Coupling large-eddy simulations with UAV measurement through inversion technique to estimate patch-level fluxes from heterogeneous tundra landscapes

Land cover change has direct implications on natural greenhouse gas emissions, as land-atmosphere interactions are function of the changing heterogeneity of the surface. Rapidly changing ecosystems, such as the Arctic, where permafrost wetting and draining is taking place in different regions in the northern latitudes, underlines the necessity of assessing patch-level emissions of greenhouse gases to better estimate net total fluxes. In this study, we combine high-resolution modelling of the atmospheric boundary layer with inverse modelling concepts to constrain land-atmosphere exchange fluxes at local to landscape scales, and explore relationships between different land cover types within heterogeneous landscapes and the net exchange processes between surface and atmosphere. We use EULAG (EUlerian LAGrangian), an established Large-Eddy Simulation model, to simulate high-resolution flow patterns induced by heterogeneous permafrost surfaces, and apply inversion techniques to infer the fluxes of the corresponding patch type forming the mixed land cover. Uncrewed Aerial Vehicles (UAV)-based grid surveys of gas concentrations are used to benchmark the spatial variability of modeled concentrations using EULAG, where we optimize for surface fluxes associated with each patch. We present a case study at Stordalen Mire in subarctic Sweden, where we use UAV measurements of methane and carbon dioxide mole fractions, and implement this inversion method to differentiate the flux rate signatures from different patch types, namely palsa, bog, and lakes. The inferred fluxes were validated with patch-level chamber measurements of methane and carbon dioxide. Our model evaluation shows a good match between modeled and observed concentrations while the resulting patch-level fluxes agree with the observed fluxes from chamber measurements. Our novel technique shows promising results in inferring patch type flux heterogeneity while facilitating the application of inversion methods to high resolution atmospheric models.