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Sensitivity studies of model setup in the alpine region using MM5 and
RegCM
Irene Schicker, Imran Nadeem, Herbert Formayer
Institute of Meteorology, University of Natural Resources and Applied Life Sciences, Peter-Jordan-Straße 82, A-1190
Vienna, Austria, irene.schicker@boku.ac.at
1. Introduction
Regional climate modeling in the alpine area is a
challenging task. Currently, our institute is participating in
two projects, CECILIA (http://cecilia-eu.org) and
Reclip:century (Basic Data Set of Regional Climate
Scenarios), to study regional climate change in the Alpine
region using two different meteorological models, MM5
(Grell et al., 1994) and RegCM (Pal et al., 2007). The
present study is a part of these projects and focuses on
selection of domain, nesting versus direct runs, comparison
of different physical parameterization schemes and lateral
boundary conditions. The horizontal resolution of 10 km is
used to capture the effects of the complex topographical and
land use features of the region.
The case study is carried for the year 1999. This year is
particularly interesting because of flooding in Danube
Catchment in May followed by the storm in December.
2. Domain and Model setup – MM5
As the innermost domain should cover both the Alpine ridge
and the eastern parts of Austria and comparability with the
Greater Alpine Region (GAR) (Auer et al., 2007) should
also be given, no changes on the horizontal domain size
have been made. For the outermost domain, four different
grid box setups have been tested. Results of two of them,
domain ML and domain L, are shown here (see Fig. 1). Due
to computational limitations 30 vertical half σ levels have
been used.
Zängl options for alpine modeling (z-diffusion, orographic
shadowing) implemented in MM5V3.7 have been used in all
the test runs. One test run used additional improvements in
the NOAH LSM scheme implemented by G. Zängl and his
group (Mauser and Strasser, 2007). Table 1 gives an
overview of the different setups and physical
parameterizations used.
Table 1. Setups of the different sensitivity runs.
Cumulus schemes used are BM for the outermost domain
and Grell for the innermost domain.
ML1 ML2 L1 L2
PBL ETA/MRF ETA ETA/MRF ETA
radiation RRTM RRTM RRTM RRTM
Land
5 layer
5 layer
NOAH
NOAH
use
soil
soil
cumulus
scheme
BM/Grell BM/Grell BM/Grell BM/Grell
explicit
moisture
Reisner 2 Reisner 2 Reisner 2 Reisner 2
3. Domain and Model setup – RegCM
The innermost domain used by RegCM3 simulations closely
resembles that of MM5. The boundary conditions used for
various simulations were ECMWF Interim Re-Analysis
(ERA-Interim, 0.75° and 1.5° grid spacings, 6-h intervals),
the ECMWF 40 Years Re-Analysis (ERA40, 1° and 2.5°
grid spacings, 6-h interval) and finally the 2.5°, 6-h
NCEP/DOE AMIP-II Reanalysis (Reanalysis-2). Sea
Surface Temperature for the simulated periods was
obtained from a UK Met Office Global Ocean Surface
Temperature (GISST), a set of SST data in monthly 1°
area grids. Table 2 summarizes different domain settings
and Nesting strategies for RegCM3 simulations.
Table 2. Setup of RegCM sensitivity runs.
Reanalysis Resolution Nesting Physics
2 / 3 nests 1 / 2 nest
ERA 40
30 km
10 km
1 way direct
ERA 30 km
Interim 10 km
1 way direct
NCEP/DOE
AMIP-II
90 km
30 km
10 km
1 way
30 km
10 km
Domain setup of the RegCM runs is shown in Figure 1.
Grell
Conv.,PBL
(Holtslag),
BATS1e
Radiation:
NCAR
CCM3
SUBEX
Figure 1. MM5 and RegCM domains. In magenta MM5
domain 2, which has been used in all three domain
settings. In blue RegCM domain 2 and 3 respectively. In
green MM5 domain1 L, in red MM5 domain ML. RegCM
domain 1 is shown in cyan.
4. Results
Very first results of the May 1999 case study simulated
with MM5 show that the general patterns of the
precipitation are very well captured if using grid nudging
options to avoid drifting of the model. As grid nudging is
not advisable when performing climate simulations, also
some runs without grid nudging have been performed.
First results of the May 1999 flooding event of two
different L1 runs, without grid nudging, are shown in
Figures 3 and 4. In Figure 2 the 72 h precipitation sum,
obtained from the gridded observation data set of Frei and
Schär (1998) is shown for comparison.
The RegCM3 simulation driven with ERA40 and ERA-
Interim shows that direct downscaling to 10km produces
better results than Nested Run 30km10km. When
recently released ERA-Interim Reanalysis was used as
lateral and boundary conditions, the simulated