MONTHLY AND SEASONAL NUMERICAL FORECASTS BY USING THE ANOMALY OCEAN-ATMOSPHERE COUPLED FILTERED MODEL

Chao Jiping; WangXiaoxi; Chen Yingyi; Wang Lizhi

doi:10.1007/BF02682548

Impact Factor: 5.8

Volume 3 Issue 2

Apr. 1986

Article Contents

Article > ADVANCES IN ATMOSPHERIC SCIENCES > 1986 > 3(2): 139-149

MONTHLY AND SEASONAL NUMERICAL FORECASTS BY USING THE ANOMALY OCEAN-ATMOSPHERE COUPLED FILTERED MODEL

1.
National Research Center for Marine Environmental Forecasts, State Oceanic Administration, Beijing,National Research Center for Marine Environmental Forecasts, State Oceanic Administration, Beijing,National Research Center for Marine Environmental Forecasts, State Oceanic Administration, Beijing,National Research Center for Marine Environmental Forecasts, State Oceanic Administration, Beijing

doi: 10.1007/BF02682548

Abstract
References
Related papers
PDF

Abstract:
Case experiments of monthly predictions of eight winter months during 1976－1977 and 1982－1983 El Nino events are performed by using a three-layer anomalous filtered model (AFM), in which transient Rossby waves are filtered. The results show that this model predicts successfully the large-scale patterns of the monthly mean surface temperature anomalies. The correlation coefficients between observations and predic-tions are basically higher than those of persistence predictions. By comparison with the anomalous general circulation model (AGCM) the AFM gives almost the identical results, but the computation time required for running the AFM is nearly 100 times less than that required for running the AGCM. It is also shown that the results of the three-layer model are better than those of the one-layer model. In the meanwhile, four seasonal forecasts are also earned out by using the same model. It seems that the AFM possesses potential ability in predicting large-scale circulation anomalies.On the basis of the works done during the last decade and of the results in this paper, the predicting ability of the AFM is summed up in the last section.
References

[1]	Liu Hui, Jin Xiangze, Zhang Xuehong, Wu Guoxiong, 1996: A Coupling Experiment of an Atmosphere and an Ocean Model with a Monthly Anomaly Exchange Schem, ADVANCES IN ATMOSPHERIC SCIENCES, 13, 133-146. doi: 10.1007/BF02656857
[2]	Yu Yongqiang, Yu Rucong, Zhang Xuehong, Liu Hailong, 2002: A Flexible Coupled Ocean-Atmosphere General Circulation Model, ADVANCES IN ATMOSPHERIC SCIENCES, 19, 169-190. doi: 10.1007/s00376-002-0042-8
[3]	Yu Yongqiang, Guo Yufu, 1995: The Interannual Variability of Climate in a Coupled Ocean-Atmosphere Model, ADVANCES IN ATMOSPHERIC SCIENCES, 12, 273-288. doi: 10.1007/BF02656977
[4]	Wu Aiming, Ni Yunqi, 1999: A Hybrid Coupled Ocean-Atmosphere Model and ENSO Prediction Study, ADVANCES IN ATMOSPHERIC SCIENCES, 16, 405-418. doi: 10.1007/s00376-999-0019-y
[5]	Liu Shikuo, He Anguo, 1991: A Simple Quasi-Geostrophic Coupled Ocean-Atmosphere Model, ADVANCES IN ATMOSPHERIC SCIENCES, 8, 257-271. doi: 10.1007/BF02919608
[6]	Shaowu BAO, Lian XIE, Sethu RAMAN, 2004: A Numerical Study of a TOGA-COARE Squall-Line Using a Coupled Mesoscale Atmosphere-Ocean Model, ADVANCES IN ATMOSPHERIC SCIENCES, 21, 708-716. doi: 10.1007/BF02916368
[7]	LIU Zhengyu, WU Shu, ZHANG Shaoqing, LIU Yun, RONG Xinyao, , 2013: Ensemble Data Assimilation in a Simple Coupled Climate Model: The Role of Ocean-Atmosphere Interaction, ADVANCES IN ATMOSPHERIC SCIENCES, 30, 1235-1248. doi: 10.1007/s00376-013-2268-z
[8]	ZHANG Rong-Hua, 2015: A Hybrid Coupled Model for the Pacific Ocean-Atmosphere System. Part I: Description and Basic Performance, ADVANCES IN ATMOSPHERIC SCIENCES, 32, 301-318. doi: 10.1007/s00376-014-3266-5
[9]	Junya HU, Rong-Hua ZHANG, Chuan GAO, 2019: A Hybrid Coupled Ocean-Atmosphere Model and Its Simulation of ENSO and Atmospheric Responses, ADVANCES IN ATMOSPHERIC SCIENCES, 36, 643-657. doi: 10.1007/s00376-019-8197-8
[10]	LI Jianglong, ZHANG Xuehong, YU Yongqiang, DAI Fushan, 2004: Primary Reasoning behind the Double ITCZ Phenomenon in a Coupled Ocean-Atmosphere General Circulation Model, ADVANCES IN ATMOSPHERIC SCIENCES, 21, 857-867. doi: 10.1007/BF02915588
[11]	LIU Qinyu, WEN Na, YU Yongqiang, 2006: The Role of the Kuroshio in the Winter North Pacific Ocean-Atmosphere Interaction: Comparison of a Coupled Model and Observations, ADVANCES IN ATMOSPHERIC SCIENCES, 23, 181-189. doi: 10.1007/s00376-006-0181-4
[12]	YU Yongqiang, ZHANG Xuehong, GUO Yufu, 2004: Global Coupled Ocean-Atmosphere General Circulation Models in LASG/IAP, ADVANCES IN ATMOSPHERIC SCIENCES, 21, 444-455. doi: 10.1007/BF02915571
[13]	Guo Yufu, Chao Jiping, 1984: SIMPLIFIED DYNAMICAL ANOMALY MODEL FOR LONG-RANGE NUMERICAL FORECASTS, ADVANCES IN ATMOSPHERIC SCIENCES, 1, 30-52. doi: 10.1007/BF03187614
[14]	ZHOU Tianjun, YU Yongqiang, LIU Hailong, LI Wei, YOU Xiaobao, ZHOU Guangqing, 2007: Progress in the Development and Application of Climate Ocean Models and Ocean-Atmosphere Coupled Models in China, ADVANCES IN ATMOSPHERIC SCIENCES, 24, 1109-1120. doi: 10.1007/s00376-007-1109-3
[15]	Peter C. Chu, Chen Yuchun, Lu Shihua, 2001: Evaluation of Haney-Type Surface Thermal Boundary Conditions Using a Coupled Atmosphere and Ocean Model, ADVANCES IN ATMOSPHERIC SCIENCES, 18, 355-375. doi: 10.1007/BF02919315
[16]	Boyin HUANG, ZHU Jiang, YANG Haijun, 2014: Mechanisms of Atlantic Meridional Overturning Circulation (AMOC) Variability in a Coupled Ocean-Atmosphere GCM, ADVANCES IN ATMOSPHERIC SCIENCES, 31, 241-251. doi: 10.1007/s00376-013-3021-3
[17]	Bueh Cholaw, Ji Liren, 1999: The Ocean-Atmosphere Coupled Regimes and East Asian Winter Monsoon (EAWM) Activity, ADVANCES IN ATMOSPHERIC SCIENCES, 16, 91-106. doi: 10.1007/s00376-999-0006-3
[18]	Zhong Qing, Ji Liren, 1992: A Further Study on an Extended Nonlinear Ocean-Atmosphere Coupled Hydrodynamic Characteristic System and the Abrupt Feature of ENSO Events, ADVANCES IN ATMOSPHERIC SCIENCES, 9, 131-146. doi: 10.1007/BF02657504
[19]	LIU Qinyu, WU Shu, YANG Jianling, HU Haibo, HU Ruijin, LI Lijuan, 2006: A Review of Ocean-Atmosphere Interaction Studies in China, ADVANCES IN ATMOSPHERIC SCIENCES, 23, 982-991. doi: 10.1007/s00376-006-0982-5
[20]	Zhou Guangqing, Zeng Qingcun, 2001: Predictions of ENSO with a Coupled Atmosphere-Ocean General Circulation Model, ADVANCES IN ATMOSPHERIC SCIENCES, 18, 587-603. doi: 10.1007/s00376-001-0047-8

PDF

Get Citation+

Export:

Article Metrics

Article Views: 1197 Times

PDF downloads: 1114 Times

Cited by: Times

Proportional views

Manuscript History

Manuscript received: 10 April 1986

Manuscript revised: 10 April 1986

通讯作者: 陈斌, bchen63@163.com

1.
沈阳化工大学材料科学与工程学院沈阳 110142

MONTHLY AND SEASONAL NUMERICAL FORECASTS BY USING THE ANOMALY OCEAN-ATMOSPHERE COUPLED FILTERED MODEL

1. National Research Center for Marine Environmental Forecasts, State Oceanic Administration, Beijing,National Research Center for Marine Environmental Forecasts, State Oceanic Administration, Beijing,National Research Center for Marine Environmental Forecasts, State Oceanic Administration, Beijing,National Research Center for Marine Environmental Forecasts, State Oceanic Administration, Beijing

Manuscript received: 1986-04-10
Manuscript revised: 1986-04-10

Abstract: Case experiments of monthly predictions of eight winter months during 1976－1977 and 1982－1983 El Nino events are performed by using a three-layer anomalous filtered model (AFM), in which transient Rossby waves are filtered. The results show that this model predicts successfully the large-scale patterns of the monthly mean surface temperature anomalies. The correlation coefficients between observations and predic-tions are basically higher than those of persistence predictions. By comparison with the anomalous general circulation model (AGCM) the AFM gives almost the identical results, but the computation time required for running the AFM is nearly 100 times less than that required for running the AGCM. It is also shown that the results of the three-layer model are better than those of the one-layer model. In the meanwhile, four seasonal forecasts are also earned out by using the same model. It seems that the AFM possesses potential ability in predicting large-scale circulation anomalies.On the basis of the works done during the last decade and of the results in this paper, the predicting ability of the AFM is summed up in the last section.