A remarkable marine heatwave,known as the“Blob”,occurred in the Northeast Pacific Ocean from late 2013 to early 2016,which displayed strong warm anomalies extending from the surface to a depth of 300 m.This study em...A remarkable marine heatwave,known as the“Blob”,occurred in the Northeast Pacific Ocean from late 2013 to early 2016,which displayed strong warm anomalies extending from the surface to a depth of 300 m.This study employed two assimilation schemes based on the global Climate Forecast System of Nanjing University of Information Science(NUIST-CFS 1.0)to investigate the impact of ocean data assimilation on the seasonal prediction of this extreme marine heatwave.The sea surface temperature(SST)nudging scheme assimilates SST only,while the deterministic ensemble Kalman filter(EnKF)scheme assimilates observations from the surface to the deep ocean.The latter notably improves the forecasting skill for subsurface temperature anomalies,especially at the depth of 100-300 m(the lower layer),outperforming the SST nudging scheme.It excels in predicting both horizontal and vertical heat transport in the lower layer,contributing to improved forecasts of the lower-layer warming during the Blob.These improvements stem from the assimilation of subsurface observational data,which are important in predicting the upper-ocean conditions.The results suggest that assimilating ocean data with the EnKF scheme significantly enhances the accuracy in predicting subsurface temperature anomalies during the Blob and offers better understanding of its underlying mechanisms.展开更多
Efficient and accurate prediction of ocean surface latent heat fluxes is essential for understanding and modeling climate dynamics.Conventional estimation methods have low resolution and lack accuracy.The transformer ...Efficient and accurate prediction of ocean surface latent heat fluxes is essential for understanding and modeling climate dynamics.Conventional estimation methods have low resolution and lack accuracy.The transformer model,with its self-attention mechanism,effectively captures long-range dependencies,leading to a degradation of accuracy over time.Due to the non-linearity and uncertainty of physical processes,the transformer model encounters the problem of error accumulation,leading to a degradation of accuracy over time.To solve this problem,we combine the Data Assimilation(DA)technique with the transformer model and continuously modify the model state to make it closer to the actual observations.In this paper,we propose a deep learning model called TransNetDA,which integrates transformer,convolutional neural network and DA methods.By combining data-driven and DA methods for spatiotemporal prediction,TransNetDA effectively extracts multi-scale spatial features and significantly improves prediction accuracy.The experimental results indicate that the TransNetDA method surpasses traditional techniques in terms of root mean square error and R2 metrics,showcasing its superior performance in predicting latent heat fluxes at the ocean surface.展开更多
Based on the diurnal consecutively observed data in the offshore area of Jiaonan in 2005, the paper tries to make a preliminary analysis of the specificity of ocean currents, tidal current property and residual curren...Based on the diurnal consecutively observed data in the offshore area of Jiaonan in 2005, the paper tries to make a preliminary analysis of the specificity of ocean currents, tidal current property and residual current property in the area in observing dates. Then on the basis of observed data analysis and by employing the split-step method, the paper conducts a numerical simulation of the tidal current field, which can show the M2 tidal constituent tidal wave system, current ellipse distribution, maximum current velocity distribution and time-dependent current field. The calculated results agree well with the observed data, which can on the one hand reflect the basic specificities of temporal and spatial distribution of the M2 tidal constituent current field to some extent, and, on the other hand, offer more information about the hydrodynamic condition. So the paper would provide a scientific basis for the making of sea environment protection plans in the offshore area of Jiaonan under certain conditions.展开更多
The characters of marine data, such as multi-source, polymorphism, diversity and large amount, determine their differences from other data. How to store and manage marine data rationally and effectively to provide pow...The characters of marine data, such as multi-source, polymorphism, diversity and large amount, determine their differences from other data. How to store and manage marine data rationally and effectively to provide powerful data support for marine management information system and ＂Digital Ocean＂ prototype system construction is an urgent problem to solve. Different types of system planning data, such as marine resource, marine environment, marine econotny and marine management, and establishing marine data architecture frame with uniform standard are to realize the effective management of all level marine data, such as national marine data, the provincial （municipal） marine data, and meet the need of fundamental information-platform construction.展开更多
近些年城市大气污染问题尤为突出,其中PM2.5、PM10等污染物是引起雾霾天气的重要因素.本文基于2007—2016年10年中全国主要城市SO2、NO2、PM10等污染物因子的年平均浓度变化,利用Ocean Data View软件分析主要城市大气污染主控因子(二氧...近些年城市大气污染问题尤为突出,其中PM2.5、PM10等污染物是引起雾霾天气的重要因素.本文基于2007—2016年10年中全国主要城市SO2、NO2、PM10等污染物因子的年平均浓度变化,利用Ocean Data View软件分析主要城市大气污染主控因子(二氧化硫、氮氧化物以及颗粒物)的排放特征及其成因.结果表明:各污染物的区域性分布明显,污染物浓度变化的总体趋势北方高于南方,SO2、NO2、PM10年平均浓度北方分别高于南方108.15%、7.60%、48.36%;从大气污染组分来看,颗粒物的增长速度最快,石家庄2007—2016年PM10增速为28.10%;而SO2的污染物浓度在下降,乌鲁木齐的降速为84.10%.展开更多
This paper reviews the current achievements of the China Argo project. It considers aspects of both the construction of the Argo observing array, float technology, and the quality control and sharing of its data. The ...This paper reviews the current achievements of the China Argo project. It considers aspects of both the construction of the Argo observing array, float technology, and the quality control and sharing of its data. The developments of associated data products and data applications for use in the fields of ocean, atmosphere, and climate research are discussed, particularly those related to tropical cyclones （typhoons）, ocean circulation, mesoscale eddies, turbulence, oceanic heat/salt storage and transportation, water masses, and operational oceanic/atmospheric/climatic forecasts and predictions. Finaliy, the challenges and opportunities involved in the long-term maintenance and sustained development of the China Argo ocean observation network are outlined. Discussion also focuses on the necessity for increasing the number of floats in the Indian Ocean and for expanding the regional Argo observation network in the South China Sea, together with the importance of promoting the use of Argo data by the maritime countries of Southeast Asia and India.展开更多
A large number of autonomous profiling floats deployed in global oceans have provided abundant temperature and salinity profiles of the upper ocean. Many floats occasionally profile observations during the passage of ...A large number of autonomous profiling floats deployed in global oceans have provided abundant temperature and salinity profiles of the upper ocean. Many floats occasionally profile observations during the passage of tropical cyclones. These in-situ observations are valuable and useful in studying the ocean’s response to tropical cyclones, which are rarely observed due to harsh weather conditions. In this paper, the upper ocean response to the tropical cyclones in the northwestern Pacific during 2000–2005 is analyzed and discussed based on the data from Argo profiling floats. Results suggest that the passage of tropical cyclones caused the deepening of mixed layer depth (MLD), cooling of mixed layer temperature (MLT), and freshening of mixed layer salinity (MLS). The change in MLT is negatively correlated to wind speed. The cooling of the MLT extended for 50–150 km on the right side of the cyclone track. The change of MLS is almost symmetrical in distribution on both sides of the track, and the change of MLD is negatively correlated to pre-cyclone initial MLD.展开更多
The development and application of a regional ocean data assimilation system are among the aims of the Global Ocean Data Assimilation Experiment. The ocean data assimilation system in the regions including the Indian ...The development and application of a regional ocean data assimilation system are among the aims of the Global Ocean Data Assimilation Experiment. The ocean data assimilation system in the regions including the Indian and West Pacific oceans is an endeavor motivated by this goal. In this study, we describe the system in detail. Moreover, the reanalysis in the joint area of Asia, the Indian Ocean, and the western Pacific Ocean （hereafter AIPOcean） constructed using multi-year model integration with data assimilation is used to test the performance of this system. The ocean model is an eddy-resolving, hybrid coordinate ocean model. Various types of observations including in-situ temperature and salinity profiles （mechanical bathythermograph, expendable bathythermograph, Array for Real-time Geostrophic Oceanography, Tropical Atmosphere Ocean Array, conductivity-temperature-depth, station data）, remotely-sensed sea surface temperature, and altimetry sea level anomalies, are assimilated into the reanalysis via the ensemble optimal interpolation method. An ensemble of model states sampled from a long-term integration is allowed to change with season, rather than remaining stationary. The estimated background error covariance matrix may reasonably reflect the seasonality and anisotropy. We evaluate the performance of AIPOcean during the period 1993-2006 by comparisons with independent observations, and some reanalysis products. We show that AIPOcean reduces the errors of subsurface temperature and salinity, and reproduces mesoscale eddies. In contrast to ECCO and SODA products, AIPOcean captures the interannual variability and linear trend of sea level anomalies very well. AIPOcean also shows a good consistency with tide gauges.展开更多
In marine seismic exploration, ocean-bottom cable techniques accurately record the multicomponent seismic wavefield; however, the seismic wave propagation in fluid–solid media cannot be simulated by a single wave equ...In marine seismic exploration, ocean-bottom cable techniques accurately record the multicomponent seismic wavefield; however, the seismic wave propagation in fluid–solid media cannot be simulated by a single wave equation. In addition, when the seabed interface is irregular, traditional finite-difference schemes cannot simulate the seismic wave propagation across the irregular seabed interface. Therefore, an acoustic–elastic forward modeling and vector-based P-and S-wave separation method is proposed. In this method, we divide the fluid–solid elastic media with irregular interface into orthogonal grids and map the irregular interface in the Cartesian coordinates system into a horizontal interface in the curvilinear coordinates system of the computational domain using coordinates transformation. The acoustic and elastic wave equations in the curvilinear coordinates system are applied to the fluid and solid medium, respectively. At the irregular interface, the two equations are combined into an acoustic–elastic equation in the curvilinear coordinates system. We next introduce a full staggered-grid scheme to improve the stability of the numerical simulation. Thus, separate P-and S-wave equations in the curvilinear coordinates system are derived to realize the P-and S-wave separation method.展开更多
A new data insertion approach is applied to the Derber and Rosati ocean data assimilation (ODA) system, a system that uses a variational scheme to analyze ocean temperature and provide ocean model corrections continuo...A new data insertion approach is applied to the Derber and Rosati ocean data assimilation (ODA) system, a system that uses a variational scheme to analyze ocean temperature and provide ocean model corrections continuously. Utilizing the same analysis component as the original system, the new approach conducts analyses to derive model corrections intermittently at once-daily intervals. A technique similar to the Incremental Analysis Update (IAU) method of Bloom et al. is applied to incorporate the corrections into the model gradually and continuously. This approach is computationally more economical than the original.A 13-year global ocean analysis from 1986 to 1998 is produced using this new approach and compared with an analysis based on the original one. An examination of both analyses in the tropical Pacific Ocean shows that they have qualitatively similar annual and interannual temperature variability. However, the new approach produces smoother monthly analyses. Moreover, compared to the independent展开更多
A weakly coupled assimilation system, in which SST observations are assimilated into a coupled climate model （CAS- ESM-C） through an ensemble optimal interpolation scheme, was established. This system is a useful to...A weakly coupled assimilation system, in which SST observations are assimilated into a coupled climate model （CAS- ESM-C） through an ensemble optimal interpolation scheme, was established. This system is a useful tool for historical climate simulation, showing substantial advantages, including maintaining the atmospheric feedback, and keeping the oceanic tields from drifting far away from the observation, among others. During the coupled model integration, the bias of both surface and subsurface oceanic fields in the analysis can be reduced compared to unassimilated fields. Based on 30 model years of ot.tput fiom the system, the climatology and imerannual variability of the climate system were evaluated. The results showed that the system can reasonably reproduce the climatological global precipitation and SLP, bul it still sutters from the double ITCZ problem. Besides, the ENSO footprint, which is revealed by ENSO-related surface air temperature, geopotential height and precipitation during El Nifio evolution, is basically reproduced by the system. The system can also simulate the observed SST-rainfall relationships well on both interannual and intraseasonal timescales in the western North Pacific region, in which atmospheric feedback is crucial for climate simulation.展开更多
Methods for studying oceanic circulation from hydrographic data are reviewed in the context of their applications in the South China Sea. These methods can be classified into three types according to their different d...Methods for studying oceanic circulation from hydrographic data are reviewed in the context of their applications in the South China Sea. These methods can be classified into three types according to their different dynamics as follows: (1) descriptive methods, (2) diagnostic methods without surface and bottom forcing, and (3) diagnostic methods with the above boundary forcing. The paper discusses the progress made in the above methods together with the advancement of study in the South China Sea circulation.展开更多
Understanding the ocean＇s role in the global carbon cycle and its response to environmental change requires a high spatio-temporal resolution of observation.Merging ocean color data from multiple sources is an effect...Understanding the ocean＇s role in the global carbon cycle and its response to environmental change requires a high spatio-temporal resolution of observation.Merging ocean color data from multiple sources is an effective way to alleviate the limitation of individual ocean color sensors（e.g.,swath width and gaps,cloudy or rainy weather,and sun glint） and to improve the temporal and spatial coverage.Since the missions of Sea-Viewing Wide Field-of-View Sensor（Sea Wi FS） and Medium-spectral Resolution Imaging Spectrometer（MERIS） ended on December 11,2010 and May 9,2012,respectively,the number of available ocean color sensors has declined,reducing the benefits of the merged ocean color data with respect to the spatial and temporal coverage.In present work,Medium Resolution Spectral Imager（MERSI）/FY-3 of China is added in merged processing and a new dataset of global ocean chlorophyll a（Chl a） concentration（2000–2015） is generated from the remote sensing reflectance（Rrs（λ）） observations of MERIS,Moderate-resolution imaging spectra-radiometer（MODIS）-AQUA,Visible infrared Imaging Radiometer（VIIRS） and MERSI.These data resources are first merged into unified remote sensing reflectance data,and then Chl a concentration data are inversed using the combined Chl a algorithm of color index-based algorithm（CIA） and OC3.The merged data products show major improvements in spatial and temporal coverage from the addition of MERSI.The average daily coverage of merged products is approximately 24% of the global ocean and increases by approximately 9% when MERSI data are added in the merging process.Sampling frequency（temporal coverage） is greatly improved by combining MERSI data,with the median sampling frequency increasing from 15.6%（57 d/a） to 29.9%（109 d/a）.The merged Chl a products herein were validated by in situ measurements and comparing them with the merged products using the same approach except for omitting MERSI and Glob Colour and MEa SUREs merged data.Correlation and relative error between the new merged Chl a products and in situ observation are stable relative to the results of the merged products without the addition of MERSI.Time series of the Chl a concentration anomalies are similar to the merged products without adding MERSI and single sensors.The new merged products agree within approximately 10% of the merged Chl a product from Glob Colour and MEa SUREs.展开更多
It is widely recognized that assessments of the status of data-poor fish stocks are challenging and that Bayesian analysis is one of the methods which can be used to improve the reliability of stock assessments in dat...It is widely recognized that assessments of the status of data-poor fish stocks are challenging and that Bayesian analysis is one of the methods which can be used to improve the reliability of stock assessments in data-poor situations through borrowing strength from prior information deduced from species with good-quality data or other known information. Because there is considerable uncertainty remaining in the stock assessment of albacore tuna（Thunnus alalunga） in the Indian Ocean due to the limited and low-quality data, we investigate the advantages of a Bayesian method in data-poor stock assessment by using Indian Ocean albacore stock assessment as an example. Eight Bayesian biomass dynamics models with different prior assumptions and catch data series were developed to assess the stock. The results show（1） the rationality of choice of catch data series and assumption of parameters could be enhanced by analyzing the posterior distribution of the parameters;（2） the reliability of the stock assessment could be improved by using demographic methods to construct a prior for the intrinsic rate of increase（r）. Because we can make use of more information to improve the rationality of parameter estimation and the reliability of the stock assessment compared with traditional statistical methods by incorporating any available knowledge into the informative priors and analyzing the posterior distribution based on Bayesian framework in data-poor situations, we suggest that the Bayesian method should be an alternative method to be applied in data-poor species stock assessment, such as Indian Ocean albacore.展开更多
A four-dimensional variational data assimilation （4DVar） system of the LASG/IAP Climate Ocean Model, version 1.0 （LICOM1.0）, named LICOM-3DVM, has been developed using the three-dimensional variational data assimi...A four-dimensional variational data assimilation （4DVar） system of the LASG/IAP Climate Ocean Model, version 1.0 （LICOM1.0）, named LICOM-3DVM, has been developed using the three-dimensional variational data assimilation of mapped observation （3DVM）, a 4DVar method newly proposed in the past two years. Two experiments with 12-year model integrations were designed to validate it. One is the assimilation run, called ASSM, which incorporated the analyzed weekly sea surface temperature （SST） fields from Reynolds and Smith （OISST） between 1990 and 2001 once a week by the LICOM-3DVM. The other is the control run without any assimilation, named CTL. ASSM shows that the simulated temperatures of the upper ocean （above 50 meters）, especially the SST of equatorial Pacific, coincide with the Tropic Atmosphere Ocean （TAO） mooring data, the World Ocean Atlas 2001 （WOA01） data and the Met Office Hadley Centre＇s sea ice and sea surface temperature （HadISST） data. It decreased the cold bias existing in CTL in the eastern Pacific and produced a Nifio index that agrees with observation well. The validation results suggest that the LICOM-3DVM is able to effectively adjust the model results of the ocean temperature, although it＇s hard to correct the subsurface results and it even makes them worse in some areas due to the incorporation of only surface data. Future development of the LICOM-3DVM is to include subsurface in situ observations and satellite observations to further improve model simulations.展开更多
The quality of regional ocean reanalysis data for ＂the joining area of Asia and the Indian-Pacific Ocean （AIPO）＂ has been assessed from the perspective of ENSO-related ocean signals. The results derived from the A...The quality of regional ocean reanalysis data for ＂the joining area of Asia and the Indian-Pacific Ocean （AIPO）＂ has been assessed from the perspective of ENSO-related ocean signals. The results derived from the AIPO reanalysis, including SST, sea surface height （SSH）, and subsurface ocean temperature and currents, are compared with those of Hadley Center Sea Ice and Sea Surface Temperature （HadlSST） data set and Simple Ocean Data Assimilation （SODA） reanalysis data. Both the spatial pattern and the characteristics of evolution of the ENSO-related ocean temperature anomalies are well reproduced by the AIPO reanalysis data. The physical processes proposed to explain the life cycle of ENSO, including the delayed oscillator mechanism, recharge-discharge mechanism, and the zonal advection feedback, are reasonably represented in this dataset. However, the westward Rossby wave signal in 1992 is not obvious in the AIPO data, and the magnitude of the heat content anomalies is different from that of the SODA data. The reason for the discrepancies may lie in the different mod- els and methods for data assimilation and differences in wind stress forcing. The results demonstrate the high reliability of the AIPO reanalysis data in describing ENSO signals, implying its potential application value in ENSO- related studies.展开更多
In marine seismic exploration,ocean bottom cable technology can record multicomponent seismic data for multiparameter inversion and imaging.This study proposes an elastic multiparameter lease-squares reverse time migr...In marine seismic exploration,ocean bottom cable technology can record multicomponent seismic data for multiparameter inversion and imaging.This study proposes an elastic multiparameter lease-squares reverse time migration based on the ocean bottom cable technology.Herein,the wavefield continuation operators are mixed equations:the acoustic wave equations are used to calculate seismic wave propagation in the seawater medium,whereas in the solid media below the seabed,the wavefields are obtained by P-and S-wave separated vector elastic wave equations.At the seabed interface,acoustic–elastic coupling control equations are used to combine the two types of equations.P-and S-wave separated elastic migration operators,demigration operators,and gradient equations are derived to realize the elastic least-squares reverse time migration based on the P-and S-wave mode separation.The model tests verify that the proposed method can obtain high-quality images in both the P-and S-velocity components.In comparison with the traditional elastic least-squares reverse time migration method,the proposed method can readily suppress imaging crosstalk noise from multiparameter coupling.展开更多
An ensemble optimal interpolation(EnOI)data assimilation method is applied in the BCCCSM1.1 to investigate the impact of ocean data assimilations on seasonal forecasts in an idealized twin experiment framework.Pseudoo...An ensemble optimal interpolation(EnOI)data assimilation method is applied in the BCCCSM1.1 to investigate the impact of ocean data assimilations on seasonal forecasts in an idealized twin experiment framework.Pseudoobservations of sea surface temperature(SST),sea surface height(SSH),sea surface salinity(SSS),temperature and salinity(T/S)profiles were first generated in a free model run.Then,a series of sensitivity tests initialized with predefined bias were conducted for a one-year period;this involved a free run(CTR)and seven assimilation runs.These tests allowed us to check the analysis field accuracy against the"truth".As expected,data assimilation improved all investigated quantities;the joint assimilation of all variables gave more improved results than assimilating them separately.One-year predictions initialized from the seven runs and CTR were then conducted and compared.The forecasts initialized from joint assimilation of surface data produced comparable SST root mean square errors to that from assimilation of T/S profiles,but the assimilation of T/S profiles is crucial to reduce subsurface deficiencies.The ocean surface currents in the tropics were better predicted when initial conditions produced by assimilating T/S profiles,while surface data assimilation became more important at higher latitudes,particularly near the western boundary currents.The predictions of ocean heat content and mixed layer depth are significantly improved initialized from the joint assimilation of all the variables.Finally,a central Pacific El Ni?o was well predicted from the joint assimilation of surface data,indicating the importance of joint assimilation of SST,SSH,and SSS for ENSO predictions.展开更多
The first version of the Brazilian Oceano- graphic Modeling and Observation Network （REMO） ocean data assimilation system into the Hybrid Coordi- nate Ocean Model （HYCOM） （RODAS H） has recently been constructed ...The first version of the Brazilian Oceano- graphic Modeling and Observation Network （REMO） ocean data assimilation system into the Hybrid Coordi- nate Ocean Model （HYCOM） （RODAS H） has recently been constructed for research and operational purposes. The system is based on a multivariate Ensemble Optimal Interpolation （EnOI） scheme and considers the high fre- quency variability of the model error co-variance matrix. The EnOl can assimilate sea surface temperature （SST）, satellite along-track and gridded sea level anomalies （SLA）, and vertical profiles of temperature （T） and salinity （S） from Argo. The first observing system experiment was carried out over the Atlantic Ocean （78°S-50°N, 100°W-20°E） with HYCOM forced with atmospheric reanalysis from 1 January to 30 June 2010. Five integra- tions were performed, including the control run without assimilation. In the other four, different observations were assimilated： SST only （A SST）; Argo T-S profiles only （AArgo）; along-track SLA only （A_SLA）; and all data employed in the previous runs （A_All）. The A_SST, A_Argo, and A_SLA runs were very effective in improv- ing the representation of the assimilated variables, but they had relatively little impact on the variables that were not assimilated. In particular, only the assimilation of S was able to reduce the deviation of S with respect to ob- servations. Overall, the A_All run produced a good analy- sis by reducing the deviation of SST, T, and S with respect to the control run by 39%, 18%, and 30%, respectively, and by increasing the correlation of SLA by 81%.展开更多
For sequential performance of wave variational data assimilation, we proposed a temporal sliding method in which the temporal overlap is considered. The advantage of this method is that the initial wave spectrum of th...For sequential performance of wave variational data assimilation, we proposed a temporal sliding method in which the temporal overlap is considered. The advantage of this method is that the initial wave spectrum of the optimization process is modified by the observations in latter and former times. This temporal sliding procedure is important for marginal region, such as the China seas, where the duration of assimilation effectiveness is 2-3 days. Experiments were performed in the whole course of Cyclone 9403 （Russ）. Around the cyclone center, the maximum value of wave elements did not change much by assimilation, because the extreme value was determined by wind energy input that was not yet optimized. In the area outside the cyclone center, this modification is evident especially for wind wave growth.展开更多
基金supported by the National Natural Science Foundation of China [grant number 42030605]the National Key R&D Program of China [grant number 2020YFA0608004]。
文摘A remarkable marine heatwave,known as the“Blob”,occurred in the Northeast Pacific Ocean from late 2013 to early 2016,which displayed strong warm anomalies extending from the surface to a depth of 300 m.This study employed two assimilation schemes based on the global Climate Forecast System of Nanjing University of Information Science(NUIST-CFS 1.0)to investigate the impact of ocean data assimilation on the seasonal prediction of this extreme marine heatwave.The sea surface temperature(SST)nudging scheme assimilates SST only,while the deterministic ensemble Kalman filter(EnKF)scheme assimilates observations from the surface to the deep ocean.The latter notably improves the forecasting skill for subsurface temperature anomalies,especially at the depth of 100-300 m(the lower layer),outperforming the SST nudging scheme.It excels in predicting both horizontal and vertical heat transport in the lower layer,contributing to improved forecasts of the lower-layer warming during the Blob.These improvements stem from the assimilation of subsurface observational data,which are important in predicting the upper-ocean conditions.The results suggest that assimilating ocean data with the EnKF scheme significantly enhances the accuracy in predicting subsurface temperature anomalies during the Blob and offers better understanding of its underlying mechanisms.
基金The National Natural Science Foundation of China under contract Nos 42176011 and 61931025the Fundamental Research Funds for the Central Universities of China under contract No.24CX03001A.
文摘Efficient and accurate prediction of ocean surface latent heat fluxes is essential for understanding and modeling climate dynamics.Conventional estimation methods have low resolution and lack accuracy.The transformer model,with its self-attention mechanism,effectively captures long-range dependencies,leading to a degradation of accuracy over time.Due to the non-linearity and uncertainty of physical processes,the transformer model encounters the problem of error accumulation,leading to a degradation of accuracy over time.To solve this problem,we combine the Data Assimilation(DA)technique with the transformer model and continuously modify the model state to make it closer to the actual observations.In this paper,we propose a deep learning model called TransNetDA,which integrates transformer,convolutional neural network and DA methods.By combining data-driven and DA methods for spatiotemporal prediction,TransNetDA effectively extracts multi-scale spatial features and significantly improves prediction accuracy.The experimental results indicate that the TransNetDA method surpasses traditional techniques in terms of root mean square error and R2 metrics,showcasing its superior performance in predicting latent heat fluxes at the ocean surface.
文摘Based on the diurnal consecutively observed data in the offshore area of Jiaonan in 2005, the paper tries to make a preliminary analysis of the specificity of ocean currents, tidal current property and residual current property in the area in observing dates. Then on the basis of observed data analysis and by employing the split-step method, the paper conducts a numerical simulation of the tidal current field, which can show the M2 tidal constituent tidal wave system, current ellipse distribution, maximum current velocity distribution and time-dependent current field. The calculated results agree well with the observed data, which can on the one hand reflect the basic specificities of temporal and spatial distribution of the M2 tidal constituent current field to some extent, and, on the other hand, offer more information about the hydrodynamic condition. So the paper would provide a scientific basis for the making of sea environment protection plans in the offshore area of Jiaonan under certain conditions.
文摘The characters of marine data, such as multi-source, polymorphism, diversity and large amount, determine their differences from other data. How to store and manage marine data rationally and effectively to provide powerful data support for marine management information system and ＂Digital Ocean＂ prototype system construction is an urgent problem to solve. Different types of system planning data, such as marine resource, marine environment, marine econotny and marine management, and establishing marine data architecture frame with uniform standard are to realize the effective management of all level marine data, such as national marine data, the provincial （municipal） marine data, and meet the need of fundamental information-platform construction.
文摘近些年城市大气污染问题尤为突出,其中PM2.5、PM10等污染物是引起雾霾天气的重要因素.本文基于2007—2016年10年中全国主要城市SO2、NO2、PM10等污染物因子的年平均浓度变化,利用Ocean Data View软件分析主要城市大气污染主控因子(二氧化硫、氮氧化物以及颗粒物)的排放特征及其成因.结果表明:各污染物的区域性分布明显,污染物浓度变化的总体趋势北方高于南方,SO2、NO2、PM10年平均浓度北方分别高于南方108.15%、7.60%、48.36%;从大气污染组分来看,颗粒物的增长速度最快,石家庄2007—2016年PM10增速为28.10%;而SO2的污染物浓度在下降,乌鲁木齐的降速为84.10%.
基金The National Natural Science Foundation under contract No.41621064the Science and Technology Basic Work of the Ministry of Science and Technology of China under contract No.2012FY112300the Public Science and Technology Research Funds Projects of Ocean under contract No.201005033
文摘This paper reviews the current achievements of the China Argo project. It considers aspects of both the construction of the Argo observing array, float technology, and the quality control and sharing of its data. The developments of associated data products and data applications for use in the fields of ocean, atmosphere, and climate research are discussed, particularly those related to tropical cyclones （typhoons）, ocean circulation, mesoscale eddies, turbulence, oceanic heat/salt storage and transportation, water masses, and operational oceanic/atmospheric/climatic forecasts and predictions. Finaliy, the challenges and opportunities involved in the long-term maintenance and sustained development of the China Argo ocean observation network are outlined. Discussion also focuses on the necessity for increasing the number of floats in the Indian Ocean and for expanding the regional Argo observation network in the South China Sea, together with the importance of promoting the use of Argo data by the maritime countries of Southeast Asia and India.
基金the Ministry of Science and Technology of China (No.2002CB714001 and 2001CCB00200)the Youth Fund of State Oceanic Administration (No. 2004203)
文摘A large number of autonomous profiling floats deployed in global oceans have provided abundant temperature and salinity profiles of the upper ocean. Many floats occasionally profile observations during the passage of tropical cyclones. These in-situ observations are valuable and useful in studying the ocean’s response to tropical cyclones, which are rarely observed due to harsh weather conditions. In this paper, the upper ocean response to the tropical cyclones in the northwestern Pacific during 2000–2005 is analyzed and discussed based on the data from Argo profiling floats. Results suggest that the passage of tropical cyclones caused the deepening of mixed layer depth (MLD), cooling of mixed layer temperature (MLT), and freshening of mixed layer salinity (MLS). The change in MLT is negatively correlated to wind speed. The cooling of the MLT extended for 50–150 km on the right side of the cyclone track. The change of MLS is almost symmetrical in distribution on both sides of the track, and the change of MLD is negatively correlated to pre-cyclone initial MLD.
基金supported by the 973 Program (Grant No.2010CB950401)the Chinese Academy of Sciences’ Project"Western Pacific Ocean System:Structure,Dynamics and Consequences"(Grant No.XDA11010405)the National Natural Science Foundation of China (Grant No.41176015)
文摘The development and application of a regional ocean data assimilation system are among the aims of the Global Ocean Data Assimilation Experiment. The ocean data assimilation system in the regions including the Indian and West Pacific oceans is an endeavor motivated by this goal. In this study, we describe the system in detail. Moreover, the reanalysis in the joint area of Asia, the Indian Ocean, and the western Pacific Ocean （hereafter AIPOcean） constructed using multi-year model integration with data assimilation is used to test the performance of this system. The ocean model is an eddy-resolving, hybrid coordinate ocean model. Various types of observations including in-situ temperature and salinity profiles （mechanical bathythermograph, expendable bathythermograph, Array for Real-time Geostrophic Oceanography, Tropical Atmosphere Ocean Array, conductivity-temperature-depth, station data）, remotely-sensed sea surface temperature, and altimetry sea level anomalies, are assimilated into the reanalysis via the ensemble optimal interpolation method. An ensemble of model states sampled from a long-term integration is allowed to change with season, rather than remaining stationary. The estimated background error covariance matrix may reasonably reflect the seasonality and anisotropy. We evaluate the performance of AIPOcean during the period 1993-2006 by comparisons with independent observations, and some reanalysis products. We show that AIPOcean reduces the errors of subsurface temperature and salinity, and reproduces mesoscale eddies. In contrast to ECCO and SODA products, AIPOcean captures the interannual variability and linear trend of sea level anomalies very well. AIPOcean also shows a good consistency with tide gauges.
基金financially supported by the Natural Science Foundation of China(No.41774133)the Open Funds of SINOPEC Key Laboratory of Geophysics(No.wtyjy-wx2017-01-04)National Science and Technology Major Project of the Ministry of Science and Technology of China(No.2016ZX05024-003-011)
文摘In marine seismic exploration, ocean-bottom cable techniques accurately record the multicomponent seismic wavefield; however, the seismic wave propagation in fluid–solid media cannot be simulated by a single wave equation. In addition, when the seabed interface is irregular, traditional finite-difference schemes cannot simulate the seismic wave propagation across the irregular seabed interface. Therefore, an acoustic–elastic forward modeling and vector-based P-and S-wave separation method is proposed. In this method, we divide the fluid–solid elastic media with irregular interface into orthogonal grids and map the irregular interface in the Cartesian coordinates system into a horizontal interface in the curvilinear coordinates system of the computational domain using coordinates transformation. The acoustic and elastic wave equations in the curvilinear coordinates system are applied to the fluid and solid medium, respectively. At the irregular interface, the two equations are combined into an acoustic–elastic equation in the curvilinear coordinates system. We next introduce a full staggered-grid scheme to improve the stability of the numerical simulation. Thus, separate P-and S-wave equations in the curvilinear coordinates system are derived to realize the P-and S-wave separation method.
基金This research was supported bythe National Science Foundation (ATM-9321354) and the National Oceanic and Atmospheric Administration (NA46-GP0217), and computing resources were provided by the National Center for Atmospheric Research Scientific Computin
文摘A new data insertion approach is applied to the Derber and Rosati ocean data assimilation (ODA) system, a system that uses a variational scheme to analyze ocean temperature and provide ocean model corrections continuously. Utilizing the same analysis component as the original system, the new approach conducts analyses to derive model corrections intermittently at once-daily intervals. A technique similar to the Incremental Analysis Update (IAU) method of Bloom et al. is applied to incorporate the corrections into the model gradually and continuously. This approach is computationally more economical than the original.A 13-year global ocean analysis from 1986 to 1998 is produced using this new approach and compared with an analysis based on the original one. An examination of both analyses in the tropical Pacific Ocean shows that they have qualitatively similar annual and interannual temperature variability. However, the new approach produces smoother monthly analyses. Moreover, compared to the independent
基金supported by the China Postdoctoral Science Foundation(Grant No.2015M571095)the Chinese Academy of Sciences Project“Western Pacific Ocean System:Structure,Dynamics and Consequences”(Grant No.XDA10010405)
文摘A weakly coupled assimilation system, in which SST observations are assimilated into a coupled climate model （CAS- ESM-C） through an ensemble optimal interpolation scheme, was established. This system is a useful tool for historical climate simulation, showing substantial advantages, including maintaining the atmospheric feedback, and keeping the oceanic tields from drifting far away from the observation, among others. During the coupled model integration, the bias of both surface and subsurface oceanic fields in the analysis can be reduced compared to unassimilated fields. Based on 30 model years of ot.tput fiom the system, the climatology and imerannual variability of the climate system were evaluated. The results showed that the system can reasonably reproduce the climatological global precipitation and SLP, bul it still sutters from the double ITCZ problem. Besides, the ENSO footprint, which is revealed by ENSO-related surface air temperature, geopotential height and precipitation during El Nifio evolution, is basically reproduced by the system. The system can also simulate the observed SST-rainfall relationships well on both interannual and intraseasonal timescales in the western North Pacific region, in which atmospheric feedback is crucial for climate simulation.
基金supported by the National key program for Derelop-ing Basic Sciences(G 1999043805 and G19999043810)the National Natural Science Foundation of China(Grant No.40076009)the Chinese Academny of Sciences(KZCX1-SW-01-16).
文摘Methods for studying oceanic circulation from hydrographic data are reviewed in the context of their applications in the South China Sea. These methods can be classified into three types according to their different dynamics as follows: (1) descriptive methods, (2) diagnostic methods without surface and bottom forcing, and (3) diagnostic methods with the above boundary forcing. The paper discusses the progress made in the above methods together with the advancement of study in the South China Sea circulation.
基金The National Key R&D Program of China under contract No.2016YFA0600102the National Natural Science Foundation of China under contract Nos 41506203,41476159,41506204,41606197,41471303 and 41706209the Cooperation Project of FIO and KOIST under contract No.PI-2017-03
文摘Understanding the ocean＇s role in the global carbon cycle and its response to environmental change requires a high spatio-temporal resolution of observation.Merging ocean color data from multiple sources is an effective way to alleviate the limitation of individual ocean color sensors（e.g.,swath width and gaps,cloudy or rainy weather,and sun glint） and to improve the temporal and spatial coverage.Since the missions of Sea-Viewing Wide Field-of-View Sensor（Sea Wi FS） and Medium-spectral Resolution Imaging Spectrometer（MERIS） ended on December 11,2010 and May 9,2012,respectively,the number of available ocean color sensors has declined,reducing the benefits of the merged ocean color data with respect to the spatial and temporal coverage.In present work,Medium Resolution Spectral Imager（MERSI）/FY-3 of China is added in merged processing and a new dataset of global ocean chlorophyll a（Chl a） concentration（2000–2015） is generated from the remote sensing reflectance（Rrs（λ）） observations of MERIS,Moderate-resolution imaging spectra-radiometer（MODIS）-AQUA,Visible infrared Imaging Radiometer（VIIRS） and MERSI.These data resources are first merged into unified remote sensing reflectance data,and then Chl a concentration data are inversed using the combined Chl a algorithm of color index-based algorithm（CIA） and OC3.The merged data products show major improvements in spatial and temporal coverage from the addition of MERSI.The average daily coverage of merged products is approximately 24% of the global ocean and increases by approximately 9% when MERSI data are added in the merging process.Sampling frequency（temporal coverage） is greatly improved by combining MERSI data,with the median sampling frequency increasing from 15.6%（57 d/a） to 29.9%（109 d/a）.The merged Chl a products herein were validated by in situ measurements and comparing them with the merged products using the same approach except for omitting MERSI and Glob Colour and MEa SUREs merged data.Correlation and relative error between the new merged Chl a products and in situ observation are stable relative to the results of the merged products without the addition of MERSI.Time series of the Chl a concentration anomalies are similar to the merged products without adding MERSI and single sensors.The new merged products agree within approximately 10% of the merged Chl a product from Glob Colour and MEa SUREs.
基金The Innovation Program of Shanghai Municipal Education Commission under contract No.14ZZ147the Opening Project of Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources(Shanghai Ocean University),Ministry of Education under contract No.A1-0209-15-0503-1
文摘It is widely recognized that assessments of the status of data-poor fish stocks are challenging and that Bayesian analysis is one of the methods which can be used to improve the reliability of stock assessments in data-poor situations through borrowing strength from prior information deduced from species with good-quality data or other known information. Because there is considerable uncertainty remaining in the stock assessment of albacore tuna（Thunnus alalunga） in the Indian Ocean due to the limited and low-quality data, we investigate the advantages of a Bayesian method in data-poor stock assessment by using Indian Ocean albacore stock assessment as an example. Eight Bayesian biomass dynamics models with different prior assumptions and catch data series were developed to assess the stock. The results show（1） the rationality of choice of catch data series and assumption of parameters could be enhanced by analyzing the posterior distribution of the parameters;（2） the reliability of the stock assessment could be improved by using demographic methods to construct a prior for the intrinsic rate of increase（r）. Because we can make use of more information to improve the rationality of parameter estimation and the reliability of the stock assessment compared with traditional statistical methods by incorporating any available knowledge into the informative priors and analyzing the posterior distribution based on Bayesian framework in data-poor situations, we suggest that the Bayesian method should be an alternative method to be applied in data-poor species stock assessment, such as Indian Ocean albacore.
基金Acknowledgements. The authors would like to thank Mr. R. W. Reynolds for providing the guess error variance of the OISST data. All computations of this work were completed on IAP1801 computer. This work was supported jointly by the Key Direction Project of the Chinese Academy of Sciences Knowledge Innovation Program （Grant No. KZCX-SW-230）, the 973 Project （Grant No. 2005CB321703）, and the National Natural Science Foundation of China （Grant No. 40221503）.
文摘A four-dimensional variational data assimilation （4DVar） system of the LASG/IAP Climate Ocean Model, version 1.0 （LICOM1.0）, named LICOM-3DVM, has been developed using the three-dimensional variational data assimilation of mapped observation （3DVM）, a 4DVar method newly proposed in the past two years. Two experiments with 12-year model integrations were designed to validate it. One is the assimilation run, called ASSM, which incorporated the analyzed weekly sea surface temperature （SST） fields from Reynolds and Smith （OISST） between 1990 and 2001 once a week by the LICOM-3DVM. The other is the control run without any assimilation, named CTL. ASSM shows that the simulated temperatures of the upper ocean （above 50 meters）, especially the SST of equatorial Pacific, coincide with the Tropic Atmosphere Ocean （TAO） mooring data, the World Ocean Atlas 2001 （WOA01） data and the Met Office Hadley Centre＇s sea ice and sea surface temperature （HadISST） data. It decreased the cold bias existing in CTL in the eastern Pacific and produced a Nifio index that agrees with observation well. The validation results suggest that the LICOM-3DVM is able to effectively adjust the model results of the ocean temperature, although it＇s hard to correct the subsurface results and it even makes them worse in some areas due to the incorporation of only surface data. Future development of the LICOM-3DVM is to include subsurface in situ observations and satellite observations to further improve model simulations.
基金supported by the Knowledge Innovation Program of the Chinese Academy of Sciences (Grant No. KZCX2-YW-Q11-04)the Public Science and Technology Research Funds Projects of Ocean (Grant No. 201105019-3)the National Basic Research Program of China (Grant No. 2010CB951904)
文摘The quality of regional ocean reanalysis data for ＂the joining area of Asia and the Indian-Pacific Ocean （AIPO）＂ has been assessed from the perspective of ENSO-related ocean signals. The results derived from the AIPO reanalysis, including SST, sea surface height （SSH）, and subsurface ocean temperature and currents, are compared with those of Hadley Center Sea Ice and Sea Surface Temperature （HadlSST） data set and Simple Ocean Data Assimilation （SODA） reanalysis data. Both the spatial pattern and the characteristics of evolution of the ENSO-related ocean temperature anomalies are well reproduced by the AIPO reanalysis data. The physical processes proposed to explain the life cycle of ENSO, including the delayed oscillator mechanism, recharge-discharge mechanism, and the zonal advection feedback, are reasonably represented in this dataset. However, the westward Rossby wave signal in 1992 is not obvious in the AIPO data, and the magnitude of the heat content anomalies is different from that of the SODA data. The reason for the discrepancies may lie in the different mod- els and methods for data assimilation and differences in wind stress forcing. The results demonstrate the high reliability of the AIPO reanalysis data in describing ENSO signals, implying its potential application value in ENSO- related studies.
基金supported by National Natural Science Foundation of China(Nos.41904101,41774133)Natural Science Foundation of Shandong Province(ZR2019QD004)+1 种基金Fundamental Research Funds for the Central Universities(No.19CX02010A)the Open Funds of SINOPEC Key Laboratory of Geophysics(Nos.wtyjy-wx2019-01-03,wtyjywx2018-01-06)
文摘In marine seismic exploration,ocean bottom cable technology can record multicomponent seismic data for multiparameter inversion and imaging.This study proposes an elastic multiparameter lease-squares reverse time migration based on the ocean bottom cable technology.Herein,the wavefield continuation operators are mixed equations:the acoustic wave equations are used to calculate seismic wave propagation in the seawater medium,whereas in the solid media below the seabed,the wavefields are obtained by P-and S-wave separated vector elastic wave equations.At the seabed interface,acoustic–elastic coupling control equations are used to combine the two types of equations.P-and S-wave separated elastic migration operators,demigration operators,and gradient equations are derived to realize the elastic least-squares reverse time migration based on the P-and S-wave mode separation.The model tests verify that the proposed method can obtain high-quality images in both the P-and S-velocity components.In comparison with the traditional elastic least-squares reverse time migration method,the proposed method can readily suppress imaging crosstalk noise from multiparameter coupling.
基金The National Key Research and Development Program of China under contract Nos 2016YFA0602102 and2016YFC1401702the Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory(Guangzhou)under contract No.GML2019ZD0306+1 种基金the National Natural Science Foundation of China under contract No.41306005CAS Pioneer Hundred Talents Program Startup Fund by South China Sea Institute of Oceanology under contract No.Y9SL011001。
文摘An ensemble optimal interpolation(EnOI)data assimilation method is applied in the BCCCSM1.1 to investigate the impact of ocean data assimilations on seasonal forecasts in an idealized twin experiment framework.Pseudoobservations of sea surface temperature(SST),sea surface height(SSH),sea surface salinity(SSS),temperature and salinity(T/S)profiles were first generated in a free model run.Then,a series of sensitivity tests initialized with predefined bias were conducted for a one-year period;this involved a free run(CTR)and seven assimilation runs.These tests allowed us to check the analysis field accuracy against the"truth".As expected,data assimilation improved all investigated quantities;the joint assimilation of all variables gave more improved results than assimilating them separately.One-year predictions initialized from the seven runs and CTR were then conducted and compared.The forecasts initialized from joint assimilation of surface data produced comparable SST root mean square errors to that from assimilation of T/S profiles,but the assimilation of T/S profiles is crucial to reduce subsurface deficiencies.The ocean surface currents in the tropics were better predicted when initial conditions produced by assimilating T/S profiles,while surface data assimilation became more important at higher latitudes,particularly near the western boundary currents.The predictions of ocean heat content and mixed layer depth are significantly improved initialized from the joint assimilation of all the variables.Finally,a central Pacific El Ni?o was well predicted from the joint assimilation of surface data,indicating the importance of joint assimilation of SST,SSH,and SSS for ENSO predictions.
基金financially supported by the Brazilian State oil company Petróleo Brasileiro S. A. (Petrobras) and Agência Nacional de Petróleo (ANP), Gás Natural e Biocombustíveis, Brazil, via the Oceanographic Modeling and Observation Network (REMO)support of the Coordenao de Aperfeioamento de Pessoal de Nível Superior (CAPES), Ministry of Education of Brazil (Proc. BEX 3957/13-6)
文摘The first version of the Brazilian Oceano- graphic Modeling and Observation Network （REMO） ocean data assimilation system into the Hybrid Coordi- nate Ocean Model （HYCOM） （RODAS H） has recently been constructed for research and operational purposes. The system is based on a multivariate Ensemble Optimal Interpolation （EnOI） scheme and considers the high fre- quency variability of the model error co-variance matrix. The EnOl can assimilate sea surface temperature （SST）, satellite along-track and gridded sea level anomalies （SLA）, and vertical profiles of temperature （T） and salinity （S） from Argo. The first observing system experiment was carried out over the Atlantic Ocean （78°S-50°N, 100°W-20°E） with HYCOM forced with atmospheric reanalysis from 1 January to 30 June 2010. Five integra- tions were performed, including the control run without assimilation. In the other four, different observations were assimilated： SST only （A SST）; Argo T-S profiles only （AArgo）; along-track SLA only （A_SLA）; and all data employed in the previous runs （A_All）. The A_SST, A_Argo, and A_SLA runs were very effective in improv- ing the representation of the assimilated variables, but they had relatively little impact on the variables that were not assimilated. In particular, only the assimilation of S was able to reduce the deviation of S with respect to ob- servations. Overall, the A_All run produced a good analy- sis by reducing the deviation of SST, T, and S with respect to the control run by 39%, 18%, and 30%, respectively, and by increasing the correlation of SLA by 81%.
基金Supported by the High-Tech Research and Development Program of China (863 Program, No. 2001AA633070 2003AA604040)Na- tional Natural Science Foundation of China (No. 40206003).
文摘For sequential performance of wave variational data assimilation, we proposed a temporal sliding method in which the temporal overlap is considered. The advantage of this method is that the initial wave spectrum of the optimization process is modified by the observations in latter and former times. This temporal sliding procedure is important for marginal region, such as the China seas, where the duration of assimilation effectiveness is 2-3 days. Experiments were performed in the whole course of Cyclone 9403 （Russ）. Around the cyclone center, the maximum value of wave elements did not change much by assimilation, because the extreme value was determined by wind energy input that was not yet optimized. In the area outside the cyclone center, this modification is evident especially for wind wave growth.
