Phylogeography of Ceriops tagal (Rhizophoraceae) in Southeast Asia: the land barrier of the Malay Peninsula has caused population differentiation between the Indian Ocean and South China Sea

2006 ◽  
Vol 8 (1) ◽  
pp. 89-98 ◽  
Author(s):  
Pei-Chun Liao ◽  
Sonjai Havanond ◽  
Shong Huang
Keyword(s):  
Indian Ocean ◽  
South China Sea ◽  
Southeast Asia ◽  
South China ◽  
Population Differentiation ◽  
Malay Peninsula ◽  
China Sea ◽  
The Indian Ocean ◽  
Ceriops Tagal

The Maritime Routes Between China and the Indian Ocean During the Second to Ninth Centuriesc.e.

2016 ◽  
Vol 27 (1) ◽  
pp. 53-81 ◽  
Author(s):  
STEPHEN G. HAW
Keyword(s):  
Indian Ocean ◽  
South China Sea ◽  
Southeast Asia ◽  
East Asia ◽  
South China ◽  
The South China Sea ◽  
Complex Task ◽  
Malay Peninsula ◽  
China Sea ◽  
The Indian Ocean

AbstractThe interpretation of history is often a complex task. All too often, sources are misinterpreted because of historians’ preconceptions. This article takes issue with one such misinterpretation, the anachronistic view that the Strait of Melaka has been the principal sea route connecting the Indian Ocean with the South China Sea throughout most of recorded history. Beginning at a period when an overland journey across the Malay Peninsula was an essential link in the routes connecting South, Southeast and East Asia, it is suggested that the first entirely maritime itinerary to be used regularly passed through the Sunda Strait. Changes in itineraries affected the fortunes of the states of Southeast Asia, particularly of Funan and Srivijaya.

TSUNAMI HAZARD AND CASUALTY ESTIMATION IN A COASTAL AREA THAT NEIGHBORS THE INDIAN OCEAN AND SOUTH CHINA SEA

2012 ◽  
Vol 06 (02) ◽  
pp. 1250010 ◽  
Author(s):  
ANAWAT SUPPASRI ◽  
FUMIHIKO IMAMURA ◽  
SHUNICHI KOSHIMURA
Keyword(s):  
Indian Ocean ◽  
South China Sea ◽  
South China ◽  
The South China Sea ◽  
The South ◽  
Worst Case ◽  
China Sea ◽  
Coastal Population ◽  
The Indian Ocean ◽  
Hazard Level

In the Indian Ocean and the South China Sea, many hundreds of thousands of lives have been lost due to tsunami events, and almost half of the lives lost occurred following the 2004 Indian Ocean event. Potential tsunami case scenarios have been simulated in these regions by a number of researchers to calculate the hazard level. The hazard level is based on a variety of conditions, such as the tsunami height, the inundation area, and the arrival time. However, the current assessments of the hazard levels do not focus on the tsunami risk to a coastal population. This study proposes a new method to quantify the risk to the coastal population in the region that includes the Indian Ocean and the South China Sea. The method is simple and combines the use of readily available tsunami data, far-field tsunami simulation models to determine the regional risk and global population data. An earthquake-generated tsunami was simulated, following an earthquake that had a magnitude larger than 8.5 Mw and occurred along a potential subduction zone. The 2004 Indian Ocean event seemed to be a "worst case scenario"; however, it has been estimated that a potential tsunami, occurring in a coastal region with a high population density, could cause significantly greater casualties.

scholarly journals Interdecadal Difference of Interannual Variability Characteristics of South China Sea SSTs Associated with ENSO

2015 ◽  
Vol 28 (18) ◽  
pp. 7145-7160 ◽  
Author(s):  
Yali Yang ◽  
Shang-Ping Xie ◽  
Yan Du ◽  
Hiroki Tokinaga
Keyword(s):  
Indian Ocean ◽  
South China Sea ◽  
South China ◽  
El Niño ◽  
El Nino ◽  
Tropical Indian Ocean ◽  
Easterly Wind ◽  
China Sea ◽  
Sst Warming ◽  
The Indian Ocean

Abstract The correlation between sea surface temperature (SST) and El Niño–Southern Oscillation (ENSO) persists into post-ENSO September over the South China Sea (SCS), the longest correlation in the World Ocean. Slow modulations of this correlation are analyzed by using the International Comprehensive Ocean–Atmosphere Dataset (ICOADS). ENSO’s influence on SCS SST has experienced significant interdecadal changes over the past 138 years (1870–2007), with a double-peak structure correlation after the 1960s compared to a single-peak before the 1940s. According to the ENSO correlation character, the analysis period is divided into four epochs. In epoch 3, 1960–83, the SST warming and enhanced precipitation over the southeastern tropical Indian Ocean, rather than the Indian Ocean basinwide warming, induce easterly wind anomalies and warm up the SCS in the summer following El Niño. Besides the Indian Ocean effect, during epochs 2 (1930–40) and 4 (1984–2007), the Pacific–Japan (PJ) pattern of atmospheric circulation anomalies helps sustain the SCS SST warming through summer (June–August) with easterly wind anomalies. The associated increase in shortwave radiation and decrease in upward latent heat flux cause the SCS SST warming to persist into the summer. Meanwhile, the rainfall response around the SCS to ENSO shows interdecadal variability, with stronger variability after the 1980s. The results suggest that both the remote forcing from the tropical Indian Ocean and the PJ pattern are important for the ENSO teleconnection to the SCS and its interdecadal modulations.

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