Bias correction and downscaling of future RCM precipitation projections using a MOS-Analog technique
In this study we assess the suitability of a recently introduced analog-based Model Output Statistics (MOS) downscaling method (referred to as MOS-Analog) for climate change studies and compare the results with a quantile mapping bias correction method. To this aim, we focus on Spain and consider da...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2017 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/103466 |
| Acceso en línea: | https://hdl.handle.net/2117/103466 https://dx.doi.org/10.1002/2016JD025724 |
| Access Level: | acceso abierto |
| Palabra clave: | Climate--Research Climate change Precipitation anomalies Model Output Statistics (MOS) Bias correction Clima--Observacions Canvis climàtics Àrees temàtiques de la UPC::Enginyeria biomèdica |
| Sumario: | In this study we assess the suitability of a recently introduced analog-based Model Output Statistics (MOS) downscaling method (referred to as MOS-Analog) for climate change studies and compare the results with a quantile mapping bias correction method. To this aim, we focus on Spain and consider daily precipitation output from an ensemble of Regional Climate Models provided by the ENSEMBLES project. The reanalysis-driven Regional Climate Model (RCM) data provide the historical data (with day-to-day correspondence with observations induced by the forcing boundary conditions) to conduct the analog search of the control (20C3M) and future (A1B) global climate model (GCM)-driven RCM values. First, we show that the MOS-Analog method outperforms the raw RCM output in the control 20C3M scenario (period 1971–2000) for all considered regions and precipitation indices, although for the worst-performing models the method is less effective. Second, we show that the MOS-Analog method broadly preserves the original RCM climate change signal for different future periods (2011–2040, 2041–2070, 2071–2100), except for those indices related to extreme precipitation. This could be explained by the limitation of the analog method to extrapolate unobserved precipitation records. These results suggest that the MOS-Analog is a spatially consistent alternative to standard bias correction methods, although the limitation for extreme values should be taken with caution in cases where this aspect is relevant for the problem. |
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