Abstract
Over the years higher resolution Regional Climate Model simulations have emerged owing to the large increase in computational resources. The 12 Km resolution from the Coordinated Regional Climate Downscaling Experiment for the European domain (EURO-CORDEX) is a reference, which includes a larger multi-model ensemble at a continental scale while spanning at least a 130-year period. These simulations are computationally demanding but not always revealing added value. In this study, a recently developed regular gridded dataset (Iberia0.1) and a new metric for added value quantification, the distribution added value (DAV), are used to assess the precipitation of all available EURO-CORDEX Hindcast (1989–2008) and Historical (1971–2005) simulations. This approach enables a direct assessment between the higher resolution regional model runs against their forcing Global model or ERA-Interim reanalysis, with respect to their PDFs. This assessment is performed for the Iberian Peninsula. Overall, important gains are found for most cases, particularly in precipitation extremes. Most Hindcast models reveal gains above 15 %, namely for wintertime, while for precipitation extremes values above 20 % are reached for the summer and autumn. As for the Historical models, although most pairs display gains, regional models forced by 2 GCMs reveal losses, sometimes around −5 % or stronger, for the entire year. However, the spatialization of the DAV is clear in terms of added value for precipitation, particularly precipitation extremes with significant gains, above 100 %.
Highlights
Over the years higher resolution Regional Climate Model simulations have emerged owing to the large increase in 30 computational resources
The Distribution Added Value (DAV) is a metric put forward by Soares and Cardoso (2018) which allows assessing in a direct way the gains or losses of using higher against lower resolution models relying on their probability density functions (PDF), by 140 having an observational dataset as reference
4 Discussion and conclusions In this study, the performance of Regional Climate Models (RCMs) from the Hindcast (1989-2008) and Historical (1971-2005) simulations is assessed relatively to their PDFs, by using a distribution added value metric proposed by Soares and Cardoso, (2018)
Summary
From the last decades of the 20th century up to today, climate change due to anthropogenic gas emissions become a major concern for mankind. The first to quantify the added value of the EURO-CORDEX hindcast runs were Soares and Cardoso, (2018), evaluating 5 RCMs for precipitation at both resolutions (50Km and 12 Km) considering their probability density functions with station-based dataset as observational benchmark. Torma et al (2015) evaluated precipitation over an alpine area, whereas Soares et al (2017) assessed the same variable but for Portugal Both studies describe the ability of the higher resolution runs in simulating 100 the mean spatial and temporal patterns of precipitation, as well as their distributions. The added value is computed comparing the RCMs precipitation results versus their corresponding driver GCM or ERA-Interim reanalysis, where the recently developed Iberia Gridded Dataset (IGD, Herrera et al, 2019) is considered as baseline.
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