Kyoto University · Earth and Planetary Sciences
Professor Bahareh Kamranzad's research lab specializes in coastal and oceanic climate dynamics, with a primary focus on wave climate modeling, wave energy resource assessment, and the impacts of climate change on marine renewable energy. The lab employs high-resolution numerical modeling and reanalysis datasets to study intra-annual and decadal variations in wave characteristics, particularly in data-scarce regions such as the Indian Ocean and the Persian Gulf. Key research directions include wave energy sustainability, climate-driven variability in wind and wave patterns, and the validation of global reanalysis data for regional wave modeling.
Figures are computed from collected data and may differ slightly.
In this study, based on 55 years’ worth of high-resolution simulated wave data using numerical modeling off the southern coasts of China, intra-annual and decadal variations of the wave climate and wave energy were evaluated. The results show that it is important to consider a sufficiently long time period for wave energy assessment to take into account the changing climate. The high-resolution wave dataset enabled the quantitative analysis in both nearshore and offshore, and the quantitative an
The sustainability of wave energy linked to the intra- and inter-annual variability in wave climate is crucial in wave resource assessment. In this study, we quantify the dependency of stability of wave energy flux (power) on long-term variability of wind and wave climate to detect a relationship between them. We used six decades of re-analysis wind and simulated wave climate in the entire globe and using two 30-yearly periods, we showed that not only the previously suggested minimum period of 1
The wave energy resources in the Indian Ocean can be considered as a potential alternative to fossil fuels. However, the wave energy resources are subject to short-term fluctuations and long-term changes due to climate change. Hence, considering sustainable development goals, it is necessary to assess both short-term (intra-annual) variation and long-term change. For this purpose, the simulated wave characteristics were utilized, and the wave power and its variation and change were analyzed in t
Open papers in the app to read, cite, and organize with AI.
