scholarly journals Sea level trend and variability around the Peninsular Malaysia

2014 ◽  
Vol 11 (3) ◽  
pp. 1519-1541 ◽  
Author(s):  
Q. H. Luu ◽  
P. Tkalich ◽  
T. W. Tay
Keyword(s):  
Indian Ocean ◽  
Sea Level ◽  
Satellite Altimetry ◽  
Tide Gauge ◽  
Peninsular Malaysia ◽  
Sea Level Anomalies ◽  
The Indian Ocean ◽  
Sea Level Trend ◽  
Malacca Strait

Abstract. Peninsular Malaysia is bounded from the west by Malacca Strait and the Andaman Sea both connected to the Indian Ocean, and from the east by South China Sea being largest marginal sea in the Pacific Basin. Resulting sea level along Peninsular Malaysia coast is assumed to be governed by various regional phenomena associated with the adjacent parts of the Indian and Pacific Oceans. At annual scale, sea level anomalies (SLAs) are generated by the Asian monsoon; interannual sea level variability is determined by the El Niño–Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD); while long-term sea level trend is related to global climate change. To quantify the relative impacts of these multi-scale phenomena on sea level trend and variability around the Peninsular Malaysia, long-term tide gauge record and satellite altimetry are used. During 1984–2011, relative sea level rise (SLR) rates in waters of Malacca Strait and eastern Peninsular Malaysia are found to be 2.4 ± 1.6 mm yr−1 and 2.7 ± 1.0 mm yr−1, respectively. Allowing for corresponding vertical land movements (VLM; 0.8 ± 2.6 mm yr−1 and 0.9 ± 2.2 mm yr−1), their absolute SLR rates are 3.2 ± 4.2 mm yr−1 and 3.6 ± 3.2 mm yr−1, respectively. For the common period 1993–2009, absolute SLR rates obtained from both tide gauge and satellite altimetry in Peninsular Malaysia are similar; and they are slightly higher than the global tendency. It further underlines that VLM should be taken into account to get better estimates of SLR observations. At interannual scale, ENSO affects sea level over the Malaysian coast in the range of ±5 cm with a very high correlation. Meanwhile, IOD modulates sea level anomalies mainly in the Malacca Strait in the range of ±2 cm with a high correlation coefficient. Interannual regional sea level drops are associated with El Niño events and positive phases of the IOD index; while the rises are correlated with La Niña episodes and the negative periods of the IOD index. Seasonally, SLAs are mainly monsoon-driven, in the order of 10–25 cm. Geographically, sea level responds differently to the monsoon: two cycles per year are observed in the Malacca Strait, presumably due to South Asian-Indian Monsoon; whereas single annual cycle is noted along east coast of Peninsular Malaysia, mostly due to East Asian-Western Pacific Monsoon. These results imply that a narrow topographic constriction in Singapore Strait may separate different modes of annual and interannual sea level variability along coastline of Peninsular Malaysia.

scholarly journals Sea level trend and variability around Peninsular Malaysia

Ocean Science ◽  
2015 ◽  
Vol 11 (4) ◽  
pp. 617-628 ◽  
Author(s):  
Q. H. Luu ◽  
P. Tkalich ◽  
T. W. Tay
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Satellite Altimetry ◽  
Tide Gauge ◽  
Peninsular Malaysia ◽  
Tide Gauges ◽  
Tide Gauge Records ◽  
Regional Sea Level ◽  
Malacca Strait ◽  
Singapore Strait

Abstract. Sea level rise due to climate change is non-uniform globally, necessitating regional estimates. Peninsular Malaysia is located in the middle of Southeast Asia, bounded from the west by the Malacca Strait, from the east by the South China Sea (SCS), and from the south by the Singapore Strait. The sea level along the peninsula may be influenced by various regional phenomena native to the adjacent parts of the Indian and Pacific oceans. To examine the variability and trend of sea level around the peninsula, tide gauge records and satellite altimetry are analyzed taking into account vertical land movements (VLMs). At annual scale, sea level anomalies (SLAs) around Peninsular Malaysia on the order of 5–25 cm are mainly monsoon driven. Sea levels at eastern and western coasts respond differently to the Asian monsoon: two peaks per year in the Malacca Strait due to South Asian–Indian monsoon; an annual cycle in the remaining region mostly due to the East Asian–western Pacific monsoon. At interannual scale, regional sea level variability in the range of ±6 cm is correlated with El Niño–Southern Oscillation (ENSO). SLAs in the Malacca Strait side are further correlated with the Indian Ocean Dipole (IOD) in the range of ±5 cm. Interannual regional sea level falls are associated with El Niño events and positive phases of IOD, whilst rises are correlated with La Niña episodes and negative values of the IOD index. At seasonal to interannual scales, we observe the separation of the sea level patterns in the Singapore Strait, between the Raffles Lighthouse and Tanjong Pagar tide stations, likely caused by a dynamic constriction in the narrowest part. During the observation period 1986–2013, average relative rates of sea level rise derived from tide gauges in Malacca Strait and along the east coast of the peninsula are 3.6±1.6 and 3.7±1.1 mm yr−1, respectively. Correcting for respective VLMs (0.8±2.6 and 0.9±2.2 mm yr−1), their corresponding geocentric sea level rise rates are estimated at 4.4±3.1 and 4.6±2.5 mm yr−1. The geocentric rates are about 25 % faster than those measured at tide gauges around the peninsula; however, the level of uncertainty associated with VLM data is relatively high. For the common period between 1993 and 2009, geocentric sea level rise values along the Malaysian coast are similar from tide gauge records and satellite altimetry (3.1 and 2.7 mm yr−1, respectively), and arguably correspond to the global trend.

scholarly journals Developing China’s Indian Ocean Strategy: Rationale and Prospects

2017 ◽  
Vol 03 (04) ◽  
pp. 481-497 ◽  
Author(s):  
Jiacheng Li
Keyword(s):  
United States ◽  
Indian Ocean ◽  
The United States ◽  
Adverse Conditions ◽  
Maritime Silk Road ◽  
Strategic Goals ◽  
The Indian Ocean ◽  
Strategic Perspective ◽  
Malacca Strait

From the strategic perspective, the Indian Ocean has been increasingly important to China’s foreign trade and energy security. China has been faced with a deepening dilemma in the Malacca Strait for years, in large part due to the strategic pressure from the United States and India. Under its new initiative to construct the “21st Century Maritime Silk Road,” China needs to develop a long-term, security-oriented Indian Ocean strategy based on a comprehensive analysis of all the favorable and adverse conditions. Its strategic goals should include building an Indian Ocean fleet, expanding its base networks, and sharing power peacefully with the United States and India, so as to safeguard its legitimate rights and interests in the region.

scholarly journals INVESTIGATON OF SEA LEVEL CHANGE ALONG THE BLACK SEA COAST FROM TIDE GAUGE AND SATELLITE ALTIMETRY

2015 ◽  
Vol XL-1-W5 ◽  
pp. 67-71 ◽  
Author(s):  
N. B. Avsar ◽  
S. H. Kutoglu ◽  
S. Jin ◽  
B. Erol
Keyword(s):  
Sea Level ◽  
Black Sea ◽  
Satellite Altimetry ◽  
Tide Gauge ◽  
The Black Sea ◽  
Level Change ◽  
Black Sea Coast ◽  
Grid Points ◽  
Sea Coast

In this study, we focus on sea level changes along the Black Sea coast. For this purpose, at same observation period the linear trends and the components of seasonal variations of sea level change are estimated at 12 tide gauge sites (Amasra, Igneada, Trabzon-II, Sinop, Sile, Poti, Batumi, Sevastopol, Tuapse, Varna, Bourgas, and Constantza) located along the Black Sea coast and available altimetric grid points closest to the tide gauge locations. The consistency of the results derived from both observations are investigated and interpreted. Furthermore, in order to compare the trends at the same location, it is interpolated from the trends obtained at the altimetric grid points in the defined neighbouring area with a diameter of 0.125° using a weighted average interpolation algorithm at each tide gauge site. For some tide gauges such as Sevastopol, Varna, and Bourgas, it is very likely that the trend estimates are not reliable because the time-spans overlapping the altimeter period are too short. At Sile, the long-term change for the time series of both data types do not give statistically significant linear rates. However, when the sites have long-term records, a general agreement between the satellite altimetry and tide gauge time series is observed at Poti (~20 years) and Tuapse (~18 years). On the other hand, the difference of annual phase between satellite altimetry and tide gauge results is from 1.32° to 71.48°.

scholarly journals TENDENCY FOR CLIMATE-VARIABILITY-DRIVEN RISE IN SEA LEVEL DETECTED IN THE ALTIMETER ERA IN THE MARINE WATERS OF ACEH, INDONESIA

2020 ◽  
Vol 16 (2) ◽  
pp. 165
Author(s):  
Guntur Adhi Rahmawan ◽  
Ulung Jantama Wisha
Keyword(s):  
Indian Ocean ◽  
Sea Level ◽  
Climatic Factors ◽  
Southern Oscillation ◽  
Marine Waters ◽  
Upward Trend ◽  
Sea Level Anomalies ◽  
Ocean Atmosphere ◽  
Aceh Province ◽  
The Indian Ocean

Long-term sea level rise (SLR) leads to increasing frequency in overtopping events resulting from polar ice liquefaction triggered by rising global temperatures. Aceh province is directly bordered by the Indian Ocean, and is subject to the influence of ocean–atmosphere interactions which have a role in triggering temperature and sea level anomalies. Elevated sea level is possibly caused by temperature-induced water mass redistributions. This study aimed to prove that the Indian Ocean Dipole (IOD) and El-Nino–Southern Oscillation (ENSO) had an influence on sea level change in Aceh waters over the six years 2009–2015. Sea level anomaly (SLA) was identified using Jason-2 satellite data for the 2009–2015 period, to enable the mathematical prediction of SLR rate for further years. We found that SLR was approximately 0.0095 mm/year with an upward trend during the six years of observation. Overall, negative mode of IOD and positive phase of ENSO tend to trigger anomalies of sea level at certain times, and have a stronger influence on increasing SLA and sea surface temperature anomaly (SSTA) which takes place in a ‘see-saw’ fashion. Over the period of observation, the strongest evidence of IOD-correlated SLA, ENSO-correlated SLA and SSTA-correlated SLA were identified in second transitional seasons, with more than 50% of R2 value. The upward trend in SLA is influenced by climatic factors that successively control ocean–atmosphere interactions in Aceh’s marine waters. 

scholarly journals SEA LEVEL VARIATION AND GEOSTROPHIC CURRENT OF THE SUNDA STRAIT BASED ON TIDAL AND WIND DATA IN YEAR 2008

2011 ◽  
Vol 3 (2) ◽  
Author(s):  
Resni Oktavia ◽  
John Iskandar Pariwono ◽  
Parluhutan Manurung
Keyword(s):  
Indian Ocean ◽  
Sea Level ◽  
Tide Gauge ◽  
High Tide ◽  
Level Variation ◽  
Tidal Forces ◽  
Sea Level Variation ◽  
The Indian Ocean ◽  
Java Sea ◽  
Current Flows

<p>Sea level variation from four tide-gauge data in the Sunda Strait, Indonesia, in the year 2008 has been studied by using Wavelet 1 D Daubechius 1 level 5 type and Fast Fourier Transform methods. The hourly sea level variation in April and November (representing transitional seasonal conditions) is approximately +0.49 m; whereas in January (representing Northwest Monsoon condition) and July (representing Southeast Monsoon condition) can reach up to -0.48 m. In 2008, sea level variation in the Sunda Strait is mainly influenced by the monsoon. Results from this study show that there are at least three phenomena of sea level variations in the Sunda Strait, namely (1) seasonal variation (periodicity between 4-6 months) where it is believed influenced by the Java Sea; (2) intra-seasonal (periodicity between 1-3 months), which is more influenced by the Indian Ocean; and (3) tidal forcing (periodicity between 14-17 days, suggesting fortnightly tidal forces) which propagates from the Indian Ocean into the Sunda Strait. Result from surface geostrophic approximation calculation suggests that during Southeast Monsoon (June-August), monthly mean current flows southwestwardly towards the Indian Ocean with a velocity of 0.14-0.16 m/s. Whereas during Northwest monsoon (December-February), current flows northeastwardly towards the Java Sea with a velocity of 0.14-0.17 m/s. Furthermore, on the daily time scale, tidal current in the Sunda Strait flows into the Java Sea (Indian Ocean) during high tide (low tide) with a velocity ranging from 0.51 to 0.72 m/s (0.48 to 0.51 m/s).</p><p>Keywords: sea level variation, geostrophic approximation, tides, monsoon, Sunda Strait</p>

scholarly journals Sea Level Fusion of Satellite Altimetry and Tide Gauge Data by Deep Learning in the Mediterranean Sea

2021 ◽  
Vol 13 (5) ◽  
pp. 908
Author(s):  
Lianjun Yang ◽  
Taoyong Jin ◽  
Xianwen Gao ◽  
Hanjiang Wen ◽  
Tilo Schöne ◽  
...  
Keyword(s):  
Mediterranean Sea ◽  
Sea Level ◽  
Satellite Altimetry ◽  
Tide Gauge ◽  
The Other ◽  
Tide Gauge Data ◽  
Sea Levels ◽  
Sea Level Anomalies ◽  
Gauge Data ◽  
The Mediterranean

Satellite altimetry and tide gauges are the two main techniques used to measure sea level. Due to the limitations of satellite altimetry, a high-quality unified sea level model from coast to open ocean has traditionally been difficult to achieve. This study proposes a fusion approach of altimetry and tide gauge data based on a deep belief network (DBN) method. Taking the Mediterranean Sea as the case study area, a progressive three-step experiment was designed to compare the fused sea level anomalies from the DBN method with those from the inverse distance weighted (IDW) method, the kriging (KRG) method and the curvature continuous splines in tension (CCS) method for different cases. The results show that the fusion precision varies with the methods and the input measurements. The precision of the DBN method is better than that of the other three methods in most schemes and is reduced by approximately 20% when the limited altimetry along-track data and in-situ tide gauge data are used. In addition, the distribution of satellite altimetry data and tide gauge data has a large effect on the other three methods but less impact on the DBN model. Furthermore, the sea level anomalies in the Mediterranean Sea with a spatial resolution of 0.25° × 0.25° generated by the DBN model contain more spatial distribution information than others, which means the DBN can be applied as a more feasible and robust way to fuse these two kinds of sea levels.

Reassessing sea level change rates in the Mediterranean Sea in the age of altimetry

2021 ◽  
Author(s):  
Francesco De Biasio ◽  
Stefano Vignudelli
Keyword(s):  
Mediterranean Sea ◽  
Sea Level ◽  
Satellite Altimetry ◽  
Adriatic Sea ◽  
Tide Gauge ◽  
Sea Level Change ◽  
Data Sets ◽  
Level Change ◽  
The Mediterranean

&lt;p&gt;Consistent long-term satellite-based data-sets of sea surface elevation exist nowadays to study sea level variability, globally and at regional scales. Two of them are suitable for climate-related studies: one produced in the framework of the European Space Agency (ESA)-funded Sea Level Climate Change Initiative (SL_CCI); the other offered by the European Copernicus Climate Change Service (C3S). Both data-sets cover the global ocean since 1993 to 2015 (SL_CCI) and to present (C3S) at spatial resolution of 0.25 x 0.25 degrees. The first is obtained by merging data from all the available satellite altimetry missions. The second one relies only on a couple of simultaneous altimetry missions at a time to provide stable long-term variability estimates of sea level, is constantly updated and has resolution 0.125 x 0.125 degrees in the Mediterranean Sea.&lt;br&gt;Previous studies have investigated the relationship between satellite-derived absolute sea level change rates and tide gauge observations of relative sea level change in littoral zones of the Mediterranean basin [Fenoglio-Mark, L., 2002; Fenoglio-Mark et al., 2012]. Other studies made use also of global positioning system measurements of vertical land motion in addition to tide gauge and satellite altimetry data [Rocco F.V., 2015; Zerbini et al., 2017]. Vignudelli et al., [2018] highlighted the difficulty of deriving spatially-consistent information on the sea level rates at regional scale in the Adriatic Sea. Other studies have claimed the possibility to merge locally isolated information into a coherent regional picture using a linear inverse problem approach [W&amp;#246;ppelmann and Marcos, 2012]: such approach has been successfully applied to a number of tide gauges in the Adriatic Sea [De Biasio et al., 2020]. The approach tested in the Adriatic Sea is going to be extended to the Mediterranean and major findings will be presented at conference.&lt;br&gt;The motivation of this study is that industrial areas are widely spread along the littoral zone of the southern Europe, and residential settlements are densely scattered along the coasts of the Mediterranean Sea. Not least, a strongly rooted seaside tourism is one of the main economic resources of the region, which is particularly exposed to the sea level variability of both natural and anthropogenic origin. A well known example of such a exposition is Venice (northern Italy) which has been recently hit by the second-highest tide in recorded history (November 2019), and is being protected against storm surges by the MOSE barrier since October 2020. Therefore, a re-analyses of the actual sea level rates with novel methodologies that take into account a better usage of all available observations is key to understand the future coastal sea level changes and their relative importance.&lt;/p&gt;&lt;p&gt;Fenoglio-Marc, L. 2002. DOI: 10.1016/S1474-7065(02)00084-0&lt;/p&gt;&lt;p&gt;Fenoglio-Marc, L.; Braitenberg, C.; Tunini, L. 2012. DOI: 10.1016/j.pce.2011.05.014&lt;/p&gt;&lt;p&gt;Rocco, F.V. Ph.D. Thesis, 2015. URI: https://amslaurea.unibo.it/id/eprint/10172&lt;/p&gt;&lt;p&gt;Zerbini, S.; Raicich, F.; Prati, C.M.; Bruni, S.; Conte, S.D.; Errico, M.; Santi, E. 2017. DOI: 10.1016/j.earscirev.2017.02.009&lt;/p&gt;&lt;p&gt;Vignudelli, S., De Biasio, F., Scozzari, A. Zecchetto, S., and Papa, A. 2019. DOI:10.1007/1345_2018_51&lt;/p&gt;&lt;p&gt;W&amp;#246;ppelmann, G. and Marcos, M. 2012. DOI: 10.1029/2011JC007469&lt;/p&gt;&lt;p&gt;De Biasio, F., Baldin, G. and Vignudelli, S. 2020. DOI:10.3390/jmse8110949&lt;/p&gt;

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