مهریار علی محمدی

Atmospheric conditions represent one of the most significant natural hazards for floating units. A critical issue related to these conditions is the insufficient attention given by watch officers to accurately collecting atmospheric data from the instruments on the bridge. For instance, air pressure readings are often taken without proper corrections for instrument and altitude variations and are rarely compared to long-term averages. To address this, there is a pressing need to develop and install a system on floating units that can automatically measure atmospheric parameters. This system would calculate essential parameters from the measured data, enabling informed decision-making regarding maneuvers to avoid rough seas. This research discusses the details of establishing an automatic meteorological station capable of collecting atmospheric data from the environment, storing it in a computer, and comparing the measurements with long-term averages to identify atmospheric and oceanic anomalies.

In marine navigation software, it is very important to determine the floating speed in turbulent weather. This study implements six methods of determining the speed loss of ships due to collision with waves in the Python programming environment and tries to identify the most suitable parameterization to be used in the weather routing algorithm. The six methodologies are: the methods of Bodewich, Artesen, Kwon, Tso Wecheng, Weng and Sha and Liu; In order to complete this analysis and compare the investigation methods, the features related to the seafaring situation, such as the magnitude of the height or the direction of the waves, as well as the inherent coordinates of the ship, are analyzed. By taking into account the different sailing conditions and matching them on the selected vessel, the effect of the ship's speed loss due to the presence of waves is investigated through the implementation of the aforementioned six methods. In the end, from the obtained results, it was determined that Artesen and Wang's method provided the best parameterization regarding loss and speed reduction, and it was also determined what the differences between these methods and other methods are when they are applied to a vessel.

Climate change is caused by global warming, and its consequences have become one of the most important concerns and public policies in many countries. The Fourth Assessment Report (AR4) of the UN's International Panel on Climate Change (IPCC) in November 2007 said that global warming cannot be stopped and that, at best, average temperatures in 2090-2099 will be 1.1 to 6.4 degrees above 1980-1999. If the global average temperature increases by more than 1.5 to 2.5 °C, about 20-30 % of animal and plant species could disappear. The perspective of national security actors on climate change is important. Climate changes change the military's strategic and operational environment and provide them with new options and challenges. Moving beyond the global warming cause-and-effect argument, this article argues that it is important for the military to begin planning to address the potentially devastating effects of global warming in the military domain. The consequences of climate change can affect the organization, training, equipping, and planning of the military services. Today, scientists and military leaders must determine the potential impacts of climate change on the ability to perform missions in support of national security objectives. Most countries already recognize the risk of climate change in their military installations and warn that more resources and monitoring systems are needed to increase preparedness. In this article, the causes of global warming and climate change are discussed first, and then the consequences of global warming are discussed with an emphasis on the military aspect.

This study aims to examine the various consequences of global warming. As mentioned in the introduction section, the rate of global warming can be slowed down but this warming process will continue. Since some of the consequences of global warming are caused by previous consequences, the consequences of global warming can be placed in the main sections and sub-sections; since some of the consequences of warming can be reduced by taking control measures; Therefore, we defined the consequences of warming in the form of two scenarios. The first scenario was considered for the case where no control measures were taken. The second scenario was for the case where control measures are taken to prevent secondary consequences. In the first scenario, in the first stage, the primary consequences of global warming were determined using numerous reliable internal and external libraries internet sources, and articles. In the second stage of this scenario, by holding a meeting with 5 experts in this matter, other different consequences of global warming were identified and categorized in general along with the consequences extracted from the first stage; In the second scenario, by holding an expert meeting (five experts in this matter), control measures to prevent the consequences of warming and the consequences of global warming after the control measures were determined.

Global warming, directly and indirectly, causes an increase in the temperature of the air near the surface of the earth and the ocean, the melting of polar ice (increasing the tension between the countries of the Arctic region), and the rise of the sea level, the increase in the intensity of storm waves, the submergence of some areas that have a low height compared to the free sea level, drought in some areas, especially areas located in the arid and semi-arid belt of the earth, intensification of torrential rains in some areas, increase in the intensity of tropical storms in storm-prone areas, water and food crisis, poverty and hunger, migration, destruction of equipment and military bases, especially those located near coastal areas, reduction of the efficiency of military personnel. There will be an increase in fine dust and pollution, common rivers and war over it both at the domestic and regional levels, increasing the role of the military and security forces, marginalization around the cities due to internal migration, and an increase in the risk of terrorism at the international level.

We defined the consequences of warming in the form of two scenarios. The first scenario was considered for the case where no control measures were taken. The second scenario is for the case where control measures are taken to prevent secondary consequences. In the first stage of this research, the primary consequences of global warming were determined using numerous reliable internal and external libraries internet sources, and articles. In the second stage of the research, by holding a meeting with 10 experts in this matter, other different consequences of global warming and control measures were identified and categorized in general along with the consequences extracted from the first stage; rising sea levels, increasing intensity of tropical storms in storm-prone areas, increasing intensity of storm waves, submergence of coastal areas, destruction of equipment and military bases near the coast, drought, migration and use of common rivers and war over it on dimensions both domestically and regionally are among the most important consequences of global warming in the form of the first scenario. In the second scenario, where it was assumed that control measures are taken to prevent the consequences of global warming, only the natural consequences of global warming appeared and it can be said that security is guaranteed to a good extent and practically the consequences that involve the military dimension are reaches its lowest value.

Atmospheric condition is one of the most important natural hazards for floating units. One of the shortcomings related to the weather situation is the lack of attention of the watch officers to the correct collection of weather data through the devices in the command bridge. For example, air pressure is read without instrument and altitude corrections and is never compared to a long-term average. Therefore, the aim of this research is to build a system on floating units that can automatically measure the atmospheric parameters and by calculating the required parameters from the measured parameters and comparing with the long-term average data, it can identify the atmospheric anomaly and as a result, make the right decisions regarding the appropriate maneuvers.

In this research, using existing sensors, a meteorological device has been built that can collect atmospheric data from the environment and store it in the computer, and by using a computer program, it can compare the measured data with the long-term average and detect atmospheric and oceanic anomalies. to identify By identifying the atmospheric anomaly, the phenomenon related to this anomaly is also identified, and the guard officer can have an appropriate maneuver related to the identified phenomenon. Finally, in this research, the way the device works has been evaluated using numerical tests. In this numerical experiment, a floating unit moves from the origin of Bandar Abbas in such a way that it collides with cyclone Gonu along the way and the measured pressure is compared with the average pressure of 40 years.

The first point along the track to experience a pressure drop of 3 hPa compared to the 40-year average is at approximately 135° ˚ and 120 miles from the storm's center. In fact, the distance of 120 miles from the center of the storm is a close distance, and in this case, the pressure has decreased by only 3 hectopascals compared to the 40-year average. The first point where the pressure has reached 5 hPa below the 40-year average is when the center of the storm is southeast and about 50 miles from the center of the storm. Therefore, it can be seen that the floating unit is very close to the storm and in this case it experienced only 5 hectopascal pressure drop.

The results show that a pressure drop of 5 millibars is a suitable criterion to definitively prove that the floating unit is in a tropical storm, and of course, due to the extreme proximity of the floating unit to the center of the storm in this case, a pressure drop of 1 hectopascal is suggested as a warning.

The great circle is of special importance as the shortest distance between two points in navigation. Navigating officers must always be able to calculate the path of the great circle and the turning points on that path. One of the drawbacks of calculations in the path of the great circle is the large volume of calculations and the uncertainty of the correct result. In this research, using the method of composite triangles, the path of the great circle is solved, and two general methods for calculating the rotation points of the great circle, which include a) calculating the rotation point with equal longitude difference and b) calculating the rotation point with distance difference equal is used. Next, using the method of equal longitude difference in calculating the points of rotation, a fast and reliable relationship has been developed to calculate the points of rotation. The premise of the developed method is that the point of rotation is always equal to the difference in longitude between the origin and destination. The developed method has the advantage that it will be able to calculate the turning points on the path of the Great Circle by calculating only 5 sentences from Norris's book in a much shorter time and with fewer calculations.

Successfully penetrating a defended beach is the most difficult phase of a amphibious operation, the purpose of this article is to identify the influencing factors on anti- amphibious operations and their importance. According to the nature of the subject, the type of applied research is the descriptive research method with a mixed approach and the method of collecting field and library information.After studying the literature, the background of the research and interviewing 5 experts, the influential components in anti- amphibious operations were extracted by the researcher and an expert panel was formed to validate them, and among the 20 factors counted, 16 factors were approved, and then a questionnaire with The five-level Likert scale was set with 15 questions and distributed among 50 expert employees who were selected by purposive sampling. The results of this research show that, in order of priority, 15 factors: having the doctrine of anti-landing operations, offensive minelaying capability and defensive minelaying capability, information, command relations and coordination between ground, air and naval commanders, having long-range precision missiles, compliance The principles of fully passive defense, sea control and air superiority, having a spirit of martyrdom, effective coastal defense, having coastal fortifications, effective air defense, having an obstacle plan on the coast, complete familiarity with the techniques of psychological operations and anti-psychological operations, determining target priorities and the knowledge of marine characteristics have a great influence on anti- amphibious operations.

Considering the safe route, short route, less time to reach the destination leads to economic savings in fuel consumption, less depreciation of the vessel and green seafaring (less pollution). The path that meets the above conditions is called the optimal path. The purpose of this research is to evaluate the influencing factors in weather routing from the two dimensions of safety and economic savings. Influential factors in weather routing include providing weather forecast data, network generation based on the great circle route, interpolation of weather data on the network, calculation of floating speed in different routes taking into account the weather condition, considering the safety restrictions of the float and searching of the shortest route. The results showed that in order to achieve an optimal route, all the above factors must be carefully considered in the routing process.

Water resources management needs to consider the effects of climate change on its main hydrologic cycle components. Therefore, the present study was conducted to analyze the impact of high and low flow variables from rainfall and temperature changes in the rivers of Sabalan in Ardabil Province. The rainfall and temperature gauge stations corresponding to hydrometric stations were selected. Then, the dependency of discharge and climatic components were examined during 1969 to 2019. The Change Point Analysis was used to test the significant changes in rainfall and temperature time series. Then, the discharge data were divided into periods before and after the change of climatic variables. For both periods, 41 variables of high and low indicators were calculated using RAP software. Based on the results in Lay, Nir and Pol-e-Soltani stations, the maximum flow discharge in the period after the change in climatic components has a decreasing trend compared to the before period. The trend of the average value of rising rate in most stations was decreasing. The number of zero days in Ahl-e-Iman and Pol-e-Soltani stations has increased by 201 and 947 percent in the post-effect period, respectively. The mean values ​​of the 3-day moving maximum in Ahl-e-Iman, Nir, Pol-e-Soltani and Viladaraq hydrometer stations decreased by 29.53%, 45.58%, 35.24% and 39.42%, respectively. In conclusion, the hydrological behavior of the stations has changed under the influence of precipitation and temperature components.

Today, navigation systems have become an integral part of the control of the floating unit. Today, ECDIS navigation system is considered as the most important navigation assistance system. The presence of electronic maps in the memory of the Ecdys device, along with the processing ability of this device, has caused the officer guarding the command bridge to navigate the ocean routes without any worries. One of the disadvantages of conventional navigation systems (such as Ecdis and integrated navigation system) is the lack of meteorological data in these systems.In this study, a navigation system has been developed that has calculated the sea route according to the turning points. And performs estimated navigation. In this system, climatic data of wind, temperature, pressure are calculated on estimated points over a period of forty years. Calculating climatic data on estimated points can help navigating officers decide on a seafaring route.

In this study, the huge sea waves and how they were formed were studied. Although there are many foreign studies on the huge waves of the sea, which are addressed in this study, but inside the country is still an almost unknown subject. huge waves are distinct from a tsunami. Tsunami waves are formed on the ocean floor due to earthquakes, and when they reach the shore, they increase in height and cause damage near the shore; While huge waves form in the sea for a moment and are dangerous. The basic physics that make phenomena such as huge waves possible is that different waves can travel at different speeds and can therefore accumulate under certain conditions known as constructor interference. Accumulation of waves by diffraction phenomenon, compression of waves by opposing currents and interaction of wave with current are other reasons that lead to the formation of huge waves. Since about 1997, most leading authors have confirmed the existence of huge waves with the warning that wave models have not been able to predict giant waves, in fact, waves with a significant height (Hs) above 12 meters (39.4 feet). But today, with changes in the parameters of wave models, such as WW3, they are predicting huge sea waves, which need to be addressed comprehensively in the country.

The aim of this study is analyzing the sequential pattern of monthly river flow wet and dry spells in some hydrometric stations (a 20-year period), West-Azarbaijan Province. The wet-dry spells of river flow were determined using Runs theory and the Power Laws Analysis method was used to determine the long-term pattern of low and high flow periods. Then, the drought severity and duration value of wet and dry periods were represented on double-logarithmic plots. Also, the sequence counts of dry and wet periods were determined through 1 to 47-month periods. The results showed that there is an inverse relationship between the severity and persistence of dry periods. The maximum severity of drought was observed in Ghasemlou and Dashbnd stations (0.55 slope of fitted line), and the highest intensity of wet period was related to Pei-Qaleh station (slope of fitted line is 0.6). In other words, the Ghasemlou and Dashbnd stations had the persistent dry periods and Pei-Qaleh station had the highest stability in occurrence of wet periods. The maximum duration of dry and wet periods was observed in Pole-Bahramlou and Sariqmysh stations, respectively having 11 and 15-month average maximum duration occurrence through the studied stations. Also, the results showed that the occurred dry spells over the South parts of the study area had the highest duration and intensity with respect to central and Northest parts of the study area. The results can be used to determine the susceptible area with high drought duration and intense drought periods in planning of surface water resources. The use of power analysis method allows the study of dry and wet periods and also the determination of changes in the behavior of time series of hydrological data due to climate change or human intervention.

This article aims to investigate the effects of climate change on tropical cyclones. The present study has been carried out by using and examining the available library resources. The results show that ocean surface warming leads to more intense tropical storms. On the other hand, with the rise of the ocean water level, the destructive power of storms in coastal areas will increase. The rise of the sea level itself is caused by climate change. On the other hand, the proportion of very intense tropical cyclones (Category 4 and 5) is projected to increase, even though most climate model studies predict that the total number of tropical cyclones per year will decrease or remain nearly constant. Also, models predict that as the Earth warms in the coming decades, some regions will experience an increase in the rate of intensification, a poleward shift of the geographic latitude of the maximum intensity, or a decrease in tropical cyclone forward motion.

Since the planet Earth acts like a black body like the planet, and always in a quasi-conditioned state, as much energy as it receives from the sun, it loses energy through long-wave radiation from the earth. The solar radiation absorbed on the ground is converted to heat; however, due to the reflection of the earth, the earth is not hot and hot. The energy reflection process by the earth is called earth reflection or long infrared wavelength, which is indicated by watts per square meter (w / m2). The low OLR values are related to the cloud at high latitudes, so that high values of the long-wave radiation of the Earth's output mean smooth skies and low values of the clouds. This indicator is also used to estimate rainfall in the tropical region. OLR calculations and estimates are a key component of the MJO, MNO, Negative and Positive Phases (ENSO), North Atlantic Oscillation (NAO), and also to study the assessment of weather indicators.

In the present study, in order to calculate the long-wave IR radiation, the OLR data from 1975-2015 were daily from NCEP / NCAR databases of the National Oceanic and Oceanographic Organization of the United States with a spatial resolution of 2.5 * 2.5 degrees longitude and 4-hour time resolution (hours, 00:00, 06:00, 12:00 and 18:00) were extracted and analyzed. In order to calculate the long-wave radiation of Iran, in the region of Iran's Earth's atmosphere (from 25 to 40 degrees north and from 42.5 to 65 degrees east), using Grads and MiniTab programming facilities, weighted earth integral Watts per square meter. First, the general characteristics of the long wave were studied. In this study, linear regression (VIA) regression methods were used to analyze the trend. In this procedure, the amount of variability of the long wave of earthquake is estimated over time. In the present study, in order to better understand the data and make a more accurate decision about the level of statistical confidence, the method of analysis of the Moran model was used; also, the Moran Model and GeoDa software were used to calculate and map the corresponding graphs. In order to calculate the Moran index or index, first the z and P-value points are calculated, and in the next step, the index is evaluated and significant.

The results of this study showed that the mean long wave length of Iran is 263/3 W / m2. The highest mean longitude of the Earth's longitude is due to latitudes below 30 degrees north, especially in the southern and southeastern parts of the country. Nevertheless, it was observed that more than half of the country's average surface longitude was greater than the average. The lowest mean radiation of the long wave of earth exits was seen as a belt from the northeast to the northwest of the country, but its minimum core is in the northwest and northeast. The lowest daily spatial variation coefficient of Iran's high-tide wave is seen in the southeast and southern coast of the country and in parts of the central and eastern parts of the country. Therefore, the geographic latitudes are higher than the mean long wave of the earth and the coefficient of spatial variation increases. Spatial Distribution The temporal and spatial variations of the temporal and spatial variations of the long wave of Iran's annual output in most areas of Iran have been increasing. The most extreme slope is the increasing trend (on average, between 0.8121 and 0.696296 watts per square meter) in the southern part of the southern belt of the Persian Gulf and the Oman Sea. In order to better understand the result of the temporal and spatial changes of the long-wave IR radiation to 4 periods of 10 years (1975-2015), during the first period, the total area of the country had an insignificant increase trend . Of course, in the second period, in contrast to the first period, most of the country's area had a decreasing trend, so that the areas that had a growing trend in the first period had a decreasing trend in the second period. Also, in the third period, again, in the second period, the majority of the country's area was incrementally and statistically insignificant. Of course, in the fourth period, the long-wave radiation of the Earth's surface throughout the southeastern region of Iran has been increasing and statistically insignificant, which includes 14.3% of the country's total area; but in general, during the fourth period, 96% of the country's area has a decreasing trend, of which 50.32% is statistically significant, and 43.53% are statistically non-significant. This suggests that in all four 10-year periods, I have had a photographic process at the outlet of the tidal wave in Iran. The results of the spatial distribution of the local Moran index showed that the long wave of Iranian outbound radiation in the south-east, south, and in the east and west of the region, consisted of a high cluster pattern with 47/60 percent of the country's land area. The cluster pattern regions of the north are drawn from the northeast to the northwest and include the northeastern, north and northwest regions of the country as well as the northern heights of the Zagros Mountains of the country. The spatial self-correlation model has a similar positive correlation with the pattern of spatial autocorrelation, with the difference that the spatial spatial dependence pattern of the second period is decreasing, while the positive spatial self-dependency model from the third period to the next It will slow down. Nevertheless, it can be said that throughout the course of the model, the spatial self-sufficiency pattern negatively affects the recent periods of decline and also the positive spatial self-correlation pattern with 0.75 percent ascendance.

This study aims to explain the role of IRI Navy in the development of Makran coasts and its impact on economic security of the southeast of the country.

 This mixed-method research is both qualitative and quantitative. The statistical population of the study consists of 186 senior officers of IRI Navy, based on random sampling method using Krejcie and Morgan table, who have served in operational and combat areas. In the qualitative part, sampling was done purposefully with interview tools, based on which 7 organizational experts with operational and information records were interviewed. The questionnaires were researcher-made and the analysis of the collected data was performed by SMART PLS statistical software.

 The results of this study revealed 22 factors related to the role of IRI Navy, 13 indicators for the development of Makran Coasts, and 9 factors for its economic security

 The findings of the study showed that IRI Navy has a positive and statistically meaning impact on the development of Makran Coasts. Meanwhile, the development of the Makran Coasts has a positive and statistically meaning effect on its economic security.

The northern Indian Ocean (Bay of Bengal and Northwest Ocean) is one of the areas under Nedaja mission, one of the areas prone to the formation of tropical cyclons. In this study, we investigated the timing and pattern of forming tropical cyclons in the northern Indian Ocean region using data from the Indian Meteorological Organization from 1990 to 2017. The results showed that the highest number of cyclons occurred in November, June and October, respectively. There were no cyclons in the months of April, August, September, February and March. The frequency distribution graphs of cyclons formed in both the Bay of Bengal and Northwest Ocean regions show two maximum points. The first peak is related to the consecutive months of May and June and the second peak occurs in the months of October, November and December. The lack of intra-tropical convergence zone in the northern ocean causes no tropical cyclons in the area to occur in the summer and winter seasons. Statistical analysis also showed that if a storm occurs at any degree in the first maximum distribution, with 90% probability we will see the formation of a cyclonin the continuation of the first maximum and the second maximum and with 83.3% probability we will see a cyclon formation in the second maximum.. Background preparation using the results of this study can provide significant assistance in tackling tropical cyclons and maritime safety.

The dependence of numerical models on the selected domain, in turn, affects the accuracy of prediction and simulation of Tropical Cyclones (TCs) and is considered as a very serious challenge. In the first part of this study, the WRF model was used to determine the sensitivity of the track and intensity of TC GONU to a selective domain. In the second part, the performance of assimilation 3D in order to reduce the dependence of the sensitivity of the TC Gonu simulation to the selective domains was evaluated. The Gonu was the strongest TC occurred over the Arabian Sea. The peak intensity of TC Gonu was estimated 140 knots and 130 knots by Joint Typhoon Warning Center (JTWC) and India Meteorology Department (IMD), respectively. Four domains were separately selected. All of the simulations in this study were initialized at 00 UTC of 2 June for six days. In all simulations, authors used the data from NCEP global final analysis (FNL) on a 1.0°×1.0° grid to provide initial and boundary conditions. Despite the little difference in selective domains, the results in the first section showed the simulated tracks differed compared with each other, considerably. For performing simulations in the second part, the QSCAT, BUOY, METAR, SHIPS, SONDE, and SYNOP data to number 2064, 30, 63, 18, 37, and 208, were used, respectively. The results in the second part showed that assimilation of the satellite and synoptic data at the time of the start of the model, lead to improving quality of the first guess data. Therefore, the accuracy of the simulated tracks in all selected domains was enhanced and reduced the sensitivity of TC Gonu simulation to the selected domain. Regardless of the great difference in simulated tracks, especially in the case of no use of assimilation, which in turn influences the intensification of the TC, in all of the simulations, the simulated intensity during the intensity peak of the TC is higher compared with the IMD reference data and is less compared with JTWC reference data. Since during the simulations, the sea-surface temperature  has been used constantly and on the other hand, the exact values of sea-surface temperature have a significant impact on the intensity of the TC simulation, the WRF model coupled with an ocean model for accurate determination of sea-surface temperature during simulation can improve the accuracy of the results of this study. There is, of course, another way to improve the quality of the results, when results depend on the selective domains. For every domain, one simulation is performed and the average of the simulations is considered (ensemble forecast). The high amount of time spent in this method is considered as serious trouble. It should be noted that in regional models, the sensitivity of simulations to the selected domains is also highly dependent on the boundary conditions, which should be considered.

Tropical cyclones (TCs), all over the world, are recognized as the most common and most devastating of all the natural disasters. Nearly 80–90 TCs occur around the globe that about 40–50 attain intensity of 33 m/s (Frank and George, 2007). Approximately 7% of TCs originate in north of Indian Ocean and nearly 2% in Arabian Sea (WMO report, 2008).
The prediction of TC track has been on a clear path toward improvement for many years and nearly has been achieved (Elsberry, 2005). The global and regional simulations have proved that high resolution is not a requirement for improved track prediction (Goerss, 2006). The prediction of TC intensity is very complicated, because track prediction depends more on large-scale processes, and intensity depends on the inner-core dynamics and its relationship to the environment (Marks and Shay, 1998). It means that the intensity is a multiscale problem (Goerss, 2006). Only recently has the computational capability to address multiple scales of convection (cell scale, mesoscale, and synoptic scale) been achieved. The requirement to resolve the inner core, including the eyewall, the eye, and inner spiral rain bands near the eyewall, has led to the application of models with grid lengths of only a few kilometers (e.g., Krishnamurti, 2005; Braun et al., 2006; Chen, 2006; Davis et al., 2008).
Further the importance of resolution, other key issues for TCs prediction include the effect of mixing-induced ocean-surface cooling, treatment of momentum, heat and mixture fluxes at the air–sea interface, and improvement of the initial vortex structure through data assimilation. These Allegers will be each more important when we are moving toward finer spatial resolution in simulations.
In this study, sensitivity of Gonu simulations to air–sea fluxes parameterization and model resolution are studied as key issues for improving simulation accuracy. Herein, sensitivity to atmospheric physical parameterizations such as cloud physics and the boundary layer physics that affect Gonu intensity too, are not considered explicitly.

The Indian Ocean is the third largest of the world's oceanic divisions, covering approximately 20% of the water on the Earth's surface. It is bounded by Asia—including India, after which the ocean is named—on the north, on the west by Africa, on the east by Australia, and on the south by the Southern Ocean (or, depending on definition, by Antarctica).

Gonu was strong cyclone (categury 5) that was formed in the Arabian Sea during the periods of 1-7 June 2007 .At the peak intensity, cyclones Gonu was caused 3-min sustained wind about 240 km/h and minimum pressure about 920 mb. Financial losses of Gonu cyclone was reported around 4.2 billion USD and for human casualties at least 78 persons (IMD report, 2008). Herein, we have not planned to discuss about synoptical conditions of the Gonu cyclone formation, and only the effects of Air-Sea interactions on intensification is interpreted.
The performance of Advance Hurricane WRF (Advanced Research Weather Research and Forecasting) model (AHW model: Davis et al., 2008) is evaluated in explicit simulations of Guno super cyclone (2007). The data from National Centre of Environmental prediction (NCEP) global final analysis (FNL) on a 1.0°×1.0° grid is used to provide initial and boundary conditions for numerical simulations. Sea surface temperatures were derived from the high-resolution real-time global sea surface temperature (RTG_SST) at 1/12-degree resolution analyses from NCEP/MMAB. The information of reference track for Gonu cyclone has been received from Indian Meteorological Department (IMD). The mixed layer ocean model requires specification of an initial mixed layer depth h0, and a deep-layer lapse rate Γ. The ocean model was initialized with h0 and Γ equal to 50 m 0.14 in order to the NCEP Global Ocean Data Assimilation System (GODAS), when the negative feedback of wind-driven ocean mixing on hurricane intensity was planned to be considered (Davis et al., 2008).
In order to implement the Gonu simulations we considered two domain, the first domain was fixed with 27-km horizontal grid resolution (with 145×110 grid points) and second domain was nested movable domain with 9-km horizontal grid resolution (with 49×49 grid points) that was configured with a two-way nesting (fig. 1). All domains had 41 vertical layers with a terrain that followed sigma coordinates with the model top at 0.5 hPa.
The surface-flux parameterizations include of both momentum and enthalpy (heat and moisture) exchange. Two main schemes for momentum exchange are presented by Charnock and Donelan (Charnock, 1955; Donelan et al., 2005) that Charnock formulation is a default scheme in mesoscale meteorological models. In Charnock formulation, roughness length given as
(1)

Where and m and frictional velocity defined as
(2)

Where τ is Reynolds stress (shearing stress) and ρ is air density. The relation between roughness length and frictional velocity is recursive, but the model formulations use values from the previous time step and adjusted quickly.
In atmospheric boundary layer, drag coefficient is defined as
(3)

Where V10is the wind speed at 10-m height. The Charnock relation gives a 10-m drag coefficient that generally increases from about 0.001 to 0.003 at normal TC wind strengths, and it would recent to 0.005 for category 5 storms (wind >70 m s-1). However, this estimation for category 5 storms does not match with observational evidence (e.g., Black et al. 2007) that suggests drag coefficient remains near 0.003 for high wind speeds.
Donelan is introduced a drag formulation based on the high wind speed wind-tunnel experiments (Donelan et al. 2004) that results are showed Cdlower than those from the Charnock relation for low winds with a linear increase up to a maximum near 0.0024 at about 35 m s-1. In Donelan formulation, roughness length given as
(4)

With a lower and upper limit on z0 of 0.125×10-6 and 2.85 ×10-3 m, respectively. The Donelan formulation, with less drag than the Charnock formulation shows yourself effects with higher wind speeds but also higher central pressures and a larger eyewall radius in strong TCs simulations. This subject needs to validate with TCs observations over all the tropical.
The exchange coefficients of heat (Cɵ), moisture (Cq) and enthalpy (Ck) formulate by friction velocity, scaling temperature ɵ* and scaling moisture q*. These scaling parameters define the similarity theory profile. The available schemes for estimation of molecular viscosity sub-layer roughness length confirm an inverse relationship between roughness length and wind speed, and has the effect of a resistance to the eddy scalar transports that increases with wind speed. It means that the q* contribution to the surface moisture flux u*q* tends to oppose the effect of u* increasing with wind speed (similarly for heat and enthalpy). The coefficients of Cɵ, Cq and Ck formulate as
(5)

Where Δθ and Δq are difference in water vapor mixing ratio and potential temperature between the surface and 10-m. CP and Lv are heat capacity at constant pressure and specific latent heat of vaporization, respectively.
For example, estimated exchange coefficient of enthalpy (Ck)during the simulations are related to selected scheme for estimation of ɵ* and q*. The Ck will increase slowly in Carlson and Boland, stay steady in Large and Pond and decrease in Garratt parameterizations with increasing of wind speed (Carlson and Boland, 1978; Large and Pond, 1981; Garratt, 1992).
According above description, considering different schemes for different roughness lengths velocity, water vapor mixing ratio and potential temperature scaling in atmospheric surface layer over water would significantly affect estimated Ckand CD and also TC intensity. For example, the ratio of Ckto CDis introduced as an important factor in TC intensity (Emanuel, 1995; Braun and Tao, 2000; Davis et al. 2008).

In the first, the results of simulated intensity (minimum pressure and maximum wind speed) for coarse domain (Fig. 2) are analyzed. It is clearly showed that the sensitivity of simulations to the different three air–sea fluxes parameterization for simulations of Gonu at 27-km grid resolution at 0000 UTC 02 June 2007 (144-h model forecast). The Donelan-Large formulation, with less drag and steady Ckthan the Charnock-Carlson formulation that have higher drag and increasing Ckwith wind speed, results in higher wind speeds also lower central pressures. This happens after 48-h simulation where that wind speed increase until 78-knot. After this condition, high drag in the Charnock-Carlson formulation tends to oppose increasing wind speed. Comparison between Donelan-Large formulation and Donelan- Garratt simulation results with the same drag but different Ckin this interval shows Ck decreasing with wind speed that it tends to oppose wind speed increasing. Also Fig.2 shows steadily wind speed increase and decrease during first 48-h and last 48-h simulation for all three parameterizations for air–sea fluxes. The comparison of the sensitivity of simulated Gonu intensity with air–sea exchange parameterizations clearly showed that the Donelan-Large configuration has achieved significantly better simulated results at 27-km grid resolution but with 30-knot wind speed less than reported speed by IMD.
In order to study sensitivity of simulated Gonu intensity to horizontal grid resolution, it was conducted three experiments at 9-km grid resolution similar to last three experiments. The results were showed similar sensitivities at 27-km grid resolution but it was significantly improved the wind speed at the peak of cyclone intensity for these three air–sea exchange parameterizations (Fig. 3). Also these results showed that the central pressure simulated by Charnock-Carlson formulation, has been better compared to the 27-km resolution (as Donelan-Large formulation).
The results of simulated tracks were not significantly sensitive to these surface exchange parameterizations (not shown) but it showed more sensitivity to horizontal grid resolution (Fig.4). As can be seen in Fig. 4, the simulated track for 27-km resolution is better than the 9-km resolution that it consistent with the results of Goerss (2006). This proved that high resolution is not a requirement for improvement of track prediction.

In this study, it is seen a significant sensitivity of simulated intensity of one TC to air–sea exchange parameterization and horizontal grid resolution. For selected TC, the experiment with Donelan parameterization for momentum exchange and Large - Pond parameterization for heat and enthalpy are found more efficient. Also the results showed that simulated track could be more sensitive to horizontal grid resolution than applied air–sea fluxes parameterization. The difference in drag between the two drag formulations (Donelan and Charnock) is relatively smaller than reality. It must be pointed out that the real drag force on surface winds is determined by the time-evolving ocean wave spectrum, prediction of which requires a wave model (e.g., Chen et al. 2007). Therefore the drag parameterizations discussed above must be considered as crude representations of the bulk effects of waves in TCs. This sensitivity of differences in the three air–sea fluxes parameterization is less than would be inferred from the dependence of maximum wind on (Ck/Cd)1/2, derived by Emanuel (1995), While the proper wind speed dependence of Ck remains a topic of active research.