GC51A-0750: Comparing CMIP3 20th Century Experiments and Developing Dynamic Downscaling Method Using Numerical Weather Prediction Model
BCCR_BCM2_0
CCCMA_CGCM3_1_T63
CCCMA_CGCM3_1
CNRM_CM3
Scorr.=0.80, RMSE=6.46
Scorr.=0.93, RMSE=0.91
Scorr.=0.92, RMSE=1.17
Scorr.=0.90, RMSE=1.55
CSIRO_MK3_0
CSIRO_MK3_5
GFDL_CM2_0
GFDL_CM2_1
GISS_AOM
Scorr.=0.91, RMSE=1.55
Scorr.=0.42, RMSE=3.97
Scorr.=0.85, RMSE=1.84
Scorr.=0.88, RMSE=1.11
Scorr.=0.63, RMSE=1.96
GISS_MODEL_E_H
GISS_MODEL_E_R
IAP_FGOALS1_0_G
INGV_ECHAM4
INMCM3_0
Scorr.=0.80, RMSE=1.29
Scorr.=0.69, RMSE=1.59
Scorr.=0.43, RMSE=3.69
Scorr.=0.33, RMSE=3.15
Scorr.=0.84, RMSE=2.18
IPSL_CM4
MIROC_3_2_HIRES
MIROC_3_2_MEDRES
MPI_ECHAM5
MRI_CGCM2_3_2A
Scorr.=0.45, RMSE=3.40
Scorr.=0.29, RMSE=3.94
Scorr.=0.55, RMSE=3.04
NCAR_CCSM3_0
NCAR_PCM1
UKMO_HADCM3
UKMO_HADGEM3
Scorr.=0.56, RMSE=2.36
Scorr.=0.70, RMSE=2.65
Scorr.=0.71, RMSE=2.11
Scorr.=0.90, RMSE=2.64
• Monthly mean air temperature averaged for 1979-2000 (or 1999).
• Three (or two) layers for three regions in Asia (See Fig. 6).
• Results of CMIP3/20C3M widely varied in upper layer. For Indochina
peninsula, the variation is also significant in middle/lower layer.
• For Tibet and Japan, variations are relatively small in middle/ lower layer.
Indochina Peninsula 200hPa
Indochina Peninsula 500hPa
Indochina Peninsula 850hPa
Around Japan 200hPa
Around Japan 500hPa
Around Japan 850hPa
Tibetan Plateau 200hPa
Tibetan Plateau 500hPa
Regions for spatial average
Scorr.=0.51, RMSE=4.18
Kelvin
Scorr.=0.03, RMSE=3.57
4.2 Air temperature over the Tibet, Indochina, and Japan
Kelvin
JRA25 (Reference)
(Kelvin)
3.2 Precipitation averaged for summer
• Every model shows some monsoon rainfall in Asia, but the values of
spatial correlation are smaller than the results of air temperatures (Fig. 4).
• Rainfall around India and Bay of Bengal are underestimated (Fig. 4).
• Around Japan, the “Baiu” rain band is missing in some models (Fig. 4).
GPCP (Reference)
BCCR_BCM2_0
Scorr.=0.69, RMSE=2.32
CSIRO_MK3_0
CSIRO_MK3_5
Scorr.=0.76, RMSE=2.10
Scorr.=0.73, RMSE=2.39
GISS_MODEL_E_H
GISS_MODEL_E_R
Scorr.=0.55, RMSE=3.15
Scorr.=0.72, RMSE=2.50
IPSL_CM4
MIROC_3_2_HIRES
Scorr.=0.70, RMSE=2.40
Scorr.=0.75, RMSE=2.35
NCAR_CCSM3_0
NCAR_PCM1
CCCMA_CGCM3_1_T63
Scorr.=0.75, RMSE=2.28
GFDL_CM2_0
Scorr.=0.79, RMSE=2.11
IAP_FGOALS1_0_G
Scorr.=0.62, RMSE=2.51
MIROC_3_2_MEDRES
Scorr.=0.76, RMSE=2.22
UKMO_HADCM3
CCCMA_CGCM3_1
CNRM_CM3
Scorr.=0.76, RMSE=2.24
GFDL_CM2_1
Scorr.=0.67, RMSE=2.57
GISS_AOM
Scorr.=0.80, RMSE=2.11
INGV_ECHAM4
Scorr.=0.74, RMSE=2.19
INMCM3_0
Scorr.=0.74, RMSE=2.25
MPI_ECHAM5
Scorr.=0.56, RMSE=2.83
MRI_CGCM2_3_2A
Scorr.=0.73, RMSE=2.69
UKMO_HADGEM3
Scorr.=0.69, RMSE=2.52
MIUB_ECHO_G
Air Temperature
Precipitation
Tibetanplateau
Tibetan
plateau
Kelvin
Figure 3 Distribution of air temperature at 200 hPa of JRA25 & CMIP3 20C3M
Figure-3
20C3M.
India
Japan
Indochina Peninsula
Figure-6 Temporal variation of air temperature for JRA25 and CMIP3 20C3M.
Target regions are shown in the lower-right.
5. Dynamic Downscaling by WRF
• Following the comparison results,
results the
CMIP3 products are not directly used
as initial and boundary conditions for
DDS, but we have applied a pseudo
global warming conditions, based
on Sato et al. (2007).
• Before downscaling future climates,
the current conditions are downscaled
with the three nested domains: 90 km,
30 km,
k
6 km
k (time
( i step: 360s,
360 120s,
120
40s). The target region of the finest
domain is around Tokyo.
• Precipitation in the South Asia is
relatively well reproduced, however,
the reproducibility of precipitation
around Japan due to typhoons is low
(Figs. 7 and 8). Further investigation
for settings
g of WRF is necessary.
y
a) GPCP rainfall
b) Downscaled (for domain of Δx=90 km )
Figure-7 Monthly daily-mean rainfall
for July 2000. a) GPCP, b) DDS result.
a) Radar rainfall
b) Downscaled
(for domain of Δx=6 km )
Figure-8 Monthly daily-mean rainfall
for July 2000. a) Radar, b) DDS result.
Scorr.=0.71, RMSE=2.37
Scorr.=0.51, RMSE=3.58
Scorr.=0.77, RMSE=2.50
Scorr.=0.75, RMSE=2.65
Scorr.=0.73, RMSE=2.31
(mm/day)
Figure-4 Distribution of daily mean precipitation of GPCP and CMIP3 20C3M.
4. Temporal Variation of 20C3M Experiments in CMIP3
4 1 Precipitation around India
4.1
India, Indochina Peninsula and Japan
• Monthly mean daily-precipitation averaged for 1979-2000 (or 1999).
• Three regions in Asia (India, Indochina Peninsula, and Japan. See Fig. 6).
• Widely varied but rainy/dry season can be recognized in India and
Indochina. On the other hand, reproducibility of the seasonal
variation of precipitation around Japan is quite low (Fig. 5).
India (70-80E, 7.5N-20N)
Indochina Peninsula (95-110E, 10N-20N)
Japan (130-140E, 30N-45N)
6. Discussion
• In CMIP3/20C3M runs, the reproducibility of the air temperature at
lower layer is relatively good. However, as shown in temporal variation,
the variability among the models are large in some region. Such area
characteristics must be known before assessment or downscaling.
g
• The large variability and the lower reproducibility of air temperature in
upper layer may negatively affect in dynamic downscaling by numerical
weather prediction models. Therefore a “pseudo global warming method”
is recommended to use CMIP3 data for downscaling future climate.
• Temporal variation shows that the reproducibility of a model differs with
the season. In such case, a simple average of multiple models may not
appropriate to asses future climate conditions.
• In this study, we have examined limited variables for limited season and
regions Other conditions in CMIP3/20C3M should be investigated and
regions.
appropriate models must be selected for downscaling.
References
Figure-5 Temporal variation of GPCP and CMIP3/20C3M precipitation
1) Onogi, K., J. Tsutsui, H. Koide, M. Sakamoto, S. Kobayashi, H. Hatsushika, T.Matsumoto, N. Yamazaki, H. Kamahori,
K. Takahashi, S. Kadokura, K. Wada, K. Kato, R. Oyama, T. Ose, N. Mannoji, and R. Taira: The JRA-25 Reanalysis,
J. Meteor. Soc. Japan, Vol.85 (3), pp.369-432, 2007.
2) Reynolds, R. W., T. M. Smith, C. Liu, D. B. Chelton, K. S. Casey and M. G. Schlax : Daily High-resolution Blended
Analyses for sea surface temperature, J. Climate, Vol.20, pp.5473-5496, 2007.
3) Sato T., F. Kimura and A. Kitoh: Projection of global warming onto regional precipitation over Mongolia using a
regional climate model, J. Hydrology, Vol.333, pp.144-154, 2007.