@misc{10481/81529,
year = {2023},
month = {3},
url = {https://hdl.handle.net/10481/81529},
abstract = {This work presents the performance analysis of a multi-model ensemble of wave climate projections in the Mediterranean
Sea against hindcast data. The wave projections were developed with the numerical model Wavewatch III forced by surface
wind fields of 17 EURO-CORDEX GCM-RCMs providing time series of the main wave parameters on a 3-h and 10-km
resolution. The performance of the wave GCM-RCM simulations during the baseline period (1979–2005) was assessed by
means of the deterministic metrics RMSE and Bias. Different bias correction methodologies were analyzed by means of the
application of the widespread Empirical Quantile Mapping method considering different time periods of significant wave
height in order to analyze the ability of the bias-correcting methods to capture the different wave climate temporal scales
ranging from storm events, monthly, seasonal and interannual variability. The results show that the use of the EQM method
for the full-time series without taking into account other timescales, can lead to increased biases in some regions and seasons
and that the use of time-dependent bias-correction techniques leads to an improved accurate characterization of biases
considering the interannual temporal variability of significant wave height. More specifically the use of the EQM method for
monthly data provides a good performance in capturing the correlation and interannual temporal variability of wave climate.},
publisher = {Springer Nature},
keywords = {Bias-correction},
keywords = {Waves},
keywords = {Eqm},
title = {On the role of wave climate temporal variability in bias correction of GCM‑RCM wave simulations},
doi = {10.1007/s00382-023-06756-0},
author = {Lira Loarca, Andrea and Berg, Peter and Baquerizo Azofra, Asunción and Besio, Giovanni},
}