AN APPLICATION OF THE THRESHOLD AUTOREGRESSION PROCEDURE TO CLIMATE ANALYSIS AND FORECASTING

Shi Jiuen; Zhou Qinfang; Xiang Jingtian

doi:10.1007/BF02680052

Impact Factor: 3.9

Volume 3 Issue 1

Jan. 1986

Article Contents

Article > ADVANCES IN ATMOSPHERIC SCIENCES > 1986 > 3(1): 134-138

AN APPLICATION OF THE THRESHOLD AUTOREGRESSION PROCEDURE TO CLIMATE ANALYSIS AND FORECASTING

1.
Beijing Institute of Meteorology, Beijing,Beijing Meteorological Center, State Meteorological Administration, Beijing,Institute of Applied Mathematics, Academia Sinica, Beijing

doi: 10.1007/BF02680052

Abstract
References
Related papers
PDF

Abstract:
In this paper a nonlinear method of time series analysis-threshold autoregressive (TAR) model in discrete time is used. The TAR procedure consists of four parts: model building, statistical identification, parameter estimation and forecasting.The object of this study is to estimate monthly total precipitation of Shanghai and Beijing by using open loop TAR model. We can see that the trend of forecasting is in agreement with observations.
References

[1]	Linye SONG, Wansuo DUAN, Yun LI, Jiangyu MAO, 2016: A Timescale Decomposed Threshold Regression Downscaling Approach to Forecasting South China Early Summer Rainfall, ADVANCES IN ATMOSPHERIC SCIENCES, 33, 1071-7084. doi: 10.1007/s00376-016-5251-7
[2]	WANG Geli, YANG Peicai, LU Daren, 2004: On Spatiotemporal Series Analysis and Its Application to Predict the Regional Short Term Climate Process, ADVANCES IN ATMOSPHERIC SCIENCES, 21, 296-299. doi: 10.1007/BF02915717
[3]	John ABBOT, Jennifer MAROHASY, 2012: Application of Artificial Neural Networks to Rainfall Forecasting in Queensland, Australia, ADVANCES IN ATMOSPHERIC SCIENCES, 29, 717-730. doi: 10.1007/s00376-012-1259-9
[4]	Wang Shaowu, 1984: THE RHYTHM IN THE ATMOSPHERE AND OCEANS IN APPLICATION TO LONG-RANGE WEATHER FORECASTING, ADVANCES IN ATMOSPHERIC SCIENCES, 1, 7-29. doi: 10.1007/BF03187612
[5]	HUANG Yanyan, XUE Jishan, WAN Qilin, CHEN Zitong, DING Weiyu, ZHANG Chengzhong, 2013: Improvement of the Surface Pressure Operator in GRAPES and Its Application in Precipitation Forecasting in South China, ADVANCES IN ATMOSPHERIC SCIENCES, 30, 354-366. doi: 10.1007/s00376-012-1270-1
[6]	Shi Neng, Chen Jiyi, 1986: QUADRATIC DISCRIMINATION THROUGH ORTHOGONAL TRANSFORMATION AND ITS APPLICATION TO LONG-RANGE FORECASTING OF DROUGHT AND EXCESSIVE RAINFALL, ADVANCES IN ATMOSPHERIC SCIENCES, 3, 125-133. doi: 10.1007/BF02680051
[7]	CHOU Jieming, DONG Wenjie, FENG Guolin, 2010: Application of an Economy--Climate Model to Assess the Impact of Climate Change, ADVANCES IN ATMOSPHERIC SCIENCES, 27, 957-965. doi: 10.1007/s00376-009-8166-8
[8]	Jing WANG, Bin WANG, Juanjuan LIU, Yongzhu LIU, Jing CHEN, Zhenhua HUO, 2020: Application and Characteristic Analysis of the Moist Singular Vector in GRAPES-GEPS, ADVANCES IN ATMOSPHERIC SCIENCES, 37, 1164-1178. doi: 10.1007/s00376-020-0092-9
[9]	Yongqiang LIU, 2005: Land Breeze and Thermals: A Scale Threshold to Distinguish Their Effects, ADVANCES IN ATMOSPHERIC SCIENCES, 22, 889-902. doi: 10.1007/BF02918688
[10]	Keon Tae SOHN, Sun Min PARK, 2008: Guidance on the Choice of Threshold for Binary Forecast Modeling, ADVANCES IN ATMOSPHERIC SCIENCES, 25, 83-88. doi: 10.1007/s00376-008-0083-8
[11]	Vladimir A. Lobanov, 2001: Empirical-Statistical Methodology and Methods for Modeling and Forecasting of Climate Variability of Different Temporal Scales, ADVANCES IN ATMOSPHERIC SCIENCES, 18, 844-863.
[12]	WANG Pengfei, HUANG Gang, WANG Zaizhi, 2006: Analysis and Application of Multiple-Precision Computation and Round-off Error for Nonlinear Dynamical Systems, ADVANCES IN ATMOSPHERIC SCIENCES, 23, 758-766. doi: 10.1007/s00376-006-0758-y
[13]	SHOU Yixuan, LI Shenshen, SHOU Shaowen, ZHAO Zhongming, 2006: Application of a Cloud-Texture Analysis Scheme to the Cloud Cluster Structure Recognition and Rainfall Estimation in a Mesoscale Rainstorm Process, ADVANCES IN ATMOSPHERIC SCIENCES, 23, 767-774. doi: 10.1007/s00376-006-0767-x
[14]	LI Zhen, YAN Zhongwei, 2010: Application of Multiple Analysis of Series for Homogenization to Beijing Daily Temperature Series (1960--2006), ADVANCES IN ATMOSPHERIC SCIENCES, 27, 777-787. doi: 10.1007/s00376-009-9052-0
[15]	Yan GAO, Jiali FENG, Xin XIA, Jian SUN, Yulong MA, Dongmei CHEN, Qilin WAN, 2023: Multi-scale Incremental Analysis Update Scheme and Its Application to Typhoon Mangkhut (2018) Prediction, ADVANCES IN ATMOSPHERIC SCIENCES, 40, 95-109. doi: 10.1007/s00376-022-1425-7
[16]	Qiujie REN, Mu MU, Guodong SUN, Qiang WANG, 2023: A New Sensitivity Analysis Approach Using Conditional Nonlinear Optimal Perturbations and Its Preliminary Application, ADVANCES IN ATMOSPHERIC SCIENCES, 40, 285-304. doi: 10.1007/s00376-022-1445-3
[17]	Myoung-Hwan AHN, Mee-Ja KIM, Chu-Yong CHUNG, Ae-Sook SUH, 2003: Operational Implementation of the ATOVS Processing Procedure in KMA and Its Validation, ADVANCES IN ATMOSPHERIC SCIENCES, 20, 398-414. doi: 10.1007/BF02690798
[18]	Jeong-Hyeong LEE, Byungsoo KIM, Keon-Tae SOHN, Won-Tae KOWN, Seung-Ki MIN, 2005: Climate Change Signal Analysis for Northeast Asian Surface Temperature, ADVANCES IN ATMOSPHERIC SCIENCES, 22, 159-171. doi: 10.1007/BF02918506
[19]	YAN Zhongwei, Phil D. JONES, 2008: Detecting Inhomogeneity in Daily Climate Series Using Wavelet Analysis, ADVANCES IN ATMOSPHERIC SCIENCES, 25, 157-163. doi: 10.1007/s00376-008-0157-7
[20]	Zhao Ming, Zeng Xinmin, 2002: A Theoretical Analysis on the Local Climate Change Induced by the Change of Landuse, ADVANCES IN ATMOSPHERIC SCIENCES, 19, 45-63. doi: 10.1007/s00376-002-0033-9

PDF

Get Citation+

Export:

Article Metrics

Article Views: 1343 Times

PDF downloads: 1047 Times

Cited by: Times

Proportional views

Manuscript History

Manuscript received: 10 January 1986

Manuscript revised: 10 January 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

AN APPLICATION OF THE THRESHOLD AUTOREGRESSION PROCEDURE TO CLIMATE ANALYSIS AND FORECASTING

1. Beijing Institute of Meteorology, Beijing,Beijing Meteorological Center, State Meteorological Administration, Beijing,Institute of Applied Mathematics, Academia Sinica, Beijing

Manuscript received: 1986-01-10
Manuscript revised: 1986-01-10

Abstract: In this paper a nonlinear method of time series analysis-threshold autoregressive (TAR) model in discrete time is used. The TAR procedure consists of four parts: model building, statistical identification, parameter estimation and forecasting.The object of this study is to estimate monthly total precipitation of Shanghai and Beijing by using open loop TAR model. We can see that the trend of forecasting is in agreement with observations.