The El Niño-Southern Oscillation (ENSO) is a significant climate phenomenon with far-reaching impacts on global weather patterns, ecosystems, and economies. This study aims to enhance ENSO forecasting with the Ex...The El Niño-Southern Oscillation (ENSO) is a significant climate phenomenon with far-reaching impacts on global weather patterns, ecosystems, and economies. This study aims to enhance ENSO forecasting with the Extended Reconstruction Sea Surface Temperature v5 (ERSSTv5) climate model. The M-band discrete wavelet transforms (DWT) are utilized to capture multi-scale temporal and spatial features effectively. Long-short term memory (LSTM) autoencoders are also used to capture significant spatial and temporal patterns in sea surface temperature (SST) anomaly data. Deep learning techniques such as the convolutional neural networks (CNN) are used with non-image and image time series data. We also employ parallel computing in a various support vector regression (SVR) approximators to enhance accuracy. Preliminary results indicate that this hybrid model effectively identifies key precursors and patterns associated with El Niño events, surpassing traditional forecasting methods. Results of the hybrid model produce a correlation of 0.93 in 4-month lagged forecasting of the Oceanic Niño Index (ONI)—indicative of high success rate of the model. Future work will focus on evaluating the model’s performance using additional reanalysis datasets and other methods of deep learning to further refine its robustness and applicability. We propose wavelet-based deep learning models which have potential to shine a light on achieving United Nations’ 2030 Agenda for Sustainable Development’s goal 13: “Climate Action”, as an innovation with potential in improving time series image forecasting in all fields.展开更多
The El Nifio-Southern Oscillation （ENSO） is an interannual phenomenon involved in the tropical Pacific Oceanatmosphere interactions. In this paper, an asymptotic method of solving the nonlinear equation for the ENSO...The El Nifio-Southern Oscillation （ENSO） is an interannual phenomenon involved in the tropical Pacific Oceanatmosphere interactions. In this paper, an asymptotic method of solving the nonlinear equation for the ENSO model is used. And based on a class of oscillator of ENSO model, the approximate solution of a corresponding problem is studied by employing the perturbation method. Firstly, an ENSO model of nonlinear time delay equation of equatorial Pacific is introduced, Secondly, by using the perturbed method, the zeroth and first order asymptotic perturbed solutions are constructed. Finally, from the comparison of the values for a figure, it is seen that the first asymptotic perturbed solution using the perturbation method has a good accuracy. And it is proved from the results that the perturbation method can be used as an analytic operation for the sea surface temperature anomaly in the equatorial Pacific of the atmosphere-ocean oscillation for the ENSO model.展开更多
The Indonesian Throughflow(ITF)plays important roles in global ocean circulation and climate systems.Previous studies suggested the ITF interannual variability is driven by both the El Niño-Southern Oscillation(E...The Indonesian Throughflow(ITF)plays important roles in global ocean circulation and climate systems.Previous studies suggested the ITF interannual variability is driven by both the El Niño-Southern Oscillation(ENSO)and the Indian Ocean Dipole(IOD)events.The detailed processes of ENSO and/or IOD induced anomalies impacting on the ITF,however,are still not clear.In this study,this issue is investigated through causal relation,statistical,and dynamical analyses based on satellite observation.The results show that the driven mechanisms of ENSO on the ITF include two aspects.Firstly,the ENSO related wind field anomalies driven anomalous cyclonic ocean circulation in the western Pacific,and off equatorial upwelling Rossby waves propagating westward to arrive at the western boundary of the Pacific,both tend to induce negative sea surface height anomalies(SSHA)in the western Pacific,favoring ITF reduction since the develop of the El Niño through the following year.Secondly,the ENSO events modulate equatorial Indian Ocean zonal winds through Walker Circulation,which in turn trigger eastward propagating upwelling Kelvin waves and westward propagating downwelling Rossby waves.The Rossby waves are reflected into downwelling Kelvin waves,which then propagate eastward along the equator and the Sumatra-Java coast in the Indian Ocean.As a result,the wave dynamics tend to generate negative(positive)SSHA in the eastern Indian Ocean,and thus enhance(reduce)the ITF transport with time lag of 0-6 months(9-12 months),respectively.Under the IOD condition,the wave dynamics also tend to enhance the ITF in the positive IOD year,and reduce the ITF in the following year.展开更多
Owing to the complexity of droughts,detailed assessments of drought events have become a key issue in water resource management and planning.In this study,three-dimensional copula models at Standard Precipitation Evap...Owing to the complexity of droughts,detailed assessments of drought events have become a key issue in water resource management and planning.In this study,three-dimensional copula models at Standard Precipitation Evapotranspiration Index(SPEI)-1,SPEI-3,SPEI-6,and SPEI-12 were used to assess drought risks in the Haihe River Basin(HRB)of China from 1961–2020.Drought duration,severity,and peak,as indicated by SPEI,were extracted based on run theory and fitted with suitable marginal distributions.The difference between the joint return period(Tor)and the co-occurrence return period(Tand)could explain the intrinsic correlation between drought characteristics.The smaller the difference,the stronger the correlation.The results showed that droughts in the north-western region of the HRB were characterized by high peak,intense severity,and long duration.In contrast,the eastern region exhibited a higher frequency of drought occurrence.Furthermore,the decreasing trend in precipitation dominated droughts,and topography of the northwest region creates the features of low annual precipitation with more days of precipitation.The drought events in the HRB were influenced by the phase shift between El Niño and La Niña.There was a strong negative phase coupling between SPEI-12 and Niño3.4(R^(2)≥0.77).The transition from La Niña to El Niño was responsible for severe droughts in the HRB.The El Niño-Southern Oscillation could predict droughts with lag times of 0.15–4.35 mon in mountainous areas.展开更多
El Niño-Southern Oscillation(ENSO)affects the changes in ocean physical elements in Taiwan Strait(TWS)primarily by regulating the strength of the East Asian Winter Monsoon(EAWM)and the intrusion of the Kuroshio.A...El Niño-Southern Oscillation(ENSO)affects the changes in ocean physical elements in Taiwan Strait(TWS)primarily by regulating the strength of the East Asian Winter Monsoon(EAWM)and the intrusion of the Kuroshio.Additionally,the fluctuating impact between nutrient-poor seawater with high dissolved inorganic carbon(DIC)that infiltrates owing to the Kuroshio during El Niño phases and nutrient-rich seawater with low DIC from the South China Sea(SCS)carried by the EAWM during La Niña phases determines the nutrient content in TWS,thereby sculpting appropriate or unsuitable biochemical environment.In this study,based on high-resolution sea-surface partial pressure of carbon dioxide(pCO_(2))data,we investigate the relationship between pCO_(2)level of TWS and ENSO events in winter.The physical mechanisms affecting the anomalous distribution of pCO_(2)level during ENSO are also explored.Stepwise regression was employed to identify the optimal influencing factors for modeling pCO_(2).Results indicate a significant positive correlation between Niño3.4 index and pCO_(2),which is significantly influenced by factors such as sea-surface temperature(SST),chlorophyll-a(Chl a),and DIC.These are related to the anomalously strong Kuroshio intrusion and weaker EAWM during El Niño years.It brings a large amount of high SST water with low nutrient concentration and high DIC,which is detrimental to CO_(2)dissolution and phytoplankton growth over the TWS,leading to an increase in pCO_(2).Conversely,pCO_(2)level is significantly low under the influence of SCS seawater during La Niña years.Based on the characterization of the pCO_(2)level response to ENSO,the carbon balance at TWS can be explored.展开更多
Internal solitary waves(ISWs)have considerable energy to drive the mixing of water masses in the Sulu Sea.The propagation speed is one of the critical parameters in quantifying the energy budget of the ISWs.We collect...Internal solitary waves(ISWs)have considerable energy to drive the mixing of water masses in the Sulu Sea.The propagation speed is one of the critical parameters in quantifying the energy budget of the ISWs.We collected 1354 groups of ISWs’speeds from tandem satellite remote sensing images with temporal intervals shorter than 25 min and analyzed their spatial and multi-scale temporal variations in the Sulu Sea.We found that water depth plays an important role in modulating the spatial variation of wave speeds,which increase exponentially with water depth with a power of 0.26.Tidal currents,ocean stratification,background circulation,and climate affect the temporal variations of wave speeds from days to months or years.The fortnightly spring/neap tidal currents cause daily variations of wave speeds up to 40%by modulating the ISW amplitudes.In addition to the well-accepted results that monthly variations of wave speeds are related to density stratification,we found that enhanced stratification increases wave speeds,and the background circulation leads to a maximum decrease of 0.27 m/s in the linear counterparts of wave speed.Moreover,the averaged wave speed collected in October is lower than the corresponding linear one possibly due to some unknown dynamical processes or underestimation of background current.As for the interannual variations,we show that wave speed increases in La Niña years and decreases in El Niño years as a result of the climatic modulation on the depth of the maximum value of buoyancy frequency.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
Understanding the catch composition of multispecies fisheries is fundamental to effective spatial fishery management.In the Equatorial Western and Central Pacific Ocean(EWCPO),the main catches of the tuna purse-seine ...Understanding the catch composition of multispecies fisheries is fundamental to effective spatial fishery management.In the Equatorial Western and Central Pacific Ocean(EWCPO),the main catches of the tuna purse-seine fishery include skipjack tuna(Katsuwonus pelamis),yellowfin tuna(Thunnus albacares),and bigeye tuna(Thunnus obesus).Studying the spatiotemporal distribution of the catch composition in the context of climate change contributes to the sustainable development of this fishery.Our study analyzed purse seine fishery data and environmental data from 1997 to 2019,using a random forest model to explore the changing mechanisms of catch composition under different El Niño-Southern Oscillation(ENSO)episodes with catch mean trophic level(CMTL)as the response variable.Emerging hot spot analysis was used to identify significant spatiotemporal hot(cold)spot areas.The results revealed two hot spot areas,namely the western hotspot area(WHA)and the eastern hotspot area(EHA),and two cold spot areas,namely the northern cold spot area(NCA)and the southern cold spot area(SCA).EHA spans the entire central Pacific east of 170°E among different ENSO episodes,expanding and contracting in tandem with the 28℃isotherm.WHA is mainly influenced by surface organic matter and the Western Boundary Currents and remains among different ENSO episodes.NCA is formed by the westerly anomalies and positive wind stress curl anomalies and exists only under La Niña episodes.SCA persists within the unproductive South Equatorial Current(SEC)and remains stable among different ENSO episodes.Our study contributes to revealing the spatiotemporal dynamics in tuna catch composition and their relationships with environmental factors and interspecies competition,providing valuable insights for ecosystem-based dynamic fishery management.展开更多
In this study,we conducted an experiment to construct multi-model ensemble(MME)predictions for the El Niño-Southern Oscillation(ENSO)using a neural network,based on hindcast data released from five coupled oceana...In this study,we conducted an experiment to construct multi-model ensemble(MME)predictions for the El Niño-Southern Oscillation(ENSO)using a neural network,based on hindcast data released from five coupled oceanatmosphere models,which exhibit varying levels of complexity.This nonlinear approach demonstrated extraordinary superiority and effectiveness in constructing ENSO MME.Subsequently,we employed the leave-one-out crossvalidation and the moving base methods to further validate the robustness of the neural network model in the formulation of ENSO MME.In conclusion,the neural network algorithm outperforms the conventional approach of assigning a uniform weight to all models.This is evidenced by an enhancement in correlation coefficients and reduction in prediction errors,which have the potential to provide a more accurate ENSO forecast.展开更多
The Jin-Neelin model for the El Nio–Southern Oscillation(ENSO for short) is considered for which the authors establish existence and uniqueness of global solutions in time over an unbounded channel domain. The resu...The Jin-Neelin model for the El Nio–Southern Oscillation(ENSO for short) is considered for which the authors establish existence and uniqueness of global solutions in time over an unbounded channel domain. The result is proved for initial data and forcing that are sufficiently small. The smallness conditions involve in particular key physical parameters of the model such as those that control the travel time of the equatorial waves and the strength of feedback due to vertical-shear currents and upwelling; central mechanisms in ENSO dynamics.From the mathematical view point, the system appears as the coupling of a linear shallow water system and a nonlinear heat equation. Because of the very different nature of the two components of the system, the authors find it convenient to prove the existence of solution by semi-discretization in time and utilization of a fractional step scheme. The main idea consists of handling the coupling between the oceanic and temperature components by dividing the time interval into small sub-intervals of length k and on each sub-interval to solve successively the oceanic component, using the temperature T calculated on the previous sub-interval, to then solve the sea-surface temperature(SST for short) equation on the current sub-interval. The passage to the limit as k tends to zero is ensured via a priori estimates derived under the aforementioned smallness conditions.展开更多
Climate models are vital for understanding and projecting global climate change and its associated impacts.However,these models suffer from biases that limit their accuracy in historical simulations and the trustworth...Climate models are vital for understanding and projecting global climate change and its associated impacts.However,these models suffer from biases that limit their accuracy in historical simulations and the trustworthiness of future projections.Addressing these challenges requires addressing internal variability,hindering the direct alignment between model simulations and observations,and thwarting conventional supervised learning methods.Here,we employ an unsupervised Cycle-consistent Generative Adversarial Network(CycleGAN),to correct daily Sea Surface Temperature(SST)simulations from the Community Earth System Model 2(CESM2).Our results reveal that the CycleGAN not only corrects climatological biases but also improves the simulation of major dynamic modes including the El Niño-Southern Oscillation(ENSO)and the Indian Ocean Dipole mode,as well as SST extremes.Notably,it substantially corrects climatological SST biases,decreasing the globally averaged Root-Mean-Square Error(RMSE)by 58%.Intriguingly,the CycleGAN effectively addresses the well-known excessive westward bias in ENSO SST anomalies,a common issue in climate models that traditional methods,like quantile mapping,struggle to rectify.Additionally,it substantially improves the simulation of SST extremes,raising the pattern correlation coefficient(PCC)from 0.56 to 0.88 and lowering the RMSE from 0.5 to 0.32.This enhancement is attributed to better representations of interannual,intraseasonal,and synoptic scales variabilities.Our study offers a novel approach to correct global SST simulations and underscores its effectiveness across different time scales and primary dynamical modes.展开更多
The Indonesian Throughflow(ITF), which connects the tropical Pacific and Indian oceans, plays important roles in the inter-ocean water exchange and regional or even global climate variability. The Makassar Strait is t...The Indonesian Throughflow(ITF), which connects the tropical Pacific and Indian oceans, plays important roles in the inter-ocean water exchange and regional or even global climate variability. The Makassar Strait is the main inflow passage of the ITF, carrying about 77% of the total ITF volume transport. In this study, we analyze the simulated ITF in the Makassar Strait in the Simple Ocean Data Assimilation version 3(SODA3) datasets. A total of nine ensemble members of the SODA3 datasets, of which are driven by different surface forcings and bulk formulas, and with or without data assimilation, are used in this study. The annual mean water transports(i.e.,volume, heat and freshwater) are related to the combination of surface forcing and bulk formula, as well as whether data assimilation is employed. The phases of the seasonal and interannual variability in water transports cross the Makassar Strait, are basically consistent with each other among the SODA3 ensemble members. The interannual variability in Makassar Strait volume and heat transports are significantly correlated with El Ni?oSouthern Oscillation(ENSO) at time lags of-6 to 7 months. There is no statistically significant correlation between the freshwater transport and the ENSO. The Makassar Strait water transports are not significantly correlated with the Indian Ocean Dipole(IOD), which may attribute to model deficiency in simulating the propagation of semiannual Kelvin waves from the Indian Ocean to the Makassar Strait.展开更多
The subtropical North and South Pacific Meridional Modes(NPMM and SPMM)are well known precursors of El Niño-Southern Oscillation(ENSO).However,relationship between them is not constant.In the early 1980,the relat...The subtropical North and South Pacific Meridional Modes(NPMM and SPMM)are well known precursors of El Niño-Southern Oscillation(ENSO).However,relationship between them is not constant.In the early 1980,the relationship experienced an interdecadal transition.Changes in this connection can be attributed mainly to the phase change of the Pacific decadal oscillation(PDO).During the positive phase of PDO,a shallower thermocline in the central Pacific is responsible for the stronger trade wind charging(TWC)mechanism,which leads to a stronger equatorial subsurface temperature evolution.This dynamic process strengthens the connection between NPMM and ENSO.Associated with the negative phase of PDO,a shallower thermocline over southeastern Pacific allows an enhanced wind-evaporation-SST(WES)feedback,strengthening the connection between SPMM and ENSO.Using 35 Coupled Model Intercomparison Project Phase 6(CMIP6)models,we examined the NPMM/SPMM performance and its connection with ENSO in the historical runs.The great majority of CMIP6 models can reproduce the pattern of NPMM and SPMM well,but they reveal discrepant ENSO and NPMM/SPMM relationship.The intermodal uncertainty for the connection of NPMM-ENSO is due to different TWC mechanism.A stronger TWC mechanism will enhance NPMM forcing.For SPMM,few models can simulate a good relationship with ENSO.The intermodel spread in the relationship of SPMM and ENSO owing to SST bias in the southeastern Pacific,as WES feedback is stronger when the southeastern Pacific is warmer.展开更多
A 110-year ensemble simulation of an ocean general circulation model(OGCM)was analyzed to identify the modulation of salinity interdecadal variability on El Niño-Southern Oscillation(ENSO)amplitude in the tropica...A 110-year ensemble simulation of an ocean general circulation model(OGCM)was analyzed to identify the modulation of salinity interdecadal variability on El Niño-Southern Oscillation(ENSO)amplitude in the tropical Pacific during 1901-2010.The simulating results show that sea surface salinity(SSS)variation in the region exhibits notable and coherent interdecadal variability signal,which is closely associated with the Interdecadal Pacific Oscillation(IPO).As salinity increases or reduces,the SSS modulations on ENSO amplitude during its warm/cold events vary asymmetrically with positive/negative IPO phases.Physically,salinity interdecadal variability can enhance or reduce ENSO-related conditions in upper-ocean stratification,contributing noticeably to ENSO variability.Salinity anomalies associated with the mixed layer depth and barrier layer thickness can modulate ENSO amplitude during positive and negative IPO phases,resulting in the asymmetry of sea surface temperature(SST)anomaly in the tropical Pacific.During positive IPO phases,SSS interdecadal variability contributes positively to El Niño amplitude but negatively to La Niña amplitude by enhancing or reducing SSS interannual variability,and vice versa during negative IPO phases.Quantitatively,the results indicate that the modulation of the ENSO amplitude by the SSS interdecadal variability is 15%-28%during negative IPO phases and 30%-20%during positive IPO phases,respectively.Evidently,the SSS interdecadal variability associated with IPO and its modulation on ENSO amplitude in the tropical Pacific are among factors essentially contributing ENSO diversity.展开更多
文摘The El Niño-Southern Oscillation (ENSO) is a significant climate phenomenon with far-reaching impacts on global weather patterns, ecosystems, and economies. This study aims to enhance ENSO forecasting with the Extended Reconstruction Sea Surface Temperature v5 (ERSSTv5) climate model. The M-band discrete wavelet transforms (DWT) are utilized to capture multi-scale temporal and spatial features effectively. Long-short term memory (LSTM) autoencoders are also used to capture significant spatial and temporal patterns in sea surface temperature (SST) anomaly data. Deep learning techniques such as the convolutional neural networks (CNN) are used with non-image and image time series data. We also employ parallel computing in a various support vector regression (SVR) approximators to enhance accuracy. Preliminary results indicate that this hybrid model effectively identifies key precursors and patterns associated with El Niño events, surpassing traditional forecasting methods. Results of the hybrid model produce a correlation of 0.93 in 4-month lagged forecasting of the Oceanic Niño Index (ONI)—indicative of high success rate of the model. Future work will focus on evaluating the model’s performance using additional reanalysis datasets and other methods of deep learning to further refine its robustness and applicability. We propose wavelet-based deep learning models which have potential to shine a light on achieving United Nations’ 2030 Agenda for Sustainable Development’s goal 13: “Climate Action”, as an innovation with potential in improving time series image forecasting in all fields.
基金Project supported by the National Natural Science Foundation of China (Grant Nos 40676016 and 10471039)the State KeyProgram for Basic Research of China (Grant Nos 2003CB415101-03 and 2004CB418304)+2 种基金the Key Project of the Chinese Academy of Sciences (Grant No KZCX3-SW-221)in partly by E-Institutes of Shanghai Municipal Education Commission (Grant NoN.E03004)the Natural Science Foundation of Zhejiang Province,China (Grant No Y606268)
文摘The El Nifio-Southern Oscillation （ENSO） is an interannual phenomenon involved in the tropical Pacific Oceanatmosphere interactions. In this paper, an asymptotic method of solving the nonlinear equation for the ENSO model is used. And based on a class of oscillator of ENSO model, the approximate solution of a corresponding problem is studied by employing the perturbation method. Firstly, an ENSO model of nonlinear time delay equation of equatorial Pacific is introduced, Secondly, by using the perturbed method, the zeroth and first order asymptotic perturbed solutions are constructed. Finally, from the comparison of the values for a figure, it is seen that the first asymptotic perturbed solution using the perturbation method has a good accuracy. And it is proved from the results that the perturbation method can be used as an analytic operation for the sea surface temperature anomaly in the equatorial Pacific of the atmosphere-ocean oscillation for the ENSO model.
基金The Fund of Laoshan Laboratory under contract No.LSKJ202202700the Basic Scientific Fund for National Public Research Institutes of China under contract No.2024Q02+1 种基金the National Natural Science Foundation of China under contract Nos 42076023 and 42430402the Global Change and Air-Sea InteractionⅡProject under contract No.GASI-01-ATP-STwin.
文摘The Indonesian Throughflow(ITF)plays important roles in global ocean circulation and climate systems.Previous studies suggested the ITF interannual variability is driven by both the El Niño-Southern Oscillation(ENSO)and the Indian Ocean Dipole(IOD)events.The detailed processes of ENSO and/or IOD induced anomalies impacting on the ITF,however,are still not clear.In this study,this issue is investigated through causal relation,statistical,and dynamical analyses based on satellite observation.The results show that the driven mechanisms of ENSO on the ITF include two aspects.Firstly,the ENSO related wind field anomalies driven anomalous cyclonic ocean circulation in the western Pacific,and off equatorial upwelling Rossby waves propagating westward to arrive at the western boundary of the Pacific,both tend to induce negative sea surface height anomalies(SSHA)in the western Pacific,favoring ITF reduction since the develop of the El Niño through the following year.Secondly,the ENSO events modulate equatorial Indian Ocean zonal winds through Walker Circulation,which in turn trigger eastward propagating upwelling Kelvin waves and westward propagating downwelling Rossby waves.The Rossby waves are reflected into downwelling Kelvin waves,which then propagate eastward along the equator and the Sumatra-Java coast in the Indian Ocean.As a result,the wave dynamics tend to generate negative(positive)SSHA in the eastern Indian Ocean,and thus enhance(reduce)the ITF transport with time lag of 0-6 months(9-12 months),respectively.Under the IOD condition,the wave dynamics also tend to enhance the ITF in the positive IOD year,and reduce the ITF in the following year.
基金Under the auspices of the Shandong Provincial Natural Science Foundation(No.ZR2024ME171,ZR2024QD207)the National Natural Science Foundation of China(No.41471160,42377077)。
文摘Owing to the complexity of droughts,detailed assessments of drought events have become a key issue in water resource management and planning.In this study,three-dimensional copula models at Standard Precipitation Evapotranspiration Index(SPEI)-1,SPEI-3,SPEI-6,and SPEI-12 were used to assess drought risks in the Haihe River Basin(HRB)of China from 1961–2020.Drought duration,severity,and peak,as indicated by SPEI,were extracted based on run theory and fitted with suitable marginal distributions.The difference between the joint return period(Tor)and the co-occurrence return period(Tand)could explain the intrinsic correlation between drought characteristics.The smaller the difference,the stronger the correlation.The results showed that droughts in the north-western region of the HRB were characterized by high peak,intense severity,and long duration.In contrast,the eastern region exhibited a higher frequency of drought occurrence.Furthermore,the decreasing trend in precipitation dominated droughts,and topography of the northwest region creates the features of low annual precipitation with more days of precipitation.The drought events in the HRB were influenced by the phase shift between El Niño and La Niña.There was a strong negative phase coupling between SPEI-12 and Niño3.4(R^(2)≥0.77).The transition from La Niña to El Niño was responsible for severe droughts in the HRB.The El Niño-Southern Oscillation could predict droughts with lag times of 0.15–4.35 mon in mountainous areas.
基金The Key R&D Project of Zhejiang Province under contract No.2023C03120the General Scientific Research Project of Zhejiang Province under contract No.Y202353957the National Natural Science Foundation of China under contract No.42106017.
文摘El Niño-Southern Oscillation(ENSO)affects the changes in ocean physical elements in Taiwan Strait(TWS)primarily by regulating the strength of the East Asian Winter Monsoon(EAWM)and the intrusion of the Kuroshio.Additionally,the fluctuating impact between nutrient-poor seawater with high dissolved inorganic carbon(DIC)that infiltrates owing to the Kuroshio during El Niño phases and nutrient-rich seawater with low DIC from the South China Sea(SCS)carried by the EAWM during La Niña phases determines the nutrient content in TWS,thereby sculpting appropriate or unsuitable biochemical environment.In this study,based on high-resolution sea-surface partial pressure of carbon dioxide(pCO_(2))data,we investigate the relationship between pCO_(2)level of TWS and ENSO events in winter.The physical mechanisms affecting the anomalous distribution of pCO_(2)level during ENSO are also explored.Stepwise regression was employed to identify the optimal influencing factors for modeling pCO_(2).Results indicate a significant positive correlation between Niño3.4 index and pCO_(2),which is significantly influenced by factors such as sea-surface temperature(SST),chlorophyll-a(Chl a),and DIC.These are related to the anomalously strong Kuroshio intrusion and weaker EAWM during El Niño years.It brings a large amount of high SST water with low nutrient concentration and high DIC,which is detrimental to CO_(2)dissolution and phytoplankton growth over the TWS,leading to an increase in pCO_(2).Conversely,pCO_(2)level is significantly low under the influence of SCS seawater during La Niña years.Based on the characterization of the pCO_(2)level response to ENSO,the carbon balance at TWS can be explored.
基金Supported by the National Natural Science Foundation of China(Nos.U23A2032,42006193)supported by the Hainan Provincial Excellent Talent Team Project(Space Observation of Deep-sea)。
文摘Internal solitary waves(ISWs)have considerable energy to drive the mixing of water masses in the Sulu Sea.The propagation speed is one of the critical parameters in quantifying the energy budget of the ISWs.We collected 1354 groups of ISWs’speeds from tandem satellite remote sensing images with temporal intervals shorter than 25 min and analyzed their spatial and multi-scale temporal variations in the Sulu Sea.We found that water depth plays an important role in modulating the spatial variation of wave speeds,which increase exponentially with water depth with a power of 0.26.Tidal currents,ocean stratification,background circulation,and climate affect the temporal variations of wave speeds from days to months or years.The fortnightly spring/neap tidal currents cause daily variations of wave speeds up to 40%by modulating the ISW amplitudes.In addition to the well-accepted results that monthly variations of wave speeds are related to density stratification,we found that enhanced stratification increases wave speeds,and the background circulation leads to a maximum decrease of 0.27 m/s in the linear counterparts of wave speed.Moreover,the averaged wave speed collected in October is lower than the corresponding linear one possibly due to some unknown dynamical processes or underestimation of background current.As for the interannual variations,we show that wave speed increases in La Niña years and decreases in El Niño years as a result of the climatic modulation on the depth of the maximum value of buoyancy frequency.
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)。
文摘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.
基金The National Key Research and Development Program of China under contract No.2023YFD2401303.
文摘Understanding the catch composition of multispecies fisheries is fundamental to effective spatial fishery management.In the Equatorial Western and Central Pacific Ocean(EWCPO),the main catches of the tuna purse-seine fishery include skipjack tuna(Katsuwonus pelamis),yellowfin tuna(Thunnus albacares),and bigeye tuna(Thunnus obesus).Studying the spatiotemporal distribution of the catch composition in the context of climate change contributes to the sustainable development of this fishery.Our study analyzed purse seine fishery data and environmental data from 1997 to 2019,using a random forest model to explore the changing mechanisms of catch composition under different El Niño-Southern Oscillation(ENSO)episodes with catch mean trophic level(CMTL)as the response variable.Emerging hot spot analysis was used to identify significant spatiotemporal hot(cold)spot areas.The results revealed two hot spot areas,namely the western hotspot area(WHA)and the eastern hotspot area(EHA),and two cold spot areas,namely the northern cold spot area(NCA)and the southern cold spot area(SCA).EHA spans the entire central Pacific east of 170°E among different ENSO episodes,expanding and contracting in tandem with the 28℃isotherm.WHA is mainly influenced by surface organic matter and the Western Boundary Currents and remains among different ENSO episodes.NCA is formed by the westerly anomalies and positive wind stress curl anomalies and exists only under La Niña episodes.SCA persists within the unproductive South Equatorial Current(SEC)and remains stable among different ENSO episodes.Our study contributes to revealing the spatiotemporal dynamics in tuna catch composition and their relationships with environmental factors and interspecies competition,providing valuable insights for ecosystem-based dynamic fishery management.
基金The fund from Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)under contract No.SML2021SP310the National Natural Science Foundation of China under contract Nos 42227901 and 42475061the Key R&D Program of Zhejiang Province under contract No.2024C03257.
文摘In this study,we conducted an experiment to construct multi-model ensemble(MME)predictions for the El Niño-Southern Oscillation(ENSO)using a neural network,based on hindcast data released from five coupled oceanatmosphere models,which exhibit varying levels of complexity.This nonlinear approach demonstrated extraordinary superiority and effectiveness in constructing ENSO MME.Subsequently,we employed the leave-one-out crossvalidation and the moving base methods to further validate the robustness of the neural network model in the formulation of ENSO MME.In conclusion,the neural network algorithm outperforms the conventional approach of assigning a uniform weight to all models.This is evidenced by an enhancement in correlation coefficients and reduction in prediction errors,which have the potential to provide a more accurate ENSO forecast.
基金supported by the Office of Naval Research Multidisciplinary University Research Initiative(No.N00014-16-1-2073)the National Science Foundation(Nos.OCE-1658357,DMS-1616981,DMS-1206438,DMS-1510249)the Research Fund of Indiana University
文摘The Jin-Neelin model for the El Nio–Southern Oscillation(ENSO for short) is considered for which the authors establish existence and uniqueness of global solutions in time over an unbounded channel domain. The result is proved for initial data and forcing that are sufficiently small. The smallness conditions involve in particular key physical parameters of the model such as those that control the travel time of the equatorial waves and the strength of feedback due to vertical-shear currents and upwelling; central mechanisms in ENSO dynamics.From the mathematical view point, the system appears as the coupling of a linear shallow water system and a nonlinear heat equation. Because of the very different nature of the two components of the system, the authors find it convenient to prove the existence of solution by semi-discretization in time and utilization of a fractional step scheme. The main idea consists of handling the coupling between the oceanic and temperature components by dividing the time interval into small sub-intervals of length k and on each sub-interval to solve successively the oceanic component, using the temperature T calculated on the previous sub-interval, to then solve the sea-surface temperature(SST for short) equation on the current sub-interval. The passage to the limit as k tends to zero is ensured via a priori estimates derived under the aforementioned smallness conditions.
基金supported by the National Natural Science Foundation of China(Grant Nos.42141019 and 42261144687)the Second Tibetan Plateau Scientific Expedition and Research(STEP)program(Grant No.2019QZKK0102)+4 种基金the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB42010404)the National Natural Science Foundation of China(Grant No.42175049)the Guangdong Meteorological Service Science and Technology Research Project(Grant No.GRMC2021M01)the National Key Scientific and Technological Infrastructure project“Earth System Science Numerical Simulator Facility”(EarthLab)for computational support and Prof.Shiming XIANG for many useful discussionsNiklas BOERS acknowledges funding from the Volkswagen foundation.
文摘Climate models are vital for understanding and projecting global climate change and its associated impacts.However,these models suffer from biases that limit their accuracy in historical simulations and the trustworthiness of future projections.Addressing these challenges requires addressing internal variability,hindering the direct alignment between model simulations and observations,and thwarting conventional supervised learning methods.Here,we employ an unsupervised Cycle-consistent Generative Adversarial Network(CycleGAN),to correct daily Sea Surface Temperature(SST)simulations from the Community Earth System Model 2(CESM2).Our results reveal that the CycleGAN not only corrects climatological biases but also improves the simulation of major dynamic modes including the El Niño-Southern Oscillation(ENSO)and the Indian Ocean Dipole mode,as well as SST extremes.Notably,it substantially corrects climatological SST biases,decreasing the globally averaged Root-Mean-Square Error(RMSE)by 58%.Intriguingly,the CycleGAN effectively addresses the well-known excessive westward bias in ENSO SST anomalies,a common issue in climate models that traditional methods,like quantile mapping,struggle to rectify.Additionally,it substantially improves the simulation of SST extremes,raising the pattern correlation coefficient(PCC)from 0.56 to 0.88 and lowering the RMSE from 0.5 to 0.32.This enhancement is attributed to better representations of interannual,intraseasonal,and synoptic scales variabilities.Our study offers a novel approach to correct global SST simulations and underscores its effectiveness across different time scales and primary dynamical modes.
基金The Fund of Laoshan Laboratory under contract No. LSKJ202202700the National Natural Science Foundation of China under contract Nos 42076023, 42076024 and 41876027the Global Change and Air-Sea Interaction Ⅱ Project under contract No.GASI-01-AIP-STwin。
文摘The Indonesian Throughflow(ITF), which connects the tropical Pacific and Indian oceans, plays important roles in the inter-ocean water exchange and regional or even global climate variability. The Makassar Strait is the main inflow passage of the ITF, carrying about 77% of the total ITF volume transport. In this study, we analyze the simulated ITF in the Makassar Strait in the Simple Ocean Data Assimilation version 3(SODA3) datasets. A total of nine ensemble members of the SODA3 datasets, of which are driven by different surface forcings and bulk formulas, and with or without data assimilation, are used in this study. The annual mean water transports(i.e.,volume, heat and freshwater) are related to the combination of surface forcing and bulk formula, as well as whether data assimilation is employed. The phases of the seasonal and interannual variability in water transports cross the Makassar Strait, are basically consistent with each other among the SODA3 ensemble members. The interannual variability in Makassar Strait volume and heat transports are significantly correlated with El Ni?oSouthern Oscillation(ENSO) at time lags of-6 to 7 months. There is no statistically significant correlation between the freshwater transport and the ENSO. The Makassar Strait water transports are not significantly correlated with the Indian Ocean Dipole(IOD), which may attribute to model deficiency in simulating the propagation of semiannual Kelvin waves from the Indian Ocean to the Makassar Strait.
基金Supported by the National Natural Science Foundation of China(NSFC)(No.41976027)。
文摘The subtropical North and South Pacific Meridional Modes(NPMM and SPMM)are well known precursors of El Niño-Southern Oscillation(ENSO).However,relationship between them is not constant.In the early 1980,the relationship experienced an interdecadal transition.Changes in this connection can be attributed mainly to the phase change of the Pacific decadal oscillation(PDO).During the positive phase of PDO,a shallower thermocline in the central Pacific is responsible for the stronger trade wind charging(TWC)mechanism,which leads to a stronger equatorial subsurface temperature evolution.This dynamic process strengthens the connection between NPMM and ENSO.Associated with the negative phase of PDO,a shallower thermocline over southeastern Pacific allows an enhanced wind-evaporation-SST(WES)feedback,strengthening the connection between SPMM and ENSO.Using 35 Coupled Model Intercomparison Project Phase 6(CMIP6)models,we examined the NPMM/SPMM performance and its connection with ENSO in the historical runs.The great majority of CMIP6 models can reproduce the pattern of NPMM and SPMM well,but they reveal discrepant ENSO and NPMM/SPMM relationship.The intermodal uncertainty for the connection of NPMM-ENSO is due to different TWC mechanism.A stronger TWC mechanism will enhance NPMM forcing.For SPMM,few models can simulate a good relationship with ENSO.The intermodel spread in the relationship of SPMM and ENSO owing to SST bias in the southeastern Pacific,as WES feedback is stronger when the southeastern Pacific is warmer.
基金Supported by the National Natural Science Foundation of China(No.42030410)the Laoshan Laboratory(No.LSKJ 202202403)supported by the Startup Foundation for Introducing Talent of NUIST。
文摘A 110-year ensemble simulation of an ocean general circulation model(OGCM)was analyzed to identify the modulation of salinity interdecadal variability on El Niño-Southern Oscillation(ENSO)amplitude in the tropical Pacific during 1901-2010.The simulating results show that sea surface salinity(SSS)variation in the region exhibits notable and coherent interdecadal variability signal,which is closely associated with the Interdecadal Pacific Oscillation(IPO).As salinity increases or reduces,the SSS modulations on ENSO amplitude during its warm/cold events vary asymmetrically with positive/negative IPO phases.Physically,salinity interdecadal variability can enhance or reduce ENSO-related conditions in upper-ocean stratification,contributing noticeably to ENSO variability.Salinity anomalies associated with the mixed layer depth and barrier layer thickness can modulate ENSO amplitude during positive and negative IPO phases,resulting in the asymmetry of sea surface temperature(SST)anomaly in the tropical Pacific.During positive IPO phases,SSS interdecadal variability contributes positively to El Niño amplitude but negatively to La Niña amplitude by enhancing or reducing SSS interannual variability,and vice versa during negative IPO phases.Quantitatively,the results indicate that the modulation of the ENSO amplitude by the SSS interdecadal variability is 15%-28%during negative IPO phases and 30%-20%during positive IPO phases,respectively.Evidently,the SSS interdecadal variability associated with IPO and its modulation on ENSO amplitude in the tropical Pacific are among factors essentially contributing ENSO diversity.
