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Regional climate model skill to develop small-scale transient eddies
Martin Leduc, René Laprise, Mathieu Moretti-Poisson and Jean-Philippe Morin
Canadian Regional Climate Modelling and Diagnostics (CRCMD) Network - ESCER Centre - Université du Québec à
Montréal, Montréal, Canada, leduc@sca.uqam.ca.
1. Introduction
Over the last few years, the perfect-model approach has
been used in several experiments to measure the sensitivity
of the Canadian Regional Climate Model (CRCM) to
various parameters characterizing its nesting technique.
Leduc and Laprise (2008, hereafter LL08) recently
conducted a domain-size experiment that highlighted a wellknown
characteristic of RCM: the control of the lateral
boundary conditions (LBC) on the large-scale component of
the solution becomes weaker when using wide domains
(unless spectral nudging at large scales is applied). Another
effect measured after changes in domain size is related to the
small-scale transient activity, not excited by the LBC but
generated within the RCM domain by local forcing and
through non-linear interactions. Evidence has been found
that the generation of such variability can be highly
penalized over a region of interest if located near to the
inflow boundary. This region where small-scale transient
eddies are deficient in intensity has been interpreted as the
characteristic distance of spin-up that the large-scale inflow
must travel to generate small-scale features with sufficient
intensity. Similarly, de Elía (2006) measured the
characteristic spin-up time for the small scales when
developed from initial conditions containing only large-scale
features.
The LL08 experiment has been performed by running the
CRCM for the winter season over midlatitudes. In order to
generalize, we have extended this work to include the
summer season, where the flow is rather turbulent and
subject to strong convective processes. These new results
give a homogenous spatial spin-up overall the domain of
interest since summer circulation shows frequent changes in
the domain ventilation regime.
An additional experiment has been made by reproducing the
winter experiment but including spectral nudging at large
scales (SN). This technique strongly diminishes variations of
the large-scale flow between two simulations using different
domain sizes. It hence facilitates to unambiguously attribute
differences in small-scale transient patterns to the distance
traveled by the large-scale inflow from the lateral
boundaries. In the following, the perfect-model approach is
used to evaluate the skill of an RCM to develop small-scale
features, for both winter and summer and under conditions
of strong SN.
2. Experimental framework
The perfect-model approach consists of integrating an RCM
over a large domain, called the Big-Brother simulation (BB).
Secondly, BB is low-pass filtered to result in a coarsely
detailed dataset, similar to what usually constitutes the LBC
for driving an RCM. This filtered time series is used to drive
the same RCM over a smaller domain, called the Little-
Brother (LB), which is finally compared to the unfiltered
reference (BB) solution.
The BB simulations produced for winter and summer
seasons are labeled BW and BS respectively. These short
“climates” consist of appending four February (winter) and
four July (summer) months by driving the CRCM with
NCEP reanalyses for the years 1990 to 1993. The BB
domain of integration covers 196x196 grid points with a
center located over Québec, Canada. LB simulations for
winter are named L1W, L3W and L4W for domains of
144x144, 96x96 and 72x72 grid points respectively. Also,
the smallest domain (72x72) has been integrated for the
summer season (L4S). Finally, L1W have been repeated
with the use of a strong SN (L1WN). In Tab. 1 are
summarized the labels and characteristics defining the
CRCM simulations analyzed here. A common domain of
38x38 grid points is used for comparing the simulations.
In the following, we focus on the small-scales features of
the flow, which have been extracted by Fourrier filtering
and correspond to the length scales smaller than 1080 km,
including a smooth transition that reaches 2160 km.
Reader is invited to refer to Leduc and Laprise (2008) for
a detailed description of the experimental procedure.
Name Season Domain
size
SN
strength
BW, BS W, S 196 2 no
L1W W 144 2 no
L3W W 96 2 no
L4W, L4S W, S 72 2 no
L1WN W 144 2 yes
Table 1 Characteristics of the simulations where winter
and summer are respectively represented by W and S and
domain sizes are given in grid points.
3. Small-scales features sensitivity to season
The RCM skill to develop small-scale features are
compared for winter and summer experiments. The
transient eddies of the small-scales features are plotted on
Fig. 1 for the 700-hPa relative humidity field. Virtual
reference simulations (BW and BS) are displayed for both
seasons (Fig. 1 a and b) with associated Little-Brother
(Fig. c and d) integrated over a very small domain (L4W
and L4S on Tab. 1). The first noticeable feature of LBs
compared to BBs is that they display important
underestimations of transient activity. Averaged over the
displayed domain, L4W regenerates 46% of the BW
transient variance while for L4S a value of 59% is
obtained. When attention is devoted to the shape of
patterns compared to the BBs, spatial correlation (R*) for
L4W is poor (R* = 50%) compared to L4S which gives a
value of 90%. The winter small-scale transient pattern is
highly distorted due to a strong westerly inflow and
proximity of the western boundary from the domain of
interest. For the summer case, L4S retains the general
features of the BS pattern, as the northern maximum and
the south-north gradient of relative humidity. Better skill
of the summer simulation to preserve BB pattern in both
intensity and spatial correlation in comparison to same
domain size in winter is partly due to the fact that summer
inflow is weaker and often changes in direction over short
periods (few hours). It results in a spatial spin-up that is
homogenously distributed over the domain of interest,
unlike the winter case where spatial spin-up is
concentrated on a specific region. Also, a better ability to
reproduce small-scale transient variability in summer may
be related to stronger convective processes occurring in