LONG TERM VARIATIONS OF SIGNIFICANT WAVE HEIGHT AROUND INDONESIA SEAS

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1 International Journal of Civil Engineering and Technology (IJCIET) Volume 9, Issue 9, September 2018, pp , Article ID: IJCIET_09_09_089 Available online at ISSN Print: and ISSN Online: IAEME Publication Scopus Indexed LONG TERM VARIATIONS OF SIGNIFICANT WAVE HEIGHT AROUND INDONESIA SEAS Muhammad Zikra Ocean Engineering Department, Institut Teknologi Sepuluh Nopember , Kampus ITS, Keputih Surabaya, Indonesia ABSTRACT In this study, long term variations of significant wave height are studied using ERA-Interim reanalysis data from ECMWF (European Centre for Medium-Range Weather Forecasts) for 35 years period from in Indonesia Seas. The ERA- Interim reanalysis data provides wave height data with resolution of 0,750 x 0,750. This paper studied monthly variation in significant wave height by creating monthly data and taking the mean of those months over 35 years period. A statistical analysis of wave time series data has been performed to test the significance of trend during 35 years period. The results show that the mean significant wave height in the south of Java Sea show statistically significant increasing trend for all month. Key words: Wave Height, Indonesia Sea, ERA-Interim Cite this Article: Muhammad Zikra, Long Term Variations of Significant Wave Height around Indonesia Seas. International Journal of Civil Engineering and Technology, 9(9), 2018, pp INTRODUCTION Climate change has a significant impact on the wind and wave climate condition. Knowledge of wave climate change due to global warming is required for engineering purpose. Indonesia as an archipelago country, especially in coastal area is very vulnerable to climate change such as sea level rise, warmer ocean temperature and increased of wave height [1]. Therefore, understanding the long-term variations in the wave parameter is key element in for sustainable management both offshore and coastal activities. For example, marine transportation activities in Indonesia use significant wave height prediction or information to decrease accident at the sea. Data of significant wave height is used to calculate the probability of deck wetness according to several significant wave heights for some vessel [2]. The descriptions of wind effect of the sea surface also used by mariners for observing the condition of the sea (sea states). Beaufort scale represents the sea states based on the average wind speed calculation by report. ERA-Interim reanalysis data has used to analysis temporal variations in wind speed and significant wave height (SWH) in the eastern Arabian Seas by monsoonal cycle [3]. ERA-Interim is the latest global atmospheric reanalysis produced by the European Centre for Medium-Range Weather Forecasts editor@iaeme.com

2 Long Term Variations of Significant Wave Height around Indonesia Seas (ECMWF) (Dee et.al, 2011). Also, ERA-Interim data has proved a better spatial resolution than ERA 40 to analysis SWH at North Sea [4]. The objective of this study is to quantify the monthly variability of the wave climate at Indonesia Sea based on the significant wave height (SWH) obtained from ECMWF reanalysis ERA-Interim data for 35 years period ( ). Figure 1 Observations points in Indonesia seas 2. DATA Because long-term wave records based on in situ measurements are still limited in Indonesia Sea, in this study, long-term variation of significant wave height is studied using ERA-Interim reanalysis data from ECMWF (European Centre for Medium-Range Weather Forecasts) for 35 years period from The ERA-Interim reanalysis data provides significant wave height data with resolution of 0,750 x 0,750 [5]. The location of observation points in Indonesia seas are shown in the Figure 1 and Table 1. Table 1 Observation points Point Coordinate Location A N and E Malacca Strait B N and E Natuna sea, Riau Island C N and E Pacific Ocean D S and E Indian Ocean, Mentawai Island E S and E Sunda Strait F S and E Java Sea G S and E Flores Sea H S and E Banda Sea I S and 2.25 E South of Java Sea, Indian Ocean ERA-Interim reanalysis data are produced by European Centre for Medium Range Weather Forecast. ERA-Interim has built to reanalysis ERA-40 to show forecast and climate condition by satellite derived data of wind and wave [6][7]. WAVEWATCH III used by ERA-Interim to derive wind and wave data from sea surface temperature data collected by scatter meters and radio-meter of satellite. The result contains several parameter of wind (wind speed at 10 meter height) and wind direction every 30 minutes, significant wave height of sea and swell and wave period every 6 hours A statistical analysis of wave time series data by calculates monthly mean SWH for 35 years has been performed to find the trend pattern and the significance of trend during the editor@iaeme.com

3 Muhammad Zikra years period. Mann-Kendall test is used to evaluate the trend of time series data in terms of mean and maximum value for significant wave height. 3. RESULTS AND DISCUSSION In Indonesia, wave condition is influenced by the east monsoon and the west monsoon wind seasons [8]. Monsoon period that occurred in Indonesia is divided into four periods; there are the period of the Asian Monsoon (December-January-February), Transition Monsoon Australia (March- April-May), Monsoon Australia (June- July-August) and Transition Monsoon Asia (September- October-November). The condition of wave climate for Indonesia seas is shown in Fig. 2. Figure 2 showed the averaged of significant wave height (SWH) from January until December for 35 years period. In all year, the averaged of SWH over the Indonesian seas is between 0.3 to 2.4 m. The highest averaged of SWH is 2.4 m in the South of Java as shown in Table 2. In the Asian monsoon period (December to February), the averaged of SWH is between 0.5 to 2.4 m in height with corresponding period around 4.0 to 8.5 s. The highest averaged of SWH during this period is 2.4 m. In the month March, April and May, the heights of SWH are around 0.3 to 2.0 m in height with corresponding period around 4.0 to 9.0 s. In the Australian monsoon (June, July and August), the averaged of SWH is between 0.4 to 2.2 m in height with corresponding period around 3.9 to 9.1 s. The highest averaged of SWH during this period is 2.21 m. In the month September, October and November, the heights of SWH are around 0.3 to 2.3 m in height with corresponding period around 4.1 to 9.2 s Variation in significant wave height from Indian Ocean near south Java has the highest trend of mean SWH on January, 5.05 cm/years and it statically significant as shown in Table 6 and 7. The trends of monthly mean SWH in January also statically significant in Sunda Strait, Java Sea and Banda Sea. Indian and Pacific Ocean around Indonesia, have a positive value of monthly mean SWH trends in March, but only at Banda Sea and Indian Ocean near south Java show a statically significant trend. In April, Indian Ocean near south Java and Pacific Ocean have an upward trend of monthly mean SWH, but at Indian Ocean near west Sumatera show a decreasing trend. Natuna Sea and Flores Sea show a increasing trend from April to May. Indian Ocean and Pacific Ocean have a statically significant trend of monthly mean SWH on June. On July, monthly mean SWH trends in Java Sea show decreasing value become cm/years. Almost all monthly mean SWH trends in August show a decreasing value from July. The trend of mean monthly SWH at Indian Ocean near south Java is statically significant with the value 2.54 cm/years. The trends of monthly mean SWH have increase from August to September for all observation location, except in Flores Sea, the trend on September is lower than August with the value cm/years. Indian and Pacific Ocean have increasing trends of monthly mean SWH on October. On November, monthly mean SWH trends has increase at Indian Ocean near west Sumatera and decrease at Indian Ocean near south Java and both location show statistically significant trends. On December, monthly mean SWH trends are statistically insignificant for all observation location editor@iaeme.com

4 Long Term Variations of Significant Wave Height around Indonesia Seas Figure 2 Results of monthly variations of mean significant wave height (SWH) editor@iaeme.com

5 Muhammad Zikra Table 2 Monthly averaged significant wave height in Indonesian Sea Month Monthly Mean Significant Wave Height (m) A B C D E F G H I January 1,27 0,86 0,82 1,26 0,67 1,32 0,44 1,24 2,40 February 1,25 0,65 0,67 1,24 0,68 1,29 0,44 1,21 2,24 March 1,22 0,51 0,62 1,21 0,53 1,18 0,40 1,17 1,91 April 1,21 0,40 0,35 1,20 0,51 1,03 0,45 1,19 1,96 May 1,35 0,39 0,34 1,34 0,72 0,86 0,57 1,38 2,03 June 1,57 0,45 0,41 1,57 0,92 0,80 0,65 1,53 2,14 July 1,62 0,51 0,48 1,62 0,97 0,82 0,64 1,64 2,17 August 1,69 0,54 0,51 1,68 0,89 0,84 0,60 1,70 2,21 September 1,61 0,47 0,45 1,61 0,69 0,80 0,46 1,61 2,17 October 1,44 0,54 0,51 1,44 0,51 0,94 0,38 1,41 2,28 November 1,29 0,58 0,56 1,29 0,39 1,06 0,33 1,20 2,32 December 1,24 0,84 0,81 1,23 0,51 1,28 0,39 1,18 2,35 Table 3 Trend of monthly mean significant wave height during Month Monthly Mean SWH Trend (cm/years) A B C D E F G H I January February March April May June July August September October November December Table 4 Kendall significance test for SWH trend analysis in point Malacca Strait January February Not March Not April Not May Not June Not July Not August Not September Not October Not November Not December Not editor@iaeme.com

6 Long Term Variations of Significant Wave Height around Indonesia Seas Table 5 Kendall significance test for SWH trend analysis in point Natuna Sea January Not February Not March Not April May June Not July Not August Not September October November Not December Not Table 6 Kendall significance test for SWH trend analysis in point Pacific Ocean January February March April May June July August September October Not November December Not Table 7 Kendall significance test for SWH trend analysis in point Indian Ocean January Not February Not March Not April Not May Not June Not July Not August Not September Not October Not November Not December Not editor@iaeme.com

7 Muhammad Zikra Table 8 Kendall significance test for SWH trend analysis in point Sunda Strait January February Not March Not April Not May Not June Not July Not August Not September Not October Not November Not December Not Table 9 Kendall significance test for SWH trend analysis in point Java Sea January February March April May Not June July August September October November December Table 10 Kendall significance test for SWH trend analysis in point Flores Sea January Not February Not March Not April May June July Not August Not September Not October Not November Not December Not editor@iaeme.com

Long Term Variations of Significant Wave Height around Indonesia Seas Table 11 Kendall significance test for SWH trend analysis in point Banda Sea January 0.37 207 5250.00 2.843 1.65 February 0.

8 Long Term Variations of Significant Wave Height around Indonesia Seas Table 11 Kendall significance test for SWH trend analysis in point Banda Sea January February Not March April May Not June Not July August Not September October November December Not Table 12 Kendall significance test for SWH trend analysis in point Indian Ocean January Significant February Significant March Significant April Significant May Significant June Significant July Significant August Significant September Significant October Significant November Significant December Significant Figure 4 Example of variation of monthly means SWH in Indian Ocean near south of Java (Point I) editor@iaeme.com

9 Muhammad Zikra 4. CONCLUSIONS In this paper, long term variation of wave height around Indonesia Sea is presented. Wave climate data from ECMWF for 35 years period from is used in this study. The results show that long term variations in wave height have an associated pattern with monsoonal wind cycle. In addition, the mean significant wave height in the south of Java Sea show statistically significant increasing trend for all months from 1980 to Added, the trends of monthly mean significant wave height (SWH) are statically significant from January to December. ACKNOWLEDGEMENTS This research was funded by Lembaga Penelitian dan Pengabdian kepada Masyarakat, Institut Teknologi Sepuluh Nopember (LPPM ITS). REFERENCES [1] Zikra, M., Hashimoto, N., Mitsuyasu, K. & Sambodho, K., Monthly Variations of Global Wave Climate due to Global Warming, Jurnal Teknologi, 74(5), 2015, pp [2] Zikra, M., Suntoyo, Lukijanto Climate change impacts on Indonesian coastal areas. Procedia Earth and Planetary Science. 14. DOI: /j.proeps [3] Zaky, Moch., Putama, Ika., Kurniawan., Arif., Syarif., Rosihan., A.M. Wasito Initial Study on The Development of Minimum Bow Height Formula Indonesian Waterways Based on Probability of Deck Wetness. The 9 th International Conference on Marine Technology. [4] Shanas, P.R., Kumar, V. Sanil Temporal Variations in the Wind and Wave Climate at a Location in the Eastern Arabian Sea Based on ERA-Interim Re-Analysis Data. Natural Hazard and Earth System Sciences. 14: [5] Dee, D.P., Uppala. Simmons The ERA-Interim Re-Analysis: Configuration and Performance of The Data Assimilation System. Quarterly Journal of the Royal Meteorological Society. 137: [6] Tolman, Hendrik. L User Manual and System Documentation of WAVEWATCH III version Enviromental Modeling Center Marine Modeling and Analysis Branch. [7] Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N. and Vitart, F., " The ERA- Interim reanalysis: configuration and performance of the data assimilation system". Q.J.R. Meteorol. Soc., 137: doi: /qj.828. [8] Zikra M., A. Putika and Mukhtasor "Analysis of wave climate variations based on ERA-Interim Reanalysis data from 1980 to 2014 to support wave energy assessment in Indonesia". ARPN Journal of Engineering and Applied Sciences, Vol. 11, No. 2, pp editor@iaeme.com

Wave Climate Variations in Indonesia Based on ERA-Interim Reanalysis Data from 1980 to 2014

Wave Climate Variations in Indonesia Based on ERA-Interim Reanalysis Data from 1980 to 2014 Muhammad Zikra, a,* and Putika Ashfar b a) Department of Ocean Engineering, Institut Teknologi Sepuluh Nopember