Reducing uncertainties in the Vegetation Photosynthesis and Respiration Model (VPRM)

The Vegetation Photosynthesis and Respiration Model (VPRM) is a light-use efficiency model used to estimate biogenic CO₂ fluxes based on satellite indices, land cover maps, and meteorological data. It models net ecosystem exchange (NEE) with a simple function that uses four adjustable parameters for each vegetation type, fitted using eddy covariance measurements. VPRM is both accurate and computationally efficient, making it a popular choice for calculating CO₂ fluxes at high spatial and temporal resolutions, such as in regional inversion studies.

Initially designed for use with MODIS satellite data at a 500-meter resolution, our updated implementation now supports Sentinel-2 data with a much finer 20-meter resolution. This higher resolution improves the accuracy of biospheric flux estimates by (1) better resolving heterogeneous landscapes, such as croplands, and (2) enabling the incorporation of time-dependent flux tower footprints into the parameter fitting procedure. We compared the flux footprint approach to the traditional implementation for Sentinel-2 for Europe. To ensure robust comparisons, we used Monte Carlo Markov Chain (MCMC) sampling to estimate the range of parameter values for both model versions.