Climate Downscaling for Fire Managemen

Abstract

Climate, a primary driver for fire activity, is important for fire management. Climate information is necessary for understanding and predicting fire regimes, seasonal and inter-annual variability, and future trends. Most wildfires are up to tens of kilometers in size, while global climate models usually have horizontal resolutions of hundreds of kilometers. Therefore,  downscaling is required to provide high-resolution climate information for fire management applications. The climate and fire communities have made great strides in developing and applying climate downscaling techniques. Here we introduce fire managers and researchers to available techniques and products in this active field and their significance for fire management. Dynamical downscaling (running regional climate models with boundary conditions provided by global climate modeling or from measurements) and statistical downscaling (applying statistical tools such as regression and spatial analyses to connect historical meteorological measurements and global climate model data) are described. Their strengths and weaknesses are compared to provide a basis for selecting the products needed to achieve the specific fire management goals. A number of downscaling tools and products are described. Examples of actual fire applications are illustrated.

Citation

Liu Y.-Q., Goodrick S., Stanturf J.A.,. 2021. Climate downscaling for fire management,In: Sustainability in Natural Resources Management and Land Planning W. Leal Filho et al. (eds.), World Sustainability Series