Progress in Developing the Short-range Operational Climate Prediction System of China National Climate Center

Wu Tongwen; Song Lianchun; Liu Xiangwen; Li Qiaoping; Liang Xiaoyun; Cheng Yanjie; Zhou Wei; Nie Suping; Zhang Li; Jie Weihua; Fang Yongjie; Zhang Yanwu; Lu Yixiong; Chu Min; Li Jianglong

Vol.24, NO.5, 2013

Article Contents

Article Navigation > Journal of Applied Meteorological Science > 2013 > 24(5): 533-543

Wu Tongwen, Song Lianchun, Liu Xiangwen, et al. Progress in developing the short-range operational climate prediction system of China national climate center. J Appl Meteor Sci, 2013, 24(5): 533-543.

Citation:

Wu Tongwen, Song Lianchun, Liu Xiangwen, et al. Progress in developing the short-range operational climate prediction system of China national climate center. J Appl Meteor Sci, 2013, 24(5): 533-543.

Wu Tongwen, Song Lianchun, Liu Xiangwen, et al. Progress in developing the short-range operational climate prediction system of China national climate center. J Appl Meteor Sci, 2013, 24(5): 533-543.

Citation:

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Progress in Developing the Short-range Operational Climate Prediction System of China National Climate Center

National Climate Center, Beijing 100081

Received Date: 2013-04-08
Rev Recd Date: 2013-07-08
Publish Date: 2013-10-31

Abstract

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.

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Figures and Tables

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

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Fig. 2 Schematic structure of DERF2.0

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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

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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

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Fig. 5 Schematic structure of the second-generation seasonal climate forecast model system

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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

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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)
变量	区域	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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