Pag-asa orients local disaster council on new weather equipment

By Jose Mari Garcia

Tuesday 17th of July 2012

CITY OF BALANGA, Bataan, July 17 (PIA) -- The Philippine Atmospheric, Geophysical and Astronomical Services Administration (Pag-asa) briefed local disaster councils in Bataan on the new automatic weather station (AWS) installed here that will provide quicker flood and disaster forecasts in specific areas of the province.

A team from Pag-asa has explained to the provincial and municipal disaster risk reduction and management councils the use of AWS as an early warning system that records weather parameters in the area including rainfall, wind speed, wind pressure, humidity, and temperature, among others.

An AWS was installed on May in Bataan National High School in Balanga City and another in Mariveles town.

Veronica Chin of Pag asa said the function of the P700,000-worth system is to provide early warning to barangays within five to 10 km-radius where the AWS is installed.

“For example, when the rainfall reading is high, people can be advised that the water has reached a critical level and that they should be vigilant,” said Chin.

Dennis Mariano, head of the Balanga City Public Safety Office, said more lives will be saved using data from the weather system because they will now have a concrete basis to present to the people during the stormy season.

“It is very hard to evacuate people if we don’t have basis. With this data, we can show this to the people and give them an early warning,” said Mariano.

Aside from the AWS, Balanga has three rain gauges, four river gauges, and one manual weather station located in strategic areas of the city.

Chin added, all barangays should have their own AWS that automatically transmits information to a central server which posts the data in a website for every 15 minutes.

To view the weather data, visit the site named PREDICT which stands for Philippine Real-Time Environment Data Acquisition and Interpretation for Climate-Related Tragedy Prevention and Mitigation. It can be accessed through http://202.90.128.12/predict/stations.php. (CLJD/JMG-PIA3)