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of the simulations due to the difference of the initial
conditions. The dark bars in Figure 2 show the results from
the simple vertical interpolation (P2S), whereas the white
bars indicate the incremental interpolation (INC). The
incremental interpolation significantly improves regional
simulation for nearly all ranges of pressure levels with the
exception of precipitation in 17L, 9L, and 3L. The
performance of the 7L results became very similar to that of
17L without the incremental interpolation (P2S-17L), and
even 3L produced a reasonably good regional simulation
compared to P2S-17L. Therefore, from a practical point of
view, approximately 5 pressure levels will be sufficient to
obtain reasonably accurate regional simulations. We should
note that the improvement is more apparent for 2-meter
temperature and 10-meter winds. Reasonable improvement
is also seen in precipitation.
resolution. Integration was done for one year (year of 2047
in A1B scenario, according to MIROC experiment) with
identical initial conditions.
Figure 3 shows monthly precipitation distributions
and their difference from CTL. Due to less vertical
information given by the forcing data, more precipitation
is simulated over the Central Valleys in COA, whereas the
wet condition is fixed in INC, even though exactly same
amount of information has been used. As shown in Figure
4, this is mainly due to more surface convergence
simulated in COA.
Total Precipitation
*Precipitation intensified
over central valley.
improved
Figure 3. Monthly precipitation from 10-km
regional dynamical downscaling of MIROC’s global
future projection results. Upper panels show
monthly distribution and lower panels show
difference from the control (CTL).
Surface Wind field
Figure 2. Ensemble means of area averaged RMS
between CTL and experiments with different numbers
of vertical levels used as forcings are shown for 2-
meter air temperature (a), 10-meter wind speed (b) and
precipitation (c).
4. Application to Regional Future Projection
Though highly expected, few of IPCC/WCRP’s CMIP3
simulation results can be directly used as lateral boundary
condition for dynamical downscaling study because these
data are archived with small number of vertical levels and
scarce temporal interval (at most daily). We therefore
investigated the impact of small number of vertical levels
and longer intervals of forcing data, particularly focused on
a purpose of the regional future projection. Japanese T106
MIROC simulation results are used, and all 23-level data are
used as lateral boundary for the control regional integration
(CTL). Similarly to the previous section, we applied the
simple vertical interpolation from coarse vertical data
(COA) and the incremental interpolation (INC) from the
lowest 9 levels (up to 200 hPa). In this experiment, we used
the ECPC RSM, but for a domain covering western U.S.A.
and Mexico and vicinity oceans in 10 km horizontal
*Virtual convergence
leads more precipitation
improved
and cooling.
Figure 4. Same as Figure 3, but for surface wind
fields.
References
Yoshimura, K. and M. Kanamitsu, Specification of
external forcing for regional model integrations, Mon.
Wea. Rev., 2009. (in print)
Kanamaru, H. and M. Kanamitsu, Scale-selective bias
correction in a downscaling of global analysis using a
regional model, Mon. Wea. Rev., 135, 334–350, 2006.