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An ensemble of regional climate change simulations
Erik Kjellström, Grigory Nikulin, Lars Bärring, Ulf Hansson, Gustav Strandberg and Anders Ullerstig
SMHI, SE 60176 Norrköping, Sweden, erik.kjellstrom@smhi.se
1. Introduction
Uncertainties in future climate change are related to
uncertainties in external forcing, model formulation and
natural variability. A common way to deal with uncertainties
in external forcing is to use different emission scenarios
thereby sampling a multitude of possible outcomes
Nakićenović et al. (2000). By using multiple climate models
or an ensemble of simulations with one model perturbed in
its formulation of the physics, parts of the uncertainties
related to how changes in forcing influence the climate can
be assessed (e.g. Meehl et al., 2007, Murphy et al., 2007).
To get a grip on the natural variability one may use several
simulations with one climate model under the same emission
scenario differing only in initial conditions. A way to handle
all three main uncertainties is to perform several simulations
constituting an ensemble. Previous attempts to do this on the
regional scale in the European projects PRUDENCE (e.g.
Déqué et al., 2007) and ENSEMBLES (Sanchez-Gomez et
al, 2008) have limitations in that only a few GCMs have
been used to provide lateral boundary conditions
(PRUDENCE) or that only one emission scenario has been
considered (ENSEMBLES). At the Rossby Centre, a
regional ensemble has been created that makes use of a
number of GCMs, several emission scenarios, and in some
case several simulations differing only in initial conditions
in the GCM. The ensemble can be used to illustrate
uncertainties on the regional scale and to produce
probabilistic climate change information in a region.
2. Model and simulations
We use the regional climate model RCA3 (Kjellström et al.,
2005) to dynamically downscale several experiments with
global coupled atmosphere-ocean general circulation models
(AOGCMs). Table 1 summarizes the experiments in terms
of AOGCM (references for these are given in Meehl et al.
(2007), emission scenario and horizontal resolution. In
particular we study a subset of the simulations all under the
A1B emission scenario and with five different forcing
AOGCMs. This subset is denoted ENS5 in the following.
Figure 1. Difference in seasonal mean T 2m between
ENS5 and the ENSEMBLES gridded dataset
(Haylock et al., 2008) for winter (DJF) conditions in
the 1961-1990 period.
3. The recent past climate
We evaluate the ability of RCA3 to reproduce the recent
past climate when forced on the lateral boundaries by the
different AOGCMs. As the AOGCMs, and thereby RCA3,
in general show a somewhat too zonal climate during
winter the simulated temperature climate is too warm (Fig.
1) and too wet (not shown) over much of the continent.
Table 1. Simulations in the Rossby Centre regional
climate change ensemble. Number of simulations is
given in parenthesis if more than 1. 3* denotes that 3
different members from the perturbed physics
ensemble with HadCM3 are used. Simulations in
italics constitute the “sub-ensemble” ENS5.
AOGCM Emission
scenario
Horizontal
resolution (km)
BCM A1B 25, 50
CCSM3 A2, A1B, B2 50
CNRM A1B 50
ECHAM4 A2, B2 50
ECHAM5 A1B (3 at 12.5, 25, 50
50km), B1, A2
HadCM3 A1B 25, 50(3*)
IPSL A1B 50
Figure 2. Difference in seasonal mean T 2m between
ENS5 and the ENSEMBLES gridded dataset
(Haylock et al., 2008) for summer (JJA) conditions
in the 1961-1990 time period.
In summer there is also a (weaker) warm bias in central
Europe but now also a cold bias in the northeastern part of
the domain (Fig. 2). The cold bias in the northeast is seen
also in experiments in which RCA3 is forced by reanalysis
data (Kjellström et al. 2005). In summer there are no