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this season, as well as the higher residency time (Picher et
al. 2008) that could provide a longer time for small-scale
features spin-up.
to be attributable to the fact that the different large-scale
circulation occurring in L1W does not allow such feature
to develop.
Figure 1. Small-scale transient eddies of the 700-hPa
relative humidity for a) BW, b) BS, c) L4W and d) L4S. The
scale is given in %. The spatial correlation coefficient (R*)
with BW and BS for L4W and L4S are of 50 and 90%
respectively.
4. Effect of spectral nudging at large scales
This section focuses on how applying SN can affects
development of small-scale features simultaneously with
variations of the domain size. On Fig. 2 are shown the smallscale
transient eddies of the 700-hPa relative vorticity for the
virtual reference simulation (BW; Fig. 2 a), the largedomain
Little-Brother using SN (L1WN; Fig. 2 b) and
without SN (L1W; Fig. 2 c) and a smaller domain Little-
Brother with no SN (L3W; Fig. 2 d). See Tab. 1 for an
overview of simulations.
Let’s first concentrate on the similarities between patterns
by using the spatial correlation coefficient of the Little-
Brothers with the virtual reference climate (BW). L1W
displays the most different pattern with R* = 50% compared
to 79 and 72% for L1WN and L3W respectively. Since
small-scales features are somewhat preconditioned by the
large-scale information penetrating the domain through its
lateral boundaries, the fact that L1W shows such a different
small-scale pattern is principally attributable to the use of a
large domain without applying SN. Such conditions
engender a weak control of the LBC on the RCM large-scale
solution, and have a consequence on the small-scale
features. For the cases of L1WN and L3W, skills for pattern
matching with BW are higher than L1W for two different
reasons. L1WN uses a strong SN allowing a sufficient
control of the nesting data on the large-scale solution, in
despite of its large domain. Also, the large domain allows
for a sufficient distance needed to spin-up the small-scale
transient eddies. For L3W, SN does not seem required to
obtain a significant matching in small-scale feature patterns
since proximity of the lateral boundaries from the validation
area provides the control needed for keeping the large-scale
flow similar to the driving data.
Another interesting point is about potential side effects that
may be related to the use of a strong SN (Alexandru et al.
2009). From the results presented on Fig. 2, effect of SN on
intensity of small-scale transient eddies is not significant
when averaged overall the domain. However, it is clearly
visible that the southern maximum is not captured by the
large-domain simulation without SN (Fig. 2 c). This seems
Figure 2. Small-scale transient eddies of the 700-hPa
relative vorticity for a) BW, b) L1WN, c) L1W and d)
L3W. The scale is given in 1.0e-05 s -1 . The spatial
correlation coefficient (R*) with BW for L1WN, L1W and
L3W gives respective values of 79, 50 and 72 %.
5. Conclusions
The domain-size perfect-model experiment for a winter
short climate (LL08) has been compared with new results
obtained for the summer season. Simulations presented
here display a seasonal dependence of the domain-size
effect on the small-scale transient eddies. For winter, a
small domain of integration engender lacks in the transient
variability of the small-scale features, particularly on the
inflow side of the domain. In summer, simulations also
display such underestimations but those are homogenously
distributed overall the domain of interest. Differences in
the ventilation regimes that depend on season seem to
partly explain such different spatial spin-up. By
performing supplementary winter experiments using a
strong SN permitted a direct comparison of the smallscales
features for different domain sizes since the largescale
flow remains approximately the same. By this way,
it has been possible to isolate the effect of the distance
traveled by the inflow to explain the differences residing
in the intensity of small-scales transient eddies.
References
Alexandru, A., R. de Elia, R. Laprise, L. Separovic and S.
Biner, 2009: Sensitivity Study of Regional Climate
Model Simulations to Large-Scale Nudging
Parameters. Mon. Wea. Rev. (accepted)
de Elía R, Laprise R, Denis B, 2006: Forecasting skill
limits of nested, limited-area models: a perfect-model
approach. Mon. Wea. Rev., 130:2006–2023
Leduc, M. and R. Laprise, 2008: Regional Climate Model
sensitivity to domain size. Clim. Dyn., (Published
online, DOI 10.1007/s00382-008-0400-z).
Lucas-Picher, P., D. Caya, S. Biner and R. Laprise, 2008:
Investigation of regional climate models’ internal
variability with a ten-member ensemble of 10-year
simulations over a large domain. Mon. Wea. Rev.,
136:4980-4996.