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Progress in Developing the Short-range Operational Climate Prediction System of China National Climate Center
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摘要: 该文简要介绍了国家气候中心短期气候预测模式系统的研发成果，并侧重于从海洋资料同化系统、陆面资料同化系统、月动力延伸预测模式系统、季节气候预测模式系统4个方面介绍了第2代短期气候预测模式系统的业务化进展。第2代海洋资料同化系统已初步建成，其对温盐的同化效果总体上优于第1代同化系统；陆面资料同化系统正在研发中，目前已完成其中的多源降水融合子系统的业务建设工作，可为陆面分量提供实时的大气降水强迫分析场；第2代月动力延伸预测系统基于国家气候中心大气环流模式BCC_AGCM2.2建立，已于2012年8月进入准业务运行阶段；第2代季节预测模式系统基于国家气候中心气候系统模式BCC_CSM1.1(m) 建立，将于2013年底投入准业务运行。初步评估表明：第2代月动力延伸预测模式系统和季节气候预测模式系统分别对候、旬、月和季节、年际时间尺度的气候变率体现出了一定的预测能力，其对降水、气温、环流等要素的预测技巧总体上要高于第1代预测系统。
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关键词:
- 海洋资料同化系统;
- 陆面资料同化系统;
- 月动力延伸预测模式系统;
- 季节气候预测模式系统
Abstract: The progress in developing the second-generation short-range climate forecast system of National (or Beijing) Climate Center (NCC or BCC) is introduced, focusing on four items, i.e., the global ocean data assimilation system, the land data assimilation system, the monthly-scale dynamical extended-range forecast system (DERF), and the seasonal climate forecast system. With a better assimilation of temperature and salinity than the first-generation system, the second-generation ocean data assimilation system is now at the quasi-operational level. The land data assimilation system is still under development, but the multisource precipitation merging subsystem is now quasi-operational and can produce reanalysis of precipitation as a forcing to land system. The atmospheric general circulation model BCC_AGCM2.2 and the climate system model BCC_CSM1.1(m) are the main tools for the second-generation monthly-scale DERF and the second-generation seasonal prediction system, respectively. The former has entered quasi-operational use since middle August of 2012 and conducted four-member real-time forecast jobs and 80 hindcast jobs every day, and the latter will enter its quasi-operational stage by the end of 2013. A preliminary evaluation indicates that the second-generation system shows a certain capability in predicting the pentad, ten-day, monthly, seasonal and inter-annual climate variability. It exhibits a higher prediction skill, compared to the first-generation system, in terms of precipitation, surface air temperature, atmospheric circulation and El Ni o-Southern Oscillation, and so on. As shown by the hindcasts by two generations of DERF (i.e., DERF1.0 and DERF2.0) for the monthly mean surface air temperature in January and July, DERF2.0 shows overall higher prediction skill than DERF1.0, especially over the tropical Indian Ocean and Pacific and most mid-high latitude areas in the Northern Hemisphere in January, and most regions in global tropics and subtropics in July. Also, the 20-year hindcasts initialized in the end of February of each year by the two generations of seasonal climate prediction system indicate that, the second-generation system shows significant prediction skill of surface air temperature over most areas in spring, especially over the tropical Pacific, Atlantic and Indian Ocean. In contrast, the skills over most areas of the first-generation system are relative lower. -
图 1 2010年11月—2011年4月FY-3B和MODIS陆表温度相对于GLDAS的全球月平均偏差 (a) 和均方根误差 (b)
Fig. 1 Monthly-mean bias (a) and root mean square error (b) of FY-3B and MODIS LST data compared to GLDAS LST data from October 2010 to April 2011
图 3 DERF2.0和DERF1.0预测的1983—2010年1月、7月气温与观测相关分布 (阴影区表示达到0.05显著性水平)
(a)1月DERF2.0预测与观测，(b)1月DERF1.0预测与观测，(c)7月DERF2.0预测与观测，(d)7月DERF1.0预测与观测
Fig. 3 Correlations between observation and prediction by DERF2.0 and DERF1.0 for temperature in January and July during 1983—2010 (the shaded denotes passing the test of 0.05 level)
(a) prediction by DERF2.0 and observation in January, (b) prediction by DERF1.0 and observation in January, (c) prediction by DERF2.0 and observation in July, (d) prediction by DERF1.0 and observation in July
图 4 DERF2.0提前5, 3, 1 d预报2012年11月3—4日的气温距平和降水距平百分率与实况对比
(a) 提前5 d气温距平预报，(b) 提前5 d降水距平百分率预报，(c) 提前3 d气温预报，(d) 提前3 d降水距平百分率预报，(e) 提前1 d气温距平预报，(f) 提前1 d降水距平百分率预报，(g) 气温距平实况，(h) 降水距平百分率实况
Fig. 4 Distribution of temperature anomaly and precipitation anomaly percentage averaged during 3—4 November 2012 for predictions of 5-day, 3-day, and 1-day leading by DERF2.0 and observations
(a) temperature prediction of 5-day leading, (b) precipitation prediction of 5-day leading, (c) temperature prediction of 3-day leading, (d) precipitation prediction of 3-day leading, (e) temperature prediction of 1-day lead, (f) precipitation prediction of 1-day leading, (g) temperature observation, (h) precipitation observation
图 5 第2代季节气候预测模式系统的结构示意图
Fig. 5 Schematic structure of the second-generation seasonal climate forecast model system
图 6 第1代、第2代季节气候预测模式系统3月初预测的1991—2010年春季、夏季气温与观测相关分布 (a) 春季第1代系统预测与观测，(b) 夏季第1代系统预测与观测，(c) 春季第2代系统预测与观测，(b) 夏季第2代系统预测与观测
Fig. 6 Correlations between observation and prediction at the start of March by the first-generation and second-generation seasonal climate forecast model systems for temperature in spring and summer during 1991—2010 (a) prediction by the first-generation system and observation in spring, (b) prediction by the first-generation system and observation in summer, (c) prediction by the second-generation system and observation in spring, (d) prediction by the second-generation system and observation in summer
表 1 第1代、第2代季节预测系统回报的1991—2010年多年平均场与观测的空间相关
Table 1 Spatial correlation between observation and prediction by the first-generation and second-generation seasonal climate forecast model systems for the climatological fields during 1991—2010
变量 区域 春季 (3—5月) 夏季 (6—8月) BCC_CSM1.1(m) BCC_CM1.0 BCC_CSM1.1(m) BCC_CM1.0 500 hPa位势高度 全球 0.997 0.960 0.998 0.990 热带 0.930 0.680 0.970 0.930 亚洲 0.998 0.980 0.989 0.968 200 hPa纬向风 全球 0.950 0.770 0.96 0.900 热带 0.940 0.740 0.960 0.920 亚洲 0.987 0.500 0.970 0.780 850 hPa纬向风 全球 0.960 0.920 0.950 0.880 热带 0.870 0.740 0.900 0.800 亚洲 0.850 0.670 0.850 0.500 地面气温 全球 0.995 0.810 0.990 0.450 热带 0.950 0.190 0.960 -0.230 亚洲 0.990 0.830 0.970 0.660 中国 0.980 0.620 0.970 0.330 地面降水 全球 0.860 0.520 0.780 0.470 热带 0.850 0.520 0.770 0.430 亚洲 0.740 0.180 0.730 0.220 中国 0.610 0.400 0.670 0.410 
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