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We present a newly developed upper-thermocline, open-ocean biogeochemical flux model that is complex and flexible enough to capture open-ocean ecosystem dynamics but reduced enough to incorporate into highly resolved numerical simulations and parameter optimization studies with limited additional computational cost. The model, which is derived from the full 56-state-variable Biogeochemical Flux Model (BFM56; Vichi et al., 2007), follows a biological and chemical functional group approach and allows for the development of critical non-Redfield nutrient ratios. Matter is expressed in units of carbon, nitrogen, and phosphate, following techniques used in more complex models. To reduce the overall computational cost and to focus on upper-thermocline, open-ocean, and non-iron-limited or non-silicate-limited conditions, the reduced model eliminates certain processes, such as benthic, silicate, and iron influences, and parameterizes others, such as the bacterial loop. The model explicitly tracks 17 state variables, divided into phytoplankton, zooplankton, dissolved organic matter, particulate organic matter, and nutrient groups. It is correspondingly called the Biogeochemical Flux Model 17 (BFM17). After describing BFM17, we couple it with the one-dimensional Princeton Ocean Model for validation using observational data from the Sargasso Sea. The results agree closely with observational data, giving correlations above 0.85, except for chlorophyll (0.63) and oxygen (0.37), as well as with corresponding results from BFM56, with correlations above 0.85, except for oxygen (0.56), including the ability to capture the subsurface chlorophyll maximum and bloom intensity. In comparison to previous models of similar size, BFM17 provides improved correlations between several model output fields and observational data, indicating that reproduction of in situ data can be achieved with a low number of variables, while maintaining the functional group approach. Notable additions to BFM17 over similar complexity models are the explicit tracking of dissolved oxygen, allowance for non-Redfield nutrient ratios, and both dissolved and particulate organic matter, all within the functional group framework.

A three-dimensional ocean general circulation model (Princeton Ocean Model) along with hydraulic calculations were used to evaluate the velocity of currents from the Sea of Azov into the Black Sea, which form at the displacement of domains of higher atmospheric pressure from northern rhumbs. Flow velocity was analyzed at different sections in the Kerch Strait for meteorological situations with the highest rise of atmospheric pressure over period 1948–2017 according to data of NCEP/NCAR reanalysis. The possible increase in flow velocities due to the local deepening of the channel at bridge pillars and the compression of jets before the cross-section at Tuzla Island was determined. The available hydrometeorological data were used to show the recurrence of the cases of increase of atmospheric pressure above the Azov–Black Sea region in 2005–2017.

In this study, both an atmospheric model [Weather Research and Forecasting (WRF) model] and an atmosphere (WRF)-ocean (Princeton Ocean Model; POM) coupled model are used to simulate the tropical cyclone (TC) Kaemi (2006). By comparing the simulation results of the models, effects of oceanic elements, especially the TC-induced sea surface temperature (SST) cooling, on the simulated TC size and destructiveness are identified and analyzed. The results show that there are no notable differences in the simulated TC track and its intensity between the uncoupled and coupled experiments; however, there are large differences in the TC size (i.e., the radius of gale-force wind) between the two experiments, and it is the TC-induced SST cooling that decreases the TC size. The SST cooling contributes to the decrease of air-sea moisture difference (ASMD) outside the TC eyewall, which subsequently leads to the decreases in surface enthalpy flux (SEF), radial sea-level pressure gradient, absolute vorticity advection, and wind speed outside the TC eyewall. As a result, the TC size and size-dependent TC destructive potential all decrease remarkably.

Tidal characteristics in the well-known Coastal Marine Proving Ground near Chudao Island located in Shandong Province, China, are firstly investigated based on Princeton Ocean Model (POM) with a generalized coordinate system. Numerical results having been validated by available observations, the ensemble transform–based sensitivity method that calculates the gradient of forecast error variance reduction is used to identify sensitive areas of the water level and the current velocity in the Marine Proving Ground and its vicinity. Sensitive areas of the water level are mainly distributed around Chudao Island, the spatial range of which distributes smaller than that of the current velocity. When sensitivities of the water level and the current velocity are considered together, the coincidence areas serve as the most appropriate areas for adaptively deploying observation instruments. We found that a particular area west of Chudao Island is the most appropriate area for the hydrological observations in the Marine Proving Ground, which provide an insight into rational targeted observation analysis in tide-dominated shallow water areas.

This study explores the influence of Stokes drift and the thermal effects on the upper ocean bias which occurs in the summer with overestimated sea surface temperature (SST) and shallower mixed layer depth (MLD) using Mellor-Yamada turbulence closure scheme. The upper ocean thermal structures through Princeton ocean model are examined by experiments in the cases of idealized forcing and real observational situation. The results suggest that Stokes drift can generally enhance turbulence kinetic energy and deepen MLD either in summer or in winter. This effect will improve the simulation results in summer, but it will lead to much deeper MLD in winter compared to observational data. It is found that MLD can be correctly simulated by combining Stokes drift and the thermal effects of the cool skin layer and diurnal warm layer on the upper mixing layer. In the case of high shortwave radiation and weak wind speed, which usually occurs in summer, the heat absorbed from sun is blocked in the warm layer and prevented from being transferred downwards. As a result, the thermal effects in summer nearly has no influence on dynamic effect of Stokes drift that leads to deepening MLD. However, when the stratification is weak in winter, the thermal effects will counteract the dynamic effect of Stokes drift through enhancing the strength of stratification and suppress mixing impact. Therefore, the dynamic and thermal effects should be considered simultaneously in order to correctly simulate upper ocean thermal structures in both summer and winter.

The Caspian Sea is the largest enclosed basin on Earth and a unique subject for the analysis of tidal dynamics. Tides in the basin are produced directly by the tide-generating forces. Using the Princeton Ocean Model (POM), we examine details of the spatial and temporal features of the tidal dynamics in the Caspian Sea. We present tidal charts of the amplitudes and phase lags of the major tidal constituents, together with maps of the form factor, tidal range, and tidal current speed. Semi-diurnal tides in the Caspian Sea are determined by a Taylor amphidromic system with anticlockwise rotation. The largest M2 amplitude is 6 cm and is located in Türkmen Aylagy (called Turkmen Bay hereafter). For the diurnal constituents, the Absheron Peninsula separates two individual amphidromes with anticlockwise rotation in the north and in the south. The maximum K1 amplitudes (up to 0.7–0.8 cm) are located in (1) the south-eastern part of the basin, (2) Türkmenbaşy Gulf, (3) Mangyshlak Bay; and (4) Kizlyar Bay. As a result, the semi-diurnal tides prevail over diurnal tides in the Caspian Sea. The maximum tidal range, of up to 21 cm, has been found in Turkmen Bay. The strongest tidal currents have been located in the straits to the north and south of Ogurja Ada, where speeds reach 22 and 19 cm s−1, respectively. Numerical simulations of the tides using different mean sea levels (within a range of 5 m) indicate that spatial features of the Caspian Sea tides are strongly sensitive to changes in mean sea level.

A storm surge hindcast for the west coast of Canada was generated for the period 1980–2016 using a 2D nonlinear barotropic Princeton Ocean Model forced by hourly Climate Forecast System Reanalysis wind and sea level pressure. Validation of the modeled storm surges using tide gauge records has indicated that there are extensive areas of the British Columbia coast where the model does not capture the processes that determine the sea level variability on intraseasonal and interannual time scales. Some of the discrepancies are linked to large-scale fluctuations, such as those arising from major El Niño and La Niña events. By applying an adjustment to the hindcast using an ocean reanalysis product that incorporates large-scale sea level variability and steric effects, the variance of the error of the adjusted surges is significantly reduced (by up to 50%) compared to that of surges from the barotropic model. The importance of baroclinic dynamics and steric effects to accurate storm surge forecasting in this coastal region is demonstrated, as is the need to incorporate decadal-scale, basin-specific oceanic variability into the estimation of extreme coastal sea levels. The results improve long-term extreme water level estimates and allowances for the west coast of Canada in the absence of long-term tide gauge records data.

The object of the present study is mesoscale sea level oscillations in the Caspian Sea being the largest inland water body on the Earth. The main forces inducing sea level oscillations in this frequency range are variations in air pressure, wind stress, and tidal potential. These factors form a wide range of the Caspian Sea level variability including storm surges, seiches, and tides. To investigate the features of these oscillations, the POM (Princeton Ocean Model) numerical model was adapted to the Caspian Sea conditions. The tide-generating force in the equations of motion was specified through the tidal potential gradients over the Caspian Sea area. NCEP/CFSR reanalysis data are used to calculate meteorological impacts on the sea surface (wind stress and air pressure). The numerical model simulates well the statistical characteristics of mesoscale sea level variability in the Caspian Sea including seiches and tides.

Oceanographic observations carried out during 2016 and 2017 onboard INS Sagardhwani in the Southeastern Arabian sea are used to study the inter-annual variability of the upwelling. In 2016, the strong upwelling signatures are noticed in the observations (SST < 27°C and strong up-slopping of isotherms) as well as in the satellite derived sea level anomaly data. Whereas in 2017 the low sea level in June (-2 cm) are weakened during the mid of July (+3 cm) along the southern track (8 °N and 9 °N). This decrease in the strength in 2017 can be attributed to two major reasons. One is the presence of an anti-cyclonic eddy along the coast (8.5 °N, 76.5 °E) weakens the upwelling processes and second is the weak northerly component of the wind compared to 2016. In addition, Lakshadweep low is less prominent and situated towards the southern side (around 7°N) of its usual region of occurrence in 2017. The inter-annual variability of upwelling during July 2016 and 2017 is investigated using the 3D ocean model Princeton Ocean Model. Experiments with model in different combinations of forcing reveals that the alongshore wind component is the major parameter influencing the upwelling characteristics during these periods.

Coastal-trapped waves (CTWs) in Jervis Bay were investigated using a Jervis Bay Ocean Model (JBOM), based on the Princeton Ocean Model. Under the typical temperature stratification in Jervis Bay in summer, the first three modes of external CTWs can scatter into the bay. The wind stress inside Jervis Bay can generate CTWs, and the wind stress on the adjacent shelf can also generate CTWs in the bay by oscillations at the bay's opening, which are associated with temperature fluctuations there. The actual subinertial CTWs in Jervis Bay are a result of the interference of these CTWs. The amplitudes of the first three CTW modes were calculated from the observed sea level data. Three numerical experiments were designed to identify the major forcing for the observed subinertial temperature oscillations in Jervis Bay during an observational program in the summer of 1988/89. It was found that the local wind stress was the major contributor to the observed oscillations.

A method based on the use of statistical models and mathematical procedures to obtain regular information on the temperature and salinity of the Sea of Azov in the form of maps of their vertical and surface distribution is proposed. We used the measurements of temperature and salinity for the period 1913–2012 and the observations data from MODIS-Aqua/Terra instruments regularly passing over the Sea of Azov, and the simulation results of three-dimensional hydrodynamic Princeton Ocean Model supplemented by mathematical procedures. The possibility of the operative recovery of salinity values is based on regression statistics on the bio-optical characteristics index34 = RRS(531)/RRS(488) and bbp(555). They are obtained from remote sensing observations and indicate the total absorption of light and its scattering by suspended particles in top layer of water.

Persian Gulf (PG) is a semi-enclosed water basin that is connected to the Gulf of Oman through the Strait of Hormuz. There are different forcing and climatic parameters influencing the thermocline development in the PG from winter to summer. These factors include tide, river inflow, solar radiation, evaporation, northwestern wind, and water exchange with the Gulf of Oman. In fact, the thermocline, which is often observed in the oceans and open seas, can be considered as a seasonal phenomenon in the ocean. In the present study, it is studied theoretically; and compared with the results of the Princeton Ocean Model (POM) in the PG. During winter to summer, solar heating created an intense thermocline that decoupled the surface mixed layer from the interior water. The data are reviewed as the measurements collected in 1992 and recent modeling results. Overall, through a theoretical study, it is concluded that thermocline formation is a seasonal phenomenon in the PG.

The coastal area located in front of the Volturno river's estuary (Gulf of Gaeta, central-eastern Tyrrhenian Sea) has been synoptically sampled during seven surveys, between June 2012 and October 2014. The vertical profiles of temperature and salinity have been acquired on a high resolution nearly-regular grid, in order to describe the spatial and temporal variability of the water masses characteristics. Moreover, to provide a first assessment of the steady circulation at small scale, the three-dimensional velocity field associated to each survey has been obtained through the full momentum equations of the Princeton Ocean Model. The data analysis has shown the entire water column characterized by an evident thermal cycle and a vertical thermohaline structure dominated by three types of water masses: the freshwater of river's origin, the saltier coastal Tyrrhenian waters and transitional waters, resulting from the mixing of them. The freshwater inflow strongly affected the density distribution, causing a strong temporal variability in the upper layer. Its impact was more evident in winter inducing also a temperature inversion along the water column. In case of rainy events, its effect was clear also in condition of high vertical temperature stratification, forming a surface-trapper layer characterized by high density gradients. Together with wind forcing, they contributed to the formation of small scale shallow features, such as longshore currents, cyclonic and anticyclonic eddies. The latter influenced the vertical stratification and modify the coastal circulation preserving the transitional waters from the surrounding saltier ones.

Level and current oscillations in the basin of the Sea of Azov have been studied by hydrodynamic modeling using the Princeton ocean model (POM). The hypothesis on the role of the resonance mechanism in the occurrence of extremely large amplitudes of storm surge and seiche oscillations depending on the velocity and time of motion of atmospheric fronts of the Sea of Azov has been tested. It is found that at the same wind, pressure perturbations moving over the Sea of Azov induce forced oscillations, and after the perturbations cease, free oscillations with amplitudes that are 14% higher than those obtained at constant atmospheric pressure. It is shown that the motion of the atmospheric front (whose velocity and time are selected under the assumption that waves with maximum amplitudes are generated) plays an important but not decisive role in the formation of the structure of currents and level oscillations in the Sea of Azov.

Ways of combined usage of data obtained by the satellite sounding of the marine surface along with modeling approaches are considered. The technique of data application is proposed to combine satellite surveys and forecasts using the hydrodynamic Princeton Ocean Model (POM). Based on this, information is provided on transfer directions, particle sizes, and particulate matter concentrations at the time of complete or partial absence of satellite images. The satellite multispectral images were treated using an approach based on the calculations of the total indices of light absorption or backscattering by seawater containing particulate matter of various origins. As the information sources, data from the MODIS device of the Aqua satellite for 2013–2014 were used. The analysis of the correspondence of modeling and survey information confirmed the efficiency of regular usage of satellite data.

The Princeton Ocean Model (POM) was used to investigate an upwelling event in Jervis Bay, New South Wales (SE Australia), with varying wind directions and strengths. The POM was adopted with a downscaling approach for the regional ocean model one-way nested to a global ocean model. The upwelling event was detected from the observed wind data and satellite sea surface temperature images. The validated model reproduced the upwelling event showing the input of bottom cold water driven by wind to the bay, its subsequent deflection to the south, and its outcropping to the surface along the west and south coasts. Nevertheless, the behavior of the bottom water that intruded into the bay varied with different wind directions and strengths. Upwelling-favorable wind directions for flushing efficiency within the bay were ranked in the following order: N (0°; northerly) > NNE (30°; northeasterly) > NW (315°; northwesterly) > NE (45°; northeasterly) > ENE (60°; northeasterly). Increasing wind strengths also enhance cold water penetration and water exchange. It was determined that wind-driven downwelling within the bay, which occurred with NNE, NE and ENE winds, played a key role in blocking the intrusion of the cold water upwelled through the bay entrance. A northerly wind stress higher than 0.3 N m−2 was required for the cold water to reach the northern innermost bay.

Longterm hourly data from 28 tide gauges were used to examine the main features of tides in the Black Sea. The tides in this basin are directly caused by tide-generating forces and the semidiurnal tides prevail over diurnal tides. Based on the Princeton Ocean Model (POM), a numerical model of tides in the Black Sea and adjacent Sea of Azov was developed and found to be in good agreement with tide gauge observations. Detailed tidal charts for amplitudes and phase lags of the major tidal harmonics in these two seas were constructed. The results of the numerical modelling and observations reveal for the semidiurnal tides the presence of an amphidromy with clockwise rotation and another one with counterclockwise rotation for the diurnal tides, both located in the central part of the sea near the Crimean Peninsula. Therefore, for this part of the sea the amplitudes of harmonics M2 and K1 are less than 0.1 cm. Relatively larger M2 amplitudes are observed on the east and west coasts of the sea (2–3 cm). The maximum amplitude of the harmonic M2 was found at Karkinit Bay—up to 4.5 cm—while the maximum tidal range varies from 1 cm near the Crimean Peninsula to 18–19 cm in the Dnieper–Bug Estuary and Karkinit Bay. Radiational tides, initiated mainly by sea breezes, make an important contribution to the formation of tidal oscillations in the Dnieper–Bug Estuary.

The effect of seawater movement through the Kerch Strait for extreme deviations in the level and speed of currents in the Sea of Azov caused by the action of climate wind fields has been studied using the Princeton ocean model (POM), a general three-dimensional nonlinear model of ocean circulation. Formation of the water flow through the strait is caused by the long-term action of the same type of atmospheric processes. The features of the water dynamics under conditions of changing intensity and active wind direction have been studied. Numerical experiments were carried out for two versions of model Sea of Azov basins: closed (without the Kerch Strait) and with a fluid boundary located in the Black Sea. The simulation results have shown that allowance for the strait leads to a significant change in the velocities of steady currents and level deviations at wind speeds greater than 5 m/s. The most significant effect on the parameters of steady-state movements is exerted by the speed of the wind that generates them; allowance for water exchange through the strait is less important. Analysis of the directions of atmospheric circulation has revealed that the response generated by the movement of water through the strait is most pronounced when a southeast wind is acting.

We explored the variability of the Egyptian shelf zone circulation connected to atmospheric forcing by means of a numerical simulation of the general circulation. A high resolution model grid was used at 1/60° horizontal resolution and 25 sigma layers. The simulation was carried out using the most recent version of the Princeton Ocean Model (POM). The initialised model was run the whole year of 2006 using the analysis forcing data for the same year obtained from ECMWF and MFS (Mediterranean Forecasting System, Pinardi et al., 2003). The model skills were evaluated by means of the root mean square error (RMSE) and correlations. The Egyptian Shelf Model (EGYSHM) simulation suggests the presence of an Egyptian Shelf Slope Current (ESSC), which is flowing eastward at different depths in the domain. We found that the maximum velocity of the ESSC [0.25 m/s] is located near the continental slope during the summer time, while in winter the velocity of ESSC is weaker [0.12 m/s] in the same location. The ESSC appears to be directly affected by Mersa-Matruh gyre system. EGYSHM reproduced the main region circulation patterns, especially after adding the Nile River outflow. We found that wind stress is crucial to force the circulation of the Egyptian shelf zone. EGYSHM SST was significantly correlated to satellite SST in all months at a 95% confidence limit, with a maximum of 0.9743 which was obtained in May 2006. The RMSE between EGYSHM and Argo floats salinity data was about 0.09. We compared our results with satellite altimetry to verify the positions and shapes of mesoscale features.

An operational three-dimensional oil spill model is developed by the National Marine Environmental Forecasting Center (NMEFC), State Oceanic Administration, China, and the model has been running for 9 a. On June 4 and 17, 2011, oil is spilled into the sea water from two separate oil platforms in the Bohai Bay, i.e., Platforms B and C of Penglai 19-3 oilfield. The spill causes pollution of thousands of square kilometres of sea area. The NMEFC’s oil spill model is employed to study the Penglai 19-3 oil-spill pollution during June to August 2011. The wind final analysis data of the NMEFC, which is based on a weather research and forecasting (WRF) model, are analyzed and corrected by comparing with the observation data. A corrected current filed is obtained by forcing the princeton ocean model (POM) with the corrected wind field. With the above marine environmental field forcing the oil spill model, the oil mass balance and oil distribution can be produced. The simulation is validated against the observation, and it is concluded that the oil spill model of the NMEFC is able to commendably simulate the oil spill distribution. Thus the NMEFC’s oil spill model can provide a tool in an environmental impact assessment after the event.