Future Projection for Wave Climate around Taiwan Using Weather-Type Statistical Downscaling Method

Abstract

Taiwan is surrounded by sea; therefore, coastal hazards might become severe due to climate change. The analysis of wave climate characteristics at different time scales (long-term historical period, seasonal prediction, and future prediction) can be used as a reference for the impact of climate change on coastal environments. This model associates the significant wave height with the atmospheric predictor defined by the sea level pressure (SLP) field. We applied SLP based on the outputs of a global climate model (GCM) under two possible future scenarios (RCP4.5 and RCP8.5) in the Fifth Assessment Report, AR5 (IPCC, 2014), then used the historical data of the predictor (sea level pressure) and predictand (sea-state parameters) from reanalysis databases to calibrate the model. The recent historical atmospheric conditions responsible for the swell wave component at the target site are included in the predictor definition. The 18 days sea level pressure fields are used as a predictor by utilizing the evaluation of source and travel-time of wave energy reaching a local area (ESTELA) method. The verification proves the model’s skill to reproduce the seasonal and interannual variability of monthly sea state parameters and can be used to further evaluate the wave climate change around Taiwan under different climate change scenarios. The prediction of wave climate on weather types provides a physical explanation for the relationship between the multivariate wave climate characterization and atmospheric forces. Through the analysis of the similarity and consistency between GCM data and reanalysis data, we can evaluate the suitability of GCM for wave climates in the Taiwan sea area. It shows how the weather type statistical method can be used to quantify the wave climate prediction results of each GCMs and to evaluate their differences and uncertainties, which will improve the estimation of the impact of wave climate change on Taiwan’s coast.