Analyzing Long-Term Records of Global Average Sea Level Change Using ARIMA Model
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Asian Institute of Research, Journal Publication, Journal Academics, Education Journal, Asian Institute
Asian Institute of Research, Journal Publication, Journal Academics, Education Journal, Asian Institute

Economics and Business

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asian institute research, jeb, journal of economics and business, economics journal, accunting journal, business journal, managemet journal
asian institute research, jeb, journal of economics and business, economics journal, accunting journal, business journal, managemet journal
asian institute research, jeb, journal of economics and business, economics journal, accunting journal, business journal, managemet journal
asian institute research, jeb, journal of economics and business, economics journal, accunting journal, business journal, managemet journal
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Published: 12 May 2020

Analyzing Long-Term Records of Global Average Sea Level Change Using ARIMA Model

Yeong Nain Chi

University of Maryland Eastern, USA

asian institute research, jeb, journal of economics and business, economics journal, accunting journal, business journal, management journal

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doi

10.31014/aior.1992.03.02.230

Pages: 672-681

Keywords: Sea Level Rise, Long–Term Records, Time Series Analysis, ARIMA

Abstract

The purpose of this study was to demonstrate the role of time series model in predicting process and to pursue analysis of time series data using long-term records of global average sea level change from 1880 to 2013 extracted from the U.S. Environmental Protection Agency using data from Commonwealth Scientific and Industrial Research Organization, 2015. Following the Box–Jenkins method, ARIMA(0,1,1,) model was the best fitted model in prediction for the data, Global Average Absolute Sea Level Change, 1880-2013, in this study. Forecasting process with ARIMA(0,1,1) model for prediction indicated global average sea level change at a constant increasing rate in the short-term. Understanding past sea level is important for the analysis of current and future sea level changes. In order to sustain these observations, research programs utilizing the resulting data should be able to significantly improve our understanding and narrow projections of future sea level rise and variability.

References

  1. Bolin, D., Guttorp, P., Januzzi1, A., Jones1, D., Novak1, M., Podschwit, H., Richardson, L., S¨arkk¨a, A., Sowder, C., & Zimmerman, A. (2015). Statistical prediction of global sea level from global temperature. Statistica Sinica, 25, 351-367. doi: 10.5705/ss.2013.222w

  2. Box, G. E. P., & Jenkins, G. M. (1970). Time series analysis: forecasting and control. Holden-Day, San Francisco.

  3. Box, G. E. P., Jenkins, G. M., Reinsel, G. C., & Ljung, G. M. (2016). Time series analysis: forecasting and control(5thed.). Hoboken, N.J.:  John Wiley and Sons Inc.

  4. Cazenave, A., & Llovel, W. (2010). Contemporary sea level rise. Annual Review of Marine Science, 2, 145-173. doi: 10.1146/annurev-marine-120308-081105.

  5. Cazenave, A., & Cozannet, G. Le. (2013). Sea level rise and its coastal impacts. Earth’s Future, 2, 15–34, doi:10.1002/2013EF000188.

  6. Church, J. A., White, N. J., Coleman, R., Lambeck, K., & Mitrovica, J.X. (2004). Estimates of the regional distribution of sea level rise over the 1950–2000 period. Journal of Climate, 17(13), 2609-2625. http://hdl.handle.net/102.100.100/189020?index=1

  7. Church, J. A., & White, N. J. (2006). A 20thcentury acceleration in global sea-level rise. Geophysical Research Letters, 33, L01602, 1-4. doi:10.1029/2005GL024826

  8. Church, J. A., White, N. J., Aarup, T., Wilson, W. S., Woodworth, P. L., Domingues, C. M., Hunter, J. R., &d Lambeck, K. (2008). Understanding global sea levels: past, present and future. Sustainability Science, 3, 9-22. doi: 10.1007/s11625-008-0042-4

  9. Church, J. A., & White, N. J. (2011). Sea-level rise from the late 19thto the early 21stcentury. Surveys in Geophysics, 32, 585-602. doi:10.1007/s10712-011-9119-1

  10. Foster, G., & Brown, P. T. (2014). Time and tide: analysis of sea level time series. Climate Dynamics, 45(1-2), 291-308. doi:10.1007/s00382-014-2224-3

  11. Haasnoot, M., Kwadijk, J., Alphen, J. van, Bars, D. Le, Hurk, B. van den, Diermanse, F., Spek, A. van der, Essink, G. O., Delsman, J.,& Mens, M. (2020). Adaptation to uncertain sea-level rise; how uncertainty in Antarctic mass-loss impacts the coastal adaptation strategy of the Netherlands. Environmental Research Letters, 15, 034007, 1-15. doi.org/10.1088/1748-9326/ab666c

  12. Horton, B. P., Kopp, R. E., Garner, A. J., Hay, C. C., Khan, N. S., Roy, K., & Shaw, T. A. (2018). Mapping sea-level change in time, space, and probability. Annual Review of Environment and Resources, 43, 481-521.doi.org/10.1146/annurev-environ-102017-025826

  13. IPCC, (2014). Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, R.K. Pachauri and L.A. Meyer (eds.)]. IPCC, Geneva, Switzerland, 151 pp.Retrieved from: https://www.ipcc.ch/report/ar5/syr/

  14. Kulp, S. A., & Strauss, B. H. (2019). New elevation data triple estimates of global vulnerability to sea-level rise and coastal flooding. Nature Communications, 10:4844, 1-12. doi.org/10.1038/s41467-019-12808-z

  15. Ljung, G. M., & Box, G. E. O. (1978). On a measure of lack of fit in time series models. Biometrika, 65(2), 297-303.doi: 10.2307/2335207

  16. Montgomery, D. C., Jennings, C. L., & Kulahci, M. (2008). Introduction to time series analysis and forecasting. Hoboken, N.J.: John Wiley & Sons. Inc.

  17. Srivastava, P. K., Islam, T., Singh, S. K., Petropoulos, G. P., Gupta, M., & Dai, Q. (2016). Forecasting Arabian sea level rise using exponential smoothing state space models and ARIMA from TOPEX and Jason satellite radar altimeter data. Meteorological Applications, 23, 633-639. doi:10.1002/met.1585

  18. U.S. Global Change Research Program (USGCRP), (2017). Climate science special report: Fourth National Climate Assessment, Volume I. [Wuebbles, D.J., D.W. Fahey, K.A. Hibbard, D.J. Dokken, B.C. Stewart, and T.K. Maycock (eds.)]. U.S. Global Change Research Program, Washington, DC, USA, 470 pp. Retrieved from: https://science2017.globalchange.gov/

  19. Visser, H., Dangendorf, S., & Petersen, A. C. (2015). A review of trend models applied to sea level data with reference to the “acceleration-deceleration debate”. Journal of Geophysical Research: Oceans, 120(6), 3873-3895. doi:10.1002/2015JC010716

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