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18
The Asian summer monsoon in ERA40 driven CLM simulations
A. Dobler and B. Ahrens
Institute for Atmosphere and Environment, Goethe-University, Frankfurt am Main, Germany (dobler@iau.uni-frankfurt.de)
1. Introduction
Regional climate simulations using the CLM (the climate
version of the COSMO-model, see http://www.clmcommunity.eu)
have been carried out in a South Asian
domain. The simulations are driven by ERA40 reanalysis
data and have a grid resolution of 0.44°. Similar simulations
with CLM are successfully performed for European
simulation domains (e.g., Dobler & Ahrens 2008). A shown
in Fig. 1 the precipitation climate simulated with CLM in
South Asia shows substantial deficiencies. The objective of
this paper is to discuss the representation of the monsoonal
system in the CLM and its relationship to the realized
precipitation fields.
2. Methods
There are several indices available which try to quantify the
strength and variability of the South Asian summer
Monsoon. These indices are based on rainfall (e.g.,
Parthasarathy et al., 1992), vertical zonal or meridional
wind shear (e.g., Webster and Yang, 1992; Goswami et al.,
1999), and on combinations of these parameters. In Wang
and Fan (1999) the choice of the appropriate index is
discussed and further indices are introduced.
In this work we apply the indices to the CLM simulations.
The results are compared to observations or ERA40 (Uppala
et al., 2005) and NCEP (Kalnay et al., 1996) re-analysis data
to find possible reasons for the CLM deficiencies.
3. Results
While the magnitudes of the different indices are of similar
order in CLM, ERA40 and NCEP, the correlations between
the time series of the indices from single data sources vary
considerably (not shown). Thus, we take a look at the spatial
distribution of the parameter fields involved in the index
calculations.
Figs. 1-3 show the spatial distribution of the precipitation
model bias of CLM, ERA40 and NCEP data compared to
GPCC for JJAS from 1960 to 2000. While the CLM shows
an overestimation of precipitation at the Indian west coast,
both re-analysis data sets show an underestimation in the
same region, but an overestimation just behind the coast.
The same holds for the east coast of the Bay of Bengal.
Over the whole Tibetan plateau, both ERA40 and NCEP
data show an overestimation of precipitation. Here the CLM
shows good agreement with the observational data set.
The differences in the 200-hPa winds are only small (not
shown). However, looking at the 850-hPa zonal winds in the
CLM model, the ERA40 and the NCEP re-analysis data
(Figs. 4-6), we see that the CLM shows higher wind speeds
between Somalia and the Indian west coast, and over the
Bay of Bengal.
At the foothills of the Himalayas, the CLM shows some
significant westward winds, which are not visible in the
ERA40 or NCEP data. This is also the region, where the
CLM shows the highest underestimation of precipitation.
But, we expect that these deficiencies are related to regional
phenomena and on only indirectly to the monsoonal
system representation.
The meridional 850-hPa winds east of Somalia are also
higher in the CLM model than in the re-analysis data (not
shown).
4. Conclusions
The generally high wind speeds at 200 hPa show only
small differences between the different data sets resulting
in vertical wind shear indices, which are of similar
magnitude in all three models. Therefore, it is difficult to
interpret the monsoonal dynamics in the model simulation
based on these indices.
However, looking into the parameter fields involved in the
applied monsoon indices allows a preliminary conclusion:
the simulation of the 850-hPa winds (especially the zonal
component) and in consequence the moisture flux have a
strong influence on the simulated precipitation climate in
the three models examined.
References
Dobler, A., B. Ahrens, Precipitation by a regional
climate model and bias correction in Europe and
South-Asia. Meteorol. Zeitschrift, 17(4), 499-509,
2008.
Goswami, B.N., et al., A broad scale circulation index for
the interannual variability of the Indian summer
monsoon, Quart. J. Roy. Meteor. Soc., 125 (554), pp.
611-633, 1999.
Kalnay, E., et al., The NCEP/NCAR 40-Year Reanalysis
Project, Bull. Amer. Meteor. Soc., 77, 437–471, 1996.
Parthasarathy, B., et al., Indian summer monsoon rainfall
indices, 1871–1990. Meteor. Mag., 121, pp. 174–186,
1992.
Uppala, S.M., et al., The ERA-40 re-analysis, Quart. J.
Roy. Meteor. Soc., 131 (612), pp. 2961-3012, 2005.
Wang, B. and Z. Fan, Choice of South Asian monsoon
indices, Bull. Amer. Meteorol. Soc., 80 (4), pp. 629-
638, 1999.
Webster P.J. and S. Yang, Monsoon and ENSO:
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Soc., 118, pp. 877–926, 1992.