Soil moisture active passive data improve sensitivity assessment of permafrost active layer thickness to wildfire disturbance

Abstract

Wildfires have intensified permafrost degradation across the pan-Arctic region, underscoring the urgent need for sensitivity assessments of the active layer thickness (ALT) to improve permafrost carbon emission estimates. However, the limited availability of soil parameters hinders simulations of heat transfer processes. Soil moisture active passive (SMAP) data will likely fill these gaps. We utilized the Kudryavtsev model to simulate the volumetric water content-based ALT (VWC-ALT) and SMAP-based ALT (SMAP-ALT) and compared their sensitivities to wildfires. The SMAP-ALT exhibits significant sensitivity compared with the VWC-ALT. Regions with high SMAP-ALT heterogeneity were associated with wildfires, facilitating the differentiation between burned and unburned areas while enabling the characterization of temporal changes and variations in influencing factors during prefire, fire, and postfire periods. These results highlight that SMAP data enhance sensitivity assessment of the ALT concerning wildfires. This approach also holds significant potential for reflecting other environmental disturbances associated with soil moisture, which is crucial for accurately estimating permafrost carbon emissions.