IMPROVEMENT OF OCEAN DATA ASSIMILATION SYSTEM AND CLIMATE PREDICTION BY ASSIMILATING ARGO DATA

LI Qing-quan; ZHANG Ren-he; LIU Yi-min

Abstract:

The Argo (Array for Real-time Geostrophic Oceanography) data from 1998 to 2003 were used in the Beijing Climate Center-Global Ocean Data Assimilation System (BCC-GODAS). The results show that the utilization of Argo global ocean data in BCC-GODAS brings about remarkable improvements in assimilation effects. The assimilated sea surface temperature (SST) of BCC-GODAS can well represent the climatological states of observational data. Comparison experiments based on a global coupled atmosphere-ocean general circulation model (AOCGM) were conducted for exploring the roles of ocean data assimilation system with or without Argo data in improving the climate predictability of rainfall in boreal summer. Firstly, the global ocean data assimilation system BCC-GODAS was used to obtain ocean assimilation data under the conditions with or without Argo data. Then, the global coupled atmosphere-ocean general circulation model (AOCGM) was utilized to do hindcast experiments with the two sets of the assimilation data as initial oceanic fields. The simulated results demonstrate that the seasonal predictability of rainfall in boreal summer, particularly in China, increases greatly when initial oceanic conditions with Argo data are utilized. The distribution of summer rainfall in China hindcast by the AOGCM under the condition when Argo data are used is more in accordance with observation than that when no Agro data are used. The area of positive correlation between hindcast and observation enlarges and the hindcast skill of rainfall over China in summer improves significantly when Argo data are used.

Get Citation+

LI Qing-quan, ZHANG Ren-he, LIU Yi-min. IMPROVEMENT OF OCEAN DATA ASSIMILATION SYSTEM AND CLIMATE PREDICTION BY ASSIMILATING ARGO DATA [J]. Journal of Tropical Meteorology, 2015, 21(2): 171-184.

Export:

Article Metrics

IMPROVEMENT OF OCEAN DATA ASSIMILATION SYSTEM AND CLIMATE PREDICTION BY ASSIMILATING ARGO DATA

Laboratory for Climate Studies, National Climate Center, China Meteorological Administration, Beijing 100081 China Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters , Nanjing University of Information Science & Techno

Abstract: The Argo (Array for Real-time Geostrophic Oceanography) data from 1998 to 2003 were used in the Beijing Climate Center-Global Ocean Data Assimilation System (BCC-GODAS). The results show that the utilization of Argo global ocean data in BCC-GODAS brings about remarkable improvements in assimilation effects. The assimilated sea surface temperature (SST) of BCC-GODAS can well represent the climatological states of observational data. Comparison experiments based on a global coupled atmosphere-ocean general circulation model (AOCGM) were conducted for exploring the roles of ocean data assimilation system with or without Argo data in improving the climate predictability of rainfall in boreal summer. Firstly, the global ocean data assimilation system BCC-GODAS was used to obtain ocean assimilation data under the conditions with or without Argo data. Then, the global coupled atmosphere-ocean general circulation model (AOCGM) was utilized to do hindcast experiments with the two sets of the assimilation data as initial oceanic fields. The simulated results demonstrate that the seasonal predictability of rainfall in boreal summer, particularly in China, increases greatly when initial oceanic conditions with Argo data are utilized. The distribution of summer rainfall in China hindcast by the AOGCM under the condition when Argo data are used is more in accordance with observation than that when no Agro data are used. The area of positive correlation between hindcast and observation enlarges and the hindcast skill of rainfall over China in summer improves significantly when Argo data are used.

HTML

Reference (28)

[1]	WCRP. CLIVAR Science Plan. [M]. WCRP Pub. No.89, WMO/TD-No.690, Geneva: World Meteorological Organization, 1995.
[2]	LI Qing-quan, YANG Song, KOUSKY V E, et al. Features of cross-Pacific climate shown in the variabilityof China and United States precipitation [J]. Int J Climotol, 2005，25, 1 675-1 696.
[3]	LI Qing-quan, SUN Cheng-hu, YUAN Yuan, et al. Major advances of China climate monitrong and diagnostic operation in recent 20 years[J]. J Appl Meteorol Sci, 2013, 24(6): 666-676 (in Chinese).
[4]	RONG Xin-yao, ZHANG Ren-he, LI Tim. Impacts of Atlantic sea surface temperature anomalies on Indo�CEast Asian summer monsoon�CENSO relationship [J]. Chin Sci Bull, 2010, 55(22): 2 458-2 468.
[5]	ZHENG Fei, ZHU Jiang, ZHANG Rong-hua, et al. Improved ENSO forecasts by assimilating sea surface temperature observations into an intermediate coupled model [J]. Adv Atmos Sci, 2006, 23(4): 615-624.
[6]	ZHENG F, ZHU J, ZHANG R H, et al. Ensemble hindcasts of SST anomalies in the tropical Pacific using an intermediate coupled model [J]. Geophys Res Lett, 2006, 33: L19604, doi:10.1029/2006GL026994.
[7]	ZHENG F, ZHU J, ZHANG R H. The impact of altimetry data on ENSO ensemble initializations and predictions [J]. Geophys Res Lett, 2007, 34: L13611, doi:10.1029/2007GL030451.
[8]	ZHENG F, ZHU J. Coupled assimilation for an intermediated coupled ENSO prediction model [J]. Ocean Dyn, 2010, 60: 1 061-1 073, doi: 10.1007/s10236-010-0307-1.
[9]	China Argo Real-time data Center. Advance in Implement of International Argo Program [J]. Argo Newsletter, 2006, 8: 21.
[10]	XU Jian-ping. Argo global oceanic observation exploration [M]. Beijing: China Ocean Press, 2002: 115.
[11]	XU Dong-feng, LIU Zeng-hong, XU Xiao-hua, et al. The influence of typhoon on sea surface salinity in the Warm Pool of the Northwest Pacific [J]. Acta Oceanol Sinica, 2005, 27(6): 1-7.
[12]	LIU Zeng-hong, XU Jiang-ping, Zhu Bo-kang, et al. Upper ocean response to tropical cyclones in northwestern Pacific during 2001-2004 by Argo data [J]. J Trop Oceanogr, 2006, 25(1): 1-8.
[13]	PAN Aai-jun, LIU Qin-yu. Mesoscale eddy effects on the wintertime vertical mixing in the formation region of the North Pacific subtropical mode water [J]. Chin Sci Bull, 2005, 50(1): 1-8.
[14]	ZHANG Ren-He, LIU Yi-Min, YIN Yong-Hong, et al. Utilizing ARGO data to improve the ocean data assimilation and the relative physical processes in ZC ocean model [J]. Acta Meteorol Sinica, 2004, 6(5): 613-622.
[15]	LIU Yi-min, ZHANG Ren-he, YIN Yong-hong, et al. The application of Argo data to the global ocean data assimilation operational system of NCC [J]. Acta Meteorol Sinica, 2005, 19(3): 355-365.
[16]	ZHANG Ren-he, LI Qiang. Impact of Sea Temperature Variability of Tropical Oceans on East Asian Monsoon [J]. Chin J Meteorol, 2004, 30 (12): 22-26.
[17]	LIU Yi-min, LI Wei-jing, ZHANG Pei-qun. A global 4-dimensional ocean data assimilation system and the studies on its results in the tropic Pacific [J]. Acta Oceanol Sinica, 2005, 27(1): 27-35.
[18]	JIN Xiang-ze, ZHANG Xue-hong, ZHOU Tian-jun. Fundamental framework and experiments of the third Generation of IAP/LASG world ocean general circulation model [J]. Adv Atmos Sci, 1999, 16(2): 197-215.
[19]	JIA Xiao-long, CHEN Li-juan, LUO Jing-jia. Climate prediction experiment for tropical cyclone genesis frequency using the large-scale circulation forecast by a coupled global model[J]. J Trop Meteorol, 2014, 20(2): 103-111.
[20]	LI Yong-ping, LIANG Xu-dong, DENG Zhi-ying. Prediction of annual frequency of affecting tropical cyclone using the products of a hybrid coupled air-sea model [J]. J Trop Meteorol, 2001, 7(1): 63-68.
[21]	LI Qing-quan, ZHAO Zong-ci. Diagnostic analysis and verification of prediction of the tropical Pacific sea surface temperature anomalies during 1997- 1998 [J]. J Trop Meteorol，2001，7(2)：144-153.
[22]	LI Qing-quan, DING Yi-hui, ZHANG Pei-qun. Primary verification and assessment on the extra-seasonally predictive capability of a global atmospheric-oceanic coupled model in raining season [J]. Acta Meteorol Sinica, 2004, 62(6): 740-751.
[23]	YU Yong-qiang, ZHANG Xue-hong. Air-sea flux anomaly coupling scheme. Study on dynamical model for short-term climate prediction operation [M]. Beijing: China Meteorological Press, 2000, 201-207.
[24]	YU Yong-qiang, ZHENG Wei-peng, ZHANG Xue-hong, et al. LASG coupled climate system model FGCM-1.0 [J]. Chin J Geophys, 2007, 50(6): 1 677-1 687.
[25]	LIU Hai-long, ZHANG Xue-hong, LI Wei, et al. An eddy-permitting oceanic general circulation model and its preliminary evaluations [J]. Adv Atmos Sci, 2004, 21: 675-690.
[26]	YUE Cai-jun, LU Wei-song, LI Qing-quan. The impact of initial forced wind on the predictability of the Zebiak-Cane coupled ocean-atmosphere model [J]. J Trop Meteorol, 2006, 12(1): 67-75.
[27]	ZHANG Ren-he, YIN Yong-hong, LI Qing-quan, et al. Utilizing AGRO data to improve the prediction of ENSO and short-term climate prediction of summer rainfall in China [J]. J Appl Meteorol Sci, 2006, 17(5): 538-547.
[28]	ZHANG Ren-he, ZHU Jiang, XU Jian-ping, et al. Argo global ocean data assimilation and its applications in short-term climate prediction and oceanic analysis [J]. Chin J Atmos Sci, 2013, 37 (2): 411-424.

IMPROVEMENT OF OCEAN DATA ASSIMILATION SYSTEM AND CLIMATE PREDICTION BY ASSIMILATING ARGO DATA

Abstract:

References

Get Citation+

Share Article

Article Metrics

Proportional views

Manuscript History

Online:

通讯作者: 陈斌, bchen63@163.com