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Fire and Haze Early Warning System Prototype Developed by APCC for Southeast Asia Region

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Admin
 
Date
2016.02.01
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559

 

 

The APEC Climate Center (APCC) has developed a fire and haze early warning system prototype for the Southeast Asian Region as a part of the Asia-Pacific Network for Global Change Research (APN).

Smoke haze from forest fires is among Southeast Asia’s most serious environmental problems. However, measures to prevent these fires and mitigate their impacts are limited by the absence of long-lead early warning systems. To address this, APCC investigated how seasonal forecasts can be used to predict drought conditions triggering forest fires. By using long-term climate predictions and statistical downscaling climate models, APCC has developed a prototype that can deliver earlier fire and haze warnings. The prototype predictions are released in April, months before the trial region’s dry season, which runs from September to October.

The benefits of a larger lead time are clear, suggesting that this information should be added to existing early warning systems, which would allow for more effective measures and policies on forest fire. Additionally, this integration would facilitate cooperation between Southeast Asian governments, requiring activities such as equipment support.

While the researchers were developing this system, they also conducted a training workshop to explain the fire and haze early alarming system. This training program has heightened the fire and forest officer’s interests and intensified future application ability.

APN is an intergovernmental network that promotes policy oriented research and capacity-building activities related to global changes in the region. APN was established in 1992 with the financial support from USA and Japan government and its vision is to make an Asia-Pacific region that successfully addresses the challenges of global change and sustainability. The organization selects their research projects through a competitive selection process among the submitted tasks.