جستجوی مقالات مرتبط با کلیدواژه « persian gulf » در نشریات گروه « فیزیک »

Eddies formation is an important oceanic phenomenon that plays a significant role in the transport of fluid in the ocean. The main eddy in the Persian Gulf is mainly due to factors such as wind, tide and density variations. This paper uses the HD model of MIKE3D packages to perform the simulations; first a large-scale flow model is implemented for the entire area of the Oman Sea and the Persian Gulf, and then the formation of mesoscale in the Persian Gulf and the Oman Sea is simulated by the output of Model 3 MIKE with a resolution of ten kilometers for 2013 in 30 layers of Sigma and Z coordinates. Almost all year round, a thermohaline stream enters the Oman Sea Persian Gulf and penetrates deeper areas, causing fluctuations in the temperature and salinity in the Oman Sea. This thermohaline flow that enters the Oman Sea causes temperature changes and these changes cause the formation of eddy in the Oman Sea. It was also seen that a coastal stream in the northwest direction from the north of the Strait of Hormuz enters the Persian Gulf and there is a southwest stream in the southern part of the strait. The main eddy in the Persian Gulf is clockwise and it was observed that the general shape of the eddy in the Persian Gulf is clockwise and the counterclockwise eddy in the center of the Persian Gulf becomes stronger from April to July and in August, it has the highest resolution. In this study, more attention was paid to the months when eddy has more clarity.

In this research, satellite has been used for the purpose of identifying and finding the waters of the PersianGulf in the Sea of Oman.Finding the subsurface water exiting the PersianGulf through the cross of the Strait of Hormuz by identifying the temperature characteristics of Oman's surface water in the area where the presence of subsurface water in the Persian Gulf has been confirmed in previous studies can lead to finding the subsurface water.In this study, the sea surface temperature data of OSTIA for the studied basin, which is the Persian Gulf and a part of the Oman Sea(47 to59.45degrees of east and 22.60 to 32 degrees of north)was prepared.Then, according to the studies based on the73-year measurement data available in the region and identifying the temperature range of the surface water of the Oman Sea(22.20-23.00C) and the subsurface water of the Persian Gulf(16.00-22.20C)superimposed on each other, the satellite data were filtered. In order to filter the data and draw the figures, it was used coding in MATLAB environment.The results show that the water of the Persian Gulf can be transported to the middle parts of the Oman Sea, surface water (temperature 28.5 to 30 degrees of centigrade)in the cold season in the range of58.5to59degrees of east and in the warm season it advances towards the longitudes up to 59.5 degrees of east.As a result, the infiltration rate of Persian Gulf water in the Oman Sea in the warm season is half a degree of longitude more than the cold season.

Persian Gulf (PG) is a shallow semi-enclosed sea that connects to the open ocean through the Strait of Hormuz. Thermocline occurs as a sharp decrease in temperature with depth in the subsurface layer as a result of water column classification in Persian Gulf on a seasonal basis. Impulses such as the northwest wind affect this process. In this paper, according to the results of Monte Michel research (1992) and the numerical study of Princeton ocean model (POM), with wind stress in both steady state and monthly average, the formation and development of summer thermocline in PG is investigated. The model results show that with the monthly variable wind, the thermocline develops as indicated by the summer observations. The formation of thermocline seems to decrease the dissolved oxygen in the water column due to lack of mixing as a result of induced stratification. The formation of thermocline seems to reduce the dissolved oxygen in the water column due to the lack of mixing, which is created as a result of water stratification. Also, the formation and development of thermocline as a fast temperature gradient in the water column affects the sound propagation used in offshore detection devices. According to the results of some sources of this research, The thermocline development happens more rapidly in Persian Gulf from spring to summer. Correlation coefficients of temperature and salinity between the model results and measurements were 0.85 and 0.80, respectively. In this paper, the research results obtained from the POM model are compared with the measurements. The rate of thermocline development was found to be between 0.1 to 0.2 meter per day in the Persian Gulf during the 6 months from winter to early summer

In this study, using filed data measurement and time series spectral analysis on velocity factors, the period for diurnal and semidiurnal tide elements of the current were determined. The direction of the residual currents showed a surface current into the Persian Gulf and another current out of the Gulf. This indicates that in this region, the anticlockwise gyre takes place at the same time as time stratification and thermocline. The velocity of the residual current is about 10 cm/s and the velocity of the tidal current is measured at 50 cm/s. the diagrams show that the tidal current has affected the temperature up to the 30 m depth and in lower depth, it has less effect on temperature. It also has a stronger effect in spring than in winter. Therefore, moving from surface to depth, as the water temperature decreases, the effect of the tide on the temperature is decreased. The maybe related to the formation of temperature gradient and thermocline in the spring or the back and forth movement of the tidal current which created the waves and caused the increase in the temperature and decrease in the salinity. Where there are stronger layers, there is a stronger gradient as well as stronger tide effect. Also, the effect of the tide on salinity on the surface is very weak while it is stronger in some depths which may be related to the area topography and back and forth movement of the tide current.

In this study, to investigate the seasonal changes in some biological parameters of the Persian Gulf, a coupled physical-biological ROMS model is used. The biological model coupled with the physical model has seven state variables includes two nutrients, phytoplankton, chlorophyll, zooplankton and small and large detritus (N2PChlZD2). The results show that the pattern of seasonal changes in chlorophyll-a in the Persian Gulf can be divided into two regions. The first region is the northwestern part, where the growth of chlorophyll begins in spring and extends eastwards along the southern coasts until late summer and early autumn. The amount of chlorophyll-a in this region throughout the year is higher than the other parts of the Gulf and also peaks in early spring. The second region, which includes the middle and east parts of the Persian Gulf blooms in summer and peaks from late summer until early autumn. Moreover the results also show that the pattern of growth and expansion of chlorophyll-a in the Persian Gulf are independent of the Sea of Oman pattern, and its changes follow the pattern of Persian Gulf currents. In addition, the results show that there is a high concentration of nitrate in the northwest of the Persian Gulf, that it is a good reason for beginning of the phytoplankton blooms from the northwestern part of the Persian Gulf and its extension to the other parts along with the regional currents.

The propagation of sound waves in shallow water is complex and unknown due to the special conditions of the surface and bed of water bodies. In recent years, the use of a wide range of application software to recognize this effect on the propagation of sound waves to improve the performance of sonar systems has increased. In shallow water and coastal areas, the interference caused by surface and seabed reflections is very important and effective. Several methods have been developed to model the propagation of sound waves. In the present research, the method of parabolic equations by considering the frequencies of 500, 1000 and 10000 Hz for the transmitter has been used to model the propagation of sound waves in the Persian Gulf. The results showed that the effects of the seabed are the main factor attenuating the energy of sound waves. Also, the highest penetration of sound waves in the bed layers occurred at frequencies lower than 1 kHz. The interaction of sound beams with the seabed is also increased, with increasing the depth of the transmitter and as a result more loss in the transmission path is recorded.

Nowadays, marine data containing both observational and measured values as well as the output of numerical models are largely available; But analyzing and processing this data is time consuming and tedious due to the heavy volume of information.Identifying and extracting eddies is one of the most important aspects of physical oceanography, and automatic detection algorithms of eddies are one of the most basic tools for analysing eddies. The general circulation of the Persian Gulf is a cyclonic circulation that is affected by tide, wind stress, and thermohaline forces. In this study, using the Mike model based on the three-dimensional solution of the Navier Stokes equations, assumption of incompressibility, Boussinesq approximation and hydrostatic pressure, the circulation in the Persian Gulf was modeled. Then a vector geometry algorithm has been used for detection of eddies in this region. Four constraints were derived in conformance with the eddy velocity field definition and characteristics in this algorithm. Eddy centers are determined at the points where all of the constraints are satisfied. The four constraints follow: (i) Along an east–west (EW) section, v has to reverse in sign across the eddy center, and its magnitude has to increase away from it; (ii) Along a north–south (NS) section, u has to reverse in sign across the eddy center, and its magnitude has to increase away from it: the sense of rotation has to be the same as for v; (iii) Velocity magnitude has a local minimum at the eddy center; and (iv) Around the eddy center, the directions of the velocity vectors have to change with a constant sense of rotation. The constraints require two parameters to be specified: one for the first, second, and fourth constraints and one for the third one. The first parameter, a, defines how many grids points away the increases in the magnitude of v along the EW axes and u along the NS axes are checked. It also defines the curve around the eddy center along which the change in direction of the velocity vectors is inspected. The second parameter, b, defines the dimension (in grid points) of the area used to define the local minimum of velocity. The main data used to detect eddies are numerical model outputs, including velocity components. These outputs are the result of numerical modeling with thermohaline and wind stress forces. In total, 4308 cyclonic and 2860 anticyclonic eddies are detected at the surface and 617 cyclonic and 329 anticyclonic eddies are found in the deepest layer, depth of 50 meters, for daily data during one year. The number of eddies is highest in winter, and the lowest in summer and the average radius of anticyclonic eddies is maximum in winter and minimum in summer for cyclonic eddies. Most eddies have a radius of 5-10 km and lifespan of 3-6 days. Also, as the lifespan of eddies increases, they penetrate deeper into the water. The percentage of eddy penetration or the ratio of the number of eddies of the deepest layer to the surface layer is 15% for cyclonic eddies and 10% for anticyclonic eddies. This indicates that the energy loss in the cyclonic eddies is less than in the anticyclonic eddies and is probably due to the alignment of the rotating eddy with the overall circulation of the Persian Gulf.

Sea Surface Temperature (SST) variability, especially its slow variability, creates a potentially predictable source for climate fluctuations. Therefore, the SST variability study sheds light at climate changes, marine life, and prediction of short term and long term climate variation. In this research, the trend and interannual variability of the Persian Gulf SST were analyzed by employing monthly detrended Optimum Interpolation Sea Surface Temperature (OISST) data in 1982-2018. According to the effects of teleconnection patterns on atmospheric and oceanic parameters in different regions, the correlation between NAO, IOD, and ENSO with Persian Gulf SST anomaly is considered in this research. For this purpose, OISST data and MEI.V2, IOD, and NAO indices from 1982 to 2018 were analyzed. The Climatological mean of Persian Gulf SST during this period is shown in figure 5. According to figure 5, northwest of the Persian Gulf was found to be the coolest and southeast of the Persian Gulf was the warmest regions of the Persian Gulf. According to the investigation of this research on monthly variability of the Persian Gulf SST, there are two main seasons with four months, including Summer (June, July, August, September), and Winter (December, January, February, March), and two transition periods with two months, including Spring (April, May), and Autumn (October, November). Based on figure 6, February was the coldest month of winter and August was the warmest month of summer. In both of these months the minimum temperature was observed in the northeast, and the maximum temperature in the southeast of the Persian Gulf. The strongest and the weakest temperature gradient were calculated to be 5 ̊C in winter and 2 ̊C in summer, respectively. There was more than 13 ̊C difference between the spatial mean temperature of February and August. Evaluation of the SST anomaly variance indicated that the maximum variance belonged to the northwest of the Persian Gulf at the coast of Khuzestan province and Kuwait and also to the southwest of the Persian Gulf on the coast of Bahrain, Qatar, and east of Saudi Arabia. Sea surface temperature time series trend triggered by global warming from 1982 to 2018 was calculated to be 0.4 ̊C per decade using the least linear square method. Spatial distribution of trend implies that the maximum trend is observed in the northwest of the Persian Gulf in Khuzestan province and Kuwait coast and the minimum trend is observed in the east and southeast of the Persian Gulf. According to the Pearson correlation method, the maximum (minimum) correlation was calculated to be -0.23 (0.16) employing ENSO (IOD) index considering 4(13) months of delays. The spatial distribution of the correlation between teleconnection patterns indices and the Persian Gulf SST anomaly is demonstrated in figure 9. Results of the analysis pointed out that regarding IOD index, the maximum correlation (0.18) was found at the northwest of the Persian Gulf and the minimum correlation (0.12) was observed at the southeast of the Persian Gulf. Regarding ENSO index, the maximum correlation (-0.24) was at the central region of the Persian Gulf and the minimum correlation (-0.18) was at the south of the Persian Gulf. Concerning NAO index, the maximum correlation (-0.20) was seen at the northwest and the southwest of the Persian Gulf, and the minimum correlation (-0.16) was at the northwest and southeast of the Persian Gulf, near the strait of Hormuz. Therefore, the spatial distribution of correlation between the teleconnection patterns indices and SST anomaly, reveals that there is no center with significant maximum correlation which could give the possibility of distinguishing these areas from the others.

Tidal asymmetry in the south-east of the Kish Island (Persian Gulf) is investigated in this study using water-level and velocity profile (3 layers) data recorded by an ADCP for a period of 35 days at a station with the depth of 12m. In the whole water column, the dominant current is forced by tide which periodically alters velocities in east (in high tide) and west (during low tide) directions. The weak residual current diverts current field as partially southward especially in two deep layers. Due to atmospheric forces, residual current partially disperse observed current from east-west direction in the upper layer. Tide is mixed mainly semidiurnal at the study area and principal triad tides K1-O1-M2 produce 13.66-day periodic asymmetries including an ebb-dominance and a flood-dominance during spring and neap tides respectively. Although, the contribution of the ebb-dominance asymmetry induced by this triad is dominant in all 35 days. During the whole period, shallow water components induce a flood-dominance asymmetry condition.

Wind-induced waves are the most complex waves among sea waves. In special circumstances such as extreme winds and storms however, it is essential to estimate and predict them correctly. In this research, the height and period of waves was investigated during winter Shamal wind using SPM method and a numerical simulation employing Coupled Ocean-Atmosphere-Wave Sediment Transport COAWST, in the northwest of the Persian Gulf in January 2015. The beginning of the winter Shamal wind coincides with the passage of a cold front over the Persian Gulf, when the wind speed increases and the direction of wind changes to north and northwest. According to the results simulated wave height and period from COAWST show better agreement with field data compared with those of SPM method. This conclusion is also verified with statistical methods such as RMSE. In both methods, the frequency spectrum of the region is single-peak. Besides, the peak of the spectrum of SPM and COAWST, shows under-prediction in comparison with the field data. According to the standard spectrums, the JONSWAP represents the closest wave spectrum of the area under investigation.

In this study, the turbulent properties of the bottom Ekman layer of the Persian Gulf is studied, using a Parallelized Large-Eddy Simulation Model (PALM). Three numerical experiments were carried out with emphasis on stratification effects. A reference experiments (EXP C) without vertical gradients of the potential temperature and salinity and two experiments with vertical gradient of the potential temperature and salinity. The initial values of the surface potential temperature and salinity and their vertical gradients, provided from in situ data, were chosen according to August (EXP A) and November (EXP N) condition of the Persian Gulf. The eastern part of the Iranian coastal area of the Persian Gulf near the Hormuz Strait was chosen because there is a considerable western current during the year in this area. Also, the sea is deep enough to observe a distinctive pycnocline layer which separates surface and bottom mixed layer. The domain size is 200m×200m×100m in x, y and z directions respectively. A pycnocline layer with 40m and 20m deep was considered for August and November, respectively. A Geostrophic current with 0.15m s^(-1) speed is supposed to flow in x direction over the rough sea bed. The bottom boundary condition of the momentum flux was set to Dirichlet in order to create a no-slip condition at the sea bed. The simulations were carried out for 48h to include at least two inertial periods and avoid inertial oscillations. The results showed that the stratification limits the bottom Ekman layer depth and it does not grow with time. While in EXP C, where the fluid is neutral, a rapid growth of the bottom Ekman layer is obvious during the first 20h and its maximum depth reaches 60m. The Ekman cross-stream current component cannot entrain into pycnocline layer and it vanished at the bottom of the pycnocline layer. In autumn in which the pycnocline layer is thinner, the Ekman spiral is broadened and the magnitude of the Ekman cross-stream current component is 25% larger in compare to summer. The maximum value of the Ekman cross-stream current component is about 0.04m s^(-1) in EXP C and EXP A while it is about 0.05m s^(-1) in EXP N. The hodograph of the horizontal velocity in EXP C is more similar to Ekman theoretical solution. The stream-wise component of the horizontal velocity decrease with the same rate near the sea bed in all experiments which implies that the stratification does not have much effect on bottom stress. It is concluded that when an intense pycnocline exists and the bottom mixed layer is thin, less time is needed to trigger the turbulence. The bulk turbulent kinetic energy in all experiments is the same. Since the bottom boundary is assumed adiabatic and there is no heat flux from the bottom, the heat budget in the neutral BBL is approximately conserved (molecular diffusion is not considerable compared). Then a pycnocline is necessary to maintain heat conservation after the formation of a mixed layer. These intensified pycnocline can be observed as distinctive peaks in vertical profiles of the buoyancy frequencies near the top and bottom of the stratified layer. The thickness of the intensified pycnocline grows with time and at the end of simulation reaches about few meters. These intensified pycnocline layers in November is thicker than that of August. Also at the bottom interface of the stratified, the shear stress increases.

This Paper Investigates and estimates the variations of sea surface salinity (SSS) in the Persian Gulf using moderate resolution imaging spectro-radiometer (MODIS) data on the Aqua satellite and the advanced microwave sounding Unit-B (AMSU-B) sensor on the NOAA-16 satellite in order to use remote sensing science for a more efficient and with more time distribution of salinity in the Persian Gulf. In this research a multiple-linear regression model in R software was developed using the data of MODIS and AMSU-B sensors. The data were obtained during a period of one year and fed to the R software. After processing the data in the R software, the correlation coefficient (R2) for salinity was calculated between field data and MODIS and AMSU-B sensors data. The correlation coefficients for MODIS and AMSU-B sensors were 0.86 and 0.85, respectively. Also, root mean square error (RMSE) between satellite data and in Situ data for salinity using MODIS and AMSU-B sensors were 0.62 Psu and 0.07 Psu respectively. The results show the accuracy of sensors for determining the sea surface salinity pattern in this study.

Recently, the occurrences of extreme events such as droughts have been on the rise almost worldwide. Several researchers speculated the chance of an increase in meteorological extreme conditions in relation to local climate change. Rainfall is the final response to complex global atmospheric phenomena and long-term prediction of rainfall remains a challenge for years to come. An accurate long-term rainfall prediction is necessary for water resources management, food production and maintaining flood risks. Several large-scale climate phenomena affect the occurrence of rainfall around the world; of these large - scale climate modes El Nino Southern Oscillation (ENSO) and Multivariate ENSO Index (MEI) are well known. Many studies have tried to establish the relationship between these climate modes for daily, monthly and seasonal rainfall occurrence around the world but the majority of these studies have not considered the effect of lagged climate modes on future monthly rainfall predictions.
Interannual to multidecadal natural local climate variability is afflicted by the El Niño/Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO) and Atlantic Multidecadal Oscillation (AMO). ENSO phenomenon on the tropical Pacific and also PDO are quite important because of their enormous impacts on hydro-meteorological disasters like droughts and floods. The El Niño-Southern Oscillation (ENSO) is strongly linked to the inter-annual to inter-seasonal modifications of Sea Surface Temperature (SST) over the Pacific Ocean equators. On the other hand, the Decadal Pacific Oscillation (PDO) is related to near decadal fluctuations of the Pacific SSTs in the northeastern parts of the ocean. The influence of these oscillations on the global climate is generally more obvious when the ENSO or PDO is in its extreme condition. For such circumstances, the SST deviance over a per-defined ocean waters are highly positive or negative (positive or negative period, respectively).
Identifying factors impacting the fluctuations in rainfall and forecasting seasonal trends over several months before any significant role in the planning and development of water resources, are among the significant factors impacting different areas of climate signals. Principal component analysis (PCA) was used in this study to explore the impact of climatic indices on the amount of wet and dry season’s precipitation variability in the Persian Gulf and Oman Sea watershed. PCA is used to reduce the dimensionality of spatially distributed time series of precipitation and to interpret spatial patterns, from a statistical viewpoint, through the distribution of significant eigenvectors that explain an important portion of the series variability. PCA can summarize the prevailing variability in a number of dependent factors into fewer principal components.
Wet and dry season data were explored from 22 rain gauge stations in the Persian Gulf and Oman Sea watershed in which 40 climatic indices are analyzed in the period of 1970-2014. PCA analysis is performed using PAST software for the area with 40 synoptic stations. Result showed that there are three variables that determine more than 96.6% of variance consists of NAO, AO and AMO in the dry season, while AO, Nino1 and SOI determine more than 97.8% of variance in the wet season. These climate indices can be attributed to precipitation changes over the Persian Gulf and Oman Sea in the dry and wet season, respectively.
The study also shows correlation between SPI of 23 rainfall gauges of the Persian Gulf and Oman Sea watershed and climatic signals. These are significant in large number of weather stations. Numbers of stations with significant correlations are 100% and 95% with NAO and AO in the dry season, whereas 85% and 65% have significant correlations with AO and Nino1 in wet season. The linkage between climatic signals and precipitation presented in this paper can be used as one of the important components for wet and dry season precipitation prediction over Iran southern stations

The Persian Gulf with subtropical climate is located between latitudes of 23-30 degrees, whit its coast adjoiner to Iraq, Kuwait, Saudi Arabia, Qatar and United Arab Emirates from one side and to Iran from the other side. The Persian Gulf’s width in widest part is 370 km and its length is 990 km. For people living near the sea and the surrounding coastal area as well as construction of onshore and offshore structures, knowledge and understating of the wind field and its variability is essential. In addition, the most common effect of wind is seen in wind driven currents, swells, upwelling and down-welling systems. Moreover wind stress plays a key role in the modeling of air sea interaction phenomenon, e.g., determination of the drag coefficient. Although other factors such as wind palfern and oceanic current are also contributing to the in determination of this coefficient but the wind is the main governing factor. In other words, any inaccuracy in determination of the sea surface wind field could cause a large over or under estimations in atmospheric and oceanic estimations.
This work is devoted to verify the effects of different initial and boundary condition in global data (using reanalysis and analysis datasets) on numerical simulations of WRF (Weather Research and Forecasting) model over the Persian Gulf area. The main obstacle in the verification and evaluation of a model simulation is the lack of observation data with fine spatial and temporal resolution, in particular for offshore areas. Fortunately, in onshore areas, the existence of weather stations has solved the problem somehow, and for offshore areas satellite data are found to be the best dataset considering the spatial coverage. In the present study, simulations of WRF model are compared with different type of observation data. In this research, two types of data are used for verifying the model, i.e. Synoptic stations data and Satellite data (QuikSCAT and ASCAT).
The WRF model version 3.4.1 is employed with ARW dynamical core for simulating of sea surface wind field over the Persian Gulf region. Considering the connection and information exchange between the domains, a two way nesting method is applied in simulations. As the goal was just to verify the effects of different initial and boundary conditions on simulations, therefore, for all the simulations the number of domains and their analogous grid sizes are considered the same. For these simulations three domains are considered the main domain approximately covers the whole are of the Middle East, from West and some parts of Far East with 36km spatial grid spacing. First nested domain covers the southern half of Iran along with marginal countries of Persian Gulf, with a 12km spatial grid resolution and ultimately, the innermost domain of the Persian Gulf that also includes some parts of Oman Sea with 4km grid spacing. The time step for simulations is assumed 216seconds and the time period for each simulation is 30hours, from which the first 6 hours are assumed as spin-up time. To provide the initial and boundary conditions three datasets of ERA-Interim (ECMWF Re-Analysis Interim), NCEP-FNL and NCEP-R2 are employed.
Along with lots of effective factors, results from this research show that one of the sources of error in the WRF model wind simulations is the selection of initial and boundary conditions (input data). The obtained results of this work reveal that for the surface wind hindcast simulations over the Persian Gulf using WRF model, the ECMWF ERA-Interim data is a more suitable dataset to provide the initial and boundary conditions, rather than the NCEP-FNL and NCEP-R2 data. However, the NCEP-FNL is an alternative data set when the ERA-Interim data has some lacks.

Detecting by the means of the marine magnetic anomaly maps is one of the detection and passive controlling methods for the surface and subsurface equipments including the submarines. Considering the point that nowadays, that submarines are made very silent in an acoustic view, detection and recognition of them by using acoustic detector in the sea has become hard and almost impossible. Thus, using magnetic anomaly methods seems to be necessary. By using this method, the fluctuation in the earth's magnetic field due to a ferromagnetic object is detected and by the help of computer processing, the magnetic map of the area is prepared. In this study, by processing and analyzing magnetometric data, a magnetic anomaly map was created in the region of the Persian Gulf near the Genaveh coast, after necessary corrections. Magnetic anomalies were first used to highlight superficial anomaly using the first-order derivative filter. The maps are further processed using Euler de-convolution method to determine the depth of anomalies. Both methods show surface abnormalities with low depth in the north and south in the lower and middle regions of the study area.

Tidal observations have been widely used for a variety of applications. Realistic functional and stochastic models of tidal observation are then required. The functional model is complete if one knows the tide characteristics such as tidal frequencies (M2 and S2 for instance). The stochastic model is complete if we know noise characteristics of tidal observations. There is always a prediction error between the predicted values and the observed tide heights. This can be investigated when taking the noise characteristics of tidal time series observations. Functional model identification is however the subject of discussion in the present contribution. Tide data are frequently used for different applications such as safe navigation. Real tide gauge data can be expressed by their tidal constituents (frequencies) and a noise structure. Using tidal frequencies and tidal observations one can employ the functional model to predict tide. Therefore identifying tidal frequencies is an important issue for tidal analysis. So far, most of the available methods to determine tidal frequencies have been based on the theory, and sea level height observations have not seriously been used to extract tidal frequencies. The theory-based methods usually apply the ephemeris of Moon, Sun and other planets to extract tidal frequencies without the use of tidal observations. Following-up the study by Amiri-Simkooei et al. (2014), we further focus on extracting tidal frequencies using tidal observations. For this purpose, we apply the least squares harmonic estimation (LS-HE) to the multivariate tidal time series. As a generalization of the Fourier spectral analysis, LS-HE is neither limited to evenly spaced data nor to integer frequencies. We may also note that the main tidal constituents may change from one area to another area. In this contribution, we use the data sets of eight coastal tide gauge stations in Persian Gulf and Oman Sea between 1999 and 2010 with a sampling rate of 30 min using a multivariate analysis. In multivariate analysis, the frequencies contributed in tide structure are more obvious than in the univariate analysis. Such signals can thus simply be detected in the multivariate analysis. Using the above-mentioned data, 414 main tidal constituents have been extracted. Our extracted lists of frequencies (of the Persian Gulf and Oman Sea) are compared with the two lists of frequencies consisting of 50 and 121 frequencies by the study of Amiri-Simkooei et al. (2014), which was applied to UK tide gauge stations. In the present contribution, new frequencies that belong to the tide gauge stations of the Persian Gulf and Oman Sea have been identified. Finally, a six-month prediction is performed for all stations using the two lists of main frequencies obtained in the two studies. The prediction results of the two studies are then compared using the estimated root mean squared error (RMSE). The RMSE difference of our predicted data show a reduction ranging from 2 cm to 7 cm compared to that predicted using the frequency lists of Amiri-Simkooei et al. (2014). The estimated RMSE of tide prediction using the frequencies obtained in this study ranges from 9 to 16 cm.

The main purpose of this paper is to examine the monthly change of main constituents of tide in the northern coast of Persian Gulf and Oman Sea. So the coastal tide gauge data in the port of Bushehr, Jask and Chabahar is used. Duration of tide gauge data collection stations from the sea surface height is listed by about 24, 6 and 7 years. By analyzing the data monthly of tide, the tidal constituents of M2, S2, K1 and O1 were obtained separately for each month. Results obtained show that, the greatest tidal range is for lunar semi diurnal component (M2) about 72 cm in Jask. However, the main constituents of the monthly changes are for K1 with a range of about 30 centimeters. As well as for other constituents such as S2, O1 and M2 to the monthly change in values of 18, 11 and 9 cm are obtained.

This work is devoted to present the results of an ensemble prediction system developed for the Weather Research and Forecasting (WRF) model to predict surface wind over the Persian Gulf. To construct the ensemble members a combination of perturbed initial condition (using Monte Carlo method) and model perturbations (using multi physical parameterization schemes) is employed. Here, an ensemble prediction system with 15 members (three physical parameterization schemes and five initial condition perturbations for each one) is used to generate the surface wind and other meteorological field predictions over the Persian Gulf. Assessment of the ensemble mean against the observational in situ and satellite (e.g., ASCAT and QuikSCAT) data indicates promising performance of the ensemble prediction system over the deterministic predictions.