Statistical wave climate projections for coastal impact assessments

Abstract

Global multimodel wave climate projections are obtained at 1.0° × 1.0° scale from 30 Coupled Model Intercomparison Project Phase 5 (CMIP5) global circulation model (GCM) realizations. A semi‐supervised weather‐typing approach based on a characterization of the ocean wave generation areas and the historical wave information from the recent GOW2 database are used to train the statistical model. This framework is also applied to obtain high resolution projections of coastal wave climate and coastal impacts as port operability and coastal flooding. Regional projections are estimated using the collection of weather types at spacing of 1.0°. This assumption is feasible because the predictor is defined based on the wave generation area and the classification is guided by the local wave climate. The assessment of future changes in coastal impacts is based on direct downscaling of indicators defined by empirical formulations (total water level for coastal flooding and number of hours per year with overtopping for port operability). Global multimodel projections of the significant wave height and peak period are consistent with changes obtained in previous studies. Statistical confidence of expected changes is obtained due to the large number of GCMs to construct the ensemble. The proposed methodology is proved to be flexible to project wave climate at different spatial scales. Regional changes of additional variables as wave direction or other statistics can be estimated from the future empirical distribution with extreme values restricted to high percentiles (i.e., 95th, 99th percentiles). The statistical framework can also be applied to evaluate regional coastal impacts integrating changes in storminess and sea level rise.

Historical and future storm surge around New Zealand: From the 19th century to the end of the 21st century

“…Even though storm surge projections studies are limited, the same dipole between islands was found in previous analysis on wave global projections (Hemer et al ., ; Semedo et al ., ; Camus et al ., ), leading to a storm surge decrease in the north island while an increase in storm surge is predicted in the south island. In the analysis developed at the Port of Tauranga, Bell et al .…”

Future Wave Conditions of Europe, in Response to High‐End Climate Change Scenarios

“…In this study we used dynamical models to study the behavior of waves around NW European coasts, which requires a large amount of computational effort, compared to studies done by statistical downscaling methods (e.g., Camus et al, 2017). Therefore, we decided to choose one well-tested GCM with good performance over NW Europe rather than using several models in an ensemble.…”

“…Hemer and Trenham () show that high performance of GCMs for standard climate variables does not imply high performance for GCM‐forced wave simulations. Camus et al (), using weather typing and statistical downscaling, informed by a historical data set of wave data, showed how this method could be used to provide high‐resolution coastal impact assessment, including additional variables such as wave period and direction as well as SWH. Their results show that the global multimodel projections of the SWH and peak period are consistent with changes obtained in previous studies, that is, a decrease in mean wave height and peak period for the North Atlantic.…”

Coastal wetland resilience to climate change: modelling ecosystem response to rising sea level and salinity in a variable climate

“…The 2, 4, and 8 year recurrence interval water levels were estimated for respective sea level rise RCP scenarios. Current research suggests that coastal water levels during extreme events are rising with an increase in wave height and sea level (e.g., Hemer et al 2013;Camus et al 2017;Mentaschi et al 2017;Vousdoukas et al 2018). Statistical tests of the tidal gauge data indicated no significant change in extreme sea levels over the period of record.…”