The daily 3D Ozone produced by the Chemical Transport Model forJRA-25.
Takashi MAKI1, Ayataka EBITA2, Takahisa ISHIMIZU3, Kazuhiko NAGATA4, Masaaki
IKEGAMI1 and Toru SASAKI5
1

Atmospheric Environment Division, Global Environment and Marine Department, Japan Meteorological Agency,Japan
2
Administration Division, Global Environment and Marine Department, Japan Meteorological Agency, Japan
3
Climate Prediction Division, Global Environment and Marine Department, Japan Meteorological Agency, Japan
4
Forecast Division, Forecast Department, Japan Meteorological Agency, Japan
5
Director of the Utsunomiya Local Meteorological Observatory, Japan Meteorological Agency, Japan
Correspondence: maki@met.kishou.go.jp

INTRODUCTION
An ozone 3D distribution influences atmospheric energy balance through radiation. However, Japan
Meteorological Agency (JMA) had only monthly 2D climatology of ozone as of 2002. Analyzed 3D ozone fields
were keenly required for JRA-25. We have run our Chemical Transport Model (CTM) nudging with satellite
observational data and analyzed meteorological field from 1979 to 2004. The simulated ozone field could almost
reproduce realistic ozone distribution. The simulated total ozone tends to lower in the tropical region and theperiod when there are not enough satellite data.
METHOD and DATA
We have calculated ozone distribution from 1979 to 2004. Also we continue this calculation from 2005 topresent in order to provide 3D ozone distribution for JMA Climate Data Analysis System (JCDAS).
We make use of chemical transport model (CTM) developed in Meteorological Research Institute. One of themost important features of CTM is that a chemical module is directly coupled with the MRI-JMA98 General
Circulation Model (Shibata et al., 1999, figure 1) and can make use of several GCM parameters without temporalor spatial interpolation. The horizontal resolution is T42 (280km) and vertical resolution is 45 layers (from surface
to 0.01hPa).

GCM（MRI/JMA98）
Chemical module
Meteorolo
gicalanalysis

Boundary
condition

Nudging

Chemical process

Meteorology

Production andremoval

・Dynamics
・Moist convection
・Land surface
・Large scale condensation
・Turbulent diffusion
・Gravity wave drag・Radiation

Boundary
condition

Transport

Satellite
Total O3O3 nudging
Output result

Figure 1 Structure of Chemical Transport Model (CTM)

outputThe chemical module was developed in the Meteorological Research Institute (Shibata et al., 2005). The
resolution of the CTM (and GCM) is T42L45. The chemical module is composed of chemical processes and atransport process. The chemical process is based on the family method and contains major stratospheric species,
i.e., 34 long-lived species including 7 families and 15 short-lived species with 79 gas phase reactions and 34
photo-dissociations.
The GCM has a built-in, four-dimensional data assimilation system with a nudging scheme incorporating anassimilated meteorological field (ERA-15, ECMWF operational analysis and JMA operational analysis). Also theCTM has a nudging system which could assimilate total ozone obtained once a day by several satellites. The
weight of the model guess and satellite data are determined by the root mean square error against the surface
observational data. Used data are shown in table 1.

Table 1 Adopted data in producing daily O3
Data type
Data name
Meteorological Field
ERA-15
ECMWF (operational)
JMA (operational)
CIRA-86
Satellite Observation
TOMS
SBUV (bias corrected)
TOVS (bias corrected)
Ozone profile data
AMIP climatology
Analyzed climatology

Remarks
1979.1 – 1992.121993.1 – 2002.8
2002.8 – 2004.12
First priority
Second priority
Third priority
Vertical profile from SAGE II

We could use satellite data almost every day. But, the satellite data coverage ratio reduced from 1993 to 1996
(Figure 2). During this period, we could only use SUBV or TOVS data.

Satallite Data Coverage ratio (Grid)

Coverage ratio

1.00.80.6
0.4
Coverage ratio
0.20.0
1982

1986

1990

1994

1998

2002

Year
Figure 2 Satellite Observational data coverage ratio according to the number of model grids.
At first step, we add only prepared Cl boundary condition to CTM. We call this as calculation A. The simulated
ozone field show smaller and lower ozone peak concentration and higher ozone concentration in the tropospherecomparing with the climatology and observation. According to these results, we add Br boundary condition,

tropospheric ozone destruction and vertical profile nudging scheme to calculation A. We call this as calculation B.
This calculation resolves almost all problems of calculation A. But we found another problem that total column
ozone tends to reduce in this revision. Therefore, we enhanced satellite nudging ratio and we define this version ascalculation B2.
RESULTS
The simulated total column ozone amount shows good agreement with satellite observation (Figure 3). We canobtain ozone distribution even in lack of observational area.

Figure 3 Comparison with satellite observation
But, we could find some problems in vertical profile of ozone concentration shown in figure 4.

Figure 4 Vertical profiles of ozone concentrations. First row shows stratospheric concentrations and second row
shows tropospheric one. Left column shows AMIP climatology, second left column shows calculation A, second rightcolumn shows calculation B and right column shows calculation B2.

We can easily know that the calculation A shows some problems. First, the ozone peak concentration is too low
comparing with AMIP climatology. Second, the ozone concentration at stratosphere is too low. Third,
Tropospheric ozone concentration is too high. We can see that the calculation B almost solves these problems. But
the total column ozone amount tends to reduce. Therefore, we enhance satellite nudging ratio and call this ascalculate B2. Considering these points and suitability for our global model radiation scheme, ozone field ofcalculation B2 is adopted in JRA-25. We also provide monthly 3D ozone climatology using this method to JMA
operational global forecast model.
Figure 5 shows time serious of total column ozone comparing against satellite data in each latitudinal zone. The
biases of simulated total O3 are remarkably reduced in 1993 – 1997. The data availability rate is relatively lowexactly in this period comparing to the other period (Figure 2). The low total O3 bias in the tropics may comefrom the ozone reduction scheme in the lower troposphere. This scheme was adopted to avoid high ozone
tendency of CTM in the lower troposphere. We consider that we can reduce such bias by using less biased CTM.
We could find that the simulated total column ozone amount tend reduce especially in the tropics during
calculated period. This may come from Cl and Br boundary condition which we have introduced.

Simulated total O3 against Satellites0.99

90N-75N
75N-60N
60N-45N
45N-30N
30N-15N
15N-EQ
EQ-15S
15S-30S
30S-45S
45S-60S
60S-75S
75S-90S

0.98
0.97
0.96
0.95
0.94
0.93
0.92
0.91
0.90
1982

1986

1990

1994

1998

2002

Figure 5 Total column ozone bias against satellite observational data
SUMMARY
We have produced a daily 3D ozone field from 1979 to 2004 with CTM, satellite data and meteorologicalanalysis. We made use of TOMS, SBUV and TOVS satellite observational data. The calculated ozone field could
reproduce rational ozone distribution even in lack of observational data area. The calculated total column ozone
tends to smaller than satellite observational data. This tendency consists of data coverage ratio. Comparing withAMIP climatology, the ozone field tends to show a larger ozone peak and lower concentration at upper
stratosphere. The ozone peak position tends to little lower comparing against ozone sonde observation. The
precision of ozone data tend to reduce from 1993 to 1996 (satellite missing period).
We have some plans to modify our ozone field to prepare next re-analysis. First, we have a plan to use revised
CTM developed in MRI. We consider this can improve vertical profile of ozone field. Second, we have a plan tocorrect other satellite observational data (especially from 1993 to 1996). We think this can avoid the ozone
reduction at this period. Finally, we have a plan to modify ozone assimilation scheme. We consider this will

improve ozone distribution at all area.
REFERENCES
McPeters, R.D., D. F. Heath and P. K. Bhartia, 1984：Averaged ozone profiles for 1979 from the NIMBUS7SBUV instrument. J. Geophys. Res., 89, 5199-5214.
McPeters, R.D., P. K. Bhartia, Arlin J. Krueger, and Jay R. Herman, 1996: Nimbus–7 Total Ozone Mapping
Spectrometer (TOMS) Data Products User's Guide, NASA/Goddard Space Flight Center.
Shibata, K., H. Yoshimura, M. Ohizumi, M. Hosaka and M. Sugi, 1999: A simulation of troposphere, stratosphereand mesosphere with MRI/JMA98 GCM. Papers in Meteorology and Geophysics, 50, 15-53.
Shibata, K. et al., 2005: Development of MRI Chemical Transport Model for the Study of Stratospheric Chemistry.
Papers in Meteorology and Geophysics, 55, 75-119.