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Data assimilation of dead fuel moisture observations from remote automated weather stations

Data assimilation of dead fuel moisture observations from remote automated weather stations

Fuel moisture has a major influence on the behaviour of wildland fires and is an important underlying factor in fire risk assessment. We propose a method to assimilate dead fuel moisture content (FMC) observations from remote automated weather stations (RAWS) into a time lag fuel moisture model. RAWS are spatially …