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Present and Future of Modeling Global Environmental Change: Toward Integrated Modeling,
Eds., T. Matsuno and H. Kida, pp. 1–14.
© by TERRAPUB, 2001.
Global Warming Projection Studies at the Meteorological
Research Institute/JMA
Tatsushi TOKIOKA1 and Akira NODA2
1
2
Japan Meteorological Agency (JMA), Tokyo 100-8122, Japan
Meteorological Research Institute (MRI), Ibaraki 305-0052, Japan
STUDIES WITH THE USE OF A COUPLED ATMOSPHERE
—MIXED LAYER OCEAN MODEL
Outline of the model
Global warming studies at the Meteorological Research Institute (MRI) were
started in the late 1980s. A coupled atmosphere-mixed layer ocean model was
developed for this purpose and was applied for a quasi-equilibrium experiment
under a doubled atmospheric CO2 condition. The atmospheric model (Tokioka et
al., 1984) used has its top at 100 hPa and 5 layers and a regular 5° by 4° longitude/
latitude resolution. The model incorporates the radiative model by Katayama
(1972), Arakawa-Schubert cumulus parameterization (Arakawa and Schubert,
1974), the planetary boundary layer (PBL) model proposed by Randall and
Arakawa and the ground surface model by Katayama (1972).
The effect of the ocean is included simply as a 50 m slab without horizontal
heat transport. Sea ice is parameterized following the energy-balanced zero layer
model by Semtner (1976). Because the heat flux by the ocean is completely
neglected, the coupled model is not free from model biases caused by the neglect
of the oceanic heat transport. The meridional temperature gradient is certainly
larger than the observed one. There must be regional and localized departures of
the model climate from the observed one also, due, for example, to the unrealistic
sea ice extent. However, the realized global model climate, such as geographical
climate variations over the globe and seasons, has considerable similarity to the
observed one. Thus the model could still be used to study the climate sensitivity
of the earth and the qualitative characteristics of climate changes due to doubling
of the atmospheric CO2 concentration, as one of the simplest and most economical
tools. We will review two studies at the MRI in the following with the use of the
model; one is a study of the characteristic changes in precipitation (Noda and
Tokioka, 1989) and the other those of snowfall (Saito and Tokioka, 1994).
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T. T OKIOKA and A. NODA
Characteristic changes in precipitation under the doubling of CO2
The model is time-integrated under two conditions with seasonal cycles. In
one case (1 × CO2 experiment), the atmospheric concentration of CO2 is assumed
to be 320 ppmv. In the other (2 × CO2 experiment), it is 640 ppmv. The annual
global mean surface air temperature and precipitation increase by 4.3°C and
7.4%, respectively, due to the CO2 doubling. If we look more closely at the
results, the total precipitation increase is relatively small in low latitudes compared
to that in mid and high latitudes. We find an increase in the cumulus-type
precipitation in low latitudes throughout the year and in summer in the northern
mid latitudes, an increase in stratus-type precipitation in high latitudes especially
in winter, and a decrease in stratus-type precipitation in mid and low latitudes
throughout the year.
Figure 1 shows a scatter diagram where the abscissa is the ratio (%) of the
total grid area of non-zero precipitation in an hour to the global surface, and the
ordinate is the precipitation rate (mm/day). Crosses and small dots show data
sampled from the 1 × CO2 and 2 × CO2 experiments, respectively. Ellipses are
drawn to show the root mean square scattering in the domain for the respective
cases. This figure shows the January case. The two ellipses have no overlap and
the center of the ellipse shifts towards increasing precipitation intensity but
decreasing area coverage. Such a characteristic change is interpreted as the result
of increasing cumulus precipitation and the decreasing stratus-type precipitation
in the globally averaged sense under the global warming.
Cumulative frequency distribution for precipitation rates (mm/hour) were
also studied. The occurrence of high intensity precipitation increases in the 2 ×
CO2 case especially in mid and high latitudes caused mainly by cumulus-type
precipitation. This implies a potential increase in the meteorological disasters due
to severe rain under the global warming.
Characteristic changes in snowfall under the doubling of CO2
When precipitation occurs in the form of snow, the surface albedo changes
drastically. Snow affects the water budget of the ground surface also by holding
water at the surface until melting causes runoff. So, the characteristic changes in
snowfall under the global warming condition were studied.
Changes in snowfall are classified into four types (Saito and Tokioka, 1994).
Snowfall increases in Type + throughout the snow seasons, although it disappears
in Type Y. In Type X, it starts to fall late and disappears fast, and the snow mass
is less in 2 × CO2 than in 1 × CO2. In Type Z, there are no characteristic changes
both in the snow amount and the snow period. The snowfall change at each grid
is classified into one of these four types. Although the detailed geographical
distribution of snowfall changes is not meaningful because of model biases due
to the neglect of oceanic heat transport, the qualitative nature of the changes
might be meaningful in considering the actual changes. We find Type + in the
polar regions, and Type Y in the lowest latitudinal snowfall zone in 1 × CO2. In
between Type + and Type Y zones, we find Type X and Type Z grid points.
Global Warming Projection Studies at the Meteorological Research Institute/JMA
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Fig. 1. Scatter diagram of the precipitation rate (mm/day) versus the ratio (%) of the precipitation
grid area to the global domain for January 1 to 10. Ellipses drawn with thick solid line and thin
solid line denote the root mean square scattering for 1 × CO2 and 2 × CO 2, respectively. Data
points for 1 × CO2 and 2 × CO2 are denoted by crosses and dots, respectively (Noda and Tokioka,
1989).
STUDIES WITH THE USE OF THE MRI-CGCM1
To improve the simulated global and regional climate and to study the
transient climate response to a gradual increase in atmospheric CO2, the mixed
layer ocean model was replaced by a global ocean general circulation model
(OGCM) developed at the MRI (Nagai et al., 1992). The OGCM has a realistic
bottom topography, 21 vertical layers, 2.5° longitudinal resolution, and variable
latitudinal resolution ranging from 0.5° at the equator to 2.0° at 12° latitude and
further poleward. The AGCM adopted is described in Kitoh et al. (1995). The
horizontal resolution is 5° by 4° in the longitudinal and latitudinal directions,
respectively. There are 15 vertical levels with a top at 1 hPa. The physical
processes adopted are summarized in Table 1.
The model produced not only ENSO—(El Nino and Southern Oscillation)
like variabilities as expected but also inter-decadal Pacific variability. The latter
had a close resemblance to the observations (Yukimoto et al., 1996).
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Table 1. Comparison between the MRI-CGCM1 and the MRI-CGCM2.
Aspect
MRI-CGCM1
MRI-CGCM2
[Atmospheric component]
Horizontal resolution
Layer (top)
Solar radiation
(SW)
Terrestrial radiation
(LW)
Convection
5° (lon.) × 4° (lat.)
15 (1 hPa)
Lacis and Hansen (1974)
H2 O, O3
Shibata and Aoki (1989)
H2 O, CO2 , O3
Arakawa and Schubert (1974)
T42 (~2.8° × 2.8°)
30 (0.4 hPa)
Shibata and Uchiyama (1992)
H2 O, O3 , aerosol
Shibata and Aoki (1989)
H2 O, CO2 , O3 , CH4 , NO2
Prognostic AS
Randall and Pan (1993)
Mellor and Yamada (1974)
Iwasaki et al. (1989)
Rayleigh friction
penetrative convection
PBL
Gravity wave drag
Cloud type
Cloudiness
Cloud overlap
Cloud water content
[Land process]
[Oceanic component]
Horizontal resolution
Layer (min. thickness)
Eddy viscosity
Eddy mixing
Vertical viscosity and diffusivity
[Sea ice]
[Atmosphere-ocean coupling]
Coupling interval
Flux adjustment
bulk layer (Tokioka et al., 1988)
Palmer et al. (1986)
Rayleigh friction
penetrative convection,
middle level convection,
large scale condensation,
stratus in PBL
saturation
random for non-convective clouds
0.3 for convective clouds
function of pressure and temperature
4-layer diffusion model
large scale condensation
function of relative humidity
random + correlation
function of temperature
3-layer SiB
2.5° (lon.) × 2°–0.5° (lat.)
21 (5.2 m)
23 (5.2 m)
h. visc. 2.0 × 105 m2 s– 1
h. visc. 1.6 × 105 m2 s– 1
v. visc. 1 × 10– 4 m2 s– 1
v. visc. 1 × 10– 4 m2 s– 1
horizontal-vertical mixing
isopycnal mixing
+ Gent and McWilliams (1990)
h. diff. 5.0 × 103 m2 s– 1
isopycnal 2.0 × 103 m2 s– 1
v. diff. 5.0 × 10– 5 m2 s– 1
diapycnal 1.0 × 10– 5 m2 s– 1
Mellor and Yamada (1974, 1982)
Mellor and Kantha (1989)
6 hours
heat, salinity
24 hours
heat, salinity
+ wind stress (12°S-12°N)
The model was applied to a transient CO2 experiment, where atmospheric
CO2 is assumed to increase at the compound rate of 1%/yr (Tokioka et al., 1995).
The experiment shows a 1.6°C increase in the globally averaged surface air
temperature in the first 70-yr period. The delay in temperature rise in the Southern
Hemisphere, especially around 50°S, is dominant, as already pointed out by
Stouffer et al. (1989) and others.
The model was applied further to another experiment where the direct effect
of sulfate aerosol increase is added to the effect of CO2, which is assumed to
increase at the compound rate of 1%/yr (JMA, 1999). The aerosol forcing is not
globally uniform due to the short lifetime of sulfate aerosols in the troposphere.
Therefore, it has been inferred that their effects are mostly limited near the
Global Warming Projection Studies at the Meteorological Research Institute/JMA
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emission regions, and hence the characteristic response patterns will also reflect
such distributions. However, the MRI-CGCM1 shows a global scale response,
which is similar to that caused by the CO2-only forcing and is contrary to the
previous studies by Mitchell and Johns (1997).
STUDIES WITH THE USE OF THE MRI-CGCM2
Outline of the MRI-CGCM2
The MRI-CGCM1 had several drawbacks as pointed out in Yukimoto et al.
(2001). Firstly, the thermohaline circulation in the Atlantic Ocean was very weak,
if any. Because of this defect, the slow and small surface temperature increase in
the North Atlantic was not simulated in the transient CO2 run, although it is
typically seen in results from many other models. Secondly, the model simulated
an unrealistic sea ice cover in the Norwegian Sea which is not observed. This
caused a spurious large temperature increase through sea ice melting in the CO2
increase experiment. Finally, even though the MRI-CGCM1 successfully simulates
the ENSO, the amplitude of the Sea Surface Temperature (SST) variation was
smaller than that observed, and the equatorial SST anomaly maximum was found
around the date line, more westward than that observed.
A new version of a coupled atmosphere-ocean general circulation model
(MRI-CGCM2) was developed to improve these unsatisfactory aspects. The
model characteristics of both the MRI-CGCM1 and the MRI-CGCM2 are compared
in Table 1. The MRI-CGCM2 has actually achieved a better performance in
reproducing the mean climate and the climate variability than the MRI-CGCM1
(Yukimoto et al., 2001).
Major improvements in the model performance
Meridional overturning
The meridional deep overturning in the Atlantic Ocean produced by the
models is shown in Fig. 2. After the model integration started, the transport by the
deep overturning immediately vanished in the MRI-CGCM1 (Fig. 2a), and after
that, it remained at a small negative value in the entire model integration (Fig. 2c).
The MRI-CGCM2 reasonably simulates the meridional overturning (Fig. 2b) of
the mixed structure of both shallow and deep cells. The deep overturning cell with
sinking near 60°N is associated with the North Atlantic Deep Water (NADW). Its
mean transport is approximately 17 Sv that roughly agrees with the estimation of
13 Sv by Schmitz and McCartney (1993). The improvement seems to be related
to the change in the calculation of flux adjustment. The deep overturning cell near
the Antarctica, which is known as the origin of the Antarctic Bottom Water
(AABW), is reproduced with 8 Sv maximum transport.
ENSO
Geographical distribution of the SST anomaly (SSTA) regressed on the
NINO3 SST is shown in Fig. 3, for the observation, the MRI-CGCM1 and the
MRI-CGCM2. In the MRI-CGCM2, a prominent positive anomaly is seen in the
Fig. 2. Annual mean meridional overturning stream-functions for the global ocean in (a) the MRICGCM1 and (b) the MRI-CGCM2. Time series of the maximum (annual mean) meridional
overturning in the North Atlantic Ocean for (c) the MRI-CGCM1 and (d) the MRI-CGCM2.
Units are in Sv (Yukimoto et al., 2001).
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T. T OKIOKA and A. NODA
Global Warming Projection Studies at the Meteorological Research Institute/JMA
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Fig. 3. Sea surface temperature anomaly (SSTA) regressed on the normalized time series of the SST
in NINO3 region for (a) observation, (b) the MRI-CGCM1 and (c) the MRI-CGCM2 (Yukimoto
et al., 2001).
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Fig. 4. Time series of global annual-mean surface temperature in response to various scenarios of
trace gases and aerosol. Control run (CNTL): trace gas (CO2, CH 4, N2O and O 3) concentrations
are fixed at the present (around 1990) values for 200 years, CO 2 incr run (CMIP2): CO 2 annual
increase 1% compound for 150 years, IS92a run: CO2 only for 150 years, for 1900–1990
observed value, for 1990–2100 IS92a emission scenario (IPCC, 1992), IS92a + aerosol: IS92a
run plus the direct effect of sulfate aerosol based on the scenario of Mitchell and Johns (1997),
SRES A2: IPCC/SRES A2 scenario (1990–2100), SRES B2: IPCC/SRES B2 scenario (1990–
2100).
central eastern equatorial Pacific extending to the coast of Peru. This pattern is
similar to that observed, although it has shifted westward too much in the MRICGCM1. The unrealistic negative SSTA in the eastern equatorial Indian Ocean
in the MRI-CGCM1 is caused by an unrealistic equatorial upwelling in the
eastern Indian Ocean. This aspect is improved in the new model in association
with improvement of the eastward gradient of the equatorial thermocline in the
Indian Ocean.
Results from various greenhouse gases and aerosol scenario runs
Global mean response
Figure 4 shows the time evolution of the globally-averaged, annual-mean
surface air temperature and precipitation for the CNTL run and the other scenario
Global Warming Projection Studies at the Meteorological Research Institute/JMA
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Fig. 5. Monthly averaged precipitation over Japan calculated by the nested RCM40 when it was
time-integrated from 1986 to 1991 under the lateral and lower boundary conditions provided by
the JMA’s objective analyses (Mabuchi et al., 2000). The observed data are based on the very
dense surface observational network “AMeDAS”.
runs. Because there is little trend in the CNTL run, the time-dependent response
is evaluated by subtracting a 200-year average of the CNTL run.
Simulation of climate change using an idealized CMIP2 scenario has become
a standard experiment, and therefore, results from such experiments by many
other CGCMs are available (e.g., IPCC, 1996). For the MRI-CGCM2, the 20-year
average (61–80 or 1981–2000 in Fig. 4) globally-averaged, annual-mean
differences in surface air temperature and precipitation around the time of CO2
doubling are 1.1°C and 1.2%, respectively. This can be compared to an equilibrium
doubled-CO2 experiment with the atmospheric model (adopted in the MRICGCM2) coupled to a slab mixed layer (50 m depth) with a globally averaged
temperature increase of 2.0°C and precipitation increase of 3.4%. Compared to
the other models listed by the IPCC (IPCC, 1996), the MRI-CGCM2 shows the
lowest sensitivity to the CO 2 doubling. One of the main causes for this might be
due to cloud feedback processes in the model.
The IS92a and IS92a + aerosol runs were made to evaluate the response to
historical and future radiative forcing due to increased CO2 and the direct effect
of sulfate aerosols. Figure 4 indicates that the direct effect of aerosols is small
over the whole integration period and that the historical response is within the
range of natural variability till the 1960s. The former response is smaller than that
reported by Mitchell and Johns (1997).
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The global mean response to the SRES A2 and B2 scenarios is also shown
in Fig. 4. The slowest and smallest response for the SRES A2 run is expected from
the scenario. In addition to this, a similar warming rate is found between the SRES
A2 and B2 runs till about 2030, which may be partly attributable to the gradually
reducing aerosol emissions assumed in the SRES B2 scenario.
Scenario dependence of geographical response
The differences in annual-mean surface air temperature for the period 2071–
2100 relative to the period 1961–1990 between the CNTL and various history
plus scenario runs were studied. The greatest warming at high latitudes, particularly
in the Northern Hemisphere, as well as less warming over the southern oceans and
the northern Atlantic Ocean year-round due to deep mixing there, is consistent
with other CGCMs (IPCC, 1996). Besides these global features, regional response
patterns are also very similar among the scenario runs. Such similarities can be
consistently seen in the response patterns of other CGCMs. This fact suggests
that, for a fixed CGCM, its global warming pattern is robust, and therefore, the
amplitude of local response is basically determined by globally averaged forcing,
rather than a local one.
STUDIES ON LOCAL CLIMATE CHANGES AROUND JAPAN
For considering possible and effective ways to alleviate adverse effects
caused by the global warming, each government and climate sensitive sectors
really necessitate precise information about local climate changes. Japan is
composed of small islands. However, it has various types of climate zones
because it is located in an area influenced by both summer and winter Asian
monsoons and the topography of each island. To obtain detailed information
about possible future climate changes in Japan, a model that reproduces such
detailed local climate characteristics is required. Yasuo Sato and his group have
developed a method where a locally high-resolution atmospheric model can
reproduce the current climate well when both lateral and surface boundary
conditions are prescribed with coarse spatial resolution, i.e., several hundred
kilometers (Mabuchi et al., 2000; Sasaki et al., 2000).
A local model of Japan of 40 km resolution (RCM40) is used to simulate the
climate around Japan. The East Asian model of 120 km resolution (RCM120) is
introduced in between the global model and the RCM40 to allow smooth spatial
interpolations. Both RSM120 and RSM40 were originally developed at the JMA
for operational forecasts. The whole system was tested by replacing the boundary
conditions with the analyzed values of coarse resolutions (about 200 km), and the
system was run from 1986 to 1991 for 6 years. Figure 5 compares the monthly
averaged precipitation calculated by the model and the observed data of a very
dense network “AMeDAS” (the JMA’s automated surface meteorological
observation system with about 20 km resolution). The agreement between them
is satisfactory except in a few cases.
The same group has applied the system to the global warming problem,
where the results obtained in the transient CO2 run with the MRI-CGCM1 are
Global Warming Projection Studies at the Meteorological Research Institute/JMA
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used to prescribe boundary and surface conditions. In January, RCM40 simulates
in the control run realistic precipitation along the Japan Sea side of the mountain
range, which is completely missing in the MRI-CGCM1. In July, precipitation
corresponding to the Baiu front is improved substantially in RSM40. Preliminary
results of the climate changes at the time of CO2 doubling for July show
substantial reductions in precipitation except in the western part of Japan. To
increase confidence in the results, we have to improve the model climate further
through the improvement of both the spatial resolution and the physical processes
of the model.
STUDIES ON TROPICAL CYCLONE ACTIVITIES
Another big concern for Japan concerning the global warming is tropical
cyclones (TCs), because they are closely connected with both meteorological
disasters and water resources in summer and fall. Will the number of TCs increase
(Bengtsson et al., 1996)? Will they intensify as was suggested by Emanuel
(1987)? How will the paths of the TCs change? Sugi et al. (1997) ran a JMA
Fig. 6. Averaged total number of simulated tropical cyclones per year (Yoshimura et al., 1999).
Cumulus parameterizations of both Arakawa-Schubert (AS) and Kuo (Kuo) were adopted. Runs
were repeated by changing SST, i.e., climatological SST, typical El Nino SST, typical La Nina
SST, SST where climatological SST is uniformly increased by 2K (case 2K), and SST where the
first EOF model in SST in the MRI-CGCM1 run was added/subtracted further for case 2K.
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T. T OKIOKA and A. NODA
operational model (T106L21) using both the climatological SST and the SST
where the SST increase obtained in the transient CO2 run with the MRI-CGCM1
is added to the climatological SST. The simulated tracks of TCs in the
climatological run reproduce climatological distributions basically, although the
model resolves them marginally. They analyzed the behavior of TCs and obtained
a decrease in the number in the globally averaged sense, especially in the
equatorial western Pacific in the increased SST case. Further increase in resolution
will certainly be required to obtain conclusive results.
To explore the changes in TCs under the global warming further, Yoshimura
et al. (1999) repeated sensitivity experiments by changing the cumulus
parameterization scheme from that of Kuo (case Kuo) to that of ArakawaSchubert (case AS), and SSTA distributions. To study the occurrence of TCs
under the current climate, not only the climatological SST (case CL) but also the
cases where typical El Nino and La Nina type SSTAs are added (cases EN/LN)
are tested. In one sensitivity run, SST is increased by +2K uniformly from the
climatological SST in the low and mid latitudes (case 2K). In another run, a
natural variational pattern in the transient CO2 run with the MRI-CGCM1 (the
first EOF mode in SST) is added/subtracted further (cases MR/GF).
Figure 6 shows the averaged total number of simulated TCs per year for the
respective cases. Although the total numbers differ substantially depending on
the cumulus parameterization schemes even for the same SST, the difference in
SSTA does not seem to cause big differences in the total number of TCs for the
same cumulus scheme. It is noted also that the total number of TCs reduces
significantly in both the Arakawa-Schubert scheme and the Kuo scheme when the
SST is increased.
Yoshimura et al. (1999) discusses a possible cause of the reduction in TCs
under the global warming. They point out that the mean precipitation rate near the
TC centers increases by about 10–30% in the runs with increased SSTs. If a TC
is regarded as a system to convert latent heat into sensible heat in the tropical
atmosphere, fewer TCs are required to convert the same amount of heat.
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