Year: 2025
Type: conference-abstract
Abstract: Monitoring fluxes of greenhouse gases is crucial to attribute sources and sinks. With advancements in satellite technology offering resolutions smaller than a tower's footprint, we can now have spatially-explicit estimations at the meter scale, a comparable resolution to in-situ observations. This study explores the potential of assimilating tall tower eddy covariance fluxes to calibrate a surface model of CO2 exchange over a heterogeneous landscape. We present a bayesian inversion strategy which compares an estimated flux supposedly measured by the tower, calculated based on a priori flux map and a footprint model, and the observed flux. Two sites (Saclay and P2OA) are evaluated both consisting of a mix of agricultural, forest and urban patches. The heterogeneous landscape provides an ideal setting to assess the method's ability to distinguish and quantify greenhouse gas flux contributions from different land types.
Source: ARPHA Conference Abstracts
Language: English
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
SDGs: Climate action, Life on land
Open Access status: diamond
Funder: Université Paris-Saclay
OpenAlex ID: W4410826252