Array For Real-time Geostrophic Oceanography Research Articles

Effect of Argo Salinity Drift since 2016 on the Estimation of Regional Steric Sea Level Change Rates

Since 2016, the Argo (Array for Real-Time Geostrophic Oceanography) ocean salinity data has exhibited significant drift, directly affecting the accurate quantification of the global steric sea level (SSL) rates. To further investigate how salinity drift affects the estimation of SSL rates in different depths and regions, we divide the 0–2000 m into three layers (0–300 m, 300–1000 m and 1000–2000 m) and select five open oceans (the South and North Pacific, the South and North Atlantic, and the Indian Ocean) for discussion. By comparing the SSL rates between the periods of 2005–2015 and 2005–2019, we can evaluate the impact of salinity drift. Taking the estimated results from the IPRC (provided by the International Pacific Research Center at the University of Hawaii) and BOA (provided by the Second Institute of Oceanography, China) data as examples, we find that the effect of salinity drift is the largest at the depth of 1000–2000 m, about 29% for IPRC data and about 18% for BOA data. Moreover, the South Atlantic is susceptible to the effects of salinity drift, with an approximately 13% impact for IPRC data and 21% for BOA data.

The abnormal track of super typhoon Hinnamnor (2022) and its interaction with the upper ocean

The upper ocean response and feedback to super typhoon Hinnamnor (2022) were systematically investigated considering multi-satellite, Array for Real-time Geostrophic Oceanography (Argo) float and reanalysis data. Hinnamnor experienced three main stages: a rapid intensification (RI) stage with a high moving speed along a westward track, a rapid weakening (RW) stage with a low moving speed along a northward sudden-turning track and a re-intensification (Re-I) stage with a moderate speed along a northward track. At the westward straight-line stage, despite the thin warm water layer (D26 < 40 m) and shallow mixed layer depth (MLD) (<20 m), its fast movement (∼8.1 m/s) tended to generate weaker sea surface temperature (SST) cooling (approximately 1 °C) and shorter cooling exposure. Consequently, the negative feedback decreased (negative feedback factor FSST:approximately−0.47to−0.20), causing Hinnamnor's rapid intensification (25 knots/6 h). Although the MLD was deeper (approximately 30 m) and the warm water layer was thicker (approximately 60 m) at the sudden-turning stage, the low translation speed (<2 m/s) tended to generate stronger SST cooling (approximately 5.6 °C) and longer cooling exposure, both of which intensified the negative feedback (FSST:approximately−0.8to−0.4), causing Hinnamnor's rapid weakening (−22 knots/6 h). At the northward stage, Hinnamnor re-intensified under a weak warm eddy with a moderate moving speed (3.6–5.4 m/s). An intriguing leftward bias in SST cooling occurred due to the preexisting cold eddy (CE) on the left side of the track. Analysis of the Argo floats in the RI and RW regions showed that the enhanced upwelling and vertical mixing yielded more significant SST cooling in the CE region at the RW stage due to the CE and low translation speed (<2 m/s). The differences between the RI and RW regions were remarkable when using the Hybrid Coordinate Ocean Model (HYCOM) global ocean model output.

Performance analysis of global HYCOM flow field using Argo profiles

ABSTRACT Flow field data generated by ocean models are important for simulating ocean currents and circulation patterns, which are essential components in digital Earth construction. To evaluate the accuracy of model-simulated flow fields, Array for Real-time Geostrophic Oceanography (Argo) float observations can be considered benchmarks. In this study, a novel method for comparing Argo profiles with 3-dimensional trajectories obtained by simulating Argo floats in Hybrid Coordinate Ocean Model (HYCOM)-provided flow fields was proposed. Surface and subsurface trajectories were calculated, and their spatial matching characteristics were analyzed. The results demonstrated that (1) the HYCOM surface and subsurface flow fields generally conform to the basic characteristics and trends of ocean currents; (2) the HYCOM sea surface current field error pattern exhibits a symmetrical distribution centered on the equator in the Northern and Southern Hemispheres and increases with increasing latitude; and (3) the HYCOM subsurface flow field exhibits regional differences, with the largest differences in the Gulf Stream, North Atlantic Warm Current, and Westerly Wind Drift region. Through analysis of the disparities between HYCOM and Argo data, the effectiveness of using model simulation data can be enhanced, and the accuracy and dependability of ocean models can be improved.

The Respondence of Wave on Sea Surface Temperature in the Context of Global Change

Several aspects of global climate change, e.g., the rise of sea level and water temperature anomalies, suggest the advantages of studying wave distributions. In this study, WAVEWATCH-III (WW3) (version 6.07), which is a well-known numerical wave model, was employed for simulating waves over global seas from 1993–2020. The European Centre for Medium-Range Weather Forecasts (ECMWF), Copernicus Marine Environment Monitoring Service (CMEMS), current and sea level were used as the forcing fields in the WW3 model. The validation of modelling simulations against the measurements from the National Data Buoy Center (NDBC) buoys and Haiyang-2B (HY-2B) altimeter yielded a root mean square error (RMSE) of 0.49 m and 0.63 m, with a correlation (COR) of 0.89 and 0.90, respectively. The terms calculated by WW3-simulated waves, i.e., breaking waves, nonbreaking waves, radiation stress, and Stokes drift, were included in the water temperature simulation by a numerical circulation model named the Stony Brook Parallel Ocean Model (sbPOM). The water temperature was simulated in 2005–2015 using the high-quality Simple Ocean Data Assimilation (SODA) data. The validation of sbPOM-simulated results against the measurements obtained from the Array for Real-time Geostrophic Oceanography (Argo) buoys yielded a RMSE of 1.12 °C and a COR of 0.99. By the seasonal variation, the interrelation of the currents, sea level anomaly, and significant wave heights (SWHs) were strong in the Indian Ocean. In the strong current areas, the distribution of the sea level was consistent with the SWHs. The monthly variation of SWHs, currents, sea surface elevation, and sea level anomalies revealed that the upward trends of SWHs and sea level anomalies were consistent from 1993–2015 over the global ocean. In the Indian Ocean, the SWHs were obviously influenced by the SST and sea surface wind stress. The rise of wind stress intensity and sea level enlarges the growth of waves, and the wave-induced terms strengthen the heat exchange at the air–sea layer. It was assumed that the SST oscillation had a negative response to the SWHs in the global ocean from 2005–2015. This feedback indicates that the growth of waves could slow down the amplitude of water warming.

The effect of normal and abnormal eddies on the mixed layer depth in the global ocean

Mesoscale eddies are broadly distributed over the global ocean and play a significant role in modulating the spatiotemporal evolution of mixed layer depth (MLD). The presence of abnormal eddies in the ocean has been shown; however, the precise quantification of the effect of eddies on MLD, given the case of abnormal eddies, has not been carried out thus far. Differently from the previous approach to identify abnormal eddies through sea surface temperature, we therefore, proposed a method to identify abnormal eddies, using potential density based on Argo data (Array for Real-time Geostrophic Oceanography) for 15 years from 2003 to 2017. Results showed that abnormal anticyclonic eddies (AAE) and abnormal cyclonic eddies (ACE) accounted for 21.67% and 20.17% of total matching anticyclonic eddies (TAE) and the total matching cyclonic eddies (TCE), respectively, in the global ocean. The proportions of abnormal eddies were relatively higher in tropical regions but lower in regions with the boundary current and strong eddy kinetic energy. The MLD changes caused by normal and abnormal eddies were estimated combining satellite altimetry data. The normal eddies were the total matching eddies with the removal of the abnormal eddies, separately called normal anticyclonic eddies (NAE) and normal cyclonic eddies (NCE). The overall influence of NAE (NCE) was more significant on MLD deepening (uplifting) than that of TAE (TCE). Globally, NAE (NCE) changed MLD deepening (uplifting) from ~66 m (~54 m) to ~67 m (~53 m) and exhibited a more pronounced change in the Indian Ocean sector of the Southern Ocean region, from ~111 m (~94 m) to ~115 m (~92 m) in the winter. AAE (ACE), exerted a relatively weak but opposite effect on MLD deepening (uplifting). In other words, the global average MLD caused by them shoaled (deepened) from ~66 m (~54 m) to ~59 m (~59 m), and the North Pacific Ocean shoaled (deepened) from ~61 m (~47 m) to ~49 m (~57 m) in winter. Given the above results, abnormal eddies should be accounted for when the impact of ocean eddies is evaluated on the global climate system.

An ocean current-oriented graph-based model for representing Argo trajectories

Argo (array for real-time geostrophic oceanography) trajectories, generated by ocean currents at different depths, are a vital data source for studying ocean currents. One traditional method for representing the trajectories ‒ which uses a time-ordered series of spatial locations ‒ confuses the Argo trajectories corresponding to the parking depths and the one corresponding to the sea surface. It is, therefore, a great challenge to study ocean currents directly based on the Argo trajectories available in the Argo Global Data Assembly Centers (GDACs). Based on the working principles of Argo floats, in this paper, a hierarchical semantic representation of Argo trajectories is proposed and an ocean current-oriented graph model for representing Argo trajectories, named CoGAT, is designed. CoGAT is based on the following ideas. 1). The complete trajectory of an Argo float is represented by a node named TrajNode, which includes several nodes labeled ParkingTrajNode and labeled SurfaceTrajNode by edges, i.e. IncludingEdges. Each ParkingTrajNode represents the trajectory that an Argo float follows at its parking depth, whereas the SurfaceTrajNode represents the trajectory at the sea surface. 2) By IncludingEdges, each ParkingTrajNode or SurfaceTrajNode includes many sub-nodes, each of which is a ParkingSubTrajNode or SurfaceSubTrajNode, and each of these sub-nodes represents a sub-trajectory within a cycle of an Argo float at a parking depth or at the sea surface. A time-ordered relationship between two ParkingSubTrajNodes or two SurfaceSubTrajNodes is represented by the edge class SequenceEdge. 3) Nodes named LocationNode record the spatial locations of an Argo float, and two LocationNodes make up a sub-trajectory within a cycle; i.e., they constitute a ParkingSubTrajNode or a SurfaceSubTrajNode. A time-ordered relationship between two LocationNodes means a direction of a sub-trajectory at a parking depth or at the sea surface; this relationship is denoted as a ParkingSubTrajEdge or SurfaceSubTrajEdge. 4) The six classes of nodes and four classes of edges described above allow CoGAT to not only separate the Argo trajectories into separate trajectories at different parking depths and at the sea surface but also enable the Argo trajectories to be stored using a temporally granular representation; e.g., monthly, seasonal or annual. In this study, global Argo trajectories for the period January 2000 to April 2020 were stored in a Neo4j-based graph database named GATDB, and comparisons with the spatial Oracle database of Argo trajectories demonstrated the ability of CoGAT to provide a spatial and temporal representation of Argo trajectories at different depths and to store these trajectories.

Variability in upper-ocean salinity stratification in the tropical Pacific Ocean

Using a gridded array for real-time geostrophic oceanography (Argo) program float dataset, the features of upper-ocean salinity stratification in the tropical Pacific Ocean are studied. The salinity component of the squared Brunt-Vaisala frequency N2 (N 2 ) is used to represent salinity stratification. Layer-max N 2 (LMN), defined as the N 2 maximum over the upper 300 m depth, and halocline depth (HD), defined as the depth where the N 2 maximum is located, are used to specifically describe the intensity of salinity stratification. Salinity stratification in the Topical Pacific Ocean has both spatial and temporal variability. Over the western and eastern equatorial Pacific, the LMN has a large magnitude with a shallow HD, and both have completely opposite distributions outside of the equatorial region. An obvious seasonal cycle in the LMN occurs in the north side of eastern equatorial Pacific and freshwater flux forcing dominates the seasonal variations, followed by subsurface forcing. At the eastern edge of the western Pacific warm pool around the dateline, significant interannual variation of salinity stratification occurs and is closely related to the El Nino Southern Oscillation event. When an El Nino event occurs, the precipitation anomaly freshens sea surface and the thermocline shoaling induced by the westerly wind anomaly lifts salty water upward, together contribute to the positive salinity stratification anomaly over the eastern edge of the warm pool. The interannual variations in ocean stratification can slightly affect the propagation of first baroclinic gravity waves.

A Regional Operational Model for the North East Atlantic: Model Configuration and Validation

An operational model for an area of the northeast Atlantic that encompasses all of Ireland’s territorial waters has been developed. The model is an implementation of the Regional Ocean Modelling System (ROMS) and uses operationally available atmospheric and boundary forcing, and a global tide solution for tidal forcing. River forcing is provided by climatological daily discharge rates for 29 rivers across Ireland, west Britain, and west France. It is run in an operational framework to produce 7-day hindcasts once a week, and daily 3-day forecasts which are published in a number of formats. We evaluated the model skill by comparing with measured data and calculating statistics such as mean error, root mean square error (RMSE), and correlation coefficient. The observations consist of satellite Sea Surface Temperature (SST), total surface velocity fields from satellite, water level time series from around the Irish coast, and temperature and salinity data from Array for Real-Time Geostrophic Oceanography (ARGO) and Conductivity Temperature Depth (CTD) profiles. The validation period is from 1 January 2016 until 31 December 2019. The correlation coefficient between the model and satellite SST is 0.97 and recorded in March and April 2018. The model error is about 5% of the total M2 amplitude in the Celtic Sea recorded at Dunmore East tide gauge station. The maximum RMSE between the model and the CTD temperature profiles is 0.8 °C while it is 0.17 PSU for salinity. The model correctly defines the shelf water masses around Ireland. In 2019 the Irish Coastal Current (ICC) was very strong and well defined along most of the western Irish coast. The model results have well reproduced the ICC front for the whole simulation period.

The pattern of sea-level rise across the North Atlantic from long-term-trend tide gauges

The long-term-trend tide gauges have monthly average mean sea levels oscillating about the same perfectly linear trend before and after 1990, across the North Atlantic, same of every other water basin. This stable pattern is clear over the full length of the records starting in the late 1800s/early 1900s having negligible acceleration. Across the North Atlantic, the absolute rate of rise of the sea levels, computed by coupling the monthly average mean sea levels signal with the position signal from Global Positioning System, is also about the same. The absolute sea levels of New York, U.S. and Brest, France, have a similar pattern since 1854. Measurements of the 41 °N Atlantic Meridional Overturning Circulation based on the Array for Real-time Geostrophic Oceanography and satellite altimetry, also show stable strength, since 1990. A proxy of this Overturning Circulation linked to the absolute mean sea levels of New York and Brest also show stability since 1854. Coastal management should acknowledge this fact.

A sea-level monopole in the equatorial Indian Ocean

In this study, we show the relationship between sea-level anomalies (SLA) and upper-ocean parameters in the Equatorial Indian Ocean (EIO). This work also focuses on the variability of SLA obtained from satellite altimeter data in different spatial and temporal scales and its relationship with computed ocean heat content (OHC), dynamic height (DH), and thermocline depth (20 °C isotherm: D20) during 1993–2015. SLA showed low Pearson’s correlation coefficient (CC) with upper-ocean parameters over central EIO resembling a “Monopole” pattern. The Array for Real-time Geostrophic Oceanography (ARGO) in situ profile data in the central EIO also confirmed this. SLA over this monopole showed low correlations with all parameters as compared with eastern and western EIO. These findings show a clear signature of a persisting sea-level monopole in the central EIO. Oscillating SLA over western and eastern EIO during summer and winter monsoon months is found to be responsible for locking this monopole in the central EIO. Both SLA and OHC increased in EIO during 2006–2015 compared with 1993–2005. The month of January showed different east–west trends at different times. This trend during 1993–2015 is neutral, but it shifted from negative during 1993–2005 to positive during 2006–2015.

The Thermohaline Modes of the Global Ocean

AbstractThe first 2000 m of the global thermohaline structure of the ocean are statistically decomposed into vertical thermohaline modes, using a multivariate functional principal component analysis (FPCA). This method is applied on the Monthly Isopycnal and Mixed-Layer Ocean Climatology (MIMOC). The first three modes account for 92% of the joint temperature and salinity (T–S) variance, which yields a surprisingly good reduction of dimensionality. The first mode (69% of the variance) is related to the thermocline depth and delineates the subtropical gyres. The second mode (18%) is mostly driven by salinity and mainly displays the asymmetry between the North Pacific and Atlantic basins and the salty circumpolar deep waters in the Southern Ocean. The third mode (5%) identifies the low- and high-salinity intermediate waters, covarying with the freshwater inputs of the upper ocean. The representation of the ocean in the space defined by the first three modes offers a simple visualization of the global thermohaline structure that strikingly emphasizes the role of the Southern Ocean in linking and distributing water masses to the other basins. The vertical thermohaline modes offer a convenient framework for model and observation data comparison. This is illustrated by projecting the repeated Pacific section P16 together with profiles from the Array for Real-Time Geostrophic Oceanography (ARGO) global array of profiling floats on the modes defined with the climatology MIMOC. These thermohaline modes have a potential for water mass identification and robust analysis of heat and salt content.

Mixed Layer Heat Variations in the South China Sea Observed by Argo Float and Reanalysis Data during 2012–2015

The atmospheric and oceanic causes of mixed layer heat variations in the South China Sea (SCS) are examined using data from six long-lived Array for Real-time Geostrophic Oceanography (Argo) floats. The mixed layer heat budget along each float trajectory is evaluated based on direct measurements, satellite and reanalysis datasets. Our results suggest that the mixed layer heat balance in the SCS has distinct spatial and seasonal variations. The amplitude of all terms in the mixed layer heat budget equation is significantly larger in the northern SCS than in the southern SCS, especially in winter. In the northern SCS, the mixed layer heat budget is controlled by the local surface heat flux and horizontal advection terms in winter, and the net heat flux term in summer. In the western and southeastern SCS, the mixed layer heat budget is dominated by the net surface heat flux in both winter and summer. Further analysis shows that in the SCS, surface shortwave radiation and geostrophic heat advection are major contributors to net heat flux and horizontal advection, respectively. Unlike the net heat flux and horizontal advection, the vertical entrainment is a sink term in general. The rate of mixed layer deepening is the most important factor in the entrainment rate, and a barrier layer may decrease the temperature difference between the bottom of the mixed layer and the water beneath. Residual analysis suggests that the residual term in the equation is due to the inexact calculation of heat geostrophic advection, other missing terms, and unresolved physical ocean dynamic processes.

Salinity effects on the 2014 warm “Blob” in the Northeast Pacific

A significant strong, warm “Blob” (a large circular water body with a positive ocean temperature anomaly) appeared in the Northeast Pacific (NEP) in the boreal winter of 2013–2014, which induced many extreme climate events in the US and Canada. In this study, analyses of the temperature and salinity anomaly variations from the Array for Real-time Geostrophic Oceanography (Argo) data provided insights into the formation of the warm “Blob” over the NEP. The early negative salinity anomaly dominantly contributed to the shallower mixed layer depth (MLD) in the NEP during the period of 2012–2013. Then, the shallower mixed layer trapped more heat in the upper water column and resulted in a warmer sea surface temperature (SST), which enhanced the warm “Blob”. The salinity variability contributed to approximately 60% of the shallowing MLD related to the warm “Blob”. The salinity anomaly in the warm “Blob” region resulted from a combination of both local and nonlocal effects. The freshened water at the surface played a local role in the MLD anomaly. Interestingly, the MLD anomaly was more dependent on the local subsurface salinity anomaly in the 100–150 m depth range in the NEP. The salinity anomaly in the 50–100 m depth range may be linked to the anomaly in the 100–150 m depth range by vertical advection or mixing. The salinity anomaly in the 100–150 m depth range resulted from the eastward transportation of a subducted water mass that was freshened west of the dateline, which played a nonlocal role. The results suggest that the early salinity anomaly in the NEP related to the warm “Blob” may be a precursor signal of interannual and interdecadal variabilities.

Global thermosteric sea level change contributed by the deep ocean below 2000 m estimated by Argo and CTD data

Due to an insufficient amount of observational data, little is known about the temperature variation in the global abyssal ocean and its contribution to sea level change. In this study, we estimated the monthly seawater temperature below 2000 m from 2005–2015 by combining Array for Real-time Geostrophic Oceanography (Argo) and conductivity-temperature-depth (CTD) data. For this purpose, we divided the global ocean into 38 regions according to the CTD temperature profile properties. For each region, we used CTD data to construct a mathematical model to describe the relation of temperatures between 1000–2000 m and those below 2000 m. We then used this mathematical model and the Argo data to reconstruct the temperature profile below 2000 m and evaluate its thermostatic contribution to sea level change. We discovered that the deep ocean below 2000 m contributed 0.12 ± 0.03 mm/yr to the mean global thermosteric sea level rise from 2005–2015. Our result was confirmed by geodetic observations, i.e., the rate of thermosteric sea level rise calculated using altimeter, Gravity Recovery and Climate Experiment (GRACE), and Argo data was approximately 0.15 ± 0.41 mm/yr. The contribution of each ocean layer generally decreased with depth, and there was an obvious fluctuation between approximately 4000–5000 m, interpreted as being caused by geothermal heating of the ocean floor.

Design and Experimental Research on Deep Water Pressure Resistance System of Argo Float

ABSTRACT Wu, H.; Liu, Y.; Xue, G.; Guo, F.; Li, Z., and Liu, M., 2018. Design and experimental research on deep water pressure resistance system of argo float. In: Liu, Z.L. and Mi, C. (eds.), Advances in Sustainable Port and Ocean Engineering. Journal of Coastal Research, Special Issue No. 83, pp. 116–123. Coconut Creek (Florida), ISSN 0749-0208. The underwater probe device such as ROV (Remote Operated Vehicle), AUV (Autonomous Underwater Vehicle) and ARGO (Array for Real-Time Geostrophic Oceanography) float are widely used in observing the salty, temperature, depth and other oceanographic parameter. As the working depth go deeper the limitation of anti-pressure case becomes vital. The optimal size of the anti-pressure should be designed in order to meet the requirement that the float's house can ensure the 4000m deep-sea pressure and has the minimum weight. However, rare researches focus on the anti-pressure house theory or designation for the ARGO float. In this paper, an innovation structure and worki...

Observed Variability of Surface Layer in the Central Bay of Bengal:Results of Measurements Using Glider

Underwater gliders measure high-resolution spatiotemporal oceanographic data. In April 2014, the National Institute of Ocean Technology, Chennai operated an underwater glider ‘Barathi’, for 127 days for observation of Bay of Bengal (BoB). In this article we present the effectiveness of the glider Barathi for high resolution temporal sampling of the surface layer in the central BoB for studying variation of temperature, salinity and density structures and acoustic characteristics on 26–27 May 2014. The results showed ‘afternoon effect’ on acoustic characteristics and formation of secondary sound channel. Our data set is strongly correlated (coefficient of determination r 2 > 0.96) with data from a nearby Array for real-time geostrophic Oceanography (Argo) float.

Contribution of Ekman pumping to the changes in properties and volume of the Eastern South Pacific Intermediate Water

An update on the Eastern South Pacifi c Intermediate Water (ESPIW) distribution has been possible based on ARGO (Array for Real-Time Geostrophic Oceanography) data. This study comprised over 46,000 profi les obtained during 2007-2012 from an area between the western coast of South America and 150°W, and 5° and 40°S. This information was complemented with data from the World Ocean Circulation Experiment (WOCE) P06 transects conducted in 1992 and 2010 at 32°30’S in the South Pacifi c Ocean. Based on a comparison of this update and data from 1990-2001, it was established that the ESPIW volume has increased by approximately 53%. Moreover, the area occupied by ESPIW in the 2010 WOCE P06 transect was 48% higher than in 1992. Ekman pumping velocity, calculated from the wind for the time and region of ESPIW formation, showed a signifi cant increase in Ekman pumping between 2000 and 2012. The increase in Ekman pumping from 2000 onward could explain the observed changes in ESPIW distribution (the water mass had extended zonally) and properties (salinity showed a decrease of 0.1). These changes could be explained as the consequence of atmospheric climate variability over the interior ocean.

An objective algorithm for reconstructing the three-dimensional ocean temperature field based on Argo profiles and SST data

While global oceanic surface information with large-scale, real-time, high-resolution data is collected by satellite remote sensing instrumentation, three-dimensional (3D) observations are usually obtained from in situ measurements, but with minimal coverage and spatial resolution. To meet the needs of 3D ocean investigations, we have developed a new algorithm to reconstruct the 3D ocean temperature field based on the Array for Real-time Geostrophic Oceanography (Argo) profiles and sea surface temperature (SST) data. The Argo temperature profiles are first optimally fitted to generate a series of temperature functions of depth, with the vertical temperature structure represented continuously. By calculating the derivatives of the fitted functions, the calculation of the vertical temperature gradient of the Argo profiles at an arbitrary depth is accomplished. A gridded 3D temperature gradient field is then found by applying inverse distance weighting interpolation in the horizontal direction. Combined with the processed SST, the 3D temperature field reconstruction is realized below the surface using the gridded temperature gradient. Finally, to confirm the effectiveness of the algorithm, an experiment in the Pacific Ocean south of Japan is conducted, for which a 3D temperature field is generated. Compared with other similar gridded products, the reconstructed 3D temperature field derived by the proposed algorithm achieves satisfactory accuracy, with correlation coefficients of 0.99 obtained, including a higher spatial resolution (0.25° × 0.25°), resulting in the capture of smaller-scale characteristics. Finally, both the accuracy and the superiority of the algorithm are validated.

Freshening of Antarctic Intermediate Water in the South Atlantic Ocean in 2005–2014

Abstract. Basin-scale freshening of Antarctic Intermediate Water (AAIW) is reported to have occurred in the South Atlantic Ocean during the period from 2005 to 2014, as shown by the gridded monthly means of the Array for Real-time Geostrophic Oceanography (Argo) data. This phenomenon was also revealed by two repeated transects along a section at 30° S, performed during the World Ocean Circulation Experiment Hydrographic Program. Freshening of the AAIW was compensated for by a salinity increase of thermocline water, indicating a hydrological cycle intensification. This was supported by the precipitation-minus-evaporation change in the Southern Hemisphere from 2000 to 2014. Freshwater input from atmosphere to ocean surface increased in the subpolar high-precipitation region and vice versa in the subtropical high-evaporation region. Against the background of hydrological cycle changes, a decrease in the transport of Agulhas Leakage (AL), which was revealed by the simulated velocity field, was proposed to be a contributor to the associated freshening of AAIW. Further calculation showed that such a decrease could account for approximately 53 % of the observed freshening (mean salinity reduction of about 0.012 over the AAIW layer). The estimated variability of AL was inferred from a weakening of wind stress over the South Indian Ocean since the beginning of the 2000s, which would facilitate freshwater input from the source region. The mechanical analysis of wind data here was qualitative, but it is contended that this study would be helpful to validate and test predictably coupled sea–air model simulations.

Pacific-Indian interocean circulation of the Antarctic Intermediate Water around South Australia

On the basis of the salinity distribution of isopycnal (σ 0=27.2 kg/m3) surface and in salinity minimum, the Antarctic Intermediate Water (AAIW) around South Australia can be classified into five types corresponding to five regions by using in situ CTD observations. Type 1 is the Tasman AAIW, which has consistent hydrographic properties in the South Coral Sea and the North Tasman Sea. Type 2 is the Southern Ocean (SO) AAIW, parallel to and extending from the Subantarctic Front with the freshest and coldest AAIW in the study area. Type 3 is a transition between Type 1 and Type 2. The AAIW transforms from fresh to saline with the latitude declining (equatorward). Type 4, the South Australia AAIW, has relatively uniform AAIW properties due to the semienclosed South Australia Basin. Type 5, the Southeast Indian AAIW, progressively becomes more saline through mixing with the subtropical Indian intermediate water from south to north. In addition to the above hydrographic analysis of AAIW, the newest trajectories of Argo (Array for real-time Geostrophic Oceanography) floats were used to constructed the intermediate (1 000 m water depth) current field, which show the major interocean circulation of AAIW in the study area. Finally, a refined schematic of intermediate circulation shows that several currents get together to complete the connection between the Pacific Ocean and the Indian Ocean. They include the South Equatorial Current and the East Australia Current in the Southwest Pacific Ocean, the Tasman Leakage and the Flinders Current in the South Australia Basin, and the extension of Flinders Current in the southeast Indian Ocean.