Comparative analysis of the North Atlantic surface circulation reproduced by three different methods

Calculation results are presented for long-term mean annual surface currents in the North Atlantic based on direct drifter measurements and numerical experiments with the ocean general circulation model using both climatic arrays of hydrological data World Ocean Atlas 2009 and Argo profiling data. The calculations show that the technique suggested for model calculations of oceanographic characteristics of the World Ocean with the use of Argo data significantly improves the climatic fields of the temperature and salinity even on a coarse grid. The comparison of the model calculation results with drifter data showed that the temperature and salinity fields found from Argo data with the use of data variational interpolation on a regular grid allow the calculation of realistic currents and can be successfully used as initial conditions in hydrodynamic models of the ocean dynamics.     

Problems of variational assimilation of observational data for ocean general circulation models and methods for their solution

Problems of the variational assimilation of satellite observational data on the temperature and level of the ocean surface, as well as data on the temperature and salinity of the ocean from the ARGO system of buoys, are formulated with the use of the global three-dimensional model of ocean thermodynamics developed at the Institute of Numerical Mathematics, Russian Academy of Sciences (INM RAS). Algorithms for numerical solutions of the problems are developed and substantiated, and data assimilation blocks are developed and incorporated into the global three-dimensional model. Numerical experiments are performed with the use of the Indian Ocean or the entire World Ocean as examples. These numerical experiments support the theoretical conclusions and demonstrate that the use of a model with an assimilation block of operational observational data is expedient.     

基于神经网络的全球三维温盐场重构技术研究

文章利用果蝇优化广义回归神经网络算法FOAGRNN (fruit fly optimization algorithm, FOA; generalized regression neural network, GRNN)对SODA (simple ocean data assimilation)再分析数据进行训练, 构建海表温度、盐度、海面高度与次表层温盐场之间的投影关系模型, 并在全球范围使用SODA和卫星遥感数据评估了模型的应用性能。首先, 利用独立的2016年SODA海表数据作为模型输入进行理想重构试验, 结果显示全球重构温、盐平均均方根误差(MRMSE)分别为0.36℃和0.08‰, 与世界海洋图集WOA13资料相比减小约50%和60%。然后, 利用卫星观测的海表信息作为模型输入进行实际应用试验, 并与Argo观测剖面进行比较评估。试验结果表明, 重构模型能有效表征海水温、盐特征, 其中重构温、盐MRMSE分别为0.79℃和0.16‰, 相比WOA气候态减小27%和11%。误差的垂向分布显示, 重构温度RMSE从海表向下迅速增大, 至100m达到峰值1.35℃, 而后又迅速回落,至250m处为0.81℃, 跃层往下不断减小; 重构盐度RMSE基本随深度增大而减小, 误差峰值位于25m附近, 约为0.25‰。此外, Argo浮标跟踪分析和区域水团统计结果也表明模型能够较好地刻画海洋三维温盐场的内部结构特征。     

Numerical modeling of ocean hydrodynamics with variational assimilation of observational data

Models and methods of the numerical modeling of ocean hydrodynamics dating back to the pioneering works of A.S. Sarkisyan are considered, with emphasis on the formulation of problems and algorithms of mathematical modeling and the four-dimensional variational assimilation of observational data. An algorithm is proposed for studying the sensitivity of the optimal solution to observational data errors in a seasurface temperature assimilation problem in order to retrieve heat fluxes on the surface. An example of a solution of the optimal problem of the World Ocean hydrodynamics with the assimilation of climatic temperature and salinity observations is offered.     

An ocean data assimilation system and reanalysis of the World Ocean hydrophysical fields

A new version of the ocean data assimilation system (ODAS) developed at the Hydrometcentre of Russia is presented. The assimilation is performed following the sequential scheme analysis–forecast–analysis. The main components of the ODAS are procedures for operational observation data processing, a variational analysis scheme, and an ocean general circulation model used to estimate the first guess fields involved in the analysis. In situ observations of temperature and salinity in the upper 1400-m ocean layer obtained from various observational platforms are used as input data. In the new ODAS version, the horizontal resolution of the assimilating model and of the output products is increased, the previous 2D-Var analysis scheme is replaced by a more general 3D-Var scheme, and a more flexible incremental analysis updating procedure is introduced to correct the model calculations. A reanalysis of the main World Ocean hydrophysical fields over the 2005–2015 period has been performed using the updated ODAS. The reanalysis results are compared with data from independent sources.     

中国海及邻近海域卫星观测资料同化试验

利用1个基于POMgcs海洋模式和多重网格三维变分同化方法建立的中国海及邻近海域海面高与三维温盐流数值预报模型,通过一系列数值试验,研究了同化卫星测高和卫星遥感海面温度观测资料对该模型预报能力的影响。试验结果表明,同化卫星测高资料可明显改善海面高度与三维温度和盐度的分析预报效果,使1 200 m以上的温度预报误差减小0.16℃,并能有效提高对海洋中尺度现象的预报能力;同化卫星遥感海面温度对100 m以上的温度和盐度的预报效果有所改善,可使海面温度的预报误差减小10%。     

Meridional heat transport determined with expendable bathythermographs—Part I: Error estimates from model and hydrographic data

Heat transports estimated CTD data collected during the World Ocean Circulation Experiment (WOCE) along the January 1993 30°S hydrographic transect (A10) and the output from a numerical model show a mean heat transport of 0.40 and 0.55±0.24 PW (standard deviation), respectively. The model shows a large annual cycle in heat transport (more than 30% of the variance) with a maximum (minimum) heat transport in July (February) of 0.68 (0.41) PW. Using these data, a method is proposed and evaluated to calculate the heat transport from temperature data obtained from a trans-basin section of expendable bathythermographs (XBTs) profiles. In this method, salinity is estimated from Argo profiles and CTD casts for each XBT temperature observation using statistical relationships between temperature, latitude, longitude and salinity computed along constant-depth surfaces. Full-depth temperature/salinity profiles are obtained by extending the profiles to the bottom of the ocean using deep climatological data. The meridional transport is then determined by using the standard geostrophic method, applying NCEP-derived Ekman transports, and requiring that the salt flux through the Bering Straits be conserved. The results indicate that the methods described here can provide heat transport estimates with a maximum uncertainty of ±0.18 PW (1 PW=10¹⁵ W). Most of this uncertainty is due to the climatology used to estimate the deep structure and issues related to not knowing the absolute velocity field and most especially characterizing barotropic motions. Nevertheless, when the methodology is applied to temperatures collected along 30°S (A10) and direct model integrations, the results are very promising. Results from the numerical model suggest that ageostrophic non-Ekman motions can contribute less than 0.05 PW to heat transport estimates in the South Atlantic.     

Modeling the global circulation response and the regional response of the Arctic Ocean to the external forcing anomalies

The problem of numerical modeling and analysis of the large-scale World Ocean circulation variability under variations of the external forcing is considered. A numerical model was developed in the INM RAS and is based on the primitive equations of the ocean circulation written in a spherical generalized σ-coordinate system. The model’s equations are approximated on a grid with resolution of 2.5° × 2° × 33, and the North Pole is displaced to the continental point (60°E, 60.5°N). There are two stages for the numerical experiments. The quasi-equilibrium circulation of the World Ocean under the climatological atmospheric forcing is simulated at the first stage. The run is carried out over a period of 3000 years during which a quasi-equilibrium model regime is formed. At the second stage, the sensitivity of the model ocean circulation to the atmospheric forcing perturbations in the Southern Hemisphere is studied. According to the results, the strongest regional changes in the hydrography take place in the Arctic Ocean. Substantial changes of sea’s surface height and local anomalies of the temperature and salinity are formed there.     

Simulating large-scale circulation in seas and oceans

The problem of simulating ocean general circulation is considered using an approach developed by G.I. Marchuk. Most attention is focused on problems associated with the application of multi-component-splitting and adjoint-equation methods and with the parameterization of turbulent-exchange processes. The statement of the problem, an algorithm of its solution, and the results of the four-dimensional temperature and salinity data assimilation in a model of World Ocean hydrodynamics are discussed. This algorithm yields qualitatively reliable results, and its main features are modularity, usability, and the possibility of using efficient implicit schemes.     

Upper Ocean Four-Dimensional Variational Data Assimilation in the Arabian Sea and Bay of Bengal

A regional ocean circulation model with four-dimensional variational data assimilation scheme is configured to study the ocean state of the Indian Ocean region (65°E–95°E; 5°N–20°N) covering the Arabian Sea (AS) and Bay of Bengal (BoB). The state estimation setup uses 10 km horizontal resolution and 5 m vertical resolution in the upper ocean. The in-situ temperature and salinity, satellite-derived observations of sea surface height, and blended (in-situ and satellite-derived) observations of sea surface temperature alongwith their associated uncertainties are used for data assimilation with the regionally configured ocean model. The ocean state estimation is carried out for 61 days (1 June to 31 July 2013). The assimilated fields are closer to observations compared to other global state estimates. The mixed layer depth (MLD) of the region shows deepening during the period of assimilation with AS showing higher MLD compared to the BoB. An empirical forecast equation is derived for the prediction of MLD using the air–sea forcing variables as predictors. The surface and sub-surface (50 m) heat and salt budget tendencies of the region are also investigated. It is found that at the sub-surface, only the advection and diffusion temperature and salt tendencies are important.     

Importance of Reference Dataset Improvements for Argo Delayed-Mode Quality Control

For the Argo Project, monitoring the global upper ocean by a large number of profiling floats, maintaining the quality of salinity data is critical; the goal for measurement accuracy is ±0.01. Experiments using the method of Wong et al. (2003), the standard delayed-mode quality control (dQC) for the Project, show that its performance depends critically on the reference datasets used. This study concludes that the method is useful for Argo and has sufficient potential to achieve the goal for salinity measurement in the North Pacific, when suitable reference datasets are prepared. Considering the Wong et al. (2003) algorithms, we suggest that reference datasets with the following characteristics will be most suitable for Argo dQC: They should be basically derived from the most extensive datasets, such as the latest World Ocean Database; in regions with denser observations, datasets with carefully quality controls should be used; in the regions with subsurface temperature inversions, such as the subarctic North Pacific, the profiles used for the reference must extend below the deepest temperature maximum to prepare proper salinities for the deep layer reference.     

南海北部海洋四维变分同化试验研究

为了研究四维变分同化方法在南海北部海洋数值预报中的适用性,使用海洋区域模式(ROMS),建立了南海北部海洋资料四维变分同化系统,进行了温盐廓线和海面温度数据同化试验,初步对比分析了三种四维变分实现方法的同化效果。研究结果表明,四维变分同化方法具有较好的同化效果,其中,增量强约束方法(I4DVar)具有较好的稳定性,其稳定性高于4DPSAS和R4DVar。本文研究成果为建立南海业务化海洋四维变分同化及预报系统奠定技术基础。     

基于广义回归神经网络的全球表层海水1°×1°二氧化碳分压数据推演

表层海水二氧化碳分压是评估海洋碳源汇强度的关键参数,但其实测数据较少、时空分布极不均匀,导致二氧化碳交换通量的估算有很大的不确定性,海洋源汇特征就不能确切获取。为了解决这个难题,在收集的表层大洋二氧化碳地图(Surface Ocean CO₂ Atlas,SOCAT)实测数据集基础上,运用广义回归神经网络建立二氧化碳分压与经纬度、时间、温度、盐度和叶绿素浓度间的非线性关系,构建了1998?2018年间全球1°×1°经纬度的表层海水二氧化碳分压格点数据,其标准误差为16.93 μatm,平均相对误差为2.97%,优于现有研究中的前反馈神经网络、自组织映射神经网络和机器学习算法等方法。根据构建的数据所绘制的全球表层海水二氧化碳分压的分布与现有研究有较好的一致性。     

Validation of interannual simulations from the 1/8° global Navy Coastal Ocean Model (NCOM)

A 1/8° global version of the Navy Coastal Ocean Model (NCOM) is used for simulation of upper-ocean quantities on interannual time scales. The model spans the global ocean from 80°S to a complete Arctic cap, and includes 19 terrain-following σ- and 21 fixed z-levels. The global NCOM assimilates three-dimensional (3D) temperature and salinity fields produced by the Modular Ocean Data Assimilation System (MODAS) which generates synthetic temperature and salinity profiles based on ocean surface observations. Model-data intercomparisons are performed to measure the effectiveness of NCOM in predicting upper-ocean quantities such as sea surface temperature (SST), sea surface salinity (SSS) and mixed layer depth (MLD). Subsurface temperature and salinity are evaluated as well. An extensive set of buoy observations is used for this validation. Where possible, the model validation is performed between year-long time series obtained from the model and time series from the buoys. The statistical analyses include the calculation of dimensionless skill scores (SS), which are positive if statistical skill is shown and equal to one for perfect SST simulations. Model SST comparisons with year-long SST time series from all 83 buoys give a median SS value of 0.82. Model subsurface temperature comparisons with the year-long subsurface temperature time series from 24 buoys showed that the model is able to predict temperatures down to 500 m reasonably well, with positive SS values ranging from 0.18 to 0.97. Intercomparisons of MLD reveal that the model MLD is usually shallower than the buoy MLD by an average of about 15 m. Annual mean SSS and subsurface salinity biases between the model and buoy values are small. A comparison of SST between NCOM and a satellite-based Pathfinder data set demonstrates that the model has a root-mean-square (RMS) SST difference of 0.61 °C over the global ocean. Spatial variations of kinetic energy fields from NCOM show agree with historical observations. Based on these results, it is concluded that the global NCOM presented in this paper is able to predict upper-ocean quantities with reasonable accuracy for both coastal and open ocean locations.     

Annual cycle of the upper-ocean circulation and properties in the tropical western Indian Ocean

A regional ocean model was used to simulate the annual cycle of the upper-ocean dynamics and its influence on ocean properties in the tropical western Indian Ocean. Surface winds and heat fluxes from the National Centers for Environmental Prediction (NCEP) reanalysis forced the model (Model_NCEP) with initial and lateral boundary conditions derived from the Simple Ocean Data Assimilation (SODA). The model findings were in good agreement with previous research, satellite and observational data as well as another model configuration forced by Comprehensive Ocean and Atmosphere Data Sets (COADS). The initial and lateral boundary conditions for Model_COADS were extracted from World Ocean Atlas 2001. Anticyclonic wind stress curl occurred to the north of Madagascar, and extended towards the Tanzanian coast throughout the year, leading to Ekman convergence and downwelling in that region. The lowest sea-surface height values during the year occurred between 5° and 12° S with an elongated and contracted shape. The East African Coastal Current (EACC) was in phase with the westward North-East Madagascar Current (NEMC) throughout the year with volume transports peaking in June through July in the model forced by NCEP reanalysis. The variability of the volume transport, ocean currents, temperature and salinity to the north of Madagascar on the path of the NEMC mirrored those in the middle Tanzanian shelf on the path of the EACC throughout the year. The NEMC seemed to influence the water masses on the Tanzanian shelf, with cooler and lower-salinity water in the South-West Monsoon, and warmer and saltier water during the North-East Monsoon.     

The Indian Ocean HydroBase: A high-quality climatological dataset for the Indian Ocean

The present study developed a high-quality climatological dataset for the Indian Ocean - the Indian Ocean HydroBase (IOHB) - from a combined dataset including the World Ocean Database 1998 version 2 (WOD98v2). Methods are similar to those used by previous studies for other oceans. Japanese data for the IOHB originated from the Japanese datasets MIRC (Marine Information Research Center) Ocean Dataset 2001 and Far Seas Collection; these datasets contain more Japanese observations than WOD98v2. Water mass properties in the IOHB climatology are consistent with previous studies. Seasonal patterns of properties near the sea surface are well reproduced, and deep-layer properties are consistent with the Reid-Mantyla climatology that is derived from high-quality observations. The isopycnal climatology of the IOHB differs from the World Ocean Atlas 2001 (WOA01) along the fronts associated with the Antarctic Circumpolar Current (ACC). The WOA01 shows a warm and saline intermediate water intrusion from South Africa to the east along the northern edge of the front. Such an intrusion is absent in IOHB where less saline intermediate water extends continuously northward from the southern ocean. The WOA01 shows a continuous belt of low potential vorticity along the ACC. This feature is less distinct in the IOHB climatology and in the Reid-Mantyla climatology. The IOHB consists of a 1° × 1° gridded climatology and the datasets of raw and quality-controlled hydrographic stations. The latter is valuable for quality control of the Argo float salinity data as climatological reference. These datasets are available freely via the Internet.     

MODAS试验数据统计分析

模块化海洋数据同化系统（MODAS）通过同化卫星遥感测得的海面温度和海面高度,产生一种动态气候态,能够更接近地预报出海洋的真实状况。介绍了MODAS基本原理,并选择试验海区,对MODAS数据进行了统计和分析。     

Detection of Intermediate Mediterranean Waters in the Atlantic Ocean by ARGO Floats Data

Peculiarities of the spatial distribution of intermediate Mediterranean waters (MW), which are the main source to maintain the heat and salt budgets at depths of 600–1500 m in the Atlantic Ocean, have been studied using the ARGO floats measurements database. About 75000 temperature and salinity profiles recorded by 900 ARGO floats in 2005–2014 in the Atlantic Ocean for latitudes from 20° to 50° N were used. To process these data, we used the ARGO-Based Model for Investigation of the Global Ocean (AMIGO). This technique allowed us for the first time to obtain a complete set of oceanographic characteristics up to a depth of 2000 m for different time averaging intervals (month, season, years). Joint analysis of the temperature, salinity, and velocity distributions at 700–1000 m depths made it possible to revise the distribution of MW and their penetration into the western part of the ocean across the Mid-Atlantic Ridge (MAR). It is shown that at depths of 700 and 1000 m, the Mid-Atlantic Ridge is a barrier to advective propagation of salty waters (>35.5 PSU) to the west and is transparent to fragments of destroyed intrathermocline lenses (ITL) with lower salinity (<35.4 PSU). In the Atlantic region, from 20° to 35° N and from 30° to 70° W, individual lens profiles with an anomalous salinity distribution were sought using ARGO measurements to detect ITL and its separate fragments. About 24 000 measurements from 370 ARGO floats were analyzed, and only about 3% of them showed weak salinity anomalies at 800–1200 m depths. No ITL were found from these observations. Analysis of long-term drifting of individual floats recording temperature and salinity profiles with anomalous layers made it possible to study the nature of MW transport through the MAR.