The atmospheric surface layer of the tropical coastal ocean is commonly very unstable and experiences weakwind conditions.How the latent(LE)and sensible(H)heat fluxes behave under such conditions are unclear because o...The atmospheric surface layer of the tropical coastal ocean is commonly very unstable and experiences weakwind conditions.How the latent(LE)and sensible(H)heat fluxes behave under such conditions are unclear because of the lack of observation stations in the tropics.Thus,this study aims to analyze LE and H and the microclimate parameters influencing them.The authors deployed an eddy covariance system in a tropical coastal region for seven months.The microclimate parameters investigated were wind speed(U),vapor pressure deficit(Δe),temperature difference(ΔT),wind-vapor pressure deficit(UΔe),wind-temperature difference(UΔT),and atmospheric stability(z/L),where z is height and L is the Monin–Obukhov length.On the daily time scale,the results show that LE was more associated with U thanΔe,while H was more related toΔT than U.Cross-wavelet analysis revealed the strong coherence in the LE-U relationship for periods between one and two days,and for H–ΔT,0.5 to 1 day.Correlation and regression analyses confirmed the time series analyses results,where strong positive correlation coefficients(r)were obtained between LE and U(r=0.494)and H andΔT(r=0.365).Compared to other water bodies,the transfer coefficient of moisture(CE N)was found to be small(=0.40×10^(-3))and independent of stability;conversely,the transfer coefficient of heat(CH N)was closer to literature values(=1.00×10^(-3))and a function of stability.展开更多
基于2002—2025年IRI(International Research Institute for Climate and Society)实时多模式预测资料,构建了一个面向事件的ENSO(El Nino-Southern Oscillation)峰值诊断框架,定量评估预测系统对峰值强度与峰值时间两项关键特征的可...基于2002—2025年IRI(International Research Institute for Climate and Society)实时多模式预测资料,构建了一个面向事件的ENSO(El Nino-Southern Oscillation)峰值诊断框架,定量评估预测系统对峰值强度与峰值时间两项关键特征的可预报性。尽管IRI系统在ENSO时间序列上可维持8~9 mon的较高技巧,但传统统计指标难以反映具体事件在峰值阶段的系统性偏差。结果表明,随着预报时效延长,预测的峰值强度普遍减弱,并呈现出显著的强度依赖特征。中等和强事件往往被低估,但弱事件更容易被高估。在模式差异方面,动力模式在再现中、强事件的峰值振幅上更有优势,但在弱事件中,统计模式的预测反而更接近观测。在峰值时间方面,模式预测普遍存在偏晚现象,并且滞后误差会随着预报时效持续累积。峰值时间偏差还呈现明显的冷暖不对称结构,拉尼娜事件的滞后程度显著强于厄尔尼诺事件。在不同模式类型的比较中,统计模式在拉尼娜事件中的峰值时间偏差远大于动力模式,而在厄尔尼诺事件中两类模式的差异相对较小。总体而言,本研究揭示了现有ENSO预测系统在峰值特征上的偏差结构,并指出动力与统计模式的互补性,为改进多模式集合策略和提升ENSO预测性能提供了科学依据。展开更多
This study investigates the distinct impacts of eastern Pacific(EP)and central Pacific(CP)El Niño events on winter shortwave solar radiation(SSR)in southern China,revealing different spatial distributions and und...This study investigates the distinct impacts of eastern Pacific(EP)and central Pacific(CP)El Niño events on winter shortwave solar radiation(SSR)in southern China,revealing different spatial distributions and underlying mechanisms.The results show that,during the developing winter of EP El Niño,significant SSR reductions occur in southwestern China and the east coast of southern China due to a strong,zonally extended Northwest Pacific anticyclone that transports moisture from the tropical Northwest Pacific and North Indian Ocean,while the northeast of southern China experiences a weak increase in SSR.In contrast,during the developing winter of CP El Niño,SSR decreases in the east of southern China with a significant decrease in the lower basin of the Yangtze River but an increase in the west of southern China with a remarkable increase in eastern Yunnan.The pronounced east-west dipole pattern in SSR anomalies is driven by a meridionally elongated Northwest Pacific anticyclone,which enhances northward moisture transport to the east of southern China while leaving western areas drier.Further research reveals that distinct moisture anomalies during the developing winter of EP and CP events result in divergent SSR distributions across southern China,primarily through modulating the total cloud cover.These findings highlight the critical need to differentiate between El Niño types when predicting medium and long-term variability of radiation in southern China.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(SO_(2))and sulfate vertical integral(SO_(4))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
In this study,based on MERRA-2 reanalysis data and a multi-algorithm integrated atmospheric river(AR)iden-tification method,the authors reveal the cross-seasonal regulation mechanism of El Niño-Southern Oscillati...In this study,based on MERRA-2 reanalysis data and a multi-algorithm integrated atmospheric river(AR)iden-tification method,the authors reveal the cross-seasonal regulation mechanism of El Niño-Southern Oscillation(ENSO)on winter-spring AR activities in East Asia.The results show that ENSO asymmetrically modulates AR ac-tivity through teleconnection and hysteresis effects,and has significant enhancement/inhibition effects on ARs in different regions.At the onset of El Niño,enhanced southwesterly flow at the western edge of the western Pacific subtropical high(WPSH)leads to enhanced AR activity in the western Pacific,and anomalous southerly winds in the Indian Ocean promote northward transport of water vapor in the Arabian Sea and Bay of Bengal.With a three-month lag,the weakening and eastward retreat of the WPSH weakens the low-latitude AR activity,but persistent southerly winds in the Bay of Bengal maintain the AR activity over Southwest China.The mid-to high-latitude AR response exhibits delayed dynamics,initially dominated by the synergistic effect of the southward deviation of the upper-air rapids and the low-level convergence(double-rapid-flow effect)and later modulated by the Pacific-North American teleconnection(PNA)-triggered East Asian ridge,which enhances the precipitation efficiency through prolonged frontal activity and enhanced cold-warm airmass convergence.Overall,El Niño promotes the development of low-and midlatitude AR activity in East Asia,while La Niña promotes(maritime continental)AR activity in the tropics.This study establishes the“ENSO teleconnection→circulation adjust-ment→East Asian AR response”chain,revealing a cross-seasonal lagged response mechanisms of East Asian AR activity,and provides a theoretical basis for winter and spring climate prediction and extreme precipitation forecasting.展开更多
The prediction of sea surface partial pressure of carbon dioxide(pCO_(2))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(pCO_(2))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 pCO_(2)in 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(R^(2))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 R^(2)of 0.994.Feature importance analysis revealed that sea surface pCO_(2)and 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 pCO_(2)with small prediction errors.The ST-ConvLSTM model provides an efficient and accurate tool for forecasting and analyzing sea surface pCO_(2)in 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
Explosive cyclones(ECs) are rapidly intensifying subtropical cyclones that can develop within a short time and pose considerable threats to coastal areas in middle and high latitudes.Gaining a comprehensive understand...Explosive cyclones(ECs) are rapidly intensifying subtropical cyclones that can develop within a short time and pose considerable threats to coastal areas in middle and high latitudes.Gaining a comprehensive understanding of their formation,evolution,and mechanisms of explosive development is essential for improving forecasts of extreme weather events and mitigating associated impacts.Potential vorticity(PV),which is closely related to cyclone dynamics,serves as a valuable diagnostic tool in the study of ECs.In this study,two wintertime ECs of differing intensity over the Northwestern Pacific Ocean are analyzed to examine how different atmospheric processes influence PV generation and the rapid development of ECs.The maximum deepening rates of the two ECs are 2.81 Bergeron(called EC1) and 1.52 Bergeron(referred to as EC2).Results indicate that different stages of EC evolution are closely associated with PV tendency changes at different atmospheric levels.Using the PV tendency equation,during the explosive development of EC1,latent heat release may trigger the downward propagation of upper-level PV.For EC2,latent heat release notably enhances low-level PV,directly contributing to its rapid intensification.To validate these findings,sensitivity tests are conducted using the Weather Research and Forecasting model,with latent heat release turned off in the microphysical scheme for both cases.The results confirm the crucial role of latent heat release in generating low-level PV,further revealing that latent heat release contributes more to the explosive development of EC2 than that of EC1.展开更多
基金supported by a PETRONAS-Academia Collabora-tion Dialogue 2022 Grant[Grant number PACD 2022]from PETRONAS Research Sdn.Bhd。
文摘The atmospheric surface layer of the tropical coastal ocean is commonly very unstable and experiences weakwind conditions.How the latent(LE)and sensible(H)heat fluxes behave under such conditions are unclear because of the lack of observation stations in the tropics.Thus,this study aims to analyze LE and H and the microclimate parameters influencing them.The authors deployed an eddy covariance system in a tropical coastal region for seven months.The microclimate parameters investigated were wind speed(U),vapor pressure deficit(Δe),temperature difference(ΔT),wind-vapor pressure deficit(UΔe),wind-temperature difference(UΔT),and atmospheric stability(z/L),where z is height and L is the Monin–Obukhov length.On the daily time scale,the results show that LE was more associated with U thanΔe,while H was more related toΔT than U.Cross-wavelet analysis revealed the strong coherence in the LE-U relationship for periods between one and two days,and for H–ΔT,0.5 to 1 day.Correlation and regression analyses confirmed the time series analyses results,where strong positive correlation coefficients(r)were obtained between LE and U(r=0.494)and H andΔT(r=0.365).Compared to other water bodies,the transfer coefficient of moisture(CE N)was found to be small(=0.40×10^(-3))and independent of stability;conversely,the transfer coefficient of heat(CH N)was closer to literature values(=1.00×10^(-3))and a function of stability.
文摘基于2002—2025年IRI(International Research Institute for Climate and Society)实时多模式预测资料,构建了一个面向事件的ENSO(El Nino-Southern Oscillation)峰值诊断框架,定量评估预测系统对峰值强度与峰值时间两项关键特征的可预报性。尽管IRI系统在ENSO时间序列上可维持8~9 mon的较高技巧,但传统统计指标难以反映具体事件在峰值阶段的系统性偏差。结果表明,随着预报时效延长,预测的峰值强度普遍减弱,并呈现出显著的强度依赖特征。中等和强事件往往被低估,但弱事件更容易被高估。在模式差异方面,动力模式在再现中、强事件的峰值振幅上更有优势,但在弱事件中,统计模式的预测反而更接近观测。在峰值时间方面,模式预测普遍存在偏晚现象,并且滞后误差会随着预报时效持续累积。峰值时间偏差还呈现明显的冷暖不对称结构,拉尼娜事件的滞后程度显著强于厄尔尼诺事件。在不同模式类型的比较中,统计模式在拉尼娜事件中的峰值时间偏差远大于动力模式,而在厄尔尼诺事件中两类模式的差异相对较小。总体而言,本研究揭示了现有ENSO预测系统在峰值特征上的偏差结构,并指出动力与统计模式的互补性,为改进多模式集合策略和提升ENSO预测性能提供了科学依据。
基金funded by a Project from China Southern Power Grid Company Ltd.(Nos.ZBKJXM20232481 and ZBKJXM20232482)。
文摘This study investigates the distinct impacts of eastern Pacific(EP)and central Pacific(CP)El Niño events on winter shortwave solar radiation(SSR)in southern China,revealing different spatial distributions and underlying mechanisms.The results show that,during the developing winter of EP El Niño,significant SSR reductions occur in southwestern China and the east coast of southern China due to a strong,zonally extended Northwest Pacific anticyclone that transports moisture from the tropical Northwest Pacific and North Indian Ocean,while the northeast of southern China experiences a weak increase in SSR.In contrast,during the developing winter of CP El Niño,SSR decreases in the east of southern China with a significant decrease in the lower basin of the Yangtze River but an increase in the west of southern China with a remarkable increase in eastern Yunnan.The pronounced east-west dipole pattern in SSR anomalies is driven by a meridionally elongated Northwest Pacific anticyclone,which enhances northward moisture transport to the east of southern China while leaving western areas drier.Further research reveals that distinct moisture anomalies during the developing winter of EP and CP events result in divergent SSR distributions across southern China,primarily through modulating the total cloud cover.These findings highlight the critical need to differentiate between El Niño types when predicting medium and long-term variability of radiation in southern China.
文摘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(SO_(2))and sulfate vertical integral(SO_(4))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 National Natural Science Foundation of China[grant number 41830964]the Natural Science Foundation of Hunan Province[grant number 2023JJ40666]。
文摘In this study,based on MERRA-2 reanalysis data and a multi-algorithm integrated atmospheric river(AR)iden-tification method,the authors reveal the cross-seasonal regulation mechanism of El Niño-Southern Oscillation(ENSO)on winter-spring AR activities in East Asia.The results show that ENSO asymmetrically modulates AR ac-tivity through teleconnection and hysteresis effects,and has significant enhancement/inhibition effects on ARs in different regions.At the onset of El Niño,enhanced southwesterly flow at the western edge of the western Pacific subtropical high(WPSH)leads to enhanced AR activity in the western Pacific,and anomalous southerly winds in the Indian Ocean promote northward transport of water vapor in the Arabian Sea and Bay of Bengal.With a three-month lag,the weakening and eastward retreat of the WPSH weakens the low-latitude AR activity,but persistent southerly winds in the Bay of Bengal maintain the AR activity over Southwest China.The mid-to high-latitude AR response exhibits delayed dynamics,initially dominated by the synergistic effect of the southward deviation of the upper-air rapids and the low-level convergence(double-rapid-flow effect)and later modulated by the Pacific-North American teleconnection(PNA)-triggered East Asian ridge,which enhances the precipitation efficiency through prolonged frontal activity and enhanced cold-warm airmass convergence.Overall,El Niño promotes the development of low-and midlatitude AR activity in East Asia,while La Niña promotes(maritime continental)AR activity in the tropics.This study establishes the“ENSO teleconnection→circulation adjust-ment→East Asian AR response”chain,revealing a cross-seasonal lagged response mechanisms of East Asian AR activity,and provides a theoretical basis for winter and spring climate prediction and extreme precipitation forecasting.
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)。
文摘The prediction of sea surface partial pressure of carbon dioxide(pCO_(2))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 pCO_(2)in 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(R^(2))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 R^(2)of 0.994.Feature importance analysis revealed that sea surface pCO_(2)and 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 pCO_(2)with small prediction errors.The ST-ConvLSTM model provides an efficient and accurate tool for forecasting and analyzing sea surface pCO_(2)in 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.
基金financially supported by the National Key R&D Program of China (No. 2022YFC3004204)the National Natural Science Foundation of China (No. 42275001)the Natural Science Foundation of Shandong Province (No. ZR2022MD038)。
文摘Explosive cyclones(ECs) are rapidly intensifying subtropical cyclones that can develop within a short time and pose considerable threats to coastal areas in middle and high latitudes.Gaining a comprehensive understanding of their formation,evolution,and mechanisms of explosive development is essential for improving forecasts of extreme weather events and mitigating associated impacts.Potential vorticity(PV),which is closely related to cyclone dynamics,serves as a valuable diagnostic tool in the study of ECs.In this study,two wintertime ECs of differing intensity over the Northwestern Pacific Ocean are analyzed to examine how different atmospheric processes influence PV generation and the rapid development of ECs.The maximum deepening rates of the two ECs are 2.81 Bergeron(called EC1) and 1.52 Bergeron(referred to as EC2).Results indicate that different stages of EC evolution are closely associated with PV tendency changes at different atmospheric levels.Using the PV tendency equation,during the explosive development of EC1,latent heat release may trigger the downward propagation of upper-level PV.For EC2,latent heat release notably enhances low-level PV,directly contributing to its rapid intensification.To validate these findings,sensitivity tests are conducted using the Weather Research and Forecasting model,with latent heat release turned off in the microphysical scheme for both cases.The results confirm the crucial role of latent heat release in generating low-level PV,further revealing that latent heat release contributes more to the explosive development of EC2 than that of EC1.
