Simple Ocean Data Assimilation Research Articles

Seasonal variation of intermediate meridional overturning circulation in the South China Sea

The seasonal variation of intermediate meridional overturning circulation (IMOC) in the South China Sea (SCS) is investigated using the Simple Ocean Data Assimilation version 2.2.4 (SODA2.2.4) product for the period of 1950–2010. The SCS IMOC displays distinct seasonal features, with a counterclockwise cell dominating the interior SCS (12∼18°N, 200∼700 m) in winter and a broader clockwise cell occupying the region for (7∼20°N, 50∼900 m) in summer. By removing the 12-month average, the main characteristics of the seasonal IMOC is captured deeply. There is a counterclockwise anomaly in winter and a clockwise anomaly in summer occurring in the region for (8∼20°N, 100∼1000 m). And the strongest anomalies of the overturning stream functions are mainly located in (12∼17°N, 200∼400 m) that is taken as the representative region to study the seasonal IMOC. A dynamical decomposition of the IMOC seasonal anomaly allows a further look into the seasonal variation of the SCS IMOC. The IMOC seasonal anomaly is decomposed into three components: the Ekman component, the vertical shear component, and the external component. The Ekman component exhibits a full cell clockwise in winter and counterclockwise in summer with a negative contribution to the IMOC anomaly. The vertical shear component has a strong cell counterclockwise in winter and clockwise in summer occupying most of the areas above 1000 m with a positive contribution to the IMOC anomaly. The external component has a relatively complex structure, and its positive and negative contributions to the IMOC anomaly alternate with increasing latitude at 200∼1000 m. According to the seasonal fractional covariance of these three components on the IMOC anomaly in the representative region, the vertical shear component and the Ekman component have the main contributions to the IMOC seasonal anomaly, and the external component has a limited impact. The vertical shear and its meridional difference can lead to a downward motion at around 12°N and an upward motion at around 17°N in winter, and reverse motions in summer. The seasonal vertical motions will cause an overturning counterclockwise in winter and clockwise in summer. The Ekman component is mainly driven by the monsoon over the SCS that generates the Ekman transport northward in winter and southward in summer. The seasonal Ekman transport and its return flow together form an overturning clockwise in winter and counterclockwise in summer. And the external component counterclockwise in winter and clockwise in summer between 14°N and 17°N is associated with the horizontal flow northeastward in winter and southwestward in summer zonally going over shallower or greater depths, which can induce seasonal reverse upwelling and downwelling at different latitudes.

Attention Pyramid Convolutional Neural Network Optimized with Big Data for Teaching Aerobics

Aerobics has emerged as a widely embraced cardiovascular exercise, fostering improved fitness through rhythmic movements that enhance heart rate, stamina, endurance, and cardiovascular health. Effective instruction by skilled professionals is crucial for maximizing the benefits of aerobics, ensuring participants' correct and safe performance. This study introduces the concept of Aerobics Movement Teaching, emphasizing its pivotal role in college physical education. The proposed method, Attention Pyramid Convolutional Neural Network optimized with big data for teaching Aerobics (AP-CNN-BTA), focuses on enhancing aesthetic ability and overall human development. Data from the Simple Ocean Data Assimilation Data Set are collected, preprocessed, and utilized in the teaching process using the Attention Pyramid Convolutional Neural Network, specifically designed for efficient aerobics instruction in coastal areas. The resulting data are stored in the cloud and accessed through a human interface unit. The implementation, carried out in Python, undergoes evaluation using various metrics, including accuracy, computational time, sensitivity, specificity, precision, and ROC analysis. The simulation results demonstrate a remarkable improvement, with the proposed technique achieving 36.52%, 39.55%, and 43.75% higher accuracy compared to existing methods such as Exploration on and thinking about aesthetic infiltration in aerobics teaching in colleges and universities(ETAI-AT-CU), sea level height depending on big data of the Internet of Things along aerobics teaching in coastal regions(SLH-BD-IOT-ATC), and impact of deep learning-based curriculum's ideological and political integration on sports aerobics instruction design(IP-CDL-TDTA), respectively. This research contributes to advancing the efficacy of aerobics instruction, particularly in coastal regions, and underscores the significance of comprehensive student development through high-quality education.

Intercomparison of tropical Indian Ocean circulation in ocean reanalysis and evaluation in CMIP6 climate models

In the present study, we assess the Tropical Indian Ocean (TIO) circulation features from the available ocean reanalysis products and the latest version of Coupled Model Intercomparison Project (CMIP6) climate model simulations. We considered the following reanalysis products; Ocean Reanalysis System 5 (ORAS5), Estimating the Circulation and Climate of the Ocean (ECCO), Global Ocean Data Assimilation System (GODAS), Ensemble Coupled Data Assimilation (ECDA), the Bluelink Reanalysis (BRAN) and Simple Ocean Data Assimilation (SODA) and compared them against in-situ observations and the satellite-derived Ocean Surface Current Analyses Real-time (OSCAR). The reanalysis products underestimate the strength and location of the Wyrtki Jets. The BRAN reanalysis performed well compared to the other products in representing the TIO surface zonal currents, followed by ORAS5. The vertical extension of subsurface zonal currents in the equatorial Indian Ocean and their seasonal maxima are well captured in ORAS5. Thus, our analysis suggests that the ORAS5 is a qualitative product to estimate the TIO circulation. We further evaluated the TIO current patterns simulated by CMIP6 models with in-situ data/ ORAS5. The majority of the models show discrepancies in simulating equatorial and south equatorial current systems with a mean bias of 0.1cms−1 and 0.2cms−1, respectively. NorESM2-MM, NorESM2-LM, CanESM5, CESM2-WACCM-FV2, and E3SM-1-ECA models showed a superior skill in reproducing the TIO circulation compared to the rest of the models. Our analysis highlights the importance of assessing various reanalysis products and coupled climate models in representing the circulation of the TIO and, consequently, their role in depicting regional weather and climate.

Multivariate Upstream Kuroshio Transport (UKT) Prediction and Targeted Observation Sensitive Area Identification of UKT Seasonal Reduction

Variation and seasonal reduction in the Upstream Kuroshio Transport (UKT) have important impacts on surrounding climate and oceanic circulation systems. Therefore, reliable UKT prediction is crucial. In this paper, we propose an intelligent UKT prediction model, KuroshioNet, which is firstly pre-trained with simulation data generated by the Regional Ocean Modeling System (ROMS) and then fine-tuned with reanalysis data of the Simple Ocean Data Assimilation (SODA). Operating at a five-day time resolution and a 0.5°spatial resolution, KuroshioNet has the capability to predict multivariate fields associated with upstream Kuroshio, including 3D variables like velocity, temperature, as well as salinity and 2D variables like sea surface height. Subsequently, the UKT is computed from the predicted fields. We evaluate and analyze the experimental results, which show that KuroshioNet has a lead time of 55 days for UKT prediction. In order to enhance the physical interpretability of KuroshioNet, we conduct an ablation experiment to evaluate the impact of each predictor on prediction skill. It demonstrates that selecting zonal velocity, meridional velocity, temperature, salinity, and SSH contributes to UKT prediction by KuroshioNet. Besides, by analyzing model performance and visualizing what the convolutional kernels learn, we find that KuroshioNet, which has learned from ROMS data, is capable of obtaining better initial performance and acquiring more active kernels to better learn the features in SODA data. Furthermore, we identify the targeted observation sensitive area of UKT seasonal reduction by KuroshioNet with the saliency map method, which is situated to the east of upstream kuroshio. The sensitive area is consistent with the result identified by numerical models and yields 38.1% improvement on prediction demonstrated by observing system simulation experiments.

Interannual variability of the South Atlantic subtropical mode water: Investigating the early aughts shift and its relationship to ENSO modulations

The South Atlantic subtropical mode water (SASTMW) is a conspicuous volume of water formed during winter and early spring that occupies the mid-latitudes of the South Atlantic. Here, we aim to investigate the interannual variability of the SASTMW's volume in response to remote processes influenced by atmospheric teleconnection. We utilized the Simple Ocean Data Assimilation (SODA) ocean reanalysis to identify this particular mode water. The SASTMW's volume time series underwent a shift during the early aughts, with the frequency spectrum changing from broad and sparse interannual peaks during 1980–2001 to narrow and frequent peaks during 2002–2018, following the interdecadal shift of El Niño–Southern Oscillation (ENSO) that occurred in 1999. Hence, the influence of ENSO on SASTMW was evaluated for each of the two periods. From 1980 to 2001, in the western side of the basin, SASTMW's volume reached its peak 21 months after the occurrence of an El Niño, and after 43 months it became thinner. The opposite pattern occurred after a La Niña event, with stronger events having a greater impact on the SASTMW. In the 2002–2018 period, the largest correlations were observed in the eastern part of the basin, with significantly shorter lags of 6–20 months.

Intraseasonal and interannual variability of sea temperature in the Arabian Sea Warm Pool

Abstract. The Arabian Sea Warm Pool (ASWP) is a part of the Indian Ocean Warm Pool, formed in the Arabian Sea before the onset of the Indian summer monsoon. The ASWP has a significant impact on climate change in the Indian Peninsula and globally. In this study, we examined the intraseasonal and interannual variability of sea temperature in the ASWP using the latest Simple Ocean Data Assimilation (SODA) reanalysis dataset. We quantified the contributions of sea surface heat flux forcing, horizontal advection, and vertical entrainment to the sea temperature using the mixed-layer heat budget analysis method. We also used a lead–lag correlation method to examine the relationship between the interannual variability of the ASWP and various large-scale modes in the Indo-Pacific Ocean. We found that the ASWP formed in April and decayed in June; its formation and decay processes were asymmetrical, with the decay rate being twice as fast as the formation rate. During the ASWP development phase, the sea surface heat flux forcing had the largest impact on the mixed-layer temperature with a contribution of up to 85 %. Its impact was divided into the net surface heat flux (0.41–0.50 ∘C per 5 d) and the shortwave radiation loss penetrating the mixed layer (from −0.08 ∘C per 5 d to −0.17 ∘C per 5 d). During the decay phase, the cooling effect of the vertical entrainment on the temperature variation increased (from −0.05 ∘C per 5 d to −0.18 ∘C per 5 d) and dominated the temperature variation jointly with the sea surface heat flux forcing. We also found that the ASWP has strong interannual variability related to the basin warming of the Indian Ocean. The lead–lag correlation indicated that the ASWP had a good synchronous correlation with the Indian Ocean Dipole. The ASWP had the largest correlation coefficient at a lag of 5–7 months of the Niño3.4 index, showing the characteristics of modulation by the El Niño–Southern Oscillation (ENSO). When the El Niño (La Niña) event peaked in the winter of the previous year, the ASWP that occurred before the summer monsoon was more significant (insignificant) in the following year.

Reduced viscosity steadily weakens oceanic currents

The viscosity of both air and water is temperature dependent. A rising temperature leads to an increased viscosity for air but a decreased viscosity for water. As climate becomes warmer, this increased air viscosity can partly inhibit the reduction of wind stress over the ocean, and the reduced water viscosity causes less downward momentum and heat transport. As these opposing effects of warming on air and water viscosity are not included in the state-of-the-art climate models, the understanding of their potential impacts on the response of the climate system to the anthropogenic warming is lacking. Here, via analyzing the Simple Ocean Data Assimilation oceanic reanalysis dataset, we show that the ocean heat content increases at a rate of ~1.3 × 1022 J/yr over 35 years, which leads to a continuous reduction of oceanic viscosity. As a result, the ocean vertical shear enhances with a shoaling of the mixed layer depth and a reduced vertical linkage in the ocean. Our calculations show a reduction of the oceanic kinetic energy at a rate of ~2.4 × 1016 J/yr. Potentially, this could generate far-reaching impacts on the energy storage of the climate system and, hence, could pace the global warming. Thus, it is important to include the temperature-dependent viscosity in our climate models. Freshwater discharged from polar ice sheets and mountain glaciers also contributes to the reduction in oceanic viscosity but, at present, to a lesser extent than that in oceanic warming. Reduced oceanic viscosity, therefore, is an important, but hitherto overlooked, response to a warming climate and contributes to many recent weather extremes including heavier rainfall rates in hurricanes, slackening of the polar vortex, and oceanic heat waves.

Interannual Migration of the Summertime Eastward Jet in the South China Sea Associated With the Upper Layer Thickness Distribution

AbstractThe summertime eastward jet (SEJ) in the South China Sea (SCS) can be regarded as the boundary between the southern and northern upper circulation of the SCS in climatology. The dynamic process of SEJ migration in response to the variation of SCS summer monsoon (SCSSM) strength on the interannual scale is investigated, based on the Simple Ocean Data Assimilation (SODA) dataset and by a 1.5‐layer reduced gravity model. Analysis shows that SEJ position is closely related to SCSSM strength, with southward/northward migration of SEJ coinciding with stronger/weaker SCSSM. Besides migration of wind stress curl (WSC) zero‐line and north‐south difference of WSC variation, the north‐south difference of the SCS upper layer thickness (ULT) in summer, that is, thick in the southern SCS and thin in the northern SCS, also plays a significant role in the dynamic process of SEJ migration. It is the joint effect of wind strength and ULT distribution. With the variation of SCSSM strength, the thinner ULT in the northern SCS corresponds to the larger magnitude of potential vorticity (PV) variation inputted by wind stress, which leads to more pronounced strengthening/weakening of the western boundary current (WBC) in the northern SCS than that in the southern SCS. Then, the north and south WBCs compete with each other until the upper layer circulation reaches a new equilibrium state, and SEJ migrates southward/northward accordingly.

Global ocean reanalysis CORA2 and its inter comparison with a set of other reanalysis products

We present the China Ocean ReAnalysis version 2 (CORA2) in this paper. We compare CORA2 with its predecessor, CORA1, and with other ocean reanalysis products created between 2004 and 2019 [GLORYS12v1 (Global Ocean reanalysis and Simulation), HYCOM (HYbrid Coordinate Ocean Model), GREP (Global ocean Reanalysis Ensemble Product), SODA3 (Simple Ocean Data Assimilation, version 3), and ECCO4 (Estimating the Circulation and Climate of the Ocean, version 4)], to demonstrate its improvements and reliability. In addition to providing tide and sea ice signals, the accuracy and eddy kinetic energy (EKE) of CORA2 are also improved owing to an enhanced resolution of 9 km and updated data assimilation scheme compared with CORA1. Error analysis shows that the root-mean-square error (RMSE) of CORA2 sea-surface temperature (SST) remains around 0.3°C, which is comparable to that of GREP and smaller than those of the other products studied. The subsurface temperature (salinity) RMSE of CORA2, at 0.87°C (0.15 psu), is comparable to that of SODA3, smaller than that of ECCO4, and larger than those of GLORYS12v1, HYCOM, and GREP. CORA2 and GLORYS12v1 can better represent sub-monthly-scale variations in subsurface temperature and salinity than the other products. Although the correlation coefficient of sea-level anomaly (SLA) in CORA2 does not exceed 0.8 in the whole region, as those of GREP and GLORYS12v1 do, it is more effective than ECCO4 and SODA3 in the Indian Ocean and Pacific Ocean. CORA2 can reproduce the variations in steric sea level and ocean heat content (OHC) on the multiple timescales as the other products. The linear trend of the steric sea level of CORA2 is closer to that of GREP than that of the other products, and the long-term warming trends of global OHC in the high-resolution CORA2 and GLORYS12v1 are greater than those in the low-resolution EN4 and GREP. Although CORA2 shows overall poorer performance in the Atlantic Ocean, it still achieves good results from 2009 onward. We plan to further improve CORA2 by assimilating the best available observation data using the incremental analysis update (IAU) procedure and improving the SLA assimilation method.

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.

Water mass transformation variability in the Weddell Sea in ocean reanalyses

Abstract. This study investigates the variability of water mass transformation (WMT) within the Weddell Gyre (WG). The WG serves as a pivotal site for the Meridional Overturning Circulation (MOC) and ocean ventilation because it is the primary origin of the largest volume of water mass in the global ocean: Antarctic Bottom Water (AABW). Recent mooring data suggest substantial seasonal and interannual variability of AABW properties exiting the WG, and studies have linked the variability to the large-scale climate forcings affecting wind stress in the WG region. However, the specific thermodynamic mechanisms that link variability in surface forcings to variability in water mass transformations and AABW export remain unclear. This study explores how current state-of-the-art data-assimilating ocean reanalyses can help fill the gaps in our understanding of the thermodynamic drivers of AABW variability in the WG via WMT volume budgets derived from Walin's classic WMT framework. The three ocean reanalyses used are the following: Estimating the Circulation and Climate of the Ocean state estimate (ECCOv4), Southern Ocean State Estimate (SOSE) and Simple Ocean Data Assimilation (SODA). From the model outputs, we diagnose a closed form of the water mass budget for AABW that explicitly accounts for transport across the WG boundary, surface forcing, interior mixing and numerical mixing. We examine the annual mean climatology of the WMT budget terms, the seasonal climatology and finally the interannual variability. Our finding suggests that the relatively coarse resolution of these models did not realistically capture AABW formation, export and variability. In ECCO and SOSE, we see strong interannual variability in AABW volume budget. In SOSE, we find an accelerating loss of AABW during 2005–2010, driven largely by interior mixing and changes in surface salt fluxes. ECCO shows a similar trend during a 4-year time period starting in late 2007 but also reveals such trends to be part of interannual variability over a much longer time period. Overall, ECCO provides the most useful time series for understanding the processes and mechanisms that drive WMT and export variability in the WG. SODA, in contrast, displays unphysically large variability in AABW volume, which we attribute to its data assimilation scheme. We also examine correlations between the WMT budgets and large-scale climate indices, including El Niño–Southern Oscillation (ENSO) and Southern Annular Mode (SAM), and find no strong relationships.

Summer Habitat and Fishing Ground of <i>Ommastrephes bartramii</i> Related with the North Pacific Subarctic Frontal Zone Using Long-term Field Research Data

The neon flying squid, Ommastrephes bartramii, is an economically important oceanic squid species that has been harvested commercially in the North Pacific by Japan, Korea, China, and Taiwan. The Fisheries Research Agency (FRA) of Japan conducted long-term research for this species from 1980 to 2009 using commercial vessels to clarify the resource ecology and it obtained a total dataset of approximately 9,000 days, where following from this and to better clarify the relationship between habitat preference and oceanographic conditions, a generalized additive model was applied and mapped onto the Simple Ocean Data Assimilation ocean/sea ice reanalysis (SODA) data. The resultant habitat map of the squid showed an area of high abundance at the Subarctic Frontal Zone (SAFZ), with abundance areas increasing the squid abundance from April to August. The SAFZ extends from 40°N to 43°N separating the cold, low-salinity, subarctic water to the north from the waters of the North Pacific Transition Zone to the south. This high abundance area intersects between subarctic area and temperate area. It has characteristic nutrient regimes, productivity cycles, and nektonic faunal compositions. This paper suggests that the SAFZ thus plays an important role in North Pacific ecosystems by providing an optimal balance between environmental temperature and food density for the neon flying squid.

Using a deep-learning approach to infer and forecast the Indonesian Throughflow transport from sea surface height

The Indonesian Throughflow (ITF) connects the tropical Pacific and Indian Oceans and is critical to the regional and global climate systems. Previous research indicates that the Indo-Pacific pressure gradient is a major driver of the ITF, implying the possibility of forecasting ITF transport by the sea surface height (SSH) of the Indo-Pacific Ocean. Here we used a deep-learning approach with the convolutional neural network (CNN) model to reproduce ITF transport. The CNN model was trained with a random selection of the Coupled Model Intercomparison Project Phase 6 (CMIP6) simulations and verified with residual components of the CMIP6 simulations. A test of the training results showed that the CNN model with SSH is able to reproduce approximately 90% of the total variance of ITF transport. The CNN model with CMIP6 was then transformed to the Simple Ocean Data Assimilation (SODA) dataset and this transformed model reproduced approximately 80% of the total variance of ITF transport in the SODA. A time series of ITF transport, verified by Monitoring the ITF (MITF) and International Nusantara Stratification and Transport (INSTANT) measurements of ITF, was then produced by the model using satellite observations from 1993 to 2021. We discovered that the CNN model can make a valid prediction with a lead time of 7 months, implying that the ITF transport can be predicted using the deep-learning approach with SSH data.

Quality Assessment of Sea Surface Salinity from Multiple Ocean Reanalysis Products

Sea surface salinity (SSS) is one of the Essential Climate Variables (ECVs) as defined by the Global Climate Observing System (GCOS). Acquiring high-quality SSS datasets with high spatial-temporal resolution is crucial for research on the hydrological cycle and the earth climate. This study assessed the quality of SSS data provided by five high-resolution ocean reanalysis products, including the Hybrid Coordinate Ocean Model (HYCOM) 1/12° global reanalysis, the Copernicus Global 1/12° Oceanic and Sea Ice GLORYS12 Reanalysis, the Simple Ocean Data Assimilation (SODA) reanalysis, the ECMWF Oceanic Reanalysis System 5 (ORAS5) product and the Estimating the Circulation and Climate of the Ocean Phase II (ECCO2) reanalysis. Regional comparison in the Mediterranean Sea shows that reanalysis largely depicts the accurate spatial SSS structure away from river mouths and coastal areas but slightly underestimates the mean SSS values. Better SSS reanalysis performance is found in the Levantine Sea while larger SSS uncertainties are found in the Adriatic Sea and the Aegean Sea. The global comparison with CMEMS level-4 (L4) SSS shows generally consistent large-scale structures. The mean ΔSSS between monthly gridded reanalysis data and in situ analyzed data is −0.1 PSU in the open seas between 40° S and 40° N with the mean Root Mean Square Deviation (RMSD) generally smaller than 0.3 PSU and the majority of correlation coefficients higher than 0.5. A comparison with collocated buoy salinity shows that reanalysis products well capture the SSS variations at the locations of tropical moored buoy arrays at weekly scale. Among all of the five products, the data quality of HYCOM reanalysis SSS is highest in marginal sea, GLORYS12 has the best performance in the global ocean especially in tropical regions. Comparatively, ECCO2 has the overall worst performance to reproduce SSS states and variations by showing the largest discrepancies with CMEMS L4 SSS.

Circulation structure and dynamic characteristics of Western Tropical Indian Ocean associated with monsoon transitions

The circulation structure in the western tropical Indian Ocean (WTIO) was investigated based on surface drifters and Simple Ocean Data Assimilation (SODA), with particular attention to the characteristics of the circulation structure associated with seasonal monsoon transitions. Surface drifter trajectories manifest three distinct seasonally dependent patterns of western boundary currents in the WTIO. The northward Somali Current (SC) flows across the equator to ∼10 °N in the boreal summer (June to August; JJA). The northward SC turns offshore near the equator during monsoon transitions. The southward SC feeds the South Equatorial Countercurrent together with the northward East African Coast Current in the boreal winter (December to February; DJF). While during the monsoon transition (MAM and SON), drifters prefer to turn eastward and feed the strong equatorial currents. Based on satellite observations, the results of a balanced diagnostic model demonstrate that the geostrophic component Uζ and the wind-driven componentUτ predominate the mean state and the seasonal variations of circulation in the WTIO. The vertical motion shows that upwelling primarily occurs along the coasts of Somali and Oman and is induced by offshore Ekman transport. Ekman transport and associated vertical motions constitute meridional overturning circulation. The SODA results confirm the existence of an equatorial roll in the boreal summer and winter. The results elucidate the dynamic relationships between 3-D circulation and monsoon transitions in the WTIO.

Interannual variations and their dynamic mechanisms of wintertime temperature inversions in the Gulf of Alaska

Using the Simple Ocean Data Assimilation Version 2.2.4 dataset from 1950 to 2010, we analyzed the interannual variations in wintertime temperature inversions in the Gulf of Alaska (GOA), and the linkages to the Aleutian Low are also examined. The results show that the climatological wintertime temperature inversions is predominantly distributed in the northwestern GOA (NWGOA) and northern GOA (NGOA), in which it is stronger in the NWGOA than in the NGOA. Interannual variations in the temperature difference (∆T) are pronounced and are mainly controlled by the temperature minimum (Tmin) of the inversions layer. The temperature inversions layer became warmer and shallower during 1950–2010, among Tmin and the temperature maximum (Tmax) was notably warming, and the upper edge depth (Dmin) and lower edge depth (Dmax) revealed significant shoaling. ∆T decreased by 0.12 °C from 1950 to 2010 in the NWGOA but had no trend in the NGOA. The interannual variations in wintertime temperature inversions are controlled by the mixed-layer temperature anomalies and are closely correlated with the changes in the Aleutian Low. The weakened (deepened) Aleutian Low during strong (weak) ∆T winters could cause the weakening (enhancement) of the cyclone wind field in the North Pacific subarctic region, which is conducive to slowing down (spinning up) the flow of the Alaskan Gyre and the transportation of warm air into the GOA. Thus, a negative (positive) Tmin anomalies within the mixed layer is larger than Tmax anomalies, resulting in a larger (smaller) ∆T; meanwhile, the strong (weak) cooling effect leads to a deeper (shallower) Dmax. The interannual variations in the wintertime temperature inversions could be influenced by net heat flux and advection anomalies in the NWGOA, but only caused by net heat flux anomalies in the NGOA.

The effects of tropical cyclones on characteristics of barrier layer thickness

The impact of tropical cyclones on the characteristics of barrier layer (BL) thickness is investigated in this study in combination with observations and numerical simulations. Statistical results based on Simple Ocean Data Assimilation reanalysis (SODA) data and Argo float measurements reveal a significant effect of TCs on the BL characteristics. The BL thickness increases remarkably with the TC approaching, reaches its maximum 1–5 days after the TC passage, and recovers to its pre-storm state within 30 days on average. The peak increase in BL thickness is slightly rightward biased relative to the TC track, reaching ∼1.31 m (26.93%) relative to the pre-storm state as revealed by SODA data. The changes in BL thickness show a strong correlation with TC characteristics in terms of intensity and translation speed, tending to be more significant with more intense or slower-moving TCs. The thickening of the isothermal layer on the right of TC tracks and shallowing of the mixed layer act together to determine the BL development. The three-dimensional Price–Weller–Pinkel (3DPWP) ocean model is applied to explore the influence of precipitation on BL thickness. The results show that the precipitation tends to decrease the mixed layer depth while the vertical mixing of TCs deepens the isothermal layer depth, both of which act together to increase the BL thickness.

Significant Difference of the Summertime Eastward Jet Enhancement in the South China Sea During the El Niño Developing Summers of 1982 and 1997

AbstractThe interannual variation of the South China Sea (SCS) summertime eastward jet (SEJ) contributes to the regional climate and ecology. Based on the Simple Ocean Data Assimilation data set, this study conducts a case analysis of SEJ in the SCS during two El Niño developing years, 1982 and 1997. In both years, the summer‐mean circulation presented a stronger SEJ with an obvious dipole pattern; however, the enhancement of SEJ was significantly weaker in 1997 than that in 1982. The reasons for enhanced SEJ and the difference of the enhancement magnitude (e.g., 256% and 52%) between 1982 and 1997 are explored. The climatological summer‐mean southwesterly wind stress is strongest in the middle SCS and decreases northward and southward (i.e., an arch‐shaped structure), forming a wind stress curl field conducive to the generation of SEJ. There is a low‐level anticyclonic anomaly during El Niño developing summer, with its northern flank enhancing the SCS monsoon. However, the structures of wind anomaly in the SCS are different in 1982 and 1997, which may relate to the earlier or later development of El Niño events modulated by the eastward migration of Madden‐Julian oscillation. In 1982, the northern flank of the anomalous anticyclone strengthened the climatological arch‐shaped structure, effectively enhancing the wind stress curls and SEJ. Whereas, in 1997, the northward deviation of the northern flank weakened the arch‐shaped structure north of 11°N, reduced the positive wind stress curl around 11°N–14.2°N, and caused the weaker enhancement of SEJ in 1997 than in 1982.

Seasonal variation of deep vertical velocity in the South China Sea

On the basis of the Simple Ocean Data Assimilation (SODA) and the Ocean General Circulation Model for the Earth Simulator (OFES), it is surprised that a distinct seasonal variation is found in the deep vertical velocity fields of the South China Sea (SCS). In summer, an upwelling band extending from the northeast to the southwest across the SCS deep basin is mainly located in the interior region of the basin, surrounded by the downwelling areas situated in the marginal region of the basin. In winter, the vertical motion is almost completely reversed, which is also enhanced in its strength and transport. A more extended downwelling band in winter replaces the upwelling band in summer, and the upwelling occurs in the marginal region. The upwelling or downwelling in the interior region of the basin is compensated by the reverse flow near the marginal basin in summer or winter, maintaining the balance of the whole deep basin without water exchange. The seasonal structures of potential density and potential temperature are consistent with the seasonal variation of the SCS deep vertical velocity. In the interior region, their isolines uplift in summer and drop in winter. The seasonal variation of the SCS deep vertical velocity in the interior region also has a good correspondence with that of basin-scale horizontal circulation, the seasonal pattern of which is cyclonic in summer and anticyclonic in winter. Just as the vertical transports always maintain a balanced, the vorticity averaged over the entire basin always remains positive, and the values in winter are one order of magnitude smaller than that in summer. This correspondence can be explained by the Sverdrup relation. The mechanism of the seasonal variation of the SCS deep vertical velocity may be related to the seasonal deepwater overflow through the Luzon Strait.

Interpretation of Subsurface Salinity EOFs on Southern ECS Shelf Using SODA Reanalysis: Large‐Scale Patterns and Seasonal to Interannual Variations

AbstractIn the southern East China Sea (ECS), low‐salinity shelf water is distinguished from high‐salinity Kuroshio water. Neutral density solution of subsurface salinity in southern ECS with Empirical Orthogonal Function (EOF) analysis of Simple Ocean Data Assimilation (SODA) reanalysis data (1958‐2008) is presented. This study focuses on seasonal to interannual variations of large‐scale patterns. We choose isopycnal 24.5 as the representative of subsurface layers, which is the deepest of the Kuroshio subsurface that can outcrop to sea surface during winter and early spring. We conducted EOF both including and excluding the seasonal signal. The results show that annual cycles dominate the first two leading EOF modes, EOF‐1 representing inner‐shelf oscillation, and EOF‐2 outer‐shelf oscillation. However, EOF‐2 also shows significant interannual variability. To this end, we removed the seasonal signal from the dataset and recalculated EOF. We found that the interannual EOF‐1 is of cross‐shelf in spatial pattern and shows significant interannual variability. This suggests that seaward penetration of the shelf water and shelfward intrusion of the Kuroshio that mainly occur in winter and early spring are a pair of contradictions in the two‐way intrusions, which are modulated by significant interannual variability. We also found that the isopycnal extending abnormally northward and outcropping in early spring corresponds to significant non‐intrusions of the Kuroshio. In the underlying dynamics, oceanic stratification, besides topography uplifting, plays an important role in the subsurface intrusion of Kuroshio off northeast Taiwan.