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The upper layer, wind-driven circulation of the South China Sea (SCS), its through-flow (SCSTF) and the Indonesian through flow (ITF) are simulated using a high resolution model, FVCOM (finite volume coastal ocean model) in a regional domain comprising the Maritime Continent. The regional model is embedded in the MIT global ocean general circulation model (ogcm) which provides surface forcing and boundary conditions of all the oceanographic variables at the lateral open boundaries in the Pacific and Indian oceans. A five decade long simulation is available from the MITgcm and we choose to investigate and compare the climatologies of two decades, 1960–1969 and 1990–1999. The seasonal variability of the wind-driven circulation produced by the monsoon system is realistically simulated. In the SCS the dominant driving force is the monsoon wind and the surface circulation reverses accordingly, with a net cyclonic tendency in winter and anticyclonic in summer. The SCS circulation in the 90s is weaker than in the 60s because of the weaker monsoon system in the 90s. In the upper 50 m the interaction between the SCSTF and ITF is very important. The southward ITF can be blocked by the SCSTF at the Makassar Strait during winter. In summer, part of the ITF feeds the SCSTF flowing into the SCS through the Karimata Strait. Differently from the SCS, the ITF is primarily controlled by the sea level difference between the western Pacific and eastern Indian Ocean. The ITF flow, consistently southwestward below the surface layer, is stronger in the 90s. The volume transports for winter, summer and yearly are estimated from the simulation through all the interocean straits. On the annual average, there is a ∼5.6 Sv of western Pacific water entering the SCS through the Luzon Strait and ∼1.4 Sv exiting through the Karimata Strait into the Java Sea. Also, ∼2 Sv of SCS water enters the Sulu Sea through the Mindoro Strait, while ∼2.9 Sv flow southwards through the Sibutu Strait merging into the ITF. The ITF inflow occurs through the Makassar Strait (up to ∼62%) and the Lifamatola Strait (∼38%). The annual average volume transport of the ITF inflow from the simulation is ∼15 Sv in the 60s and ∼16.6 Sv in the 90s, very close to the long term observations. The ITF outflow through the Lombok, Ombai and Timor straits is ∼16.8 Sv in the 60s and 18.9 Sv in the 90s, with the outflow greater by 1.7 Sv and 2.3 Sv respectively. The transport estimates of the simulation at all the straits are in rather good agreement with the observational estimates. We analyze the thermal structure of the domain in the 60s and 90s and assess the simulated temperature patterns against the SODA reanalysis product, with special focus on the shallow region of the SCS. The SODA dataset clearly shows that the yearly averaged temperatures of the 90s are overall warmer than those of the 60s in the surface, intermediate and some of the deep layers and the decadal differences (90s − 60s) indicate that the overall warming of the SCS interior is a local effect. In the simulation the warm trend from the 60s to the 90s in well reproduced in the surface layer. In particular, the simulated temperature profiles at two shallow sites at midway in the SCSTF agree rather well with the SODA profiles. However, the warming trend in the intermediate (deep) layers is not reproduced in the simulation. We find that this deficiency is mostly due to a deficiency in the initial temperature fields provide by the MITgcm., Singapore. National Research Foundation (Singapore-MIT Alliance for Research and Technology Center. Center of Environment Sensing and Modeling Program)

Decadal variability of the South China Sea (SCS) sea surface temperature (SST) during 1982–2014 is investigated using observations and ocean reanalysis datasets. The SCS SST shows an abrupt transition from a cold-to-warm regime in the late 1990s. Based on the long-term SST variability two epochs are defined, 1982–1996 and 2000–2014 as cold and warm regimes respectively, spanning on either side of the 1997–1999 SCS warming. Despite the occurrence of strong El Nino induced warming events, the SST anomalies tend to be negative in the cold regime. Conversely during the warm regime, the positive SST anomalies have dominated over the La Nina driven cooling events. The cold (warm) SST regime is marked by net heat gain (loss) by the SCS. The long-term variations of net surface heat flux are mainly driven by the latent heat flux anomalies while the short wave flux plays a secondary role. Low-frequency variability of the South China Sea throughflow (SCSTF) appears to be closely related to the SCS SST regime shift. The SCSTF shows reversing trends during the cold and warm epochs. The weakened SCSTF in the warm regime has promoted the SCS warming by limiting the outward flow of warm water from the SCS. Meanwhile, enhanced SCSTF during the cold regime acts as a cooling mechanism and lead to persistent negative SST anomalies. The change in trend of the SCSTF and SST regime shift coincides with the switching of pacific decadal oscillation from a warm to cold phase in the late 1990s., Singapore. National Research Foundation (Singapore MIT Alliance for Research and Technology’s Centre for Environmental Sensing and Modeling interdisciplinary research program)

Among the semi-enclosed basins of the world ocean, the South China Sea (SCS) is unique in its configuration as it lies under the main southwest-northeast pathway of the seasonal monsoons. The northeast (NE) monsoon (November–February) and southwest (SW) monsoon (June–August) dominate the large-scale sea level dynamics of the SCS. Sunda Shelf at the southwest part of SCS tends to amplify Sea Level Anomalies (SLAs) generated by winds over the sea. The entire region, bounded by Gulf of Thailand on the north, Karimata Strait on the south, east cost of Peninsular Malaysia on the west, and break of Sunda Shelf on the east, could experience positive or negative SLAs depending on the wind direction and speed. Strong sea level surges during NE monsoon, if coincide with spring tide, usually lead to coastal floods in the region. To understand the phenomena, we analyzed the wind-driven sea level anomalies focusing on Singapore Strait (SS), laying at the most southwest point of the region. An analysis of Tanjong Pagar tide gauge data in the SS, as well as satellite altimetry and reanalyzed wind in the region, reveals that the wind over central part of SCS is arguably the most important factor determining the observed variability of SLAs at hourly to monthly scales. Climatological SLAs in SS are found to be positive, and of the order of 30 cm during NE monsoon, but negative, and of the order of 20 cm during SW monsoon. The largest anomalies are associated with intensified winds during NE monsoon, with historical highs exceeding 50 cm. At the hourly and daily time-scales, SLA magnitude is correlated with the NE wind speed over central part of SCS with an average time lag of 36–42 h. An exact solution is derived by approximating the elongated SCS shape with one-dimensional two-step channel. The solution is utilized to derive simple model connecting SLAs in SS with the wind speeds over central part of SCS. Due to delay of sea level anomaly in SS with respect to the remote source at SCS, the simplified solutions could be used for storm surge forecast, with a lead time exceeding 1 day., Singapore. National Research Foundation (Singapore MIT Alliance for Research and Technology), Singapore-MIT Alliance for Research and Technology. Center for Environmental Sensing and Modeling

Non-tidal sea level anomalies (SLAs) can be produced by many different dynamical phenomena over many time scales, and they can induce serious damages in coastal regions especially during extreme events. In this work, we focus on the SLAs in the South China Sea (SCS) to understand whether and how they can be related to the large-scale, seasonal monsoon system which dominates the SCS circulation and dynamics. We have two major objectives. The first one is to understand whether the NE (winter) and SW (summer) monsoons can be responsible for the persistent SLAs, both positive and negative, observed at the SCS ends along the main monsoon path. The second objective is to understand the SCS response as a free system upon onset/relaxation or sudden changes in the forcing wind. It is well known that sudden changes in the forcing mechanism induce free oscillations, or seiches, in closed, semi-enclosed basins and harbors, and we want to identify the possible seiche modes of the SCS. To our knowledge, these two objectives have not been previously addressed. We address these objectives both through observational analysis and modeling simulations. Multi-year tide-gauge data from stations along the coastal regions of the SCS are analyzed examining their spatial correlations. Strong negative correlations are found between the northeast and southwest stations at the two ends of the SCS under the path of the NE/SW monsoons. They correspond to wind-induced positive/negative sea level set-ups lasting for the entire monsoon season and changing sign from winter to summer. Short periods of negative correlations are also found between the SLAs at eastern and western stations during El Niño years in which the monsoons are weaker and have an enhanced E/W component inducing corresponding sea level set-ups. The tide-gauge station at Tanjong Pagar at the southwest SCS end near Singapore is chosen to study four extreme SLAs events in the observational record during 1999. Modeling simulations are carried out to reproduce them. The observed and modeled extreme SLAs agree quite well, both in the amplitude of the highest peak and in phase. Three main peaks are identified in the observational energy spectrum of the de-tided SLAs at the same station in 1999. Using Merian’s formula to evaluate the periods of seiches in idealized basins Wilson (Adv Hydrosci 8:1–94, 1972) the first two peaks (24.4 h and 11.9 h) are found to correspond to the first two seiche modes in the direction of the main, longer axis of the SCS. The third peak (8.5 h) is found to correspond to the seiche in the transversal, shorter axis. Finally, modeling simulations are carried out by suddenly dropping a circular bump of water in the quiescent basin at different locations to excite the seiches. The periods of the modeled peaks agree quite well with the observational ones, the first two periods being actually identical, Singapore-MIT Alliance for Research and Technology (Center for Environmental Sensing and Modeling (CENSAM))

In ∼1990 a new source of deep water formation in the Eastern Mediterranean was found in the southern part of the Aegean sea. Till then, the only source of deep water formation in the Eastern Mediterranean was in the Adriatic sea; the rate of the deep water formation of the new Aegean source is 1 Sv, three times larger than the Adriatic source. We develop a simple three-box model to study the stability of the thermohaline circulation of the Eastern Mediterranean sea. The three boxes represent the Adriatic sea, Aegean sea, and the Ionian seas. The boxes exchange heat and salinity and may be described by a set of nonlinear differential equations. We analyze these equations and find that the system may have one, two, or four stable flux states. We conjecture that the change in the deep water formation in the Eastern Mediterranean sea is attributed to a switch between the different states on the thermohaline circulation; this switch may result from decreased temperature and/or increased salinity over the Aegean sea.