Wildland fires burn several hundred million hectares of vegetation every year, and increased fire activity has been reported in many global regions. Many of these fires have had serious negative impacts on human safety, health, regional economies, global climate change, and ecosystems in non-fire-prone biomes. Worldwide fire suppression expenditures are rapidly increasing in an attempt to limit the impact of wildland fires. To mitigate fire-related problems and costs, forest and land management agencies, as well as land owners and communities, require an early warning system to identify critical periods of extreme fire danger in advance of their potential occurrence. Early warding of these conditions allows fire managers to implement fire prevention, detection, and pre-suppression plans before fire problems begin. Fire danger rating is commonly used to provide early warning of the potential for serious wildfires based on daily weather data. Fire danger information is often enhanced with satellite data, such as hot spots for early fire detection, and with spectral data on land cover and fuel conditions. Normally, these systems provide a 4- to 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 profided. This paper presents a proposed Global Early Warning System for Wildland Fire to provide advanced early warning capabilities at local to global levels.