The role of microphysical processes on the mesoscale simulation over the
complex terrain, the Himalayas
Paper Number: GC41A – 0854
Rudra K Shrestha1, 2, Paul Connolly1, Martin Gallagher1
1
School of Earth, Atmospheric and Environmental Sciences, The University of Manchester, UK
2
Sustainable Consumption Institute (SCI), The University of Manchester, UK
Introduction:
South Asia is critically dependent upon monsoon precipitation which is
intrinsically linked to people’s daily lives since more than 70% of the working
population relies on agriculture (Kumar et al., 2004) and the majority of
these agricultural systems are rainfall dependent. Accurate prediction of the
monsoon features such as its onset and decay, its movement and variability
across the Asian region is important as they influence national agenda such
as sustainable development, poverty reduction and disaster management.
Improved understanding of the Indian monsoon is challenging to the
climate-weather community due to the role of the complex topography of
the Himalayas (Wang, 2006) and their representation in climate models. The
Hiymalayan topography is characterizsed by extreme altitudinal geographic
variation, from typically 70m asl in Southeastern Nepal (Kechana Kalan),
to the peak of the world, at 8850m (Mt. Everest), and extending from West
to East covering many South Asian countries: Afghanistan, Pakistan, China,
India, Nepal, Bhutan, and Myanmar (Benn and Owen, 1998). Circulation in
such a complex environment is complicated due to obstruction of flows
by mountain ranges which in turn have wide ranging effects on hydrology
through cloud and rain formation and their distribution and runoff.
The objective of this study is to evaluate the impact of the four different
cloud microphysical schemes (WSM3, WSM6, Morrison double moment and
Lin scheme) within the Weather Research and Forecasting model (WRF),
as part of simulations of mesoscale weather systems across the Nepalese
Himalayas. Modeling of the key microphysical process in this complex
terrain provides insight into the general understanding of the processes,
their different contributions in different topographical scenarios and their
spatial patterns, however there are many uncertainties in general. These
uncertainties are even more pronounced when such models are applied to
the complex terrain characteristic of the Himalayas.
Model configuration and experimental set up:
Numerical experiments are designed using the WRF model, with three nested
domains (27, 9 and 3 km grid spacing; Figure 1). The performance of the four
categories of microphysical schemes is examined in model experiments for
(i) monsoon onset, (ii) monsoon decay and (iii) winter rainfall.
Table 1
Table 1: Summary of physics
Physics
Micro-Physics
Monsoon Decay
Experiment
Monsoon Onset
Experiment
Contact: Rudra.Shrestha@postgrad.manchester.ac.uk
WSM3
WSM6
Winter Rainfall
Experiment
WRF 6-class, WRF 3-class, Lin scheme and Morrison DM
LW radiation
RRTM scheme
RRTM scheme
RRTM scheme
SW radiation
Dudhia scheme
Dudhia scheme
Dudhia scheme
Land surface
scheme
Noah land surface
model
Noah land surface
model
Noah land surface
model
Boundary layer
YSU scheme
YSU scheme
YSU scheme
Grell-Deveyni
scheme; grid > 3km
Grell-Deveyni
scheme; grid > 3km
Cumulus
Grell-Deveyni scheme;
parameterization grid > 3km
Lin
Morrison DM
Figure 5: Time series Rainfall (0730 UTC 01 - 0730 UTC 07 Sep 2007)
Model Initial and Boundary condition: NCEP/DOE reanalysis – 2
WSM3
WSM6
Lin
Morrison DM
Figure3: Water Condensate (g/kg)
WSM3
WSM6
1130 UTC 04 Sept. 2007
The Physics packages other than the microphysics include the Grell-Deveyni cumulus
parameterization scheme, Noah land-surface model, the Yonsei University planetary
boundary layer (PBL), a simple cloud-interactive shortwave radiation Dudhia scheme,
and Rapid Radiative Transfer Model (RRTM) longwave radiation schemes. No cumulus
parameterization scheme was used at 3km grid resolution owing to the fact that the
model explicitly resolves convective activities below 5km grid resolution (Table 1). Model
initial and boundary conditions were adopted from NCEP/DOE reanalysis – 2. The model
is configured with 28 vertical levels. Surface properties such as terrain/vegetation/land
use data were prescribed by the United States Geological Survey (USGS). Evaluation of the
model results was focused on the high resolution (3km x 3km) simulation.
Results and Discussion:
1730 UTC 04 Sept. 2007
Lin
2030 UTC 04 Sept. 2007
Morrison DM
Results show that; a) Simulated rainfall is very sensitive to the chosen microphysical
scheme with rainfall spatial and temporal characteristics being very different for each
scheme. However, the majority of the WRF simulations showed similar general patterns
with monsoon onset across the foothills of the Himalayas, confined to the Siwaliks and
Mahabharat ranges (geographical regions having 10 – 50 km wide swath with altitude
ranging from 200 – 3000 m extending parallel to south of the Himalayas). In general
subsequent maturation of the monsoon was observed across the Southeast region of
Nepal which then gradually moved Northwest over time before dissipating; b) It was found
that strong moist convection caused by near surface convergence of wind is responsible
for producing significant nocturnal maximum precipitation during the monsoon period.
All the WRF simulations revealed that the continuous southerly moist monsoonal flow
interacting with the South slope of the Himalayas and associated diurnal variation of
ambient atmospheric state is the major cause of the nocturnal maximum rain generally
across the region.
References:
Benn, DI and LA Owen, 1998: The role of the Indian summer monsoon and the
mid-latitude westerlies in Himalayan glaciation: review and speculative
discussion. Journal of the Geological Society 155, 353-363.
2330 UTC 04 Sept. 2007
Kumar, KK, KR Kumar, RG Ashrit, NR Deshpande, JW Hansen, 2004: Climate Impacts
on Indian agriculture. Int. J. Climatol. 24:1375–1393
Wang, B., 2006: The Asian Monsoon. Praxis Publishing Ltd. Chichester, UK, 787 pp.
Figure 1: Domain Setup
0230 UTC 05 Sept. 2007
Figure2: Precipitation Simulation (Monsoon Decay Experiment)
Figure4: Relative Humidity
Acknowledgements
The authors are grateful to SCI providing financial support to carry out the
research.