Production of final dataset of GAME-HUBEXRegional 4DDA by JSM-SiBUC∗Kenji Tanaka1 , Kazuyoshi Souma1 , Kazuhisa Tsuboki2 , Shuichi Ikebuchi1(1: WRRC, DPRI, Kyoto University, 2: HyARC, Nagoya University)* WRRC, DPRI, Kyoto University, Gokasho, Uji, 611-0011, Japane-mail: tanaka@wrcs.dpri.kyoto-u.ac.jp

Abstract
Regional land-atmosphere coupled model (JSM-SiBUC) is applied to the GAME-HUBEX
region to produce a high accuracy dataset with 30km resolution. The period of the dataset
is from 1998/6/21 00Z to 1998/7/22 00Z (31days). As for the main atmospheric model,
JSM (Japan Spectral Model) was provided from JMA (Japan Meteorolocal Agency) for
the GAME community. As for the land surface model, latest version of SiBUC is adopted
to describe presicely the land surface condition within the domain. GAME-Reanalysis
Ver1.5, which was produced by JMA, is used for initial and external boundary condition.
Through the comparison with upper air sounding data, lower level speciﬁc humidity ofGAME-Reanalysis data was found to be smaller than observed one. Therefore, upper
air sounding data in the whole GAME-HUBEX region are re-assimilated to produce
more accurate initial and boundary conditions. The ﬁnal dataset of this regional 4DDA
includes surface ﬂuxes (sensible heat, latent heat, etc.) and surface state variables (soilmoisture, surface temperature, etc.) as well as atmospheric state variables (temperature,humidity, wind, etc.).
Keyword: GAME-HUBEX, JSM-SiBUC, GAME-Reanalysis, data assimilation, humidity
1.

Introduction
Land-Atmosphere interaction and its role in the formation of meso-scale precipitation systems are oneof the most important research targets of GAMEHUBEX Projects. This kind of research becomes possible due to the existence of high accuracy datasets.
To perform the regional 4DDA (four dimensionaldata assimilation) accurately, not only the usedmodel but also the external dataset is very important. In this study, regional 4DDA is executed for
the GAME-HUBEX region by JSM-SiBUC coupledmodel. GAME reanalysis data and upper air sounding data is utilized to produce better initial andboundary conditions.
2. Model Description
2.1. JSM-SiBUC coupled model
Japan Spectral Model (JSM) was developed formesoscale numerical prediction by the Japan Meteorological Agency (JMA). Model variables are represented at 129 × 129 horizontal grid points and 23 vertical σ levels. In the original JSM model, land-surface
process was described very simply. To deal withland-atmosphere interaction properly, latest versionof SiBUC, which can treat mixed landuse/landcoverconditions, has been coupled into JSM (Fig. 1) [3].
Especially, irrigated farmland and paddy ﬁeld should
be expressed in this region[1]. The simulation domain (Fig. 2) covers the whole target area of GAMEHUBEX (E110-E122, N28-N40).
2.2. Surface parameterTwo datasets are utilized to make fractional areasof each land-use within JSM grid. For Japan area,
KS-202 data which has about a 100m resolution and15 landuse categories is available. For other parts

JSMfcstu,v,Tv,qu’,v’,Tv’,q’

PBL
u,v,Tv,qu’,v’,Tv’,q’

4 Comp.

H

τS , dgr
S ,L

c l ,c m ,c hRADIAT

Cd ,C θ ,C qu, v,θ v ,qlE

GIM

goudriaan
Grid Information
Atmos. Variable
Surface Variableu’, v’
θ ’v , q’

VDFSN

Surface Flux
New Variable

SiBUC

Fig. 1 : Structure of JSM-SiBUC

Fig. 2 : Topography for JSM-SiBUC

Table 1 : Analysis cycle and weight for overlapping period

6/20
12 130 1cycle 2..
..

6/21
23 0 111 12 13weight 1
weight 2..
..

11 12 13
23 24 25
12 110 10 1..
..
..
..
..

6/22
23 0 135 36
1 0
11 12
11 12 13weight 2
weight 3cycle 3(a)Paddy ﬁeld(b)Farmland

Fig. 3 : Paddy ﬁeld and farmland fraction

3. Experimental design
3.1. Analysis period
Initial and boundary condition is produced fromGAME Reanalysis data (ver.1.5)[7]. Target period isfrom 1998/6/21 00Z to 1998/7/22 00Z, and this period coinsides with HUBEX-IOP. A series of 36-hour
simulations initialized at 1200UTC (2000BST) everyday are executed. This means that each simulation
period overlaps 12hours. As for the overlapping period, two simulation results are combined according
to the hour from initial time. Table 1 shows theanalysis cycle and the weights for the each overlapping time.
3.2. Initialization of land surface variablesSea surface tempersture is initialized by SST analysis data of that day. Land-surface temperature isinitialized by climatological value. Soil moisture isinitialized only for the ﬁrst simulation (1998/6/20
1200UTC). For the sparcely vegetated area (grassland, bare soil), surface soil moisture is initialized by
TRMM/TMI data [6]. For the dense vegetation area(forest, cropland), initial value is set to appropriately
wet enough values. Here, vertical proﬁle of soil moisture is given by linear proﬁle of matric potential (This11 12 13..

6/2323 0 1..

11 12..

23 24 25
12 110 10 1..
..
..
..

35 361 0
11 1211 12 13..

23 24

proﬁle balances with gravity). From the second simulation, initial soil moisture is succeeded from the previous run.
4. Results
4.1. Problem in GAME reanalysis data
Analysis cycle was executed forced by GAME reanalysis data. For some events (ex. 29th June), simulated rainfall pattern and its amount was good accordance with surface measurements. But for otherevents (ex. 1st ∼ 2nd July), simulated rainfall wasmuch smaller than observed one (see Fig.6).
Vertical proﬁle of speciﬁc humidity at Wuhan(E114.13, N30.62) and Xuzhou (E117.15, N34.28) at
0600UTC on 1st July is shown in Fig. 4. Solid line
is observation (upper air sounding data), dotted line
is GAME reanalysis. For comparison, GANAL datais also shown by dashed line. Although all upper air
sounding data were utilized to produce GAME reanalysis, lower level (1000-800hPa) speciﬁc humidity
is clearly smaller than observation (GANAL is muchbetter). The spacial resolution of GAME reanalysis
is very good (0.5 degree), and wind ﬁeld is known tobe much better than other dataset. Here, we still use
GAME reanalysis, but we try to modify the humidity
ﬁeld to improve the rainfall simulation.
(98070106) station=57494(98070106) station=58027

700

700
obsGANAL
Rev1.1
Rev1.5750
pressure (hPa)of the simulation domain, the NOAA-AVHRR global
landuse/landcover dataset (from USGS), which has
about 1km resolution and 14 categories, is used. By
the way, this dataset has some problem in describing
the cropland area[4],[1]. Then, new cropland information is used in JSM-SiBUC (Fig. 3). According
to the in-situ ﬂux measurement data[2], some model
parameters are calibrated to reproduce the diurnal
variation of surface energy balance components well.

..

800
850
900
950

1000

obs
GANAL
Rev1.1
Rev1.5750
pressure (hPa)dateUTC
cycle 1

800
850
900
950

05
101520Specific Humidity (g/kg)(a) Wuhan

25100005101520
Specific Humidity (g/kg)

25(b) Xuzhou

Fig. 4 : Vertical Proﬁle of Speciﬁc Humidity at Wuhan
and Xuzhou (1998/7/1 0600UTC) solid: observation,dashed: GANAL, dotted: GAME reanalysis v1.5

4.2. Adjustment of humidity field by PW
Precipitable water (P W ) of external data (GAMEReanalysis) is calculated for each grid (P Wext ). On
the other hand, P W can be calculated from upper air
sounding data (25 stations). These station’s values(P Ws ) are horizontally interpolated with inﬂuenceradius of 5 degree to produce gridded values (P Wg ).
Then, this observation based P Wg and external databased P Wext are compared. According to the ratioof P Wext and P Wg , speciﬁc humidity value in theexternal dataset (qext ) is modiﬁed.
qext (z)∗ = qext (z) × P Wg /P Wext (z = 1, zmax ) (1)∗This modiﬁed speciﬁc humidity (qext) is given toJSM-SiBUC. Fig. 5 shows the ratio of P W between
original and re-assimilated run at 0000UTC. According to Fig. 5, speciﬁc humidity is increased by thisre-assimilation in large part of this region.
4.3. Time series of area average rainfall
To see the impact of moisture adjustment, area average rainfall is calculated for the diﬀerent spacialscale.

1. AREA1 : E110-E122,N28-N40(12deg × 12deg)
2. AREA2 : E111-E122,N31-N36(11deg × 5deg)
3. AREA3 : E114-E117,N31-N34(3deg × 3deg)
4. AREA4 : upstream of Huaihe river basin
According to Fig. 6, the rainfall amount of theoriginal run (green line) is much smaller than observation (blue line). While that of re-assimilated run (redline) is closely to observation (but still small). As forAREA3 and AREA4, the rainfall event in 29th June
is too much enhanced. But for AREA1 and AREA2,
rainfall amount of that day is almost same as observation. This means that rainfall area is slightly shiftedfrom actual one.
4.4. Horizontal distribution of correlation
Spatial distribution of the correlation coeﬃcient forthe daily rainfall time series is shown in Fig. 7. The
left panel is for the original simulation, and the rightpanel is for the re-assimilated simulation. In general,the correlation coeﬃcient is improved in many of the1 degree × 1 degree grid area. Then, not only therainfall amount, but also spatial pattern of rainfall
distribution is improved by re-assimilation of sounding data. As for the north-west part of the basin,correlation coeﬃcient becomes worse. This may be a
result of the too much moisture adjustment. Since theinﬂuence radius is 5 degree, precipitable water in thesea side area (moist area) aﬀects inner dry region. If
the sounding data in this dry region is available, thispart will be improved.
4.5. Final product
Although there is some possibility in the improvement of model output, now is the time to ﬁnalize
the GAME-HUBEX activity. The ﬁnal product ofHUBEX regional 4DDA is produced from this reassimilated run. This product is provided with 30km
resolution and 1 hour interval. It consists of the following items.
• Precipitation, Evapotranspiration, Runoﬀ• Downward short-wave and long-wave radiation,
Upward short-wave and long-wave radiation• Net radiation, Sensible heat ﬂux, Latent heatﬂux, Momentum ﬂux• Soil Moisture (3-layer), Temperature (Canopy,soil, deep soil)• Surface meteorology (air temperature, vaporpressure, wind speed)• 3-D meteorology (air temperature, vapor pressure, horizontal wind)

References[1] Kozan, O., K.Tanaka and S.Ikebuchi : The Estimation of Water and Heat Budget in the Huaihe River
Basin China - Detail Representation of Various Cropland and Irrigation -, Proc. of the 1st International
Conference on Hydrology and Water Resources in
Asia Paciﬁc Region (APHW2003), Vol.2, pp.763-768,
2003.
[2] Tanaka, K., M.Shiiba, S.Ikebuchi, M.Qian, H.Xu,
M.Yang : Analysis of Energy/Water Flux Data in
HUBEX-IOP, Proc. of Workshop on Meso-Scale Systems in Meiyu/Baiu Front and Hydrological Cycle,
pp.94-97, 1999.
[3] Tanaka, K., K.Tsuboki, M.Shiiba and S.Ikebuchi :Numerical simulation of JSM-SiBUC initialized andexternally forced by GAME reanalysis data, Proc.
of International GAME/HUBEX Workshop Sapporo
2000, pp.39-41, 2000.
[4] Tanaka, K., O.Kozan, T.Nakamura, M.Shiiba,
S.Ikebuchi : Land Data Assimilation in the GAMEHUBEX, Proc. of the Fifth Intl. Study Conference
on GEWEX in Asia and GAME, GAME Publication
No.31, pp.697-702, 2001.
[5] Tanaka, K., K.Tsuboki, M.Shiiba, S.Ikebuchi : Theimpact of landuse change on the meso-scale precipitation system : Numerical study by JSM-SiBUC,Proc. of the 3rd GAME-HUBEX Workshop on Mesoscale Systems in Meiyu/Baiu Front and Its Hydrological Cycle, pp.167-170, 2001.
[6] Tanaka, K., M.Morohashi and S.Ikebuchi : Development of a new Soil Moisture Retrieval Algorithm using TRMM/TMI polarization ratio and NDVI, Proc.
of the 2nd APHW Conference, Vol.2, pp.686-693,
2004.
[7] Yamazaki, N., N.Yamazaki, H.Kamahori, A.Yatagai
and K.Takahashi Current status of GAME reanalysis project and some preliminary results -Heavy precipitation on July 22, 1998 and diurnal variations ofprecipitable water-, Proc. of the 3rd GAME-HUBEXWorkshop on Meso-scale Systems in Meiyu/Baiu
Front and Its Hydrological Cycle, pp.24-29, 2000.

Fig. 5 : Ratio of initial Precipitable water (6/29-7/2)
Area average daily rainfall (Area1)
18

Area average daily rainfall (Area2)
35

observmodel(orig)
model(PW)

16
14

observmodel(orig)
model(PW)

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25121020

8

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6104
5200
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510day2530

Area average daily rainfall (Area4)
45

observmodel(orig)
model(PW)

60

20day

Area average daily rainfall (Area3)
70

15

observmodel(orig)
model(PW)

40
35

50

30

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25

30

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10
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5

00
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510day15

20day

Fig. 6 : Time series of daily rainfall of four diﬀerent area(a)Original run(b)Re-Assimilated run

Fig. 7 : Correlation coeﬃcient of daily rainfall

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