/Pb demonstrate negligible influence from coal combustion, and indicate that summer aerosols are influenced by open burning. In Pb triple-isotope space the PM2.5 aerosols plot away from coal, overlapping with open burning signatures. These indicate that the atmosphere is predominantly influenced by open burning of solid waste and biomass rather than coal combustion, suggesting a promising decrease in coal emissions. Bayesian mixing model demonstrates that solid waste & biomass burning is the largest anthropogenic contributor towards atmospheric Pb (up to 26%), even in a region of coal combustion and presence of medium and small-scale industries. The dominance of open burning as a pollution source in the vicinity of a lignite fired power plant highlights the necessity for better waste management strategies.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":" ","pages":"1-17"},"PeriodicalIF":8.5,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00836-6.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142672772","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 : 2024-11-20DOI: 10.1038/s41612-024-00832-w
Jonathan D. Beverley, Matthew Newman, Andrew Hoell
Climate models exhibit errors in their simulation of historical trends of variables including sea surface temperature, winds, and precipitation, with important implications for regional and global climate projections. Here, we show that the same trend errors are also present in a suite of initialised seasonal re-forecasts for the years 1993–2016. These re-forecasts are produced by operational models that are similar to Coupled Model Intercomparison Project (CMIP)-class models and share their historical external forcings (e.g. CO2/aerosols). The trend errors, which are often well-developed at very short lead times, represent a roughly linear change in the model mean biases over the 1993–2016 re-forecast record. The similarity of trend errors in both the re-forecasts and historical simulations suggests that climate model trend errors likewise result from evolving mean biases, responding to changing external radiative forcings, instead of being an erroneous long-term response to external forcing. Therefore, these trend errors may be investigated by examining their short-lead development in initialised seasonal forecasts/re-forecasts, which we suggest should also be made by all CMIP models.
{"title":"Climate model trend errors are evident in seasonal forecasts at short leads","authors":"Jonathan D. Beverley, Matthew Newman, Andrew Hoell","doi":"10.1038/s41612-024-00832-w","DOIUrl":"10.1038/s41612-024-00832-w","url":null,"abstract":"Climate models exhibit errors in their simulation of historical trends of variables including sea surface temperature, winds, and precipitation, with important implications for regional and global climate projections. Here, we show that the same trend errors are also present in a suite of initialised seasonal re-forecasts for the years 1993–2016. These re-forecasts are produced by operational models that are similar to Coupled Model Intercomparison Project (CMIP)-class models and share their historical external forcings (e.g. CO2/aerosols). The trend errors, which are often well-developed at very short lead times, represent a roughly linear change in the model mean biases over the 1993–2016 re-forecast record. The similarity of trend errors in both the re-forecasts and historical simulations suggests that climate model trend errors likewise result from evolving mean biases, responding to changing external radiative forcings, instead of being an erroneous long-term response to external forcing. Therefore, these trend errors may be investigated by examining their short-lead development in initialised seasonal forecasts/re-forecasts, which we suggest should also be made by all CMIP models.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":" ","pages":"1-13"},"PeriodicalIF":8.5,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00832-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142672806","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 : 2024-11-19DOI: 10.1038/s41612-024-00777-0
Pankaj Upadhyaya, Saroj K. Mishra, John T. Fasullo, In-Sik Kang
Over the last four decades (1980–2020), the summer westerlies that prevail in South Asia along the monsoon trough region have weakened by about 25% based on multiple reanalysis datasets. Trends in a range of climate model simulations suggest that the weakening is driven by multiple anthropogenic forcings. Over the period, sea-level pressure has increased by 0.6–1.0 hPa over South Asia’s northwestern regions, induced by cooling due to aerosol emission and changes in land use and land cover, and has decreased over the Arabian Peninsula mainly due to warming by greenhouse gases. These changes in temperature and pressure act to weaken the regional pressure gradient, deflecting the subtropical westerlies from South Asia toward the Arabian Peninsula and weakening the winds in the monsoon trough and its adjacent region. The slowing down of winds appears to result in an anomalous moisture loading and increase in rainfall over the semi-arid northwestern South Asia. This weakening and its associated changes in regional climate are highly relevant to policymaking across South Asia.
{"title":"Attributing the recent weakening of the South Asian subtropical westerlies","authors":"Pankaj Upadhyaya, Saroj K. Mishra, John T. Fasullo, In-Sik Kang","doi":"10.1038/s41612-024-00777-0","DOIUrl":"10.1038/s41612-024-00777-0","url":null,"abstract":"Over the last four decades (1980–2020), the summer westerlies that prevail in South Asia along the monsoon trough region have weakened by about 25% based on multiple reanalysis datasets. Trends in a range of climate model simulations suggest that the weakening is driven by multiple anthropogenic forcings. Over the period, sea-level pressure has increased by 0.6–1.0 hPa over South Asia’s northwestern regions, induced by cooling due to aerosol emission and changes in land use and land cover, and has decreased over the Arabian Peninsula mainly due to warming by greenhouse gases. These changes in temperature and pressure act to weaken the regional pressure gradient, deflecting the subtropical westerlies from South Asia toward the Arabian Peninsula and weakening the winds in the monsoon trough and its adjacent region. The slowing down of winds appears to result in an anomalous moisture loading and increase in rainfall over the semi-arid northwestern South Asia. This weakening and its associated changes in regional climate are highly relevant to policymaking across South Asia.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":" ","pages":"1-11"},"PeriodicalIF":8.5,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00777-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142670843","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 : 2024-11-18DOI: 10.1038/s41612-024-00834-8
Puja Das, August Posch, Nathan Barber, Michael Hicks, Kate Duffy, Thomas Vandal, Debjani Singh, Katie van Werkhoven, Auroop R. Ganguly
Precipitation nowcasting, which is critical for flood emergency and river management, has remained challenging for decades, although recent developments in deep generative modeling (DGM) suggest the possibility of improvements. River management centers, such as the Tennessee Valley Authority, have been using Numerical Weather Prediction (NWP) models for nowcasting, but they have been struggling with missed detections even from best-in-class NWP models. While decades of prior research achieved limited improvements beyond advection and localized evolution, recent attempts have shown progress from so-called physics-free machine learning (ML) methods, and even greater improvements from physics-embedded ML approaches. Developers of DGM for nowcasting have compared their approaches with optical flow (a variant of advection) and meteorologists’ judgment, but not with NWP models. Further, they have not conducted independent co-evaluations with water resources and river managers. Here we show that the state-of-the-art physics-embedded deep generative model, specifically NowcastNet, outperforms the High Resolution Rapid Refresh (HRRR) model, which is the latest generation of NWP, along with advection and persistence, especially for heavy precipitation events. Thus, for grid-cell extremes over 16 mm/h, NowcastNet demonstrated a median critical success index (CSI) of 0.30, compared with median CSI of 0.04 for HRRR. However, despite hydrologically-relevant improvements in point-by-point forecasts from NowcastNet, caveats include overestimation of spatially aggregate precipitation over longer lead times. Our co-evaluation with ML developers, hydrologists and river managers suggest the possibility of improved flood emergency response and hydropower management.
{"title":"Hybrid physics-AI outperforms numerical weather prediction for extreme precipitation nowcasting","authors":"Puja Das, August Posch, Nathan Barber, Michael Hicks, Kate Duffy, Thomas Vandal, Debjani Singh, Katie van Werkhoven, Auroop R. Ganguly","doi":"10.1038/s41612-024-00834-8","DOIUrl":"10.1038/s41612-024-00834-8","url":null,"abstract":"Precipitation nowcasting, which is critical for flood emergency and river management, has remained challenging for decades, although recent developments in deep generative modeling (DGM) suggest the possibility of improvements. River management centers, such as the Tennessee Valley Authority, have been using Numerical Weather Prediction (NWP) models for nowcasting, but they have been struggling with missed detections even from best-in-class NWP models. While decades of prior research achieved limited improvements beyond advection and localized evolution, recent attempts have shown progress from so-called physics-free machine learning (ML) methods, and even greater improvements from physics-embedded ML approaches. Developers of DGM for nowcasting have compared their approaches with optical flow (a variant of advection) and meteorologists’ judgment, but not with NWP models. Further, they have not conducted independent co-evaluations with water resources and river managers. Here we show that the state-of-the-art physics-embedded deep generative model, specifically NowcastNet, outperforms the High Resolution Rapid Refresh (HRRR) model, which is the latest generation of NWP, along with advection and persistence, especially for heavy precipitation events. Thus, for grid-cell extremes over 16 mm/h, NowcastNet demonstrated a median critical success index (CSI) of 0.30, compared with median CSI of 0.04 for HRRR. However, despite hydrologically-relevant improvements in point-by-point forecasts from NowcastNet, caveats include overestimation of spatially aggregate precipitation over longer lead times. Our co-evaluation with ML developers, hydrologists and river managers suggest the possibility of improved flood emergency response and hydropower management.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":" ","pages":"1-15"},"PeriodicalIF":8.5,"publicationDate":"2024-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-024-00834-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142670806","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}
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：