Air-Sea Interaction

This study examines societal risks and vulnerabilities to the twin disasters of floods and landslides in
Brunei Darussalam from a scientific perspective. Having observed that floods and landslides heavily
impact on communities across the country, damaging property, infrastructure and the natural/built
environment, causing evacuations and other socio-economic disruptions, the study is based on the
premise that only through a good understanding of the underlying forcing mechanisms and triggers can
effective policy disaster risk reduction (DRR) be achieved. Based on the results, the following
observations are established:
1. Floods and landslides in Brunei Darussalam which generally occur during the N.E Monsoon season are
particularly severe in the month of January;
2. Based on the cases of January 2009, 2011 and 2014, it is establishes that although the monsoons are
generally predictable, anomalous episodic deluge which is the primary trigger of floods and landslides is
largely unpredictable;
3. Intense/episodic anomalous rainfall which triggers floods, flash-floods and landslides in Brunei, is
generally forced by an anomalous synoptic air-sea coupled processes and tele-connections across the
marginal South China Sea and adjacent seas;
4). Air-sea coupled mechanisms which force anomalous rainfall are characterized by a high degree of
inter-annual variability and unpredictability.
The study concludes that challenges based on such unpredictability and complexity present a real test to
of meteorologically-induced disaster preparedness in the country and limit management
effectiveness basically to response rather than the more desirable prediction and mitigation.

The intensity of the 1997 El Niño and the 8°C sudden drop in sea surface temperature (SST) around 0°–130°W during the turn into La Niña in 1998 were a surprise to the scientific community. This succession of warm and cold events was observed from start to finish ...

Saint Martin’s island is a beautiful tourist attractive place and a unique coral island in Bangladesh. Marine biodiversity of this island is very rich for its favorable environment but its marine environment is facing threats day by day due to natural calamities, various types of pollution, and other anthropogenic activities. So it is very important to know the present physico-chemical status of seawater around the island as a baseline scenario. At first, coastal water samples were collected from 24 sites. Niskin water sampler is used to collect samples from 26 February to 02 March, 2018. Six physico-chemical parameters like temperature, salinity, conductivity, dissolved oxygen (DO), pH and total dissolved solids (TDS) were measured directly at in-situ position. The ranges for the physico-chemical parameters of coastal seawater were 25 to 30°C for temperature, 30.8 to 33.4 ppt for salinity, 48966 to 55235 μS/cm for conductivity, 5.08 to 6.87 mg/L for DO, 8.05 to 8.38 for pH and 29575 to 31980 mg/L for TDS. The highest and lowest salinity was found in the southern and northern part of the Saint Martin’s Island respectively. The highest DO is found on three sides’ especially the northern side but the lowest DO was found in the eastern side of the Island.

Studying the behaviour of the sea surface temperature (SST) is important in the examination of many oceanographic activities. The variations in the SST are mainly controlled by atmospheric conditions. However, other physical parameters are also impacting on these variations, e.g. solar radiation, relative humidity, water depth, groundwater inflow and wind speed. Using a one year (04/02/99-04/02/00) data set, the present paper aims at describing the general behaviour of the daily SST variations within the southeastern Mediterranean Sea region, off the Egyptian Mediterranean coast. The relationships between both the air temperature and wind speed, and the SST were built using regression techniques. The general pattern of the daily SST anomaly, produced in this research, reflects stability and homogeneity in the thermal distribution within the area of study. The seasonal presentation of the SST data reveals normal thermal variation behaviour, e.g. maxima in summer and minima in winter.