The prediction of sea surface partial pressure of carbon dioxide(pCO2)in the South China Sea is crucial for understanding the region’s contribution to the global carbon budget and its interactions with climate cha...The prediction of sea surface partial pressure of carbon dioxide(pCO2)in the South China Sea is crucial for understanding the region’s contribution to the global carbon budget and its interactions with climate change.We applied the Spatiotemporal Convolutional Long Short-Term Memory(STConvLSTM)model,integrating key environmental factors including sea surface temperature(SST),sea surface salinity(SSS),and chlorophyll a(Chl a),to predict and analyze sea surface pCO2in the South China Sea.The model demonstrated high accuracy in short-term predictions(1 month),with a mean absolute error(MAE)of 0.394,a root mean square error(RMSE)of 0.659,and a coefficient of determination(R2)of 0.998.For long-term predictions(12 months),the model maintained its predictive capability,with an MAE of 0.667,RMSE of 1.255,and R2of 0.994.Feature importance analysis revealed that sea surface pCO2and SST were the main drivers of the model’s predictions,whereas Chl a and SSS had relatively minor impacts.The model’s generalization ability was further validated in the northwest Pacific Ocean and tropical Pacific Ocean,where it successfully captured the spatiotemporal variation in pCO2with small prediction errors.The ST-ConvLSTM model provides an efficient and accurate tool for forecasting and analyzing sea surface pCO2in the South China Sea,offering new insights into global carbon cycling and climate change.This study demonstrates the potential of deep learning in marine science and provides a significant technical support for global changes and marine ecosystem research.展开更多
独立中尺度数值天气研究与预报(weather research and forecasting,WRF)模式在输出风速特征时,忽略了波浪传播和海流演变引起的海表变形对三维风场湍流结构的调制作用,无法输出秒级分辨率的脉动风速。针对这一问题,本文构建了一种基于WR...独立中尺度数值天气研究与预报(weather research and forecasting,WRF)模式在输出风速特征时,忽略了波浪传播和海流演变引起的海表变形对三维风场湍流结构的调制作用,无法输出秒级分辨率的脉动风速。针对这一问题,本文构建了一种基于WRF模式、近岸波浪模拟(simulating waves nearshore,SWAN)模型、区域海洋模式系统(regional ocean modeling system,ROMS)和大涡模拟(large eddy simulation,LES)耦合的中-微尺度多层嵌套风-浪-流数值模拟方法(WRF-SWAN-ROMS-LES),并开发了中尺度强迫源驱动的中-微尺度耦合软件框架Marine_CFD。利用该方法,对比分析了中尺度海气耦合的大气模式(coupled ocean-atmosphere-wave-sediment transport,COAWST)与独立大气模式(WRF和WRF_SST)在风速模拟上的差异,并验证了微尺度大涡模拟在再现湍流脉动方面的有效性。结果表明,风-浪-流耦合模型对海上风速演变过程的刻画具有更高的精度:在38 m高度处,COAWST模式的皮尔逊相关系数为0.789,高于WRF的0.733和WRF_SST模式的0.735,说明COAWST模式对海洋风速演变模拟更具优势。在微尺度模拟中,通过引入中尺度大气场的速度和位温等三维时空分布信息,驱动微尺度大涡模拟,其输出风速序列整体位于LES脉动风速曲线的中间区域,并且能够有效保持秒级的高频脉动特征。展开更多
An atmospheric general circulation model(AGCM)is used to analyze the different impact on the Barents Sea(BS)and Greenland Sea(GS)for a perturbation of sea-to-air DMS flux.We compare contemporary anthropogenic S and co...An atmospheric general circulation model(AGCM)is used to analyze the different impact on the Barents Sea(BS)and Greenland Sea(GS)for a perturbation of sea-to-air DMS flux.We compare contemporary anthropogenic S and contemporary DMS sea-to-air flux(as baseline,B00)sulfur emissions,with contemporary anthropogenic S and a perturbed DMS flux(as modified,B01)sulfur emissions.Results show that the global mean surface DMS and DMS vertically integrated concentration all peaked in June and increases more than 63%in BS and increases about 58%in GS.The concentrations of atmospheric sulfur dioxide vertical integral(SO2)and sulfate vertical integral(SO4)only increase less than 12%in both regions.Sulfur emission(SEM)peaked in June and increased about 67%and 41%in GS and BS,respectively.Aerosol optical depth(AOD)increases less than 4%in GS and in BS.Surface temperature(TSC)peaked in July and reduces 0.25 K and 0.8 K in GS and BS,respectively.Satellite data from 2003 to 2023show that chlorophyll(CHL)concentration in BS exceeds that of GS by 51%.The AOD in GS is only 0.6%higher than in BS.The recent increased rate of DMS surface concentration in BS(from 6%during 1981–2002 to 18.8%in 2003–2023)is mainly caused by elevated CHL concentrations in BS.Finally,the perturbation on DMS flux leads to increase rate of DMS and related sulfur emissions especially in the BS,this tendency will have an offsetting effect on regional warming.展开更多
This study evaluates the performance of a Regional Ocean Modeling System-based Hybrid Coupled Model(HCMROMS)in simulating tropical instability waves(TIWs),their modulation by the El Niño-Southern Oscillation(E...This study evaluates the performance of a Regional Ocean Modeling System-based Hybrid Coupled Model(HCMROMS)in simulating tropical instability waves(TIWs),their modulation by the El Niño-Southern Oscillation(ENSO)in the tropical Pacific Ocean,and their impacts on the mean state thermal conditions of the ocean.HCMROMSintegrates the Regional Ocean Modeling System(ROMS)with a statistical atmospheric model for surface wind stress anomalies based on Singular Value Decomposition(SVD),aiming to accurately represent air-sea coupling interactions and TIWs-related ocean mesoscale processes.The model successfully reproduces the climatological state and seasonal variability of sea surface temperature(SST)in the tropical Pacific.In simulating ENSO,HCMROMScaptures the quasi-three year oscillation characteristic of ENSO.Regarding TIWs,the model accurately reproduces their main features and periods.Additionally,HCMROMSshows a significantly negative correlation between the strength of TIWs and the Niño 3.4 index,being consistent with empirical analyses from observations.The model’s ability to simulate the interaction between TIWs and ENSO allows us to analyze the TIWs related energy and heat budgets.The model’s energy budget reveals that the strength of TIWs is strongly modulated by ENSO phases.The study also examines the feedback effects of TIWs on the mean state through a heat budget analysis.These results indicate that TIWs play a crucial role in the climatological heat balance,with the amplitude being comparable to sea surface heat flux.These findings underscore the importance of accurately simulating TIWs to better represent and understand their role in the tropical Pacific climate system.Overall,HCMROMSdemonstrated robust performance in representing both ENSO and TIWs,offering a reliable tool for future studies on their interactions and the broader dynamics of the tropical Pacific Ocean.The model’s precise representations of TIWs and their relationship with ENSO highlight its potential in advancing our understanding of ocean-atmosphere interactions and improving climate predictions.展开更多
Evaporation ducts,which originate at the air-sea boundary,significantly influence electromagnetic propagation,ship communication,radar ranging,and other related fields.However,the current understanding of the variabil...Evaporation ducts,which originate at the air-sea boundary,significantly influence electromagnetic propagation,ship communication,radar ranging,and other related fields.However,the current understanding of the variability in evaporation ducts under the combined effect of atmospheric and oceanic processes remains unclear.Via shipboard observations,the changes in evaporation ducts at paired oceanic submesoscale fronts(OSFs)during and after successive passage of an atmospheric cyclone and anticyclone in the northwestern Pacific Ocean were investigated.The observations indicated that under the dominant influence of sea surface temperature,air temperature,and specific humidity changes,the average evaporation duct height above the OSFs during cyclone passage reached 9.76 m,which is 446% of the 2.19 m during the period when only OSFs occurred.During the anticyclone period,the evaporation duct height ranged from 2 to 3 m.Specific humidity variation was influenced by mainly evaporation,followed by advection and divergence flow.Differences in the influence mechanisms of sea surface temperature and wind speed on evaporation during different periods were explored.展开更多
台湾海峡海面风场精细结构对区域气候及海上风能开发具有重要意义。受观测资料限制,复杂地形影响下台湾海峡海温锋面强度与海面风场响应之间的季节差异仍有待进一步认识。本文利用2004-2022年高分辨率天气研究与预报(Weather Research a...台湾海峡海面风场精细结构对区域气候及海上风能开发具有重要意义。受观测资料限制,复杂地形影响下台湾海峡海温锋面强度与海面风场响应之间的季节差异仍有待进一步认识。本文利用2004-2022年高分辨率天气研究与预报(Weather Research and Forcasting,WRF)模式数值模拟结果与多源观测资料,分析海温锋面与海面风场的季节变化特征,并通过改变海温锋面强度的敏感性试验评估局地风速响应。奇异值分解(singular value decomposition,SVD)结果表明,夏季海表温度(sea surface temperature,SST)异常与风场异常的时间协同变化最为突出,第一模态平方协方差贡献率为82.09%,两者第一模态时间系数相关系数为0.69。海温锋面强度与风场异常时间系数在夏季表现为同相变化,在冬季表现为反相变化,说明台湾海峡海温锋面与海面风场异常耦合具有季节差异,夏季局地热力作用更明显,冬季背景动力调制更突出。敏感性试验表明,相较于仅削弱海温锋面强度,完全去除海温锋面引起的局地风速响应更明显。去除海温锋面后,冬、夏季风速响应中位数分别约为0.45 m/s和0.26 m/s,且夏季风速响应主要集中在海温锋面附近,集中度约为冬季的1.5倍。结果揭示了台湾海峡海温锋面对海面风场影响的季节依赖性,可为复杂海峡区域精细化风场模拟和海上风能资源评估提供参考。展开更多
Numerical models are crucial for quantifying the ocean-atmosphere interactions associated with the El Niño-Southern Oscillation(ENSO)phenomenon in the tropical Pacific.Current coupled models often exhibit signifi...Numerical models are crucial for quantifying the ocean-atmosphere interactions associated with the El Niño-Southern Oscillation(ENSO)phenomenon in the tropical Pacific.Current coupled models often exhibit significant biases and inter-model differences in simulating ENSO,underscoring the need for alternative modeling approaches.The Regional Ocean Modeling System(ROMS)is a sophisticated ocean model widely used for regional studies and has been coupled with various atmospheric models.However,its application in simulating ENSO processes on a basin scale in the tropical Pacific has not been explored.For the first time,this study presents the development of a basin-scale hybrid coupled model(HCM)for the tropical Pacific,integrating ROMS with a statistical atmospheric model that captures the interannual relationships between sea surface temperature(SST)and wind stress anomalies.The HCM is evaluated for its capability to simulate the annual mean,seasonal,and interannual variations of the oceanic state in the tropical Pacific.Results demonstrate that the model effectively reproduces the ENSO cycle,with a dominant oscillation period of approximately two years.The ROMS-based HCM developed here offers an efficient and robust tool for investigating climate variability in the tropical Pacific.展开更多
为深入了解海–气界面CO2通量的国际研究动态,基于Web of Science数据库,运用CiteSpace和VOS-viewer软件,对1980—2023年相关文献进行可视化分析。结果表明,发文量总体上呈上升趋势,可分为萌芽期、快速增长期和稳定增长期3个阶段;美...为深入了解海–气界面CO2通量的国际研究动态,基于Web of Science数据库,运用CiteSpace和VOS-viewer软件,对1980—2023年相关文献进行可视化分析。结果表明,发文量总体上呈上升趋势,可分为萌芽期、快速增长期和稳定增长期3个阶段;美国、德国、英国、法国和中国为主要研究力量;研究方向从单因素对通量的影响向多因素耦合影响转变,从局部研究向全球视角扩展,从基础理论向应用研究深化;研究热点集中在海–气界面CO2通量的空间分布特征、动态变化的关键过程和驱动因子及其对全球气候变化与人类活动的响应。研究前沿多围绕多源遥感数据融合与机器学习算法展开,用于模拟海表CO2分压、估算通量及定量分析气候变化响应。未来的研究应聚焦高分辨率观测、多源数据融合、机器学习与大数据分析、区域和近海环境研究以及气候变化与海洋碳循环的反馈机制,同时加强跨学科协作和国际合作。研究结果可为理解全球碳循环、预测气候变化趋势及制定碳减排策略提供参考。展开更多
基金Supported by the National Key Research and Development Program of China(No.2023YFC3008202)the National Natural Science Foundation of China(No.42406019)the Scientific Research Fund of Zhejiang Provincial Education Department(No.Y202353066)。
摘要The prediction of sea surface partial pressure of carbon dioxide(pCO2)in the South China Sea is crucial for understanding the region’s contribution to the global carbon budget and its interactions with climate change.We applied the Spatiotemporal Convolutional Long Short-Term Memory(STConvLSTM)model,integrating key environmental factors including sea surface temperature(SST),sea surface salinity(SSS),and chlorophyll a(Chl a),to predict and analyze sea surface pCO2in the South China Sea.The model demonstrated high accuracy in short-term predictions(1 month),with a mean absolute error(MAE)of 0.394,a root mean square error(RMSE)of 0.659,and a coefficient of determination(R2)of 0.998.For long-term predictions(12 months),the model maintained its predictive capability,with an MAE of 0.667,RMSE of 1.255,and R2of 0.994.Feature importance analysis revealed that sea surface pCO2and SST were the main drivers of the model’s predictions,whereas Chl a and SSS had relatively minor impacts.The model’s generalization ability was further validated in the northwest Pacific Ocean and tropical Pacific Ocean,where it successfully captured the spatiotemporal variation in pCO2with small prediction errors.The ST-ConvLSTM model provides an efficient and accurate tool for forecasting and analyzing sea surface pCO2in the South China Sea,offering new insights into global carbon cycling and climate change.This study demonstrates the potential of deep learning in marine science and provides a significant technical support for global changes and marine ecosystem research.
摘要An atmospheric general circulation model(AGCM)is used to analyze the different impact on the Barents Sea(BS)and Greenland Sea(GS)for a perturbation of sea-to-air DMS flux.We compare contemporary anthropogenic S and contemporary DMS sea-to-air flux(as baseline,B00)sulfur emissions,with contemporary anthropogenic S and a perturbed DMS flux(as modified,B01)sulfur emissions.Results show that the global mean surface DMS and DMS vertically integrated concentration all peaked in June and increases more than 63%in BS and increases about 58%in GS.The concentrations of atmospheric sulfur dioxide vertical integral(SO2)and sulfate vertical integral(SO4)only increase less than 12%in both regions.Sulfur emission(SEM)peaked in June and increased about 67%and 41%in GS and BS,respectively.Aerosol optical depth(AOD)increases less than 4%in GS and in BS.Surface temperature(TSC)peaked in July and reduces 0.25 K and 0.8 K in GS and BS,respectively.Satellite data from 2003 to 2023show that chlorophyll(CHL)concentration in BS exceeds that of GS by 51%.The AOD in GS is only 0.6%higher than in BS.The recent increased rate of DMS surface concentration in BS(from 6%during 1981–2002 to 18.8%in 2003–2023)is mainly caused by elevated CHL concentrations in BS.Finally,the perturbation on DMS flux leads to increase rate of DMS and related sulfur emissions especially in the BS,this tendency will have an offsetting effect on regional warming.
基金Supported by the Laoshan Laboratory(No.LSKJ 202202402)the National Natural Science Foundation of China(No.42030410)+1 种基金the Startup Foundation for Introducing Talent of NUISTthe Jiangsu Innovation Research Group(No.JSSCTD 202346)。
摘要This study evaluates the performance of a Regional Ocean Modeling System-based Hybrid Coupled Model(HCMROMS)in simulating tropical instability waves(TIWs),their modulation by the El Niño-Southern Oscillation(ENSO)in the tropical Pacific Ocean,and their impacts on the mean state thermal conditions of the ocean.HCMROMSintegrates the Regional Ocean Modeling System(ROMS)with a statistical atmospheric model for surface wind stress anomalies based on Singular Value Decomposition(SVD),aiming to accurately represent air-sea coupling interactions and TIWs-related ocean mesoscale processes.The model successfully reproduces the climatological state and seasonal variability of sea surface temperature(SST)in the tropical Pacific.In simulating ENSO,HCMROMScaptures the quasi-three year oscillation characteristic of ENSO.Regarding TIWs,the model accurately reproduces their main features and periods.Additionally,HCMROMSshows a significantly negative correlation between the strength of TIWs and the Niño 3.4 index,being consistent with empirical analyses from observations.The model’s ability to simulate the interaction between TIWs and ENSO allows us to analyze the TIWs related energy and heat budgets.The model’s energy budget reveals that the strength of TIWs is strongly modulated by ENSO phases.The study also examines the feedback effects of TIWs on the mean state through a heat budget analysis.These results indicate that TIWs play a crucial role in the climatological heat balance,with the amplitude being comparable to sea surface heat flux.These findings underscore the importance of accurately simulating TIWs to better represent and understand their role in the tropical Pacific climate system.Overall,HCMROMSdemonstrated robust performance in representing both ENSO and TIWs,offering a reliable tool for future studies on their interactions and the broader dynamics of the tropical Pacific Ocean.The model’s precise representations of TIWs and their relationship with ENSO highlight its potential in advancing our understanding of ocean-atmosphere interactions and improving climate predictions.
基金Supported by the National Natural Science Foundation of China(Nos.42275011,41775027)the China Postdoctoral Science Foundation(No.2024M764287)。
摘要Evaporation ducts,which originate at the air-sea boundary,significantly influence electromagnetic propagation,ship communication,radar ranging,and other related fields.However,the current understanding of the variability in evaporation ducts under the combined effect of atmospheric and oceanic processes remains unclear.Via shipboard observations,the changes in evaporation ducts at paired oceanic submesoscale fronts(OSFs)during and after successive passage of an atmospheric cyclone and anticyclone in the northwestern Pacific Ocean were investigated.The observations indicated that under the dominant influence of sea surface temperature,air temperature,and specific humidity changes,the average evaporation duct height above the OSFs during cyclone passage reached 9.76 m,which is 446% of the 2.19 m during the period when only OSFs occurred.During the anticyclone period,the evaporation duct height ranged from 2 to 3 m.Specific humidity variation was influenced by mainly evaporation,followed by advection and divergence flow.Differences in the influence mechanisms of sea surface temperature and wind speed on evaporation during different periods were explored.
摘要台湾海峡海面风场精细结构对区域气候及海上风能开发具有重要意义。受观测资料限制,复杂地形影响下台湾海峡海温锋面强度与海面风场响应之间的季节差异仍有待进一步认识。本文利用2004-2022年高分辨率天气研究与预报(Weather Research and Forcasting,WRF)模式数值模拟结果与多源观测资料,分析海温锋面与海面风场的季节变化特征,并通过改变海温锋面强度的敏感性试验评估局地风速响应。奇异值分解(singular value decomposition,SVD)结果表明,夏季海表温度(sea surface temperature,SST)异常与风场异常的时间协同变化最为突出,第一模态平方协方差贡献率为82.09%,两者第一模态时间系数相关系数为0.69。海温锋面强度与风场异常时间系数在夏季表现为同相变化,在冬季表现为反相变化,说明台湾海峡海温锋面与海面风场异常耦合具有季节差异,夏季局地热力作用更明显,冬季背景动力调制更突出。敏感性试验表明,相较于仅削弱海温锋面强度,完全去除海温锋面引起的局地风速响应更明显。去除海温锋面后,冬、夏季风速响应中位数分别约为0.45 m/s和0.26 m/s,且夏季风速响应主要集中在海温锋面附近,集中度约为冬季的1.5倍。结果揭示了台湾海峡海温锋面对海面风场影响的季节依赖性,可为复杂海峡区域精细化风场模拟和海上风能资源评估提供参考。
基金Supported by the Laoshan Laboratory(No.LSKJ 202202404)the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDB 42000000)+1 种基金the National Natural Science Foundation of China(NSFC)(No.42030410)the Startup Foundation for Introducing Talent of NUIST,and the Jiangsu Innovation Research Group(No.JSSCTD 202346)。
摘要Numerical models are crucial for quantifying the ocean-atmosphere interactions associated with the El Niño-Southern Oscillation(ENSO)phenomenon in the tropical Pacific.Current coupled models often exhibit significant biases and inter-model differences in simulating ENSO,underscoring the need for alternative modeling approaches.The Regional Ocean Modeling System(ROMS)is a sophisticated ocean model widely used for regional studies and has been coupled with various atmospheric models.However,its application in simulating ENSO processes on a basin scale in the tropical Pacific has not been explored.For the first time,this study presents the development of a basin-scale hybrid coupled model(HCM)for the tropical Pacific,integrating ROMS with a statistical atmospheric model that captures the interannual relationships between sea surface temperature(SST)and wind stress anomalies.The HCM is evaluated for its capability to simulate the annual mean,seasonal,and interannual variations of the oceanic state in the tropical Pacific.Results demonstrate that the model effectively reproduces the ENSO cycle,with a dominant oscillation period of approximately two years.The ROMS-based HCM developed here offers an efficient and robust tool for investigating climate variability in the tropical Pacific.
摘要为深入了解海–气界面CO2通量的国际研究动态,基于Web of Science数据库,运用CiteSpace和VOS-viewer软件,对1980—2023年相关文献进行可视化分析。结果表明,发文量总体上呈上升趋势,可分为萌芽期、快速增长期和稳定增长期3个阶段;美国、德国、英国、法国和中国为主要研究力量;研究方向从单因素对通量的影响向多因素耦合影响转变,从局部研究向全球视角扩展,从基础理论向应用研究深化;研究热点集中在海–气界面CO2通量的空间分布特征、动态变化的关键过程和驱动因子及其对全球气候变化与人类活动的响应。研究前沿多围绕多源遥感数据融合与机器学习算法展开,用于模拟海表CO2分压、估算通量及定量分析气候变化响应。未来的研究应聚焦高分辨率观测、多源数据融合、机器学习与大数据分析、区域和近海环境研究以及气候变化与海洋碳循环的反馈机制,同时加强跨学科协作和国际合作。研究结果可为理解全球碳循环、预测气候变化趋势及制定碳减排策略提供参考。