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Dynamical Downscaling of Seasonal Climate Prediction Over East Asia for March-Septemb
er 2003 at CWB
Chih-Hui Shiao, Ying-Jui Chuang
Central Weather Bureau, Taipei
October 2003
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The plan for the CWB dynamical downscaling forecast systems
System I :
NCEP-RSM (60-km) + IRI-ECHAM4.5 (T42L18)
System II :
CWB-RSM (60-km) + CWB-GCM (T42L18)
2 system X 5 members
Model integration : 7 months
Domain : 100 。 E-135 。 E, 10 。 N-35 。 N
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The current status
Forecast period : 4 months
Domain : 100 。 E-135 。 E, 10 。 N-35 。 N
System I :
NCEP-RSM (60-km) + IRI-ECHAM4.5 (T42L18)
Two member (ASST and PSST)
System II :
In past studies, CWB-RSM was applied to simulate the 1998 and 2002 summer monsoon over East Asia has successfully captured not only the regional circulation but also the precipitation patterns.
CWB-RSM (60-km) + CWB-GCM (T42L18)
CWB-RSM (120-km) + ECHAM4.5 (T42L18)
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Base field : ECHAM4.5 (T42L18)
support by International Research Institute for Climate Prediction (IRI)
20 members of 7 month-long forecast for each month
a set of AMIP simulation
To examine the performance of NCEP RSM and CWB RSM in the dynamical downscaling precipitation forecast, based on the forecast results on the past half year.
Integration length : 4 month-long forecast for each month
Experimental period : March-September 2003
Domain : East Asia
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The evolution of precipitation on March-September 2003 by CAMS_OPI
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02468
10121416
Mar Apr May Jun Jul Aug Sep
mm
/day
CAMS_OPI
CAMS_OPI precipitation on 2003
(average over 115 。 E-125 。 E, 15 。 N-30 。 N)
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NCEP-RSM (60-km)
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The precipitation anomaly
The anomaly of analysis is the CAMS_OPI analysis in 2003 compare with the average of 1979-1995.
The forecast precipitation anomaly of NCEP RSM is the forecast in 2003 compare with the simulation of NCEP RSM forced by the ECHAM4.5 AMIP simulation averaged in 1971-1986.
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Precipitation Anomaly of M2+M3+M4 with ECHAM4.5 / NCEP RSM
NCEP RSM
ECHAM
Regional downscaling forecasts is under control of GCM strictly except those mesoscale phenomena result from high-resolution topographic and coastal effects.
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NCEP RSM
CAMS_OPI
The major difference of precipitation anomaly between forecast and analysis are the forecast is too wet along the coastline and too dry in midlatitude
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One possible source of the precipitation anomaly bias may due to the difference between the AMIP simulation and the analysis.
AMJ JJAMJJ JAS
The difference of ECHAM4.5 AMIP run to GPCP in 1979-1986 mean
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NCEP RSM
CAMS_OPI
AMJ JJAMJJ JAS
AMIP run bias
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Summary I
Anomaly forecast is possible if the model climatology is
‘realistic’.
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The precipitation difference between the GPCP analysis and ECHAM4.5/NCEP RSM downscaling AMIP simulation are used to modify the ECHAM4.5/NCEP RSM currently forecasts.
Bias Correction
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Forecast precipitation by NCEP RSM without and with bias correction (average over 115 。 E-125 。 E, 15 。 N-30 。 N)
02468
10121416
Mar Apr May Jun Jul Aug Sep
mm
/day CAMS_OPI
ECHAM_M1RSM_M1
02468
10121416
Mar Apr May Jun Jul Aug Sep
mm
/day CAMS_OPI
ECHAM_M1NRSM_M1N
02468
10121416
Mar Apr May Jun Jul Aug Sep
mm
/day CAMS_OPI
ECHAM_M2NRSM_M2N
02468
10121416
Mar Apr May Jun Jul Aug Sep
mm
/day CAMS_OPI
ECHAM_M2RSM_M2
without bias correction with bias correction
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(M3 and M4)
02468
10121416
Mar Apr May Jun Jul Aug Sep
mm
/day CAMS_OPI
ECHAM_M3RSM_M3
02468
10121416
Mar Apr May Jun Jul Aug Sep
mm
/day CAMS_OPI
ECHAM_M4
RSM_M4
02468
10121416
Mar Apr May Jun Jul Aug Sep
mm
/day CAMS_OPI
ECHAM_M3NRSM_M3N
02468
10121416
Mar Apr May Jun Jul Aug Sep
mm
/day CAMS_OPI
ECHAM_M4NRSM_M4N
without bias correction with bias correction
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Downscaling forecasts by NCEP RSM with bias correction
(average over M2+M3+M4 )
AMJ MJJ JJA JAS
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Downscaling forecasts with CWB RSM
(average over M2+M3)
AM ASMJ JJ JA
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R.M.S.E. of precipitation with different forecast start month (average over M1,M2,M3,M4)
02468
10121416
Mar Apr May Jun Jul Aug Sep
mm
/day ECHAM
NCEPRSM_NCWBRSM
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R.M.S.E. of precipitation to different forecast length
0
2
4
6
8
10
M1 M2 M3 M4
mm
/day
ECHAMNCEPRSMNCEPRSM_NCWBRSM
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Summary II
Bias correction is necessary for single model forecast.
How to eliminate the large-scale bias but keep local phenomena is still known.