Statistical wave climate projections for coastal impact assessments
| Autor: | Camus Braña, Paula, Losada Rodríguez, Iñigo, Izaguirre Lasa, Cristina, Espejo Hermosa, Antonio, Menéndez García, Melisa, Pérez García, Jorge |
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| Přispěvatelé: | Universidad de Cantabria |
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Zdroj: | Earth's future Volume 5, Issue 9 September 2017 Pages 918?933 UCrea Repositorio Abierto de la Universidad de Cantabria instname |
| Popis: | 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. The authors acknowledge the support of the Spanish Ministerio de Economía y Competitividad (MINECO) and European Regional Development Fund (FEDER) under Grant BIA2015-70644-R (MINECO/FEDER, UE). The authors are grateful to Nicolás Ripoll for his help in the performing the statistical simulations. The DAC data is produced by CLS Space Oceanography Division and distributed by Aviso, with support from Cnes (http://www.aviso.altimetry.fr/). The CMIP5 sea level pressure data are available at http://cmip-pcmdi.llnl.gov/cmip5/data_portal.html. Mean sea level projections are available at ftp://ftp.icdc.zmaw.de/ar5_sea_level_rise/ |
| Databáze: | OpenAIRE |
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