Effects of heatwave features on machine-learning-based heat-related ambulance calls prediction models in Japan.

Researchers agree that there is substantial evidence of an increasing trend in both the frequency and duration of extreme temperature events. Increasing extreme temperature events will place more pressure on public health and emergency medical resources, and societies will need to find effective and reliable solutions to adapt to hotter summers. This study developed an effective method to predict the number of daily heat-related ambulance calls.

Linking the long-term variability in global wave energy to swell climate and redefining suitable coasts for energy exploitation.

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 10 years for wave energy assessment appears to be insufficient for detecting the influence of climate variability, but also the selection period for wave energy assessment can lead to an over/underestimation of about 25% for wave power.

Modeling the combined impact of climate change and sea-level rise on general circulation and residence time in a semi-enclosed sea.

This study provides an assessment of possible changes in the general circulation and residence time in the Persian Gulf under potential future sea-level rise and changes in the wind field due to the climate change. To determine the climate-change-induced impacts, Mike 3 Flow Model FM was used to simulate hydrodynamic and transport processes in the Persian Gulf in both historical (1998-2014) and future periods (2081-2100). Historical simulation was driven by ERA-Interim data.