Expanding the Ts-VI feature space for retrieving new parameters characterising the water and carbon cycle:...

Land Surface Interactions (LSI) have an important role in shaping the complex dynamics of climate-related processes across varying spatiotemporal scales. Therefore, the accurate quantification of exchanges of turbulent fluxes and greenhouse gas is essential for the efficient management of natural resources and the adaptation to climate change mitigation strategies. Toward this direction, this study introduces a novel framework for deriving mass, energy and carbon flux directly from the Ts - VI (land surface temperature - vegetation index) feature space. In particular, herein is provided the first validation of the "analytical triangle" using Landsat-8 and the latest version of the SimSphere SVAT model, while also introduced the proof-of-concept of a new scheme that extends the application of the "analytical" triangle to retrieving new variables characterising land surface interactions. In particular, the study applied the "analytical triangle" concept, which is also proposed to be extended to include the retrievals of instantaneous maps of [O₃] and O₃ flux, GPP, [CO₂], and water use efficiency (WUE). A first evaluation of the proof-of-concept methodological framework proposed herein was performed at 3 sites belonging to the FLUXNET ground global network, representative of three biomes. The analysis yielded satisfactory RMSDs, with the best performance for GPP (6.268 μmol CO₂ m^-2 s^-1), followed by WUE (8.116 kg m^-3), [O₃] (8.270 ppb), O₃ flux (5.42 μmol mol^-1), and [CO₂] (59.91 μmol mol^-1). Overall, the most accurate predictions, with the lowest average errors were observed at cropland sites, especially for GPP predictions (R = 0.93) without requiring extensive model calibration, demonstrates the method's potential for future practical applications. All in all, the findings showed a great capacity of the "analytical triangle" and the newly proposed scheme in particular in supporting improved monitoring of key parameters characterising land-atmosphere interactions.