Mean fields and interannual variability in RCM simulations over Spain: the ESCENA project

Abstract

The ESCENA (2008 to 2012) project is a Spanish initiative, which applies the dynamical downscaling technique to generate climate change scenarios based on an ensemble of Regional Climate Models (RCMs) consisting of PROMES, WRF, MM5 or REMO over Peninsular Spain and the Balearic and Canary Islands using a high resolution of 25 km. We describe the mean fields and interannual variability for temperature and precipitation in an ensemble of simulations forced by the high resolution ERA-Interim reanalysis (1990 to 2007) and compare them to the Spain02 observed data set. Maximum surface air temperature shows seasonal cold biases up to -2.5K in all models and it is clearly underestimated during the coldest seasons, but less so during summertime (JJA). Generally, there is a better agreement between observed and simulated minimum surface air temperature, which is slightly overestimated (up to + 2K) especially during wintertime (DJF). Regarding precipitation, all models except PROMES tend to show low dry biases during all seasons, especially for autumn on the Mediterranean coast of the Iberian Peninsula. With respect to the interannual variability, the PROMES simulations overestimate the standard deviation of maximum surface air temperature, while the remaining models tend to slightly underestimate it, and most models tend to underestimate the standard deviation of precipitation. The results highlight the ability of these RCMs to reproduce the mean fields and the interannual variability in a very complex terrain such as the Iberian Peninsula, showing a great diversity of climatic behavior. The evaluation of the ensemble results indicates a great improvement in the temporal correlation and the representation of the spatial patterns of temperature and precipitation for all seasons with respect to the individual models.

Present-climate precipitation and temperature extremes over Spain from a set of high resolution RCMs

“…A similar negative bias in R20MM can be seen for all models except PROMES, but R95PTOT is rather well captured by all models. In contrast to the southwestern area, the temporal correlation (Jiménez-Guerrero et al 2013) is much lower for all the models here. This indicates that the errors for the Mediterranean coast are also linked to deficiencies in the simulation of the temporal distribution of precipitation.…”

“…The northern coast is an area with low CDD and high R20MM values. Precipitation occurs throughout the year, and the interannual variability (shown in the companion paper, Jiménez-Guerrero et al 2013) is rather low. For this regime, the spread of the model results is the lowest, as indicated by the Perkins skill score (Table 3).…”

“…But the present setup, with western lateral boundaries far away from this region and nesting in ERA-Interim, does not improve previous results. We can obtain more information about biases in this area from the companion paper (Jiménez-Guerrero et al 2013). As shown there, the interannual variability is high and is not well captured by most models.…”

“…A summary of the physics parameterizations for each of them is shown in Table 1. These models are described in more detail in Jiménez-Guerrero et al (2013).…”

Exploring adaptation choices for grapevine regions in Spain

“…From the viticulture point of view, this reference period represents the baseline conditions since irrigation was permitted in Spain; the selection of an earlier baseline would have implied a major structural change in the production system. Christensen and Christensen (2007) provide high-resolution scenarios at the European level that have been further downscaled for the Spanish territory by Jimenez-Guerrero et al (2013); the Jimenez-Guerrero et al (2013) scenarios were used because they are supported by the Spanish Ministry of the Environment ESCENA project and will likely be used in future agricultural regulations. Nineteen climate change scenarios were constructed from general circulation model (GCM) outputs (simulations with the ECHAM5r2, CNCM3, HadCM3-Q3, HadCM3-Q16 models) driven by the A1B emissions scenario (703 ppmv in CO2 concentration by the year 2100, defined in the IPCC Special Report on Emissions Scenarios-SRES- (Nakicenovic et al 2000).…”