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

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

Simple history of Beijing Climate Center WMO GPC Established 2003 2006 2009 2010 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

Organization of BCC and its prediction operation as RCC

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

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)

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: 1991-2012 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: 1991-2013

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.

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

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.

Operational prediction products for Asia(season)

Online prediction products for Asia

Operational prediction products for Asia (month)

Model based

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

Probabilistic MME

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

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

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

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.

Thanks

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：1991-2013 Three-dimensional variational data assimilation with MOM4p0