Wave height forecasting in Dayyer, the Persian Gulf

Forecasting of wave parameters is necessary for many marine and coastal operations. Different forecasting methodologies have been developed using the wind and wave characteristics. In this paper, artificial neural network (ANN) as a robust data learning method is used to forecast the wave height for the next 3, 6, 12 and 24 h in the Persian Gulf. To determine the effective parameters, different models with various combinations of input parameters were considered. Parameters such as wind speed, direction and wave height of the previous 3 h, were found to be the best inputs. Furthermore, using the difference between wave and wind directions showed better performance. The results also indicated that if only the wind parameters are used as model inputs the accuracy of the forecasting increases as the time horizon increases up to 6 h. This can be due to the lower influence of previous wave heights on larger lead time forecasting and the existing lag between the wind and wave growth. It was also found that in short lead times, the forecasted wave heights primarily depend on the previous wave heights, while in larger lead times there is a greater dependence on previous wind speeds

Investigation on wave energy in Amirabad seaport of Caspian Sea using SWAN model results

In this study, SWAN numerical model used to modeling waves and obtain the significant wave height in range of Amirabad seaport of Caspian Sea. To do this, first, a general model to modeling the wave height in the entire Caspian Sea was built. Then the boundary conditions obtained from the general model, by using the NEST operation of SWAN model, modeling the local with higher magnification in the area Amirabad Seaport was used. The local models built in the Amirabad, was calibration and verification with waves profile data recorded by buoys deployed in that area. Comparison the results with data measured by the Amirabad buoy shows that modeling done in this area had a good accuracy. Then running the SWAN model for three years and Obtained significant wave height in the desired location. Finally the wave energy obtained from significant wave height

Science–policy–practice insights for compound and multi-hazard risks

When multiple weather-driven hazards such as heatwaves, droughts, storms or floods occur simultaneously or consecutively, their impacts on society and the environment can compound. Despite recent advances in compound event research, risk assessments by practitioners and policymakers remain predominantly single-hazard focused. This is largely due to traditional siloed approaches that assess and manage natural hazards. Hence, there is a need to adopt a more ‘multi-hazard approach’ to managing compound events in practice. This paper summarizes discussions from a 2-day workshop, held in Glasgow in January 2023, which brought together scientists, practitioners and policymakers to: (1) exchange a shared understanding of the concepts of compound and multi-hazard events; (2) learn from examples of science–policy–practice integration from both the single hazard and multi-hazard domains; and (3) explore how success stories could be used to improve the management of compound events and multi-hazard risks. Key themes discussed during the workshop included developing a common language, promoting knowledge co-production, fostering science–policy–practice integration, addressing complexity, utilising case studies for improved communication and centralising information for informed research, tools and frameworks. By bringing together experts from science, policy and practice, this workshop has highlighted ways to quantify compound and multi-hazard risks and synergistically incorporate them into policy and practice to enhance risk management

Science-policy-practice insights for compound and multi-hazard risks

When multiple weather-driven hazards such as heatwaves, droughts, storms or floods occur simultaneously or consecutively, their impacts on society and the environment can compound. Despite recent advances in compound event research, risk assessments by practitioners and policymakers remain predominantly single-hazard focused. This is largely due to traditional siloed approaches that assess and manage natural hazards. Hence, there is a need to adopt a more ‘multi-hazard approach’ to managing compound events in practice. This paper summarizes discussions from a 2-day workshop, held in Glasgow in January 2023, which brought together scientists, practitioners and policymakers to: (1) exchange a shared understanding of the concepts of compound and multi-hazard events; (2) learn from examples of science–policy–practice integration from both the single hazard and multi-hazard domains; and (3) explore how success stories could be used to improve the management of compound events and multi-hazard risks. Key themes discussed during the workshop included developing a common language, promoting knowledge co-production, fostering science–policy–practice integration, addressing complexity, utilising case studies for improved communication and centralising information for informed research, tools and frameworks. By bringing together experts from science, policy and practice, this workshop has highlighted ways to quantify compound and multi-hazard risks and synergistically incorporate them into policy and practice to enhance risk management

Future climate projections in the global coastal ocean

Resilient coastal communities and sustainable marine economies require actionable knowledge to plan for and adapt to emerging and potential future climate change, particularly in relation to ecosystem services and coastal hazards. Such knowledge necessarily draws heavily on coastal ocean modelling of future climate impacts, using a great diversity of both global and regional approaches to explore multiple societal challenges in coastal and shelf seas around the world. In this paper, we explore the challenges, solutions and benefits of developing a better coordinated and global approach to future climate impacts modelling of the coastal ocean, in the context of the UN Decade of Ocean Science for Sustainable Development project Future Coastal Ocean Climates (FLAME; part of the CoastPredict programme). Particularly, we address the need for diverse modelling approaches to meet different societal challenges, how regions can be harmonised through clustering and typology approaches, and how coordination of experimental designs can promote a better understanding of uncertainties and regional responses. Improved harmonisation of future climate impact projections in the global coastal ocean would allow sectoral and cross-sectoral global scale risk assessments, improve process understanding and help build capacity in under-represented areas such as the global south and small island developing states. We conclude with a proposed framework for a Global Coastal Ocean Model Intercomparison Project

Assessment of wave energy variation in the Persian Gulf

Since wave energy has the highest marine energy density in the coastal areas, assessment of its potential is of great importance. Furthermore, long term variation of wave power must be studied to ensure the availability of stable wave energy. In this paper, wave energy potential is assessed along the southern coasts of Iran, the Persian Gulf. For this purpose, SWAN numerical model and ECMWF wind fields were used to produce the time series of wave characteristics over 25 years from 1984 till 2008. Moreover, three points in the western, central and eastern parts of the Persian Gulf were selected and the time series of energy extracted from the modeled waves were evaluated at these points. The results show that there are both seasonal and decadal variations in the wave energy trends in all considered points due to the climate variability. There was a reduction in wave power values from 1990 to 2000 in comparison with the previous and following years. Comparison of wind speed and corresponding wave power variations indicates that a small variation in the wind speed can cause a large variation in the wave power. The seasonal oscillations lead to variation of the wave power from the lowest value in summer to the highest value in winter in all considered stations. In addition, the seasonal trend of wave power changed during the decadal variation of wave power. Directional variations of wave power were also assessed during the decadal variations and the results showed that the dominant direction of wave propagation changed in the period of 1990 to 2000 especially in the western station.Full Tex

Assessment of CGCM 3.1 wind field in the Persian Gulf

Increasing of the greenhouse gases emission causes the climate changes. Therefore, usage of the marine renewable energy resources such as wind and wave energies has been increased during the last decades. Climate variability can change the wind and consequently wave patterns and the available energy amounts. Therefore, assessment of the potential effect of climate change on the wind regime is important. In this paper, wind characteristics obtained from a global climate model (CGCM 3.1) is used for assessing the effects of climate change on the wind regime in the Persian Gulf. CGCM 3.1 results were compared quantitatively with those of ECMWF in the Persian Gulf and the results showed that in comparison to ECMWF, CGCM 3.1 wind speeds are mostly underestimated for both average and maximum values. Dominant wind directions represented by two wind fields are nearly similar except for a point located in Strait of Hormuz. Variations of the annual wind speed in this area were also evaluated until 2100 and time series of annual averages of the wind speeds and statistical analysis indicate a decreasing trend in all points in the domain. Variation of wind speed frequency based on CGCM 3.1 winds was also assessed for different intervals and the results showed that the variations of wind speed frequencies are marginal. Although there is a insignificant reduction in the average wind speed, this can lead to large variations in the wind and wave energies and also extreme values of wave characteristics.Full Tex