Araştırma Makalesi
Yıl 2020,
Cilt: 5 Sayı: 1, 33 - 41, 01.02.2020
Öz
Kaynakça
- Avşar N.B., Kutoglu S.H., Erol B., Jin S.G. (2015). Sea level changes in the Black Sea using satellite altimetry and tide-gauge observations. Proceedings of the 26th IUGG General Assembly, Prag, Czech Republic.
- Cazenave A., Dieng H.B., Meyssignac B., von Schuckmann K., Decharme B. (2014). The rate of sealevel rise. Nature Climate Change, 4(5), pp.358–361.
- Ghil M., Allen R. M., Dettinger M.D., Ide K., Kondrashov D., Mann M.E., Robertson A.W., Saunders A., Tian Y., Varadi F. and Yiou P. (2002). Advanced spectral methods for climatic time series. Reviews of Geophysics, 40, pp. 1-41.
- Golyandina N. (2010). On the choice of parameters in singular spectrum analysis and related subspace-based methods. Statistics and Its Interface, 3,pp. 259-279.
- Golyandina N., Nekrutkin V., Zhigljavsky A. (2001). Analysis of time series structure: SSA and related techniques. Chapman & Hall/CRC, Boca Raton.
- Golyandina N., Zhigljavsky, A. (2013). Singular spectrum analysis for time series. Springer, doi: 10.1007/978-3-642-34913-3.
- Goriacikin I.N., Ivanov V.A. (2006). Black Sea Level: Past, Present, Future, (in Russian). EKOCI-Gidrofizica, Sevastopol,210.
- Hassani H. (2007). Singular spectrum analysis: methodology and comparison. Journal of Data Science, 5(2), pp.239-257.
- Hassani H., Heravi S., Zhigljavsky A. (2009). Forecasting European industrial production with singular spectrum analysis. International Journal of Forecasting, 25(1),pp. 103-118.
- Hassani H., Thomakos D. (2010). A review on singular spectrum analysis for economic and financial time series. Statistics and Its Interface, 3, pp. 377-397.
- Karaca M., Ünal Y.S. (2003). Potential ımplications of accelerated sea-level rise for Turkey. Journal Coastal Research, 24, pp. 288-298.
- Khelifa S., Gourine B., Rami A., Taibi H. (2016). Assessment of nonlinear trends and seasonal variations in global sea level using singular spectrum analysis and wavelet multiresolution analysis. Arabian Journal of Geosciences, 9:560, doi: 10.1007/s12517-016-2584-6.
- Kubryakov A.A., Stanichny S. (2013). The Black Sea level trends from tide gages and satellite altimetry. Russian Meteorology and Hydrology, 38(5), doi: 10.3103/S1068373913050051.
- Moreno S.R., Coelho L.D.S. (2018). Wind speed forecasting approach based on singular spectrum analysis and adaptive neuro fuzzy ınference system. Renewable Energy, 126, pp. 736-754.
- Nacef L., Bachari N.E.I., Bouda A. and Boubnia R. (2016). Variability and decadal evolution of temperature and salinity in the Mediterranean sea surface. International Journal of Engineering and Geosciences, 1, pp. 24-33.
- Osmanzade A. (2017). Singular spectrum analysis forecasting for financial time series. Master Thesis, University of Tartu, Tartu.
- Yilmaz M., Turgut B., Gullu M., Yilmaz I. (2016). Evaluation of recent global geopotential models by GNSS/Levelling data: internal Aegean region. International Journal of Engineering and Geosciences,1, pp.18-223.
- URL-1 https://tudes.harita.gov.tr/tudesportal/Hakkında.aspc.
- URL 2- https://www.psmsl.org/data/ Vigo I., Garcia D., Chao B.F. (2005). Change of sea level trend in the Mediterranean and Black seas. Journal of Marine Research, 63, pp. 1085–1100.
Yıl 2020,
Cilt: 5 Sayı: 1, 33 - 41, 01.02.2020
Öz
The mean sea level has been continuously increasing since the end of the 19th century and will continue to increase in the 21st century. The Intergovernmental Panel on Climate Change (IPCC) states that the sea level will rise by 40-60 cm until 2100. This situation will lead to social and economic problems, especially in coastal areas. For this reason, studies on sea level determination have great importance in our country. In this paper, we used the singular spectrum analysis (SSA) to investigate mean sea level variability along the coasts of the Black Sea, which is an intercontinental inland sea. This study aimed to determine the trend in sea level change along the coasts of the Black Sea over time. The mean sea level data from 10 tide gauge stations (Amasra, Batumi, Bourgas, Constantza, Igneada, Poti, Sevastapol, Trabzon II, Tuapse and Varna) are analyzed in this study. The mean sea level data were obtained from the Permanent Service for Mean Sea Level (PSMSL). SSA was applied to the mean sea level observations at tide gauges stations, and the results were interpreted. According to the analysis results, there are increasing trends at the Batumi, Poti, Tuapse, Constantza, Sevastopol and Varna stations. The obtained trend of Bourgas station is not significant. There is The results of the Amasra, Igneada and Trabzon II tide gauge stations were inadequate in interpreting any change. There were no trends at these stations. Close eigenvalues were computed from the mean sea level at the tide gauge stations. This situation shows that there is a dominant seasonal component in the time series.
Anahtar Kelimeler
Black Sea Mean Sea Level Tide Gauge Singular Spectrum Analysis
Kaynakça
- Avşar N.B., Kutoglu S.H., Erol B., Jin S.G. (2015). Sea level changes in the Black Sea using satellite altimetry and tide-gauge observations. Proceedings of the 26th IUGG General Assembly, Prag, Czech Republic.
- Cazenave A., Dieng H.B., Meyssignac B., von Schuckmann K., Decharme B. (2014). The rate of sealevel rise. Nature Climate Change, 4(5), pp.358–361.
- Ghil M., Allen R. M., Dettinger M.D., Ide K., Kondrashov D., Mann M.E., Robertson A.W., Saunders A., Tian Y., Varadi F. and Yiou P. (2002). Advanced spectral methods for climatic time series. Reviews of Geophysics, 40, pp. 1-41.
- Golyandina N. (2010). On the choice of parameters in singular spectrum analysis and related subspace-based methods. Statistics and Its Interface, 3,pp. 259-279.
- Golyandina N., Nekrutkin V., Zhigljavsky A. (2001). Analysis of time series structure: SSA and related techniques. Chapman & Hall/CRC, Boca Raton.
- Golyandina N., Zhigljavsky, A. (2013). Singular spectrum analysis for time series. Springer, doi: 10.1007/978-3-642-34913-3.
- Goriacikin I.N., Ivanov V.A. (2006). Black Sea Level: Past, Present, Future, (in Russian). EKOCI-Gidrofizica, Sevastopol,210.
- Hassani H. (2007). Singular spectrum analysis: methodology and comparison. Journal of Data Science, 5(2), pp.239-257.
- Hassani H., Heravi S., Zhigljavsky A. (2009). Forecasting European industrial production with singular spectrum analysis. International Journal of Forecasting, 25(1),pp. 103-118.
- Hassani H., Thomakos D. (2010). A review on singular spectrum analysis for economic and financial time series. Statistics and Its Interface, 3, pp. 377-397.
- Karaca M., Ünal Y.S. (2003). Potential ımplications of accelerated sea-level rise for Turkey. Journal Coastal Research, 24, pp. 288-298.
- Khelifa S., Gourine B., Rami A., Taibi H. (2016). Assessment of nonlinear trends and seasonal variations in global sea level using singular spectrum analysis and wavelet multiresolution analysis. Arabian Journal of Geosciences, 9:560, doi: 10.1007/s12517-016-2584-6.
- Kubryakov A.A., Stanichny S. (2013). The Black Sea level trends from tide gages and satellite altimetry. Russian Meteorology and Hydrology, 38(5), doi: 10.3103/S1068373913050051.
- Moreno S.R., Coelho L.D.S. (2018). Wind speed forecasting approach based on singular spectrum analysis and adaptive neuro fuzzy ınference system. Renewable Energy, 126, pp. 736-754.
- Nacef L., Bachari N.E.I., Bouda A. and Boubnia R. (2016). Variability and decadal evolution of temperature and salinity in the Mediterranean sea surface. International Journal of Engineering and Geosciences, 1, pp. 24-33.
- Osmanzade A. (2017). Singular spectrum analysis forecasting for financial time series. Master Thesis, University of Tartu, Tartu.
- Yilmaz M., Turgut B., Gullu M., Yilmaz I. (2016). Evaluation of recent global geopotential models by GNSS/Levelling data: internal Aegean region. International Journal of Engineering and Geosciences,1, pp.18-223.
- URL-1 https://tudes.harita.gov.tr/tudesportal/Hakkında.aspc.
- URL 2- https://www.psmsl.org/data/ Vigo I., Garcia D., Chao B.F. (2005). Change of sea level trend in the Mediterranean and Black seas. Journal of Marine Research, 63, pp. 1085–1100.
Toplam 19 adet kaynakça vardır.
Ayrıntılar
| Birincil Dil | İngilizce |
|---|---|
| Bölüm | Articles |
| Yazarlar | |
| Yayımlanma Tarihi | 1 Şubat 2020 |
| Yayımlandığı Sayı | Yıl 2020 Cilt: 5 Sayı: 1 |