ИСТИНА

The study focuses on the formulation, analysis, and solution of the inverse problem of remote sensing to retrieve surface greenhouse gas (GHG) fluxes from measured GHG concentrations at several, at least two levels above a ground surface. The direct problem of determining GHG concentrations in the atmospheric boundary layer is based on the application of a three-dimensional hydrodynamic model of turbulent GHG transport. It provides a GHG concentration distribution based on the solution of diffusion-advection equation using data on wind speed and direction, turbulent exchange coefficients, and GHG fluxes at some level above the plant canopy. The flux is used in the boundary condition at the lower boundary of the computational domain. The lower boundary of the domain was assumed to be parallel to the ground surface at some level above the canopy. The spatial distributions of wind velocity and turbulence coefficient "in a moment" are calculated from the relaxation problem for the averaged Navier-Stokes and continuity equations, taking into account the topography and the heterogeneity of the vegetation cover, using a 1.5 order closure scheme (E-ω model). The corresponding initial boundary value problems are solved numerically using finite difference methods. Stable implicit finite-difference schemes with process splitting are implemented. The inverse problem is to retrieve a ground surface GHG flux from measured concentrations at several levels above the lower boundary of the computational domain. The flux is calculated by minimizing the difference between the measured and modeled values. The initial approximation of the GHG flux distribution at each point of the lower boundary of the modeling domain is estimated as the product of the turbulence coefficient at the corresponding point and the ratio of the measured concentration difference at the two levels to the distance between the levels. The developed algorithm was applied to estimate carbon dioxide and methane fluxes over a non-uniform forest canopy at the Roshni-Chu experimental site in the Caucasus Mountains (Chechen Republic). To test the direct numerical problem, data on surface topography, vegetation height and density, distribution of photosynthetically active solar radiation, as well as data from soil and vegetation respiration measurements were used.