1. Introduction to the operational climate prediction for Asia in BCC
Thirteenth Session of the Forum on Regional Climate Monitoring, Assessment and Prediction for Asia (FOCRAII), April 24-26, 2017, Beijing China
Introduction to the operational climate prediction for Asia in BCC
Liu Changzheng
Beijing Climate Center
April 26, 2017

2. Content Introduction of BCC Climate model system
Prevent seasonal and monthly prediction products for Asia
The developing MME prediction system for Asian climate

3. Simple history of Beijing Climate Center
WMO GPC
Established
CEEMA
WMO RCC
in RA II
EAMAC
GPC: Global Producing Centre for long-range forecasts
RCC in RAII : Regional Climate Center in Asia
EAMAC: East Asian Monsoon Activity Centre
CEEMA: Centre for Extreme Events Monitoring in Asia

4. Organization of BCC and its prediction operation as RCC

5. The present operational climate prediction for Asia
Based on BCC’s climate model
Seasonal prediction
Monthly prediction
Precipitation
Temperature
Circulation

6. Beijing Climate Center Climate System Model (BCC_CSM)
IPCC AR5
Aerosol
(CUACEAero)
Atmosphere
(BCC_AGCM)
Chemistry
(MOZART-2)
BCC_AGCM2.2 (T106L26)
Originated from CAM3，Developed by BCC.
Model Dynamics: Wu et al.(2008, J.Atmos.Sci.)
Model Physics：
Wu et al. (2010, Climate Dynamics)
Wu, 2011, Climate Dynamics
BCC_AVIM1 (T106)
Developed by BCC.
Coupled with the dynamic vegetation
and land carbon cycle processes.
MOM4_L40v2 ( 1/3~1o )
Developed by GFDL，Modified by BCC.
A carbon cycle module (from OCMIP2) with simple biogeochemical processes was introduced.
SIS (gx1v1)
Developed by GFDL.
Under way
Under way
Seasonal climate prediction
Coupler
Sea Ice
(SIS)
Ocean
(MOM4_L40)
Land
(BCC_AVIM)
Regional Climate Model (BCC_RegCM)

7. Routine operation of climate model at BCC
0-45 days
BCC_AGCM2.2 (T106L26)
Daily four times forecast. 6-hour interval.
Integrate 45 days forced by persisted SST anomalies (persistence of the previous weekly SST anomalies).
Initial data: NCEP-R1/CMA-T639 reanalysis (u, v, ps, T) and NOAA OiSST (fixed the SST anomalies)
13 ensemble members .
The operational run stated on Dec. 1, 2013.
Re-Forecasts:
0-12 months
The fully coupled climate model BCC_CSM1.1m at T106L26 atmosphere resolution and 1/3-1° ocean resolution
Once a month (the first day every month)
Integrate 0-12 months.
24 ensemble members of 15 lagged-average-forecast and 9 singular-vector (SV) method
Initial data:
Atmosphere: NCEP-R1/CMA-T639 reanalysis;
Ocean: NCEP-GODAS / BCC-GODASv2 reanalysis
The quasi operational run stated on March 1, 2014.
Re-Forecasts:

8. Hindcast Skill: 500-hPa GPH
二代模式对热带地区的500hPa位势高度场的预报技巧最高，在中纬度的高技巧区域成波列状分布，与EU型和ENSO激发的PNA型等遥相关型类似
The model shows highest prediction skill over all the tropics. In the middle latitudes, the high skill areas are similar to the PNA patterns.

9. Hindcast Skill: T2M
For this model, prediction skills on T2m mainly locate on the tropic ocean and the areas often influenced by ENSO.

10. Hindcast Skill: Precipitation
二代模式对降水的预报技巧主要位于热带中东太平洋、印度洋和西大西洋地区；在热带外地区，该模式主要对冬季ENSO的遥相关影响区域，如东北太平洋和北美部分地区、以及我国华南和长江地区，具有一定的预报技巧
Like other climate models, BCC CSM1.1 mainly shows relatively high skills over some tropical areas including the middle and eastern Pacific, Indian Ocean, and the western Atlantic. The skills also cover a few extra-tropic areas which are tele-connected with ENSO, such as the northern-east Pacific, part of North America.

11. Operational prediction products for Asia(season)

12. Online prediction products for Asia

13. Operational prediction products for Asia (month)

16. Model based

17. A multi-model ensemble prediction system for Asia climate is developing
Based on MME and statistical downscaling technique
On monthly and seasonal timescales
Probabilistic MME : terciles
Deterministic MME: precipitation

18. Probabilistic MME

19. Model used for Probabilistic MME
System
member
hindcast
UKMO
GloSea5 42
1993～2015
NCEP
CFSv2
About 60
1982～2010
BCC
CSM1.1 24
1991～2015

20. MODES: Multi-Model Downscaling Ensemble prediction System at Beijing Climate Center
GCM
Output
Statistical
Downscaling
Ensemble ……
ECMWF
NCEP
TCC
NCC
BP-CCA
OSR
HCRE EM
MLR
Previous study shows that forecast by downscaling and ensemble perform better than that by ensemble and downscaling.(Kang H. W. et al.,2009)
Deterministic result are based on downscaling MME, similar but different from the work by APCC

21. Model used for Deterministic MME
System
Prediction Months
hindcast
ECMWF
System 4 7
1981～2010
NCEP
CFS-V2 9
1982～2010
BCC
CSM1.1 13
1991～2015

22. Main messages
BCC offers online products of seasonal and monthly prediction for Asia region
The present prediction products are made based on the BCC’s CSM
A new prediction system based on MME and statistical downscaling is developing to enhance the prediction ability for Asia climate.

23. Thanks

24. Seasonal prediction based on BCC_CSM1.1m
BCC_AGCM2.2(T106 ~110 km, L26) Top: 2.19 hPa
BCC_AVIM1.0(T106)
MOM4-L40v2(1/3°~30km)
SIS(1/3°~30km)
BCC_CSM1.1(m)
Forecast：initialized on 1st of each month, 13-month integration
Ensemble forecast：15 LAF members + 9 SV members
Hindcast period：
Three-dimensional variational data assimilation with MOM4p0