|Table of Contents|

Sea Level Prediction Based on Time Series Model(PDF)

《南京师大学报（自然科学版）》[ISSN:1001-4616/CN:32-1239/N]

Issue:
2007年01期
Page:
117-121
Research Field:
地理学
Publishing date:

Info

Title:
Sea Level Prediction Based on Time Series Model
Author(s):
Yu Zhaoyuan; Yuan Linwang; Xie Zhiren; Sun Jian; Dong Huajun
Key Lab of Virtual Geographic Environment,Ministry of Education,Nanjing Normal University,Nanjing 210097,China
Keywords:
sea-level change;  time series model;  singular spectrum analysis ( SSA ) ;  auto-regressive (AR) model
PACS:
P731.3
DOI:
-
Abstract:
Analyzing the monthly average tidal records ofWusong tidal gauge station from 1955 to 2001, SSA ( singular spectrum analysis) , ratio average method and residual method are respectively used to ex tract the components of trends, cycles, and seasons. Usingmultip lication model to fit tidal records shows that the fitting series can be perfectly compared with origin series. UsingAR model to p redict the trends of tidal records of 1955～1996, then usingmultip lication model to p redict the sea-level changes of 1997～ 2001, and comparing p rediction resultswith the original data, we find that those two series are fairly com parable. Themaximum error of p rediction ofmonthly average tidal records and yearly average tidal records do not exceed ±10% and ±4%. It shows that time2seriesmodel p rovide an efficientway to p redict sea level changes

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Last Update: 2013-05-05