Wave modelling in the oceans and in the regional seas: A critical look and perspective

The state-of-the-art in wave modelling is reviewed, with particular attention on the problems arising by its application in the regional seas. After giving a compact description of a spectral wave model, the different scales of application are discussed, highlighting the practical implications. The most relevant uses are described, with a critical analysis of the physical and numerical parts of a model. Then the relevance of the accuracy of the input wind fields is considered, stressing its importance for the accuracy of the derived wave results. The problems connected to wave forecasting are considered. The conclusions indicate expectations for further developments in the near future.

Coastal storm waves detection system design using Beaufort scale standardization and Sugianto wave forecasting method in Timbulsloko, Demak, Central Java, Indonesia

Storm is defined as a disturbance of the atmosphere marked by winds and usually by rain. Coastal storms must comprise a maritime component, such as waves, currents and/or water levels. Coastal storm detection is necessary so the number of casualties and losses caused by these events can be reduced. The method used in this system is the Sugianto wave forecasting method with standardization of coastal storms using the Beaufort scale. The purpose of this study is to built up an internet of things based system to observe coastal storm information and wave forecasting data from wind speed data that obtained in Timbulsloko, Demak, Central Java, Indonesia. The tidal data is processed using the Admiralty method. This system was built using Arduino Uno equipped with anemometer JL-FS2 to measure wind and waves parameters. The power source from 100 wp solar panels stored in a 40 Ah accumulator. Data from field instrument is stored to the IoT MAPID database using NodeMCU ESP8266. This system is placed in Timbulsloko, Demak. The results of field observation then validated using BMKG. This method could be applied in other location along the north coast of Java. The results of field observation showed an average wind speed 3.9848 m/s; significant wave height 0.4632 m; significant wave period 3.8641 s; wave energy 493.90 J/m2; wind energy 116.74 W/m2.

PEMILIHAN TIPE PEMBANGKIT LISTRIK TENAGA GELOMBANG LAUT TIPE PELAMPUNG DI PANTAI SALUBOMBA KABUPATEN DONGGALA

Indonesia is a country that has an area of sea three times larger than the land area. In line with the rapid development, the need for electricity is also increasing. So that Indonesia has great potential to produce alternative and environmentally friendly energy, namely Sea Wave Energy. Its continuous nature is available all the time. Many potential coastal areas in Indonesia, however, have not been utilized optimally. The purpose of this study is to see the potential of Wave Energy for electricity. For this reason, research was carried out at a location in the Central Sulawesi area, precisely in Salubomba, Central Banawa District, Donggala Regency. In this study a potential study was conducted on 3 types of PLTGL, namely Buoy, OWC, and Pasut Dam, where one will be chosen that meets the wave criteria requirements on the Beach. From the results of research, PLTGL that fulfills the requirements is the type of buoy. Data collection begins with secondary data, namely wind data from Mutiara Station. Then proceed with calculating wave forecasting using the SMB (Sverdrup Munk-Bretschneider) method. The results of this study, Salubomba beach has the potential to be built by the Buoy Type Wave Power Plant, a significant wave height of 0.52 - 3.37 meters with a ruptured depth of 3.95 meters.

Spectral shapes and parameters from three different wave sensors

The quality of wave measurements is of primary importance for the validation of wave forecasting models, satellite wave calibration and validation, wave physics, offshore operations and design and climate monitoring. Validation of global wave forecasts revealed significant regional differences, which were linked to the different wave buoy systems used by different countries. To fully understand the differences between the wave measurement systems, it is necessary to go beyond investigations of the integral wave parameters height, period and direction, into the frequency spectra and the four directional Fourier parameters that are used to estimate the directional distribution. We here analyse wave data measured from three different sensors (non-directional Datawell Waverider buoy, WaveRadar Rex, Optech laser) operating at the Ekofisk oil production platform located in the central North Sea over a period of several months, with significant wave height ranging from 1 to 10 m. In general, all three sensors provide similar measurements of the integral wave properties and frequency spectra, although there are some significant differences which could impact design and operations, forecast verification and climate monitoring. For example, the radar underestimates energy in frequency bands higher than 8 s by 3–5%, swell (12.5–16 s) by 5–13%, while the laser has 1–2% more energy than the Waverider in the most energetic bands. Lee effects of structures are also estimated. Lower energy at the frequency tail with the radar has an effect on wave periods (they are higher); wave steepness is seen to be reduced by 10% in the wind seas. Goda peakedness and the unidirectional Benjamin-Feir index are also examined for the three sensors.

Parallel computing efficiency of SWAN 40.91

Effective and accurate ocean and coastal wave predictions are necessary for engineering, safety and recreational purposes. Refining predictive capabilities is increasingly critical to reduce the uncertainties faced with a changing global wave climatology. Simulating WAves in the Nearshore (SWAN) is a widely used spectral wave modelling tool employed by coastal engineers and scientists, including for operational wave forecasting purposes. Fore- and hindcasts can span hours to decades, and a detailed understanding of the computational efficiencies is required to design optimized operational protocols and hindcast scenarios. To date, there exists limited knowledge on the relationship between the size of a SWAN computational domain and the optimal amount of parallel computational threads/cores required to execute a simulation effectively. To test the scalability, a hindcast cluster of 28 computational threads/cores (1 node) was used to determine the computation efficiencies of a SWAN model configuration for southern Africa. The model extent and resolution emulate the current operational wave forecasting configuration developed by the South African Weather Service (SAWS). We implemented and compared both OpenMP and the Message Passing Interface (MPI) distributing memory architectures. Three sequential simulations (corresponding to typical grid cell numbers) were compared to various permutations of parallel computations using the speed-up ratio, time-saving ratio and efficiency tests. Generally, a computational node configuration of six threads/cores produced the most effective computational set-up based on wave hindcasts of 1-week duration. The use of more than 20 threads/cores resulted in a decrease in speed-up ratio for the smallest computation domain, owing to the increased sub-domain communication times for limited domain sizes.

Numerical modeling and validating waves generated by typhoons in the East Vietnam Sea using satellite data

Calculating waves generated by typhoons is one of the most important tasks for wave forecasting at a stormy region like the East Vietnam Sea. It is, however, difficult to access the accuracy of calculated wave heights due to the lack of observed data. An approach of combining numerical models and satellite data has been widely used. In this study, we used the WAVEWATCH III model to stimulate wave fields caused by three strong typhoons: Damrey (2005), Ketsana (2009) and Haiyan (2013), then compared significant wave heights with the merged satellite observations. The results show that the BIAS values are small and negative, indicating that the wave heights from the model are lower than those from satellites in all cases. In contrast, the RMSE values of the three cases are considerably different but are still below 1 m. Finally, the average correlation coefficient is highest in typhoon Damrey (r = 0.94) whereas in typhoon Ketsana and Haiyan, r = 0.84 and r = 0.87, respectively. In conclusion, the study suggests that the WAVEWATCH III model has good performance for typhoon wave calculations and can be useful for wave forecasting in the East Vietnam Sea.