A range of computer science methods termed machine learning (ML) enables the extraction
of insight and quantitative relationships from multidimensional datasets. Here, we review the …

Coastal flood risks are rising rapidly. We provide high resolution estimates of the economic
value of mangroves forests for flood risk reduction every 20 km worldwide. We develop a …

The ports sector is critical to global transport and trade. Climate change may compromise
port operations, resulting in an increase in operational shutdowns and subsequent …

Cost-effective coastal flood adaptation requires a realistic valuation of losses, costs and
benefits considering the uncertainty of future flood projections and limited resources for …

In this paper, we evaluate the performance of 8 statistical and machine learning methods,
driven by atmospheric synoptic patterns, for long-term daily rainfall prediction in a semi-arid …

Coastal communities in tropical environments are at increasing risk from both environmental
degradation and climate change and require urgent local adaptation action. Evidences …

Long-term time series of sea state parameters are required in different coastal engineering
applications. In order to obtain wave data at shallow water and due to the scarcity of …

Flood assessment in coastal river areas is subject to complex dependencies and
interactions between flood drivers. In addition, coastal areas are especially vulnerable to …

Large-scale wave reanalysis databases (0.1°–1° spatial resolution) provide valuable
information for wave climate research and ocean applications which require long-term time …

Through assessment of wind-wave directional spectra, we provide a comprehensive
explanation of the projected 21st Century changes in the global wind-wave climatology …