Marcos Matamoros, RaülLlasat Botija, María del CarmenQuintana Seguí, PereTurco, Marco2018-03-052020-01-012018-01-010048-9697https://hdl.handle.net/2445/120430In this paper, we have compared different bias correction methodologies to assess whether they could be advantageous for improving the performance of a seasonal prediction model for volume anomalies in the Boadella reservoir (northwestern Mediterranean). The bias correction adjustments have been applied on precipitation and temperature from the European Centre for Middle-range Weather Forecasting System 4 (S4). We have used three bias correction strategies: two linear (mean bias correction, BC, and linear regression, LR) and one non-linear (Model Output Statistics analogs, MOS-analog). The results have been compared with climatology and persistence. The volume-anomaly model is a previously computed Multiple Linear Regression that ingests precipitation, temperature and in-flow anomaly data to simulate monthly volume anomalies. The potential utility for end-users has been assessed using economic value curve areas. We have studied the S4 hindcast period 1981-2010 for each month of the year and up to seven months ahead considering an ensemble of 15 members. We have shown that the MOS-analog and LR bias corrections can improve the original S4. The application to volume anomalies points towards the possibility to introduce bias correction methods as a tool to improve water resource seasonal forecasts in an end-user context of climate services. Particularly, the MOS-analog approach gives generally better results than the other approaches in late autumn and early winter.11 p.application/pdfengcc-by-nc-nd (c) Elsevier B.V., 2018http://creativecommons.org/licenses/by-nc-nd/3.0/esPrevisió del tempsPantans (Enginyeria civil)Mediterrània (Regió)Weather forecastingReservoirsMediterranean Regioninfo:eu-repo/semantics/article6755512018-03-05info:eu-repo/semantics/openAccess