Determining the human signal in burned area under a changing climate

In this study, we report the preliminary findings from a series of sans-human wildfire simulations using a process based dynamic global to regional vegetation model (DGVM), LPJ-GUESS v 4.1, coupled with the SIMple FIRE Model (SIMFIRE) and the wildfire combustion model (BLAZE), where we investigate the performance of the DGVM to reenact a specific wildfire instance in a Mediterranean catchment. For this, we compared the simulated burned area (BA^s) to that in the actual event (BA^o) in Manavgat, Antalya, Türkiye. The DGVM spatially captured the fire instance, albeit with a much smaller BA as a result. In July 2021, the largest single wildfire incidence for this region for the last two centuries occurred. The wildfire scorched an area of 60.000 ha.s where the dominant vegetation types were fire adapted dry conifer forests (mainly Pinus brutia) and Mediterranean shrubs. Previous years’ precipitation patterns had encouraged fuel build up, and the extreme heat of the summer of 2021, coupled with the seasonal drought and strong winds provided suitable environmental conditions for the wildfire’s spread. The ignitions in this specific case were intentional, majority were targeted arsons, and a plausible reason behind the ultimate extent of the BA. Here, we show the simulation results from our sans-human model runs using ERA5-Land reanalysis dataset, and compare BA^s to BA^o for this catchment for 2021. Our ultimate aim in these series of experiments where the ignition source is non-human is initially to decipher the dynamics, and later to develop a methodology to assess the human influence in BA in Mediterranean type ecosystems in the Eastern Mediterranean Basin, under a changing climate.