56-JSA-A362

advertisement
SIMULATION OF 1998 MONSOON ONSET OVER SOUTHEAST
ASIA WITH A REGIONAL CLIMATE MODEL
KOJI DAIRAKU
Atmospheric Environment Division, National Institute for Environmental Studies,
16-2 Onogawa Tsukuba, Ibaraki 305-0053, Japan
The first transition of the Asian Summer Monsoon (ASM) over Southeast Asia in 1998
was investigated using a state-of-the-art regional climate model (RAMS: Regional
Atmospheric Modeling System). Numerical experiments were conducted for 2 months
from 1st Apr to the end of May. One is control experiment (CTL) and another is the one
which removed topography within the area (NOMNT). Observed ASM transition was
fairly well captured in the CTL experiment. On the other hand, the abrupt increase during
the middle of May was not reproduced in the NOMNT experiment. In the view point of
the strength of monsoon onset, land-sea heat contrast is considered as an important
factor. By comparing two experiments with and without topography, topography helped
to induce the positive feedback between soil moisture and precipitation. On the other
hand, it seems to be negative feedback in the NOMNT experiment during the period of
first transition. Though, it needs further consideration, it seems reasonable to suppose
that orographically induced precipitation contributes significantly to the monsoon onset
and its hydrological feedback.
INTRODUCTION
The first transition of the Asian Summer Monsoon (ASM) is a matter of socially and
economically importance. Fasullo and Webster (2003 [1]) show the association between
total June-July-August-September rainfall and both onset and withdrawal using a new
criterion of monsoon. It has a critical influence on the people reside in the entire region of
Southeast Asia. Thereby the degree of predictability of monsoon constitutes a
fundamental concern in this region (Charny and Shukla, 1981 [2]).
The ASM onset begins earlier in the inland region of Indochina (Thailand) in late
April to early May than in the coastal region. Around the middle of May, the mature
ASM circulation begins to establish and the land-locked convection over southern
Thailand and northern Borneo abruptly advances northward and expands over the South
China Sea (SCS) (Lau et al, 1998 [3]; Matsumoto, 1997[4]).
Land-sea heat contrast has been shown to be linked with the strength of the ASM.
Meehl (1994 [5]), Goswami (1998 [6]), and others have noted that land surface
conditions have important factors to contribute that contrast. They investigated the
external conditions and internal feedbacks using atmospheric general circulation models
(GCM) and indicated the importance of internal feedbacks (involving soil moisture). In
the Mae Chaem watershed located at the northeastern part of Thailand, strong altituderelated rainfall enhancement was observed (Dairaku et al., 2000 [7], 2004 [8]). It might
1
2
be possible that the topography has some role to produce the land-sea heat contrast as one
of the external conditions and to affect the internal feedbacks.
In this paper, the evolution of sub-continental-scale hydrologic processes during the
first transition period of the Asian Summer Monsoon in April to May 1998, which is a
part of the Global Energy and Water Cycle Experiment (GEWEX), Asian Monsoon
Experiment Intensive Observing Period (GAME-IOP), was investigated using a state-ofthe-art atmospheric numerical model.
MODEL AND EXPERIMENTS
In 1998, intensive field observations were conducted as one of the GAME research
activities. In the year, the global climate system experienced a transition from the
strongest warm anomalies in sea surface temperatures existed in the eastern equatorial
Pacific Ocean in 1997/98. That is, global circulations were under the influence of the
warm (El Niño) phase of the ENSO Cycle (Anyamba et al., 2002 [9]). From the Global
Precipitation dataset, 1998 is a relatively dry year, though it might not be a general
relationship. The influence of the global circulation associated with ENSO on the mesoscale rainfall characteristics in this study region is not identified clearly.
A theree-dimentional, nonhydrostatic compressible dynamic-equations model
(RAMS: Regional Atmospheric Modeling System) developed by Colorado State
University (Pielke et al., 1992 [10]) was used in this study. The Kuo convective
parameterization was used to simulate cloud activity. The two-stream radiation scheme
(Harrington et al., 1999 [11]) was used as a radiation parameterization. Soil and
Figure 1. Simulated region. Solid rectangle indicates the area in which simulated results
were averaged
3
vegetation model is LEAF-2 (Walko et al., 2000 [12]). Topography data with a 30”
longitude resolution (GTOPO30) and land-use data that is estimated from satellite data
(AVHRR) by USGS were incorporated in this simulation. The OISST Ver.2 (Reynolds et
al., 2002 [13]) was used and it was updated weekly during the simulated period. The
GAME-reanalysis data was utilized as the initial and lateral boundary conditions. Two
numerical experiments were conducted for 2 months from 1 st Apr to the end of May. One
is control run (CTL) and another is the run which removed topography within the area
(NOMNT). Horizontal grid space is 20km with 200 x 160 grid points (4000 x 3200 km)
(Figure 1). Vertical grids have 35 grid points (~23.4km). Vertical grid spaces are
stretched from 100 to 1000m.
RESULTS
The transitions of simulated surface precipitation (CTL and NOMNT) were compared
with observations, pentad CPC Merged Analysis of Precipitation (CMAP; Xie and Arkin,
1997 [14]), and daily Global Precipitation Climatology Project (GPCP; Huffman et al.,
1997 [15])). All of them were averaged over the 10 by 15 degree area located at 10° N20º N by 95º E-100º E (the rectangle area indicated in Figure 1).
Because of the different time interval of each dataset, some differences among the
observations (CMAP and GPCP) can be found. Nevertheless, it can be said that relatively
large rainfall event were observed in the middle of April, and precipitation increased
abruptly during the middle of May. This transition was fairly well captured in the CTL
experiment. On the other hand, the abrupt increase during the middle of May was not
reproduced in the NOMNT experiment.
15
m m /day
12
O bs(G P C P )
O bs(C M A P )
C TL
NO M NT
9
6
3
0
4/1
4/11
4/21
5/1
5/11
5/21
Figure 2. The transition of observed and simulated precipitation in 1998. Observed daily
precipitation of GPCP is solid line. Observed pentad precipitation of CMAP is dotted line.
4
Standard simulated precipitation (CTL) is dash-dot line with circle. Simulated
precipitation of NOMNT experiment is dash-dot-dot line with triangle.
90
14
60
12
30
10
0
8
4/1
120
W /m ^2
g/K g
16
S ensible H eat
Latent H eat
S oilM oisture
4/11
4/21
5/1
5/11
5/21
16
S ensible H eat
Latent H eat
S oilM oisture
90
14
60
12
30
10
0
g/K g
W /m ^2
120
8
4/1
4/11
4/21
5/1
5/11
5/21
Figure 3. The transition of simulated sensible heat flux, latent heat flux, and soil moisture.
Sensible heat flux is solid line. Latent heat flux is dashed line. Soil moisture is dotted line.
Upper panel shows the CTL experiment. Lower panel shows the NOMNT experiment.
5
Figure 3 shows the transition of simulated sensible heat, latent heat, and soil
moisture. Upper panel in figure 3 indicates the abrupt decrease of sensible heat and the
increase of soil moisture. It coincides with the increased precipitation in that period
(Figure 2). As soil was getting saturated, latent heat flux moderately increased. Latent
heat flux associated with the abrupt transition can be found obscurely. On the other hand,
lower panel in Figure 3 indicates the gradual decrease of sensible and latent heat and
moderate increase of soil moisture associated with the weak precipitation (Figure 2).
In the view point of the strength of monsoon onset, land-sea heat contrast is
considered as an important factor. Soil moisture feedback could be positive by increasing
water vapor in the atmosphere and also be negative by cooling land surface through
enhanced evapotranspiration (e.g., Meehl, 1994 [5]).
By comparing two experiments with and without topography, topography helped to
induce soil moisture feedback to be positive. On the other hand, it seems to be negative
feedback in the NOMNT experiment during the period of first transition. Though, it
needs further consideration, it seems reasonable to suppose that orographically induced
precipitation contributes significantly to the monsoon onset and its hydrological feedback.
ACKNOWLEDGMENTS
I gratefully acknowledge helpful discussions with Prof. Jun Matsumoto. GAME
reanalysis project conducted by Meteorological Research Institute, Japan Meteorological
Agency and Earth Observation Research Center/National Space Development Agency of
Japan.
REFERENCES
[1] Fasullo J. and Webster P.J., “A Hydrological Definition of Indian Monsoon Onset
and Withdrawal”, J. Climate, Vol.16, (2003), pp 3200-3211.
[2] Charny J.G. and Shukla J., “Predictability of monsoons. In Monsoon Dynamics”,
Edited by Lighthill J. and Pearce R.P. Cambridge University Press, Cambridge, UK.,
(1981), pp 99-109.
[3] Lau K.-M. et al. “Hydrologic Processes Associated with the First Transition of the
Asian Summer Monsoon: A Pilot Satellite Study”, Bull. Amer. Meteor. Soc., Vol.79,
(1998), pp 1871-1882.
[4] Matsumoto, J., “Seasonal Transition of Summer Rainy Season over Indochina and
Adjacent Monsoon Region”, Adv. Atmos. Sci., Vol.14, (1997), pp 231-245.
[5] Meehl, G.A., “Influence of the Land Surface in the Asian Summer Monsoon:
External Conditions versus Internal Feedbacks”, J. Climate, Vol.7, (1994), pp 10331049.
[6] Goswami, B.N., “Interannual Variations of Indian Summer Monsoon in a GCM:
External Conditions versus Internal Feedbacks”, J. Climate, Vol.11, (1998), pp 501522.
6
[7] Dairaku, K. et al., “The effect of Rainfall Duration and Intensity on Orographic
Rainfall Enhancement in a Mountainous Area: A Case Study in the Mae Chaem
Watershed, Thailand”, J. Japan Soc. Hydrol. Water Resour., Vol.13, (2000), pp 5768.
[8] Dairaku, K. et al., “Rainfall amount, intensity, duration, and frequency relationships
in the Mae Chaem watershed in Southeast Asia”, J. Hydromet., (2004), (in press).
[9] Anyamba A. et al., “From El Nino to La Nina: Vegetation Response Patterns over
East and Southern Africa during the 1997-2000 Period”, J. Climate, Vol.15, (2002),
pp 3096-3103.
[10] Pielke, R.A. et al., “A comprehensive meteorological modeling – RAMS”, Meteorol.
Atmos. Phys., Vol.49, (1992), pp 69-91.
[11] Harrington, J.Y. et al., “Cloud resolving simulations of Arctic stratus. Part II:
Transition-season clouds”, Atmos. Res., Vol.51, (1999), pp 45-75.
[12] Walko, R.L. et al., “Coupled Atmosphere–Biophysics–Hydrology Models for
Environmental Modeling”, J. Appl. Meteor., Vol.39, No. 6, (2000), pp 931-944.
[13] Reynolds, R.W. et al., “An Improved In Situ and Satellite SST Analysis for Climate”,
J. Climate, Vol.15, (2002), pp 1609-1625.
[14] Xie, P., and Arkin, P.A., “Global Precipitation: A 17-Year Monthly Analysis Based
on Gauge Observations, Satellite Estimates, and Numerical Model Outputs”, Bull.
Amer. Meteor. Soc., Vol.78, (1997), pp 2539-2558.
[15] Huffman, G.J. et al., “The Global Precipitation Climatology Project (GPCP)
Combined Precipitation Dataset”, Bull. Amer. Meteor. Soc., Vol.78, (1997), pp 5-20.
Download