CMA Model Description

1. Ensemble version
 
Ensemble identifier code:   BCC-CPS-S2Sv1

Short Description:  Beijing Climate Center (BCC) Climate Prediction System version 1 for S2S is based on lagged average forecasting (LAF) method using a fully-coupled BCC Climate System Model BCC-CSM1.2. The S2S Forecasts are running on every day since 1 Jan 1994 and end with a 60-day integration. Each forecast consists of 4 LAF ensemble members, which are initialized at 00 UTC of the first forecast day and 18, 12 and 06 UTC of the previous day, respectively.
Research or operational: Operational
Data time of first forecast run:   01/05/2014
 

2. Configuration of the EPS

Is the model coupled to an ocean model ?   Yes from day 0
If yes, please describe ocean model briefly including frequency of coupling and any ensemble perturbation applied: Ocean model is MOM4 with a 1°/3-1° horizontal resolution, 40 vertical levels, initialized from BCC Global Ocean Data Assimilation System analysis. Frequency of coupling is 2-hourly.
Is the model coupled to a sea Ice model? Yes from day 0.
If yes, please describe sea-ice model briefly including any ensemble perturbation applied:  Sea ice model is the GFDL Sea Ice Simulator (SIS) with a same horizontal resolution as the ocean model. Sea ice initial conditions come from a Coordinated Initialization System (CIS) that is to use BCC-CSM1.2 integrating one month before forecast time to create a coordinated initial state in each component of BCC-CSM1.2 using nudging technique for atmospheric analyses.
Is the model coupled to a wave model? No
If yes, please describe wave model briefly including any ensemble perturbation applied: -
Ocean model: MOM4 with 1°/3-1° horizontal resolution and 40 vertical levels
Horizontal resolution of the atmospheric model: T106 (about 110 km)
Number of model levels: 40
Top of model: 0.5 hPa
Type of model levels: sigma-pressure hybrid coordinate
Forecast length: 60 days (1440 hours)
Run Frequency: once daily
Is there an unperturbed control forecast included?: Yes
Number of perturbed ensemble members: 3
Integration time step: 7.5 minutes
 
3. Initial conditions and perturbations

Data assimilation method for control analysis: 3D Var method for oceanic analysis and nudging technique for atmospheric analysis used in BCC Coordinated Initialization System (CIS). The CIS is to use BCC-CSM1.2 integrating a period time before forecast time to create a coordinated initial state in each component of BCC-CSM1.2 under the forcing of the NCEP air temperature and U- and V-velocity reanalyses, BCC merged precipitation observations, and BCC Global Ocean Data Assimilation System analyses.

Resolution of model used to generate Control Analysis: T106L40 resolution for atmospheric model component, and 1°/3-1° horizontal resolution and 40 vertical levels for oceanic model component
Ensemble initial perturbation strategy: LAF perturbations added to control analysis
Horizontal and vertical resolution of perturbations:  same as the control analysis
Perturbations in +/- pairs: No
 
4. Model Uncertainties perturbations:

Is model physics perturbed? No.
Do all ensemble members use exactly the same model version? The same
Is model dynamics perturbed? No
Are the above model perturbations applied to the control forecast? No
 
5. Surface Boundary perturbations:

Perturbations to sea surface temperature? No
Perturbation to soil moisture? No
Perturbation to surface stress or roughness? No
Any other surface perturbation? No
Are the above surface perturbations applied to the Control forecast? NA
Additional comments
 
6. Other details of the models:

Description of model grid: T106 global Gaussian grid
List of model levels in appropriate coordinates: 40 vertical layers at 0.49, 1.05, 2.26,    4.71, 8.97, 15.11, 22.51, 30.20, 37.55, 43.86, 49.77, 56.47, 64.07, 72.69, 82.46, 93.53, 106.07, 120.26, 136.35, 154.60, 175.32, 198.84, 225.43, 255.11, 287.90, 324.04, 363.80, 407.43, 455.24, 507.51, 564.57, 626.73, 694.35, 767.78, 836.82, 889.28, 927.74, 956.07, 976.35, 992.56 mbar
What kind of large scale dynamics is used?  Spectral Eulerian dynamics core for vorticity, diversity, temperature, and surface pressure; semi-lagrangian dynamics core for specific humidity and cloud waters other tracers [Wu et al., 2008]
What kind of boundary layer parameterization is used? non-local Atmospheric Boundary Layer (ABL) parameterization [Holtslag and Boville, 1993]
What kind of convective parameterization is used? Wu 2012 (Climate Dynamics)
What kind of large-scale precipitation scheme is used?  The scheme used in NCAR Community Atmosphere Model (CAM3, Collins et al., 2004).
What cloud scheme is used?  Diagnostic cloud fraction depending on relative humidity, atmospheric stability and convective mass fluxes.
What kind of land-surface scheme is used? Beijing Climate Center Atmospheric Vegetation Interactive Model version 1 (BCC-AVIM1), Wu et al., 2013 (J.G.R).
How is radiation parameterized? The radiation code originates from the CAM3 (Collins et al., 2004)
Other relevant details?  The version 1.2 of the Beijing Climate Center Climate System Model (BCC_CSM1.2) is developed at the Beijing Climate Center (BCC), China Meteorological Administration (CMA). It is an updated version of BCC_CSM1.1 (Wu et al., 2013; 2014) and is a fully coupled global climate-carbon model including interactive vegetation and global carbon cycle, in which the atmospheric component BCC Atmospheric General Model version 2.1 (BCC_AGCM2.3), ocean component Modular Ocean Model version 4 (MOM4)-L40, land component BCC Atmosphere and Vegetation Interaction Model version 1.0 (BCC_AVIM1.0), and sea ice component [sea ice simulator (SIS)] are fully coupled and interact with each other through fluxes of momentum, energy, water, and carbon at their interfaces. Information between the atmosphere and the ocean is exchanged once per 2 hours. The exchange of atmospheric carbon with the land biosphere is calculated at each model time step (7.5 min).

7. Re-forecast Configuration

Number of years covered: 20 past years (from 1 Jan 1994 to 30 April 2014)
Produced on the fly or fix re-forecasts? fix re-forecasts
Frequency: Once a day.
Ensemble size: 4 members
Initial conditions: NCEP R1 atmospheric initial conditions (2.5°×2.5° resolution) + BCC GODAS ocean initial conditions (1°/3-1° resolution)
Is the model physics and resolution the same as for the real-time forecasts: Yes
If not, what are the differences: NA
Is the ensemble generation the same as for real-time forecasts? Yes
If not, what are the differences: NA
 
8. References:

Wu T. et al., 2014: An overview of BCC climate system model development and application for climate change studies. J. Meteor. Res., 28(1), 34-56;
Wu T. et al., 2013: Global carbon budgets simulated by the Beijing climate center climate system model for the last century. J Geophys Res Atmos, 118, 4326-4347
Wu T., R. Yu, F. Zhang, Z. Wang, M. Dong, L. Wang, X.Jin, D. Chen, L. Li, 2010：The Beijing Climate Center atmospheric general circulation model: description and its performance for the present-day climate, Climate Dynamics, 34, 123-147, DOI 10.1007/s00382-008-0487-2.
Wu T., R. Yu, F. Zhang, 2008: A modified dynamic framework for atmospheric spectral model and its application, J. Atmos.Sci., 65, 2235-2253
Wu T., 2012: A Mass-Flux Cumulus Parameterization Scheme for Large-scale Models: Description and Test with Observations, Clim. Dyn., 38:725–744, DOI: 10.1007/ s00382-011-0995-3.
Jie W., T. Wu, J. Wang, W. Li, T. Polivka, 2015: Using a Deterministic Time-Lagged Ensemble Forecast with a Probabilistic Threshold for Improving 6-15 Day Summer Precipitation Prediction in China, Atmospheric Research, 156: 142–159
Liu X., T. Wu, S. Yang, W. Jie, S. Nie, Q. Li, Y. Cheng, X. Liang, 2015: Performance of the Seasonal Forecasting of the Asian Summer Monsoon by BCC_CSM1.1(m). Adv. Atmos. Sci.,doi: 10.1007/s00376-015-4194-8,in press.
Liu X., T. Wu, S. Yang, Q. Li, Y. Cheng, X. Liang, Y. Fang, W. Jie, S. Nie. 2014. Relationships between interannual and intraseasonal variations of the Asian - western Pacific summer monsoon hindcasted by the BCC_CSM1.1(m). Adv. Atmos. Sci., 31, 1051–1064.
Jie W., T. Wu, J. Wang, W. Li, X. Liu, 2014: Improvement of 6–15 day precipitation forecasts using a time-lagged ensemble method. Adv. Atmos. Sci., 31(2), 293–304, doi: 10.1007/s00376-013-3037-8.
Huang A., Y. Zhang, Z. Wang, T. Wu, D. Huang, Y. Zhou, Y. Zhao, Y. Huang, X. Kuang, L. Zhang, Y. Fang, Y. Guo, 2013: Extended range simulations of the extreme snow storms over southern China in early 2008 with the BCC_AGCM2.1 model,J. Geophys. Res. Atmos., 118, 8253–8273, doi:10.1002/jgrd.50638.

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