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Climate change projections for the XXI century over the Iberian peninsula
using dynamic downscaling
J.J. Gómez-Navarro, J.P. Montávez, S. Jerez and P. Jiménez-Guerrero
Departamento de Física, Universidad de Murcia, Edificio CIOyN, Campus de Espinardo, 30100, Spain.
(jjgomeznavarro@um.es)
1. Introduction
Climate change is one of the most concerned problems in
the actual society, as pointed by the last report of the IPCC
(IPCC, 2007). Specifically, the Iberian Peninsula (IP), as
part of the Mediterranean Region, has been identified as one
of the most responsive regions to climate change (Giorgi,
2006; Diffenbaugh et al., 2007).
Due to its orographic complexity, the IP has many different
climates, and a good spatial resolution is needed to
understand the details and possible effects of climate
change. Nevertheless, the Global Circulation Models (GCM)
have a too coarse resolution which makes them unfeasible to
study climate change implications over the IP.
4. Results
The spatial structure of the patterns and their temporal
evolution have been studied separately.
A very important feature of the warming patterns is that
they have an important annual cycle: summer patterns
look quite different from the winter ones. For example in
the Figure 1 are depicted the spatial patterns for 2-m
maximum temperatures for March (up) and July (down),
respectively. In summer months, the patterns look more
continental, meanwhile in spring and autumn they seem to
follow the orography. Nevertheless there are many
differences in the behavior of maximum and minimum 2-
m temperatures (not shown).
For this reason, a regionalization process must be carried out
to improve the spatial resolution of climate projections in
order to assess the climate change over the IP.
2. Experiments
The simulations have been performed using a climate
version of the regional atmospheric model MM5 (Montavez
et. al., 2006), over two-way nested domains with resolutions
of 90 and 30 km respectively. The inner domain covers the
full IP.
Four centennial simulations have been performed using
outputs from the GCMs ECHOG and ECHAM5 as driving
conditions. The notation for the fours experiments and the
time periods covered by each experiment is as follows:
• ECHOG-A2: covers the period 1990-2099
• ECHOG-B2: covers the period 1990-2099
• ECHAM5-A2: covers the period 2001-2099
• ECHAM5-A1B: covers the period 2001-2099
3. Methodology
In order to investigate the warming signal along the XXI
century an Empirical Orthogonal Functions (EOF) analysis
has been used. This approach increases the signal to noise
ratio, reduces the huge dimensionality of the problem and
makes possible to analyse independently the spatial and
temporal features of the 2-m temperature series (von Storch
and Zwiers, 2007).
The maximum and minimum 2-m temperature monthly
series have been studied for each month separately in each
experiment. In all cases, the variance explained by just the
first EOF is around 85% percent of the total. This implies
than the first EOF contains the warming pattern, as obtained
by others authors (e.g. Zorita et al., 2005). For this reason,
below only the first EOF is studied, and it is referred as the
spatial warming pattern.
Figure 1: Spatial warming pattern for March (up) and July
(down).