Impacts of Ice-Ocean Stress on the Subpolar Southern Ocean:Role of the Ocean Surface Current

The mechanical influences involved in the interaction between the Antarctic sea ice and ocean surface current(OSC)on the subpolar Southern Ocean have been systematically investigated for the first time by conducting two simulations that include and exclude the OSC in the calculation of the ice-ocean stress(IOS), using an eddy-permitting coupled ocean-sea ice global model. By comparing the results of these two experiments, significant increases of 5%, 27%, and 24%, were found in the subpolar Southern Ocean when excluding the OSC in the IOS calculation for the ocean surface stress,upwelling, and downwelling, respectively. Excluding the OSC in the IOS calculation also visibly strengthens the total mechanical energy input to the OSC by about 16%, and increases the eddy kinetic energy and mean kinetic energy by about38% and 12%, respectively. Moreover, the response of the meridional overturning circulation in the Southern Ocean yields respective increases of about 16% and 15% for the upper and lower branches;and the subpolar gyres are also found to considerably intensify, by about 12%, 11%, and 11% in the Weddell Gyre, the Ross Gyre, and the Australian-Antarctic Gyre, respectively. The strengthened ocean circulations and Ekman pumping result in a warmer sea surface temperature(SST), and hence an incremental surface heat loss. The increased sea ice drift and warm SST lead to an expansion of the sea ice area and a reduction of sea ice volume. These results emphasize the importance of OSCs in the air-sea-ice interactions on the global ocean circulations and the mass balance of Antarctic ice shelves, and this component may become more significant as the rapid change of Antarctic sea ice.

Hydrographic Characteristics and Oceanic Heat Flux in the Upper Arctic Ocean over the Alpha Ridge Observed by the DTOP Platform in 2018 and 2021

In 2018 and 2021,the Drift-Towing Ocean Profilers(DTOP)provided extensive temperature and salinity data on the upper 120m ocean through their drifts over the Alpha Ridge north of the Canada Basin.The thickness and temperature maximum of Alaska Coastal Water(ACW)ranged from 20m to 40m and-1.5℃to-0.8℃,respectively,and the salinity generally maintained from 30.2 to 32.5.Comparison with World Ocean Atlas 2018’s climatology manifested a 40m-thick and warm ACW roughly ex-ceeding the temperature maximum by 0.4–0.5℃in June–August 2021.This anomalously warm ACW was highly related to the ex-pansion of the Beaufort Gyre in the negative Arctic Oscillation phase.During summer,the under-ice oceanic heat flux F_(w)^(OHF)was elevated,with a maximum value of above 25Wm^(-2).F_(w)^(OHF)was typically low in the freezing season,with an average value of 1.2Wm^(-2).The estimates of upward heat flux contributed by ACW to the sea ice bottom F_(w)^(OHF)were in the range of 3–4Wm^(-2)in June–August 2021,when ACW contained a heat content of more than 80MJm^(-2).The heat loss over this period was driven by a weak stratification upon the ACW layer associated with a surface mixed layer(SML)approaching the ACW core.After autumn,F_(w)^(OHF)was reduced(<2 Wm^(-2))except during rare events when it elevated F_(w)^(OHF)slightly.In addition,the intensive and widespread Ekman suction,which created a violent upwelling north of the Canada Basin,was largely responsible for the substantial cooling and thinning of the ACW layer in the summer of 2021.

Deep learning to estimate ocean subsurface salinity structure in the Indian Ocean using satellite observations

Accurately estimating the ocean subsurface salinity structure(OSSS)is crucial for understanding ocean dynamics and predicting climate variations.We present a convolutional neural network(CNN)model to estimate the OSSS in the Indian Ocean using satellite data and Argo observations.We evaluated the performance of the CNN model in terms of its vertical and spatial distribution,as well as seasonal variation of OSSS estimation.Results demonstrate that the CNN model accurately estimates the most significant salinity features in the Indian Ocean using sea surface data with no significant differences from Argo-derived OSSS.However,the estimation accuracy of the CNN model varies with depth,with the most challenging depth being approximately 70 m,corresponding to the halocline layer.Validations of the CNN model’s accuracy in estimating OSSS in the Indian Ocean are also conducted by comparing Argo observations and CNN model estimations along two selected sections and four selected boxes.The results show that the CNN model effectively captures the seasonal variability of salinity,demonstrating its high performance in salinity estimation using sea surface data.Our analysis reveals that sea surface salinity has the strongest correlation with OSSS in shallow layers,while sea surface height anomaly plays a more significant role in deeper layers.These preliminary results provide valuable insights into the feasibility of estimating OSSS using satellite observations and have implications for studying upper ocean dynamics using machine learning techniques.

New Record Ocean Temperatures and Related Climate Indicators in 2023

The global physical and biogeochemical environment has been substantially altered in response to increased atmospheric greenhouse gases from human activities.In 2023,the sea surface temperature(SST)and upper 2000 m ocean heat content(OHC)reached record highs.The 0–2000 m OHC in 2023 exceeded that of 2022 by 15±10 ZJ(1 Zetta Joules=1021 Joules)(updated IAP/CAS data);9±5 ZJ(NCEI/NOAA data).The Tropical Atlantic Ocean,the Mediterranean Sea,and southern oceans recorded their highest OHC observed since the 1950s.Associated with the onset of a strong El Niño,the global SST reached its record high in 2023 with an annual mean of~0.23℃ higher than 2022 and an astounding>0.3℃ above 2022 values for the second half of 2023.The density stratification and spatial temperature inhomogeneity indexes reached their highest values in 2023.

An Overview on the Composition and Age of Upper Crust of Proto-Tethyan Lajishan Intra-oceanic Arc,NE Tibet Plateau

Identification and anatomy of oceanic arcs within ancient orogenic belt are significant for better understanding the tectonic framework and closure process of paleo-ocean basin.This article summarizes the geological,geochemical,and geochronological characteristics of upper crust of Proto-Tethyan Lajishan intra-oceanic arc and provides new data to constrain the subduction evolution of the South Qilian Ocean.The intra-oceanic arc volcanic rocks,including intermediate-mafic lava,breccia,tuff,and minor felsic rocks,are distributed along southern part of the Lajishan ophiolite belt.Geochemical and isotopic compositions indicate that the intermediate-mafic lava were originated from depleted mantle contaminated by sediment melts or hydrous fluids,whereas the felsic rocks were likely generated by partial melting of juvenile mafic crust in intra-oceanic arc setting.Zircons from felsic rocks yield consistent and concordant ages ranging from 506 to 523 Ma,suggesting these volcanic rocks represent the relicts of upper crust of the Cambrian intra-oceanic arc.Combined with the Cambrian forearc ophiolite and accretionary complex,we suggest that the Cambrian intra-oceanic arc in the Lajishan ophiolite belt is belonging to the intra-oceanic arc system which was generated by south-directed subduction in the South Qilian Ocean at a relatively short interval between approximately 530 and 480 Ma.

Seasonal variation of mesoscale eddy intensity in the global ocean

Mesoscale eddies are a prominent oceanic phenomenon that plays an important role in oceanic mass transport and energy conversion.Characterizing by rotational speed,the eddy intensity is one of the most fundamental properties of an eddy.However,the seasonal spatiotemporal variation in eddy intensity has not been examined from a global ocean perspective.In this study,we unveil the seasonal spatiotemporal characteristics of eddy intensity in the global ocean by using the latest satellite-altimetry-derived eddy trajectory data set.The results suggest that the eddy intensity has a distinct seasonal variation,reaching a peak in spring while attaining a minimum in autumn in the Northern Hemisphere and the opposite in the Southern Hemisphere.The seasonal variation of eddy intensity is more intense in the tropical-subtropical transition zones within latitudinal bands between 15°and 30°in the western Pacific Ocean,the northwestern Atlantic Ocean,and the eastern Indian Ocean because baroclinic instability in these areas changes sharply.Further analysis found that the seasonal variation of baroclinic instability precedes the eddy intensity by a phase of 2–3 months due to the initial perturbations needing time to grow into mesoscale eddies.

Evaluation of Nonbreaking Wave-Induced Mixing Parameterization Schemes Based on a One-Dimensional Ocean Model

Surface waves have a considerable effect on vertical mixing in the upper ocean.In the past two decades,the vertical mixing induced through nonbreaking surface waves has been used in ocean and climate models to improve the simulation of the upper ocean.Thus far,several nonbreaking wave-induced mixing parameterization schemes have been proposed;however,no quantitative comparison has been performed among them.In this paper,a one-dimensional ocean model was used to compare the performances of five schemes,including those of Qiao et al.(Q),Hu and Wang(HW),Huang and Qiao(HQ),Pleskachevsky et al.(P),and Ghantous and Babanin(GB).Similar to previous studies,all of these schemes can decrease the simulated sea surface temperature(SST),increase the subsurface temperature,and deepen the mixed layer,thereby alleviating the common thermal deviation problem of the ocean model for upper ocean simulation.Among these schemes,the HQ scheme exhibited the weakest wave-induced mixing effect,and the HW scheme exhibited the strongest effect;the other three schemes exhibited roughly the same effect.In particular,the Q and P schemes exhibited nearly the same effect.In the simulation based on observations from the Ocean Weather Station Papa,the HQ scheme exhibited the best performance,followed by the Q scheme.In the experiment with the HQ scheme,the root-mean-square deviation of the simulated SST from the observations was 0.43℃,and the mixed layer depth(MLD)was 2.0 m.As a contrast,the deviations of the SST and MLD reached 1.25℃ and 8.4 m,respectively,in the experiment without wave-induced mixing.

Predictability of the upper ocean heat content in a Community Earth System Model ensemble prediction system

Upper ocean heat content(OHC)has been widely recognized as a crucial precursor to high-impact climate variability,especially for that being indispensable to the long-term memory of the ocean.Assessing the predictability of OHC using state-of-the-art climate models is invaluable for improving and advancing climate forecasts.Recently developed retrospective forecast experiments,based on a Community Earth System Model ensemble prediction system,offer a great opportunity to comprehensively explore OHC predictability.Our results indicate that the skill of actual OHC predictions varies across different oceans and diminishes as the lead time of prediction extends.The spatial distribution of the actual prediction skill closely resembles the corresponding persistence skill,indicating that the persistence of OHC serves as the primary predictive signal for its predictability.The decline in actual prediction skill is more pronounced in the Indian and Atlantic oceans than in the Pacific Ocean,particularly within tropical regions.Additionally,notable seasonal variations in the actual prediction skills across different oceans align well with the phase-locking features of OHC variability.The potential predictability of OHC generally surpasses the actual prediction skill at all lead times,highlighting significant room for improvement in current OHC predictions,especially for the North Indian Ocean and the Atlantic Ocean.Achieving such improvements necessitates a collaborative effort to enhance the quality of ocean observations,develop effective data assimilation methods,and reduce model bias.

Characteristics and triggering mechanisms of early negative Indian Ocean Dipole

Negative Indian Ocean Dipole(nIOD)can exert great impacts on global climate and can also strongly influence the climate in China.Early nIOD is a major type of nIOD,which can induce more pronounced climate anomalies in summer than La Niña-related nIOD.However,the characteristics and triggering mechanisms of early nIOD are unclear.Our results based on reanalysis datasets indicate that the early nIOD and La Niña-related nIOD are the two major types of nIOD,and the former accounts for over one third of all the nIOD events in the past six decades.These two types of nIODs are similar in their intensities,but are different in their spatial patterns and seasonal cycles.The early nIOD,which develops in spring and peaks in summer,is one season earlier than the La Niña-related nIOD.The spatial pattern of the wind anomaly associated with early nIOD exhibits a winter monsoon-like pattern,with strong westerly anomalies in the equatorial Indian Ocean and eastly anomalies in the northern Indian Ocean.Opposite to the triggering mechanism of early positve IOD,the early nIOD is induced by delayed Indian summer monsoon onset.The results of this study are helpful for improving the prediction skill of IOD and its climate impacts.

An improved algorithm for retrieving thin sea ice thickness in the Arctic Ocean from SMOS and SMAP L-band radiometer data

The aim of this study was to develop an improved thin sea ice thickness(SIT)retrieval algorithm in the Arctic Ocean from the Soil Moisture Ocean Salinity and Soil Moisture Active Passive L-band radiometer data.This SIT retrieval algorithm was trained using the simulated SIT from the cumulative freezing degree days model during the freeze-up period over five carefully selected regions in the Beaufort,Chukchi,East Siberian,Laptev and Kara seas and utilized the microwave polarization ratio(PR)at incidence angle of 40°.The improvements of the proposed retrieval algorithm include the correction for the sea ice concentration impact,reliable reference SIT data over different representative regions of the Arctic Ocean and the utilization of microwave polarization ratio that is independent of ice temperature.The relationship between the SIT and PR was found to be almost stable across the five selected regions.The SIT retrievals were then compared to other two existing algorithms(i.e.,UH_SIT from the University of Hamburg and UB_SIT from the University of Bremen)and validated against independent SIT data obtained from moored upward looking sonars(ULS)and airborne electromagnetic(EM)induction sensors.The results suggest that the proposed algorithm could achieve comparable accuracies to UH_SIT and UB_SIT with root mean square error(RMSE)being about 0.20 m when validating using ULS SIT data and outperformed the UH_SIT and UB_SIT with RMSE being about 0.21 m when validatng using EM SIT data.The proposed algorithm can be used for thin sea ice thickness(<1.0 m)estimation in the Arctic Ocean and requires less auxiliary data in the SIT retrieval procedure which makes its implementation more practical.

Paper Analysis of Shanghai Ocean University in Bibliometric Method from Web of Science

The data of this research was mainly collected from the Web of Science (WOS) and Incites database platform, which was filtered and cataloged according to the different platforms. For tracing the change in scientific research at Shanghai Ocean University, make use of Bibliometric analysis to get the image and table of highly cited papers and hot papers. In this study, the scientific aspects in highly cited papers and hot papers, published in the last year in the core collection of Web of Science, were taken as objects, and office software was used as the main tool to carry out bibliometric and figure analysis. From the four aspects to find the difference in these fields, the production of specific fields and cited times is inconsistent. And suggest the department and management adjust the policy and method via elastic personnel and rewards to prompt the advancement of the research fields.

Assessment of the Intertropical Convergence Zone over the Atlantic Ocean through an Algorithm Based on Precipitation

The Intertropical Convergence Zone(ITCZ)is a key atmospheric system on a global scale,primarily driven by trade wind convergence near the equator.The ITCZ plays a crucial role in modulating the climate of the borders of tropical continental areas.For instance,Northeastern Brazil experiences a climate influenced by the ITCZ over the Atlantic Ocean.In some periods,the ITCZ exhibits double bands,known as the double ITCZ.While the features of the ITCZ have been described using various approaches and atmospheric variables,there is still a lack of regional studies focusing on the ITCZ and double ITCZ in the Atlantic Ocean.In this context,the main goals of this study are(1)to describe a simple algorithm based on precipitation to identify the ITCZ and double ITCZ,(2)to present a climatology(1997-2022)of the position,width,and intensity of these two convective bands,and(3)to investigate variabilities in the ITCZ characteristics associated with anomalies of sea surface temperature(SST)in the tropical Pacific and Atlantic oceans.The double ITCZ typically occurs southward of the main cloud band,and between February and April,both bands are more distant(~4.5°).In the western sector of the Atlantic Ocean,the ITCZ and its double band extend to more southerly latitudes in austral autumn.Considering the entire Atlantic basin,the annual mean of the latitudinal position,width,and intensity of the ITCZ is 4.9°N,4.2°,and 11 mm/day,respectively,while for the double ITCZ,it is 0.4°N,2.6°,10.3 mm/day,respectively.While the SST anomalies in the Pacific Ocean(El Niño and La Niña episodes)affect more the ITCZ width,the SST anomalies in the Tropical South Atlantic affect both its position and width.

Circulation Patterns Linked to the Positive Sub-Tropical Indian Ocean Dipole

The positive phase of the subtropical Indian Ocean dipole(SIOD)is one of the climatic modes in the subtropical southern Indian Ocean that influences the austral summer inter-annual rainfall variability in parts of southern Africa.This paper examines austral summer rain-bearing circulation types(CTs)in Africa south of the equator that are related to the positive SIOD and the dynamics through which specific rainfall regions in southern Africa can be influenced by this relationship.Four austral summer rain-bearing CTs were obtained.Among the four CTs,the CT that featured(i)enhanced cyclonic activity in the southwest Indian Ocean;(ii)positive widespread rainfall anomaly in the southwest Indian Ocean;and(iii)low-level convergence of moisture fluxes from the tropical South Atlantic Ocean,tropical Indian Ocean,and the southwest Indian Ocean,over the south-central landmass of Africa,was found to be related to the positive SIOD climatic mode.The relationship also implies that positive SIOD can be expected to increase the amplitude and frequency of occurrence of the aforementioned CT.The linkage between the CT related to the positive SIOD and austral summer homogeneous regions of rainfall anomalies in Africa south of the equator showed that it is the principal CT that is related to the inter-annual rainfall variability of the south-central regions of Africa,where the SIOD is already known to significantly influence its rainfall variability.Hence,through the large-scale patterns of atmospheric circulation associated with the CT,the SIOD can influence the spatial distribution and intensity of rainfall over the preferred landmass through enhanced moisture convergence.

Seismic monitoring of sub-seafloor fluid processes in the Haima cold seep area using an Ocean Bottom Seismometer (OBS)

The use of ocean bottom seismometers provides an effective means of studying the process and the dynamic of cold seeps by continuously recording micro-events produced by sub-seafloor fluid migration.We deployed a four-component Ocean Bottom Seismometer(OBS)at an active site of the Haima cold seep from 6 November to 19 November in 2021.Here,we present the results of this short-term OBS monitoring.We first examine the OBS record manually to distinguish(by their distinctive seismographic signatures)four types of events:shipping noises,vibrations from our remotely operated vehicle(ROV)operations,local earthquakes,and short duration events(SDEs).Only the SDEs are further discussed in this work.Such SDEs are similar to those observed in other sea areas and are interpreted to be correlated with sub-seafloor fluid migration.In the OBS data collected during the 14-day monitoring period.We identify five SDEs.Compared to the SDE occurrence rate observed in other cold seep regions,five events is rather low,from which it could be inferred that fluid migration,and subsequent gas seepage,is not very active at the Haima site.This conclusion agrees with multi-beam and chemical observations at that site.Our observations thus provide further constraint on the seepage activity in this location.This is the first time that cold seep-related SDEs have been identified in the South China Sea,expanding the list of sea areas where SDEs are now linked to cold seep fluid migration.

Another Year of Record Heat for the Oceans

Changes in ocean heat content(OHC), salinity, and stratification provide critical indicators for changes in Earth’s energy and water cycles. These cycles have been profoundly altered due to the emission of greenhouse gasses and other anthropogenic substances by human activities, driving pervasive changes in Earth’s climate system. In 2022, the world’s oceans, as given by OHC, were again the hottest in the historical record and exceeded the previous 2021 record maximum.According to IAP/CAS data, the 0–2000 m OHC in 2022 exceeded that of 2021 by 10.9 ± 8.3 ZJ(1 Zetta Joules = 1021Joules);and according to NCEI/NOAA data, by 9.1 ± 8.7 ZJ. Among seven regions, four basins(the North Pacific, North Atlantic, the Mediterranean Sea, and southern oceans) recorded their highest OHC since the 1950s. The salinity-contrast index, a quantification of the “salty gets saltier–fresh gets fresher” pattern, also reached its highest level on record in 2022,implying continued amplification of the global hydrological cycle. Regional OHC and salinity changes in 2022 were dominated by a strong La Ni?a event. Global upper-ocean stratification continued its increasing trend and was among the top seven in 2022.

Twenty years of ocean observations with China Argo

The international Argo program,a global observational array of nearly 4000 autonomous profiling floats initiated in the late 1990s,which measures the water temperature and salinity of the upper 2000 m of the global ocean,has revolutionized oceanography.It has been recognized one of the most successful ocean observation systems in the world.Today,the proposed decade action“OneArgo”for building an integrated global,full-depth,and multidisciplinary ocean observing array for beyond 2020 has been endorsed.In the past two decades since 2002,with more than 500 Argo deployments and 80 operational floats currently,China has become an important partner of the Argo program.Two DACs have been established to process the data reported from all Chinese floats and deliver these data to the GDACs in real time,adhering to the unified quality control procedures proposed by the Argo Data Management Team.Several Argo products have been developed and released,allowing accurate estimations of global ocean warming,sea level change and the hydrological cycle,at interannual to decadal scales.In addition,Deep and BGC-Argo floats have been deployed,and time series observations from these floats have proven to be extremely useful,particularly in the analysis of synoptic-scale to decadal-scale dynamics.The future aim of China Argo is to build and maintain a regional Argo fleet comprising approximately 400 floats in the northwestern Pacific,South China Sea,and Indian Ocean,accounting for 9%of the global fleet,in addition to maintaining 300 Deep Argo floats in the global ocean(25%of the global Deep Argo fleet).A regional BGC-Argo array in the western Pacific also needs to be established and maintained.

The Effect of Boreal Summer Intraseasonal Oscillation on Mixed Layer and Upper Ocean Temperature over the South China Sea

Intraseasonal oscillation of the mixed layer and upper ocean temperature has been found to occur over the South China Sea(SCS)in the summer monsoon season based on the multiple reanalysis and observational data in this study.The method of composite analysis and an upper ocean temperature equation assisted the analysis of physical mechanisms.The results show that the mixed layer depth(MLD)in the SCS has a significant oscillation with a 30-60 d period over the SCS region,which is closely related to boreal summer intraseasonal oscillation(BSISO)activities.The MLD can increase(decrease)during the positive(negative)phase of the BSISO and usually lags behind by approximately one-eighth of the lifecycle(5 days)of the BSISO-related convection.The BSISO may cause periodic anomalies at the air-sea boundary,such as wind stress and heat flux,so it can play a dominant role in modulating the variation in MLD.There also are significant intraseasonal seawater temperature anomalies in both the surface and subsurface layers of the SCS.In addition,during the initial phase of the BSISO,the temperature anomaly signals of the thermocline are obviously opposite to the sea surface temperature(SST),especially in the southern SCS.According to the results from the analysis of the temperature equation,the vertical entrainment term caused by BSISO-related wind stress is stronger than the thermal forcing during the initial stage of convection,and it is more significant in the southern SCS.

The Coordinated Influence of Indian Ocean Sea Surface Temperature and Arctic Sea Ice on Anomalous Northeast China Cold Vortex Activities with Different Paths during Late Summer

The Northeast China cold vortex(NCCV)during late summer(from July to August)is identified and classified into three types in terms of its movement path using machine learning.The relationships of the three types of NCCV intensity with atmospheric circulations in late summer,the sea surface temperature(SST),and Arctic sea ice concentration(SIC)in the preceding months,are analyzed.The sensitivity tests by the Community Atmosphere Model version 5.3(CAM5.3)are used to verify the statistical results.The results show that the coordination pattern of East Asia-Pacific(EAP)and Lake Baikal high pressure forced by SST anomalies in the North Indian Ocean dipole mode(NIOD)during the preceding April and SIC anomalies in the Nansen Basin during the preceding June results in an intensity anomaly for the first type of NCCV.While the pattern of high pressure over the Urals and Okhotsk Sea and low pressure over Lake Baikal during late summer-which is forced by SST anomalies in the South Indian Ocean dipole mode(SIOD)in the preceding June and SIC anomalies in the Barents Sea in the preceding April-causes the intensity anomaly of the second type.The third type is atypical and is not analyzed in detail.Sensitivity tests,jointly forced by the SST and SIC in the preceding period,can well reproduce the observations.In contrast,the results forced separately by the SST and SIC are poor,indicating that the NCCV during late summer is likely influenced by the coordinated effects of both SST and SIC in the preceding months.

The Relationship Between Indian Ocean SST and Tropical Cyclone Genesis Frequency over North Indian Ocean in May

Tropical cyclone(TC)activities in the North Indian Ocean(NIO)peak in May during the pre-monsoon period,but the TC frequency shows obvious inter-annual variations.By conducting statistical analysis and dynamic diagnosis of long-term data from 1948 to 2016,the relationship between the inter-annual variations of Indian Ocean SST and NIO TC genesis frequency in May is analyzed in this paper.Furthermore,the potential mechanism concerning the effect of SST anomaly on TC frequency is also investigated.The findings are as follows:1)there is a broadly consistent negative correlation between NIO TC frequency in May and SST in the Indian Ocean from March to May,with the key influencing area located in the southwestern Indian Ocean(SWIO);2)the anomalies of SST in SWIO(SWIO-SST)are closely related to a teleconnection pattern surrounding the Indian Ocean,which can significantly modulate the high-level divergence,mid-level vertical motion and other related environmental factors and ultimately influence the formation of TCs over the NIO;3)the increasing trend of SWIO-SST may play an essential role in the downward trend of NIO TC frequency over the past 69 years.

Wave forecast in the Atlantic Ocean using a double-stage ConvLSTM network

海浪预报对海上运输安全至关重要.本研究提出了一种涵盖物理信息的深度学习模型Double-stage ConvLSTM(D-ConvLSTM)以改进大西洋的海浪预报.将D-ConvLSTM模型与海浪持续性预测和原始ConvLSTM模型的预测技巧进行对比.结果表明,预测误差随着预测时长的增加而增加.D-ConvLSTM模型在预测准确度方面优于前二者,且第三天预测的均方根误差低于0.4 m,距平相关系数约在0.8.此外,当使用IFS预测风替代再分析风时,能够产生相似的预测效果.这表明D-ConvLSTM模型的预测能力能够与ECMWF-WAM模式相当,且更节省计算资源和时间.