Development of a Regional Climate Model for Midwest Applications, Part I: Domain Choice
Xin-Zhong Liang and Kenneth Kunkel
Illinois State Water Survey, University of Illinois at Urbana-Champaign
May 31, 2000
1. Introduction
A mesoscale regional climate model (RCM)
optimized for Midwest applications is currently
undergoing intensive development and extensive
validation. The RCM is based on the newly released MM5 version 3.3. The MM5, however,
was originally developed for short-term applications, such as those related to local storms or daily
weather disturbances. To extend its capability for
applications on regional climate time scales, we
are incorporating four crucial improvements: (1)
an optimal buffer zone treatment that integrates
realistic energy and mass fluxes across the RCM
lateral boundaries; (2) an advanced land surface
model (LSM) that represents detailed soilvegetation-atmosphere interactions; (3) a realistic
ocean interface where sea surface temperature
(SST) evolves as observed or is determined by a
coupled slab model; and (4) an accurate cloudradiation parameterization that enables multi-scale
interactions between hydrologic and thermodynamic processes. The present study, in particular,
will focus on domain choice (part of the buffer
zone treatment) and its impact on the Midwest
1993 summer flood simulation.
2. Model Physics Configuration
The RCM utilizes multiple nested-grid domains (see section 3). For the purpose of this
study, all domains adopt the identical physics configuration as follows. The land surface is treated
by the OSU LSM (Chen and Dudhia 2000). The
planetary boundary layer is parameterized by the
MRF nonlocal-K approach (Hong and Pan 1996).
Precipitation is determined by the combination of
the GSFC (Tao and Simpson 1989) explicit microphysical treatment, the Grell (1993) cumulus
parameterization and shallow convection. Solar
and infrared radiations are incorporated as in the
NCAR CCM2 (Hack et al. 1993) and are calculated every 30 minutes. The radiative effect of both
cumulus and non-convective clouds are considered. All these modules come with the MM5,
though several corrections were made to ensure
consistent coupling. Note that the SST distribution
was originally fixed at a specific time and inappropriate for climate scale integrations. Thus, a
modification was made to incorporate observed
daily SST variations into the RCM.
3. Domain Choice
The ultimate use of the RCM is to dynamically downscale GCM (general circulation model)
climate predictions onto regional and local scales
for climate-impact applications. A successful
RCM downscaling requires accurate implementation of initial atmospheric and surface conditions
as well as realistic lateral boundary forcings
across the buffer zone which separates the GCM
and RCM domains. Minor lateral forcing errors
quickly propagate into the RCM domain and
cause the model to produce unrealistic forecasts
(Warner et al. 1997), especially for seasonal predictions.
Thus an optimal buffer zone treatment is required to integrate realistic energy and mass fluxes across the RCM lateral boundaries. Davies and
Turner (1977) developed a dynamic relaxation
technique to update lateral boundary conditions
(LBCs), where appropriate relaxation coefficients
were used to damp high frequency forcing errors
within the buffer zones. The buffer zones are designed to integrate (or assimilate) robust GCM
forcings into the RCM formulation, where consistency is maintained in the zones, while the
RCM generates its own mesoscale circulation
within the domain interior (Giorgi et al. 1993). As
the default, the MM5 buffer zone contains 4 grid
points each side and nudging coefficients are linearly reduced inward from 1 to 0. Given this assimilation technique, the remaining problem is the
RCM domain choice, which in turn is determined
by specification of buffer zone locations.
Ideally, the buffer zones are chosen such that:
(1) distinct features governing regional climate are
optimally represented by the RCM; (2) local
GCM predictive skill of low frequency oscilla-
tions and moisture fluxes is maximized; (3) high
frequency LBC forcing errors are effectively absorbed. Based on these criteria and comprehensive
comparisons between the NCEP/ NCAR reanalysis (NRA; Kalnay et al. 1996), ECMWF reanalysis (ERA; Gibson et al. 1997) and NCAR CCM3
ensemble simulations during the common period
1979-1993, we chose the RCM configuration that
incorporates two nested domains (Fig. 1). The
outer domain is driven by the GCM forcings and
has a coarse grid resolution of 90x90 km2 over an
extended area including the continental US. The
inner nesting domain has a finer grid resolution of
30x30 km2 and covers the US Midwest. The two
domains are fully coupled with instantaneous interactions. Both RCM grid meshes have an identical vertical resolution, with 23 model layers and
the top at 100 hPa. Note, for local impact studies,
we can further add a nesting refinement, for example, the domain 3 with a grid resolution of
10x10 km2 over Illinois.
Fig. 1. The CTL domain design.
To study the impact of domain choice on the
RCM downscaling skill, sensitivity experiments
are conducted where various outer domain sizes,
and thus buffer zone locations, are used while the
inner domain is kept identical. In this study, we
only present the results of three experiments. The
CTL (control) integration adopts the domain design in Fig. 1. For the EWE (east-west expansion)
simulation, the outer domain is expanded by 15
grids along both east and south sides, while it is
further expanded by 10 grids to the south and
north in the ASE (all side expansion) experiment.
4. Midwest 1993 Summer Flood
Record flooding occurred in the Mississippi
River basin during May-July 1993 (Kunkel et al.
1994). Over much of the Midwest and northern
Plains, rainfall exceeded 150% of normal values
and produced major flooding from the Dakotas to
Missouri. This extreme event has been well documented and identified with physical mechanisms
from both planetary forcings and local reinforcements. It is an ideal case to evaluate the RCM
downscaling skill. Here, all RCM experiments are
initialized at May 1 and integrated for 3 months.
The initial conditions and LBCs during the period
are constructed from NRA.
Figure 2 shows the observed and simulated
June and July mean precipitation (mm day-1) over
the inner domain. In June, the CTL rainfall is insufficient and less organized, the ASE rainband is
shifted to the east, while the EWE overpredicts
the amount over South Dakota and Nebraska. This
general failure may be attributed to unrealistic soil
moisture initialization. Our initial soil moisture
condition is specified from the NRA model output
and may not be realistic. In observations, the
floods were preceded by an extended period of
moist surface conditions over the eastern half of
the United States and unusually large Rocky
Mountain snowpack. Resulting spring soil moisture and runoff were both anomalously high. The
RCM experiments do not incorporate these observed conditions during spring.
In observations, July precipitation was substantially enhanced and more concentrated over
Iowa, Missouri, Kansas and Nebraska. Another
center occurred in North Dakota. The CTL reproduces the July feature reasonably well, except that
the major rainband is somewhat shifted northward
and expanded too much to the northeast. These
biases are corrected in the ASE. The worst simulation is identified with the EWE.
For both June and July, the 500hPa height and
200hPa wind circulation are best reproduced in
the CTL and worst in the ASE. On the other hand,
the CTL Bermuda high is too strong and the corresponding lower level jet stream (LLJ) over the
Great Plain is too intensive (10 versus 8 m/s in
June and 16 versus 10 m/s in July), both systems
displaced northward. This causes the north shift of
the major rainband. In contrast, the ASE produces
a weaker LLJ (~2 m/s less) and yet more realistic
moisture distribution, especially in July. This may
explain the realistic rainfall simulation.
5. Conclusion
The result clearly shows that the RCM
downscaling skill strongly depends on the model
domain choice. No single domain reproduces all
aspects of the observed circulations. This calls for
further improvements of model dynamical (especially the buffer zone treatment) and physical (including land surface, PBL, convection and cloudradiation interactions) configurations. Yet the
poor quality of the NRA forcing conditions must
also attribute much of the biases identified in the
RCM simulations. Accurate initial and lateral
boundary conditions, however, will not be available in a foreseeable future. Therefore, a robust
buffer zone treatment, including both location
specifications and assimilation techniques must be
developed. Given such a treatment in place, we
can then rigorously improve and validate the
RCM physics parameterizations to suite Midwest
climate applications.
Acknowledgements. We thank NCAR/MMM for
the MM5 system, NCEP/NCAR for the reanalysis
data and NCSA for the supercomputing support.
We thank Jimy Dudhia and Wei Wang for their
assistance during the initial MM5 implementation.
The research was supported by the UIUC Campus
Research Board Award.
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