MODIS Rapid Response Fire Detections for 2005

JANUARY FEBRUARY MARCH APRIL MAY JUNE JULY AUGUST SEPTEMBER OCTOBER NOVEMBER DECEMBER

Fig. 20.1. Global vegetation fires detected in April 2005.

JANUARY FEBRUARY MARCH APRIL MAY JUNE JULY AUGUST SEPTEMBER OCTOBER NOVEMBER DECEMBER

Fig. 20.1. Global vegetation fires detected in April 2005.

measures of uncertainty and the likelihood of extreme conditions allow fire managers to implement fire prevention, detection and pre-suppression plans before fire problems begin. Considering the fact that the majority of uncontrolled and destructive wildfires are caused by humans as a consequence of inappropriate use of fire in agriculture, pastoralism and forestry, it is crucial that international wildland fire early warning systems are developed to complement relevant national fire danger warning systems where they exist, to provide early warning where national systems do not exist, and to enhance warnings applied or generated at the local (community) level (people-centered early warning systems - as requested by the UN Secretary General and as laid down in the Hyogo Framework for Action 2005-2015: "Building the Resilience of Nations and Communities to Disasters"), ttis will ensure delivery of targeted information reflecting specific local conditions and allowing the involvement oflocal communities in wildland fire prevention.

Fire danger rating is a mature science and has long been used as a tool to provide early warning of the potential for serious wildfires. Fire danger rating systems (FDRS) utilize basic daily weather data to calculate wildfire potential. FDRS early warning information is often enhanced with satellite data such as hot spots for early fire detection, and spectral data on land cover and fuel conditions. Normally, these systems provide a 4-6 hour early warning of the highest fire danger for any particular day that the weather data is supplied. However, by using forecasted weather data, as much as 2 weeks of early warning can be provided, depending on the length of the forecast. Ensemble weather prediction systems through multiple realisations of forecasts provide distributions of weather forecasts and capture their inherent predictability and uncertainty associated with such forecasts. As well, FDRS indices can be calibrated with local data to provide longer term early warning, such as a 30-day early warning tool developed for Southeast Asia to indicate the potential for disaster-level haze events from peatland fires (see section 20.8).

FDRS tools for early warning are highly adaptable and have demonstrated their application to a wide range of users, from independent remote field stations (for making local fire suppression and preparedness decisions) to global and regional fire information centres (for large-scale decision making, such as multi-national resource sharing), ttere are numerous examples of current operational systems utilizing CIS technology and computer modelling of landscape level fire danger, which process and transfer early warning information very quickly via the World Wide Web.

Long-term knowledge of conditions during wildfires and the utility of fire danger forecasts are important to the immediate development of early warning systems and to undertake the planning and preparation associated with the impacts of climate change. Understanding the characteristics of extreme wild fire events is a paramount consideration. A long-term global dataset of fire danger metrics is also required to meet these requirements.

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