Biomass burning is a globally significant source of aerosols, greenhouse gases and other trace gas species, influencing both regional and global climate. Although fire occurrence is for a large part driven by humans for land management purposes, fire extent and emission types are greatly controlled by biotic factors (species composition, biomass) and climate (soil moisture, temperature, precipitation). Thus, climate change may lead to more frequent and intense fires if drought conditions in areas with abundant fuel loads become more severe. Still, the impact of soil moisture on fire goes well beyond the paradigm ¿it only burns when it¿s dry¿: Soil moisture does not only impact the occurrence and spatial extent of wildfires, but as a driver of biomass production also controls fuel load, ecosystem composition, and combustion efficiency and, hence, the quantity and type of fire emissions. Yet, the precise control of soil moisture on fire emissions is only poorly understood and parameterized in state-of-the-art fire emission models.
Earth observation data provided by ESA programmes (e.g. CCI soil moisture, CCI fire, CCI land cover, CCI aerosol, CCI greenhouse gases, DUE GlobEmission, STSE BIOMASAR, SMOS soil moisture and VOD) and other (space) agencies provide a wealth of information to improve our knowledge on the role of soil moisture in driving biomass burning emissions. We will exploit these datasets to 1) infer observation-based relationships between soil moisture, fuel load production, and fire extent and emissions by using machine learning techniques, and to 2) improve parameterisations of the state-of-the-art coupled dynamic global vegetation and fire model LPJmL-SPITFIRE. The optimised process-oriented model will ultimately be used in combination with climate scenarios from coupled climate carbon cycle models to 3) make projections of future soil moisture-vegetation-fire interactions and fire emissions. Results of these experiments will result in three scientific publications in high-impact scientific journals.
The study will be carried out in close collaboration with Prof. Guido van der Werf (VU Amsterdam) and Dr. Kirsten Thonicke (PIK Potsdam) who are among the world-leading scientists in modelling global fire emissions. The study will significantly improve our knowledge on the impact of soil moisture on wildfires and allow us to better model the impact of biomass burning on atmospheric greenhouse gases, trace gases, and aerosols and hence improve predictions and impacts of global warming. Through the primary use of ESA data, the project will further increase the visibility of ESA products in the carbon cycle modelling community and through the improved fire emission model contribute to the CMIP modelling efforts in support of the IPCC assessments.